ADAPTIVE EXERCISE SYSTEM WITH DYNAMIC VIRTUAL ENVIRONMENT GENERATION AND REAL-TIME PHYSIOLOGICAL RESPONSE

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation-in-part of U.S. Patent Application No. 19/244,679, which claims the benefit of U.S. Provisional Patent Application Serial No. 63/662,084, filed June 20, 2024 and is a continuation-in-part of U.S. Patent Application No. 18/902,061, filed September 30, 2024, which is a continuation of U.S. Patent Application No. 17/962,900, filed October 10, 2022, now U.S. Patent No. 12,102,903, issued October 1, 2024, which is a continuation of U.S. Patent Application Serial No. 17/468,171, filed September 7, 2021, now U.S. Patent No. 11,465,031, issued October 11, 2022, which claims the benefit of U.S. Provisional Patent Application Serial No. 63/079,240, filed September 16, 2020, U.S. Provisional Patent Application Serial No. 63/114,251, filed November 16, 2020, U.S. Provisional Patent Application Serial No. 63/142,671, filed January 28, 2021, and U.S. Provisional Patent Application Serial No. 63/182,349, filed April 30, 2021; this application also claims the benefit of U.S. Provisional Patent Application Serial No. 63/756,541, filed February 10, 2025 and U.S. Provisional Patent Application Serial No. 63/756545, filed February 10, 2025, the disclosures of which are hereby incorporated herein by reference in their entirety.

BACKGROUND

[0002] Treadmills as well as stationary bikes and other exercise equipment are increasing in popularity as users seek exercise and other equipment that offer new features. Traditional exercise equipment is limited to manually applied settings and configurations . Accordingly, there is a need for improved systems and methods that address these and other needs.

SUMMARY

[0003] Various examples of an adaptive exercise system include a treadmill comprising:a front end; a rear end; a belt defining a running surface that extends substantially between the front end and the rear end; and one or more lifting mechanisms configured to adjust an orientation of the running surface about a pivot point positioned centrally between the front end and the rear end. The system may also include computer hardware configured for: generating a virtual

[0004]course having variations in incline and decline; operating the belt at a particular speed; receiving user context data of a user utilizing the treadmill; and automatically modifying at least one treadmill attribute based on the user context data, by at least one of: modifying the particular speed of the belt; or causing the one or more lifting mechanism to adjust the orientation of the running surface.

[0005] In some examples, the user context data includes at least one of biometric data or imaging data of the user. In various examples, the system comprises at least one infrared imaging device. In such examples, the computer hardware is further configured for: causing the at least one infrared imaging device to capture an image of at least a face of the user; deriving, based on the image, a temperature of at least one facial feature of the user; determining, based on the temperature, a current exertion level of the user; and automatically modifying the at least one treadmill attribute based on the current exertion level of the user.

[0006] In some embodiments, the computing hardware is further configured for: accessing baseline exertion data for the user; and modifying the at least one treadmill attribute based on the current exertion level of the user and the baseline exertion level.

[0007] In various examples, the system includes a display; and the computing hardware is configured for: displaying a representation of the virtual course; and modifying the virtual course based on the user context data.

[0008] In various examples, modifying the virtual course comprises including or excluding particular features form the virtual course based on the user context data. In some expmales, generating the virtual course comprises at least one of generating the virtual course on the fly or initially presetting the virtual course.

[0009] In particular embodiments, the one or more lifting mechanisms comprise: a first motor; a first connector operatively connecting the first motor to a first portion of the exercise platform adjacent the front end; a second motor; and a second connector operatively connecting the second motor to a second portion of the exercise platform adjacent the rear end.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In the course of this description, reference will be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:

[0011]FIG. 1 depicts an example of a computing environment that can be used for providing adaptive exercise systems in accordance with various aspects of the present disclosure.

[0012]FIG. 2 depicts an example of a process for modifying exercise equipment based on user context data in accordance with various aspects of the present disclosure.

[0013]FIG. 3 depicts an example of a process for determining user exertion level in accordance with various aspects of the present disclosure.

[0014]FIG. 4 depicts an example of thermal imaging of a user in accordance with various examples of the present disclosure.

[0015]FIG. 5 depicts an example of a process for modifying exercise equipment based on user exertion and training data in accordance with various aspects of the present disclosure.

[0016]FIGS. 6A-6B depict an exemplary exercise course/exercise spline modification in accordance with various aspects of the present disclosure.

[0017]FIG. 7 depicts an example of a process for modifying a virtual environment in accordance with various aspects of the present disclosure.

[0018]FIG. 8 depicts an example of identifying a user context in accordance with various aspects of the present disclosure.

[0019]FIG. 9 depicts an example of a system architecture that may be used in accordance with various aspects of the present disclosure.

[0020]FIG. 10 depicts an example of a computing entity that may be used in accordance with various aspects of the present disclosure.

[0021]FIG. 11 depicts an exemplary treadmill (e.g., exercise device) according to particular embodiments.

[0022]FIG. 12 depicts a terrain simulation module, which may, for example, receive data and control one or more operations of an exercise system (e.g., such as in the context of a treadmill system described herein).

[0023]FIG. 13 depicts an exemplary skeletal mapping of a treadmill user, which may, for example, be generated by the system using one or more imaging devices, and used in the identification of one or more gestures made by the user.

[0024]FIG. 14 depicts a diagrammatic representation of a user gait and stride length determination made by the system for use in various implementations of the system.

[0025]FIG. 15 depicts a treadmill according to other embodiments in which a pivot point enabling an incline and/or decline of the treadmill is positioned in a more central location.

[0026]FIGS. 16 depicts additional embodiments of a treadmill having a central pivot point at varying levels of incline.

DETAILED DESCRIPTION

[0027] Various embodiments now will be described more fully hereinafter with reference to the accompanying drawings. It should be understood that the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout.

OVERVIEW

[0028] In various embodiments, an adaptive exercise system (i.e., an ambulation simulation system) may include one or more custom treadmill hardware devices and one or more accompanying pieces of software and a control system which may, for example, be configured to work in tandem to simulate one or more virtual terrains within a game on a physical treadmill. The system may, for example, be utilized in one or more sport training, entertainment, rehabilitation, and other contexts. In various embodiments, the system is configured to generate custom game-terrains for walking, hiking, running, etc. In particular embodiments, the system is configured to enable a user to control a direction of a virtual avatar as the avatar traverses the virtual terrain (e.g., while the user is walking and/or running on the treadmill). The system may then be configured to manipulate the treadmill (i.e., an incline of the treadmill, speed of the treadmill, etc.) based on the terrain that the avatar is currently traversing. In particular embodiments, the system may utilize one or more imaging devices to generate a skeletal mapping of a user in order to identify particular poses and gestures performed by the user. In this way, the system may be configured provide hands free control to the user while the user is using the treadmill such that the user can move through the virtual environment (as it is displayed on a display screen) while providing input via any suitable system input described herein and physically walking/running through the environment by walking/running on the treadmill.

[0029] In various embodiments, the system is configured to utilize any suitable rapid incline/decline lifting system described herein (e.g., described above in the context of the system). In this way, the system is configured to simulate rolling hills, sudden drop-offs, and other features. The treadmill’s rapid incline/decline mechanism enables immediate physical stimulus modification in response to thermal state detection. When the system detects thermal signatures indicative of cognitive overload (escalating periorbital warming, nasal cooling exceeding productive range), it can reduce physical difficulty within seconds by adjusting incline. This latency between thermal state detection and physical environment change may prevent cognitive overload from escalating to distress, and for maintaining the precise balance required for flow state.

[0030] Conventional treadmills with slower incline mechanisms cannot achieve this response time, making closed-loop thermal-cognitive adaptation impractical. The rapid mechanical response described herein enables precise flow state maintenance by continuously adjusting physical challenge to match the user’s real-time cognitive-thermal state.

[0031]Conventional treadmills use a worm screw lift mechanism almost universally to create incline and for the few that decline. The mechanisms use require as much as 30 – 45 seconds to reach a 15% incline grade and to about the same to return to flat and when going to a decline( normally about 6 % decline) take from 15 to 25 seconds on various popular brands. Contrast this to the center pivot treadmill that can achieve full inclines in less than 2 seconds and full decline in about 1 second. The benefit of this is that rapid and importantly precise adjustments can be made to moderate exertion levels from crossing over to undesirable physical and/or cognitive states.

[0032] In some embodiments, the system is configured to modify the virtual environment in response to the user’s current exertion level. For example, if the user’s exertion level is below or above a desired exertion level, the system may automatically modify the virtual terrain or other planned running/walking course to increase or decrease the difficult of the course (increasing or decreasing the incline level of the course and therefore of the treadmill). In various embodiments, the system combines live biomechanical data with physiological signals (such as heart rate from integrated BLE sensors, thermal imaging data, and the like) in a closed-loop control system to continuously adjust the treadmill’s virtual course (e.g., slope, curvature, pace zones, etc.) and training parameters.

Example Computing Environment

[0033]FIG. 1 depicts an example of a computing environment that can be used for providing adaptive exercise systems in accordance with various aspects of the present disclosure. In various aspects, an adaptive exercise system 100 is provided within the computing environment that includes software components and/or hardware components to facilitate modification of exercise equipment attributes based on user context and other features. For instance, the adaptive exercise system 100 may provide a virtual exercise environment or other service that is accessible over one or more networks 150 (e.g., the Internet) by a user accessing a user application 122 on a user computing device 120. In other aspects, the adaptive exercise system 100 may provide such platforms for users of an exercise device 1000. The exercise device may include, for example, a display device 1005, one or more imaging devices 900, etc. In some aspects, the adaptive exercise system 100 may be accessible via a suitable user interface 1010 on the display device 1005. In some embodiments, the exercise device may include any suitable exercise device (e.g., bike, treadmill, rowing machine, etc.), such as any exercise device described in U.S. Patent No. 11,465,031, issued October 11, 2022, entitled “Ambulation systems, terrain simulation systems, treadmill systems, and related systems and methods,” which is hereby incorporated herein in its entirety.

[0034]Here, adaptive exercise system 100 may provide the user computing device 120 (e.g., or exercise device 1000 such as a connected exercise device) with one or more graphical user interfaces (e.g., webpages, software applications, etc.) through the service to access adaptive exercise system 100. The user may use the service in performing functionality associated with accessing a virtual environment that the user may traverse with the exercise device 1000. For example, the adaptive exercise system 100 may provide customized user interfaces that modified according to user context data which in turn may cause the system to modify one or more attributes of the exercise device 1000 (incline, speed, etc.). In this way, the adaptive exercise system 100 may provide graphical user interfaces that provide more adaptive exercise functionality that is more tuned to the particular user, the current context of the user’s level of exertion, the user’s training goals, and the like.

[0035]In addition to the graphical user interfaces, the adaptive exercise system 100 may include one or more interfaces (e.g., application programming interfaces (APIs)) for communicating and/or accessing the third party computing system(s) 170 over the network(s) 150. For instance, the adaptive exercise system 100 may access a third party computing system 170 via one of the interfaces to access user data, sensor data, or third party computing component data for providing more user-specific exercise adaptations. For example, the adaptive exercise system 100 may access a third party computing system 170 that stores heart rate data, fitness data, baseline exertion data, or other user-specific data that may drive modifications to the virtual terrain, exercise devices settings or attributes, and the like.

[0036] In some instances, the adaptive exercise system 100 may include one or more repositories 140 that can be used for storing data related to the user, such as device data, profile data, and other data related to user context, etc.  In other aspects, the one or more repositories 140 may store data related to accessible virtual terrains, interface modifications, etc.

[0037] In some aspects, the adaptive exercise system 100 executes an equipment modification module 200 for automatically adjusting one or more aspects of a piece of exercise equipment (e.g., treadmill setting) based on user context data. In other aspects, the system executes an exertion determination module 300 for determining a current exertion level of a user, for example, to modify the exercise system or identify a baseline exertion level of the user. In other examples, the system executes an exertion optimization module 500 to modify system properties to adjust the user’s exertion level according to one or more user goals, training goals, etc. In other aspects, the system executes a virtual environment modification module 600 to adjust or modify a user interface or virtual environment based on user context. In other aspects, the system executes a user context determination module 70 to determine user context data for the user.

[0038] Further detail is provided below regarding the configuration and functionality of the equipment modification module, 200, exertion determination module 300, exertion optimization module 500, virtual environment modification module 70, and user context determination module 70 according to various aspects of the disclosure.

[0039] The number of devices depicted in FIG. 1 are provided for illustrative purposes.  In some aspects, different number of devices may be used.  In various aspects, for example, while certain devices or systems are shown as single devices in FIG. 1, multiple devices may instead be used to implement these devices or systems.

[0040] In some aspects, the context-based gaming modification computing system 100 can include one or more third-party devices such as, for example, one or more servers operating in

[0041]a distributed manner.  The context-based gaming modification computing system 100 can include any computing device or group of computing devices, and/or one or more server devices.

[0042] Although the data repository 140 is shown as a single component, these components 140 may include, in other aspects, a single server and/or repository, servers and/or repositories, one or more cloud-based servers and/or repositories, or any other suitable configuration.

Equipment Modification Module

[0043] Turning now to FIG. 2, additional details are provided regarding an equipment modification module 200. For instance, the flow diagram shown in FIG. 2 may correspond to operations executed by computing hardware found in the adaptive exercise system 100 as it executes the equipment modification module 200.

[0044] At operation 202, the system accesses user context data. The user context data may include any suitable data described herein. This may include, for example, user context that can be captured using one or more wearables. Wrist-worn and body-worn wearable devices (including but not limited to Garmin, Apple Watch, Whoop, Fitbit, Oura, and similar devices) may be configured to capture modalities that can be captured at the wrist, chest, or finger. These include optical heart rate (photoplethysmography), heart rate variability (derived from HR signal), accelerometer-based motion, galvanic skin response (limited devices), skin temperature at point of contact, and SpO2 (pulse oximetry). Other user context data can include user context derived in the context of the user context determination module 70 described below.

[0045] At operation 204, the system modifies at least one exercise equipment attribute based on the user context data. This may include, for example, treadmill speed, incline or decline. In some embodiments the system modifies the equipment based on the user context being outside of a desired range. The system may, for example, identify that the user is working too hard (or not hard enough) and adjust the equipment until the user context is in a desired range.

[0046]For illustrative purposes, the equipment modification module 200is described with reference to implementations described above with respect to one or more examples described herein. Other implementations, however, are possible. In some aspects, the steps in FIG. 2 may be implemented in program code that is executed by one or more computing devices such as the adaptive exercise 100, the user device 120, or other system in FIG. 1. In some aspects, one or more operations shown in FIG. 2 may be omitted or performed in a different order. Similarly, additional operations not shown in FIG. 2 may be performed.

Exertion Determination Module

[0047] Turning now to FIG. 3, additional details are provided regarding an exertion determination module 300. For instance, the flow diagram shown in FIG. 3 may correspond to operations executed by computing hardware found in the adaptive exercise system 100 as it executes the module 300.

[0048] At operation 302, the system captures user imaging data. The imaging data may include thermal imaging data. In some embodiments, the thermal imaging data may be used to derive, for example: facial thermal distribution patterns, periorbital temperature changes indicating cognitive load, nasal tip temperature changes indicating stress response (Pinocchio Effect), forehead thermal patterns indicating cardiovascular distribution, upper body thermal gradients indicating exertion distribution, thermal asymmetries indicating physiological imbalance, respiratory thermal signatures at the nostrils, micro-expressions of thermal change preceding conscious awareness of state change, perspiration based cooling rate that predicts stress level and also potential for dehydration before the person becomes aware of it. FIG. 4 depicts an exemplary temperature map of a user, from which the system may derive the infrared data described herein.

[0049]At operation 304, the system derives facial temperature/coloring form the imaging data. The system computes several discriminating features in real time from the thermal image stream: Perinasal temperature delta: The single most validated marker. A sudden drop of 0.1–0.2°C at the nose tip relative to the cheeks, in the absence of a corresponding increase in overall facial temperature, signals sympathetic arousal from psychological stress rather than exercise heat load; Forehead-to-nose gradient: During exercise, both regions warm together proportionally. During anxiety, the forehead warms or holds steady while the nose cools, creating a divergent gradient absent in normal exertion; Rate of change and symmetry: Exercise-driven thermal change is slow, bilateral, and monotonically tracks workload. Psychological stress produces rapid, asymmetric shifts uncorrelated with metabolic demand.

[0050] Temporal correlation with exertion: Because the system independently measures movement intensity, speed, and gesture patterns via skeletal tracking, it can assess whether a thermal signature is proportionate to the current workload. A perinasal cooling spike during low-intensity walking, for example, is disproportionate to the exercise load and indicates a psychological rather than physical stress response.

[0051]At operation 306 the system may analyze user gait. FIG. 14 depicts a diagram indicating the system tracking a user’s stride length and gait. As may be understood from this disclosure, the system may be configured to determine, based on the skeletal mapping discussed herein: (1) a user’s gait width; (2) a users’ stride length (e.g., based on the distance between the landing of the user’s feet and a distance of belt travel between footsteps; (3) a velocity of each respective foot, etc.).

[0052]In particular embodiments, as part of the analysis, the system is configured to record information about a user’s gait characteristics, cadence, etc. in order to identify changes over time. For example, a user rehabilitating a leg injury may initially walk with a limp. The system may be configured to identify, based on the user’s skeletal mapping, one or more characteristics of the user’s limp such as: (1) the user favoring one particular leg over another; (2) the user leaning to one side; (3) one or more limits to the user’s speed or ability to navigate certain levels of incline, etc. In various embodiments, the system may be able to track improvements to the user’s gait over time in order to identify completion of a user’s rehabilitation from an injury that caused the limp.

[0053] In particular embodiments, the system is configured to track a respective position of each of the user’s feet as the user is running/walking on the treadmill. The system may then be configured to substantially automatically adjust a belt speed of the treadmill (e.g., on-the-fly) as the user increases or decreases their speed. For example, the system may be configured to monitor a change in position of each foot and cause the motor driving the belt to advance a distance based on the user’s instantaneous stride length (i.e., of each leg). In this way, the system may be configured to enable a user to adjust to any changes in terrain (i.e., incline, etc.) that the user may encounter while using the treadmill without having to provide any input to increase or decrease the belt speed (e.g., gesture input, button input, etc.). As the user’s stride length increases, for example, the system may automatically increase the speed of the treadmill. In response to measuring a decrease in the user’s stride length (e.g., at a higher incline level), the system may be configured to decrease the speed of the treadmill.

[0054] At operation 308, the system may identify one or more user behavioral signals. The behavioral signals may include, for example, hesitation patterns, postural tension, slouching , excessive arm swinging, heart rate, and gesture frequency shifts

[0055] At operation 310, the system determines exertion level for the user based on one or more factors described above. In some embodiments, the system does not rely on thermal data alone to classify stress type. It fuses three streams: (a) movement and exertion metrics from skeletal tracking, representing expected thermal load; (b) the thermal facial signature from IR, representing actual autonomic state; and (c) behavioral signals including hesitation patterns, postural tension, slouching , excessive arm swinging, and gesture frequency shifts.

[0056] When exercise stress is productive, these streams are coherent: exertion is elevated, thermal output is proportional, and movement patterns are fluid. When the user is psychologically overwhelmed, the streams diverge: thermal shows sympathetic arousal disproportionate to workload, and movement becomes hesitant or disengaged. This coherence/divergence analysis enables the system to distinguish a session of productive challenge from one of anxiety or frustration—even when heart rate and duration appear identical from the outside.

[0057] This multi-modal fusion—correlating thermal signature against independently measured exertion to identify the nature of the stress response—constitutes a novel claim space. The prior art on thermal stress detection exists predominantly in seated or static contexts (driver monitoring, interrogation research, clinical settings). Applying it in a dynamic exercise environment where the system maintains a known metabolic baseline for comparison is a meaningfully different problem. 

[0058] This feature is particularly attractive for persons of impaired cognitive ability who may not have the comprehension of their mental to physical state correlates and have a bad experience but are not able to emote sufficiently themselves. The data our multi-modal fusion approach collects in real time can allow for intervention before the benefits of a session are lost due to distress that is not identified in time.

[0059] Heart rate-based fatigue indicators and heart rate zone management are known methods for maintaining a user within a target physiological stress level during exercise. However, these methods are limited to detecting metabolic demand and cannot distinguish between physical exertion and cognitive or emotional stress overlays introduced by immersive content.

[0060] The infrared thermal imaging system of the present invention addresses this limitation by detecting sympathetic nervous system activation independent of exercise intensity. By way of example, consider two scenarios in which a user runs at an identical speed and incline: in the first, the user runs through a passive meadow environment; in the second, the user engages in a simulated fireman drill requiring time-critical decisions to rescue virtual occupants and protect virtual property. The physical workload — and therefore heart rate and perceived exertion — remain substantially identical in both scenarios. However, the cognitive and emotional demands of the rescue scenario activate sympathetic pathways that produce measurable thermal signatures, including perinasal cooling and forehead-to-perinasal gradient divergence, that are layered on top of the exercise-induced thermal baseline. Only the infrared thermal imaging method detects this additional autonomic response; heart rate-based systems are physiologically unable to differentiate between these two fundamentally different stress states.

[0061] For illustrative purposes, the exertion determination module 300 is described with reference to implementations described above with respect to one or more examples described herein. Other implementations, however, are possible. In some aspects, the steps in FIG. 3 may be implemented in program code that is executed by one or more computing devices such as the adaptive exercise 100, the user device 120, or other system in FIG. 1. In some aspects, one or more operations shown in FIG. 3 may be omitted or performed in a different order. Similarly, additional operations not shown in FIG. 3 may be performed.

Exertion Optimization Module

[0062] Turning now to FIG. 5, additional details are provided regarding an exertion optimization module 500. For instance, the flow diagram shown in FIG. 5 may correspond to operations executed by computing hardware found in the adaptive exercise system 100 as it executes the exertion optimization module 500.

[0063] At operation 502, the system determines the user exertion level, for example, using the process described above with respect to FIG. 3.

[0064] At operation 504, the system accesses user training data. The user training data may indicate one or more fitness or cognitive goals of the user. For example, the user may have a particular training regimen that requires particular time spent exercising in particular fitness zones (e.g., heart rate, speed, etc.)

[0065]At operation 506, the system modifies the exercise equipment based on the exertion level and training data. This may include, for example, increasing the effort required by the user if their exertion level is too low (e.g., by increasing belt speed, increasing incline, etc.). FIG. 6A and FIG. 6B depicts an exemplary course change. If the user, for example, is over-exerting, the system may modify a course to decrease an incline level in a hill section (62A to 62B).

Virtual Environment Modification Module

[0066] Turning now to FIG. 7, additional details are provided regarding a virtual environment modification module 600. For instance, the flow diagram shown in FIG. 2 may correspond to operations executed by computing hardware found in the adaptive exercise system 100 as it executes the module 600.

[0067] At operation 602, the system determines the user exertion level, for example, using the process described above with respect to FIG. 3.

[0068] At operation 604, the system accesses user training data. The user training data may indicate one or more fitness or cognitive goals of the user, or any other suitable goal described herein.

[0069] At operation 606, the system modifies the virtual environment based on user exertion level and training data. The treadmill's immersive content is procedurally generated to respond to the user's current state as expressed by the fused thermal and skeletal pose data. When the system detects indicators of a contented, relaxed state, it pattern-matches to similar scenes and trails, reinforcing the positive experience. When stress indicators are detected, the system initiates a gradual transition in scene composition—for example, shifting from a steep, dark wooded forest to a bright, gently undulating seaside environment—and monitors the user's thermal response to assess whether the intervention is effective. This process continues iteratively, with the system progressively adjusting environmental parameters until less stressful thermal indicators are observed, thereby closing the adaptive feedback loop. In some embodiments, the system adjust the virtual environment to corelate to the change in exercise device (e.g., treadmill) settings described herein).

User Context Determination Module

[0070] Turning now to FIG. 8, additional details are provided regarding a user context determination module 70. For instance, the flow diagram shown in FIG. 8 may correspond to operations executed by computing hardware found in the adaptive exercise system 100 as it executes the module 70.

[0071] At operation 72, the system receives user data. The user data may include, for example, user age, gender, weight and other data.

[0072] At operation 74, the system receives user imaging data. Various embodiments of the system employ an infrared thermal camera positioned forward of and facing the user to capture continuous thermal imagery of the face and upper body during exercise. Cognitive load—the total mental demand imposed on working memory during task performance—produces measurable changes in facial thermal distribution via the autonomic nervous system (ANS). These changes are invisible to wearable devices and constitute the primary novel sensing contribution of the invention.

[0073] Cognitive effort activates the sympathetic branch of the autonomic nervous system, triggering measurable redistribution of blood flow. As mental demand increases, vasoconstriction occurs in peripheral facial regions (particularly the nasal tip and skin above the sinuses), while vasodilation occurs in periorbital tissues surrounding the eyes. These hemodynamic shifts produce thermal changes detectable by infrared camera with sub-second latency.

[0074] The periorbital region—the tissue surrounding the inner canthus of the eye—is one of the most responsive facial thermal regions to cognitive and emotional state changes. Increased mental effort produces measurable warming in this region, driven by vasodilation of the periorbital vasculature under sympathetic activation. Periorbital thermal response has been validated using functional Near-Infrared Spectroscopy (fNIRS) as a concurrent neural measure, confirming that facial thermal changes are intimately linked to cortical cognitive activity.

[0075]The nasal tip region exhibits the strongest and most consistent thermal response to cognitive load across the published literature. demonstrated that facial temperatures decrease as participants perform tasks of increasing difficulty, with the strongest effect concentrated above the sinuses and at the tip of the nose demonstrated that a commercial thermal camera monitoring forehead and nose temperature changes could detect different levels of cognitive load with an average detection latency of only 0.7 seconds after stimulus exposure.

[0076] During dual-task exercise on the adaptive treadmill, the system establishes individualized thermal baselines during initial low-cognitive-load treadmill use. Thereafter, as the system introduces progressive layers of cognitive loading—visual complexity, auditory loading, navigation demands, balance perturbation via rapid incline/decline changes, and explicit dual-task challenges—the system detects changes in facial thermal patterns relative to baseline.

[0077] At operation 76, the system causes at least one of a rules-based model or a machine-learning model to identify a user context from the user data and imaging data. In various embodiments, the system may process the imaging data and user data to determine a user context or flow state.

[0078] The derived user context (i.e., flow state) may indicate the psychological state of absorbed, effortless attention during optimally challenging activity—produces a characteristic thermal signature: moderate, stable deviations from baseline in periorbital and nasal regions, absence of acute stress markers (no rapid nasal cooling, no escalating periorbital warming), and overall pattern consistency indicative of sustained attentional engagement without overload.

[0079] The system optionally classifies three states based on the composite thermal signature: (a) under-challenged/disengaged, where thermal patterns return toward baseline indicating insufficient cognitive demand; (b) optimally challenged/flow state, the target condition with moderate stable deviations and absence of stress markers; and (c) overloaded/distressed, where thermal patterns exceed individualized thresholds indicating the need for immediate difficulty reduction.

[0080] The system distinguishes between the three states based on thermal signature dynamics relative to an individualized baseline. Under-challenged or disengaged states are characterized by thermal patterns that drift toward resting baseline, indicating insufficient cognitive or physical demand to sustain elevated engagement. The optimal flow state exhibits moderate, stable deviations from baseline — elevated but consistent thermal activity in periorbital and perinasal regions without rapid fluctuation — indicating sustained attentional engagement without autonomic stress response. Overloaded or distressed states are identified by acute stress markers: rapid perinasal cooling, escalating forehead-to-nose gradient divergence, or thermal variability exceeding individualized thresholds, signaling the need for immediate difficulty reduction.  The definition of flow and the system's optimization target vary by use context. In an athletic training setting, flow represents the zone where the user is physically challenged but not overexerted or approaching dehydration — the system modulates terrain and pace to maintain progressive improvement on user-selected metrics such as speed, endurance, or heart rate control. In a cognitive engagement setting, flow represents absorbed mental attention — the system modulates scene complexity, task demands, and audio or music cues to sustain that state. In both contexts, the thermal and skeletal fusion provides the real-time feedback that enables the system to hold the user in the target zone, but the specific inputs and intervention strategies differ based on the session objective. 

[0081] Accordingly, the machine learning model may be configured using a variety of different types of supervised or unsupervised trained models such as, for example, support vector machine, naive Bayes, decision tree, neural network, and/or the like.

[0082] The system distinguishes between the three states based on thermal signature dynamics relative to an individualized baseline. Under-challenged or disengaged states are characterized by thermal patterns that drift toward resting baseline, indicating insufficient cognitive or physical demand to sustain elevated engagement. The optimal flow state exhibits moderate, stable deviations from baseline — elevated but consistent thermal activity in periorbital and perinasal regions without rapid fluctuation — indicating sustained attentional engagement without autonomic stress response. Overloaded or distressed states are identified by acute stress markers: rapid perinasal cooling, escalating forehead-to-nose gradient divergence, or thermal variability exceeding individualized thresholds, signaling the need for immediate difficulty reduction.  The definition of flow and the system's optimization target vary by use context. In an athletic training setting, flow represents the zone where the user is physically challenged but not overexerted or approaching dehydration — the system modulates terrain and pace to maintain progressive improvement on user-selected metrics such as speed, endurance, or heart rate control. In a cognitive engagement setting, flow represents absorbed mental attention — the system modulates scene complexity, task demands, and audio or music cues to sustain that state. In both contexts, the thermal and skeletal fusion provides the real- time feedback that enables the system to hold the user in the target zone, but the specific inputs and intervention strategies differ based on the session objective. 

System Performance Improvements and User-Specific Optimization

[0083] In various embodiments, the system may prevent overtraining by detecting thermal stress before injury risk, optimizes training stimulus by maintaining challenge without overwhelm, enables longer productive training sessions by managing fatigue, and personalizes intensity in real-time beyond what heart rate alone enables. As described in the preceding sections, the system detects subconscious physiological cues from the user's fused thermal and skeletal data — cues that the user may not be aware of or able to articulate. Based on these signals, the system adjusts scene environment, terrain difficulty, and cognitive load elements in real time to maintain the user within an optimal challenge zone. This closed-loop modulation maximizes session value across three dimensions: physical training stimulus, psychological stress management, and cognitive engagement — enabling longer, more productive sessions than would be possible using heart rate-based feedback alone. 

[0084] Thermal patterns indicate readiness for the next interval, improving interval training precision. The rate at which facial thermal signatures return toward baseline following an interval indicates the user’s recovery state with finer temporal resolution than HR-based recovery detection alone. Thermal stress indicators precede form breakdown. Various embodiments of the system reduces intensity before biomechanical compensation occurs, which is particularly valuable for fatigue-related injury prevention. When thermal patterns indicate accumulating fatigue stress before the user is consciously aware of decline, the system can proactively reduce demands.

[0085] In still other embodiments, the system detects cognitive overload before task failure, enables precise titration of cognitive challenge, prevents frustration and disengagement from excessive difficulty, and maximizes neuroplastic benefit by maintaining the optimal challenge zone. The thermal closed-loop ensures that cognitive challenge stays within the productive range—the zone where dual-task training produces maximum benefit. In still other aspects, user context and/or flow state induction requires and reinforces focused attention. Thermal feedback enables real-time attention state awareness. Over successive sessions, progressive training of attention capacity becomes possible as the system learns each user’s attention-thermal profile and adjusts challenge accordingly.

[0086] In some embodiments, the system trains attention capacity progressively by calibrating cognitive load to the user's current capability and expanding that capability over successive sessions. During each session, the system introduces cognitive demands — such as collecting game elements, following navigation instructions, or responding to decision prompts — while monitoring thermal signatures for stress indicators. When the user maintains a stable thermal profile (moderate elevation without acute stress markers) under a given cognitive load, the system incrementally increases task complexity in subsequent sessions. Over time, the user develops the capacity to sustain focused attention under higher cognitive demands without triggering the thermal signatures associated with overwhelm or frustration. Conversely, if load is insufficient and thermal patterns drift toward disengaged baseline, the system increases challenge to maintain engagement. This closed-loop progression prevents both frustration-induced dropout and boredom-induced disengagement, enabling systematic attention training tailored to each user's evolving capacity.

[0087] In particular aspects, the system supports task-switching under physical load, inhibition tasks during exercise, and working memory challenges with adaptive difficulty. Thermal monitoring ensures that challenge stays productive—preventing the shift from beneficial executive function training to counterproductive overload.

[0088] In particular embodiment, user context and/or flow state induction interrupts rumination and worry cycles. Thermal detection of anxiety (nasal cooling, periorbital warming escalation) enables preemptive intervention before the user experiences conscious distress. Exercise itself has anxiolytic effects; the system optimizes delivery by preventing overexertion that could paradoxically increase anxiety. Graded exposure to challenge builds stress tolerance. Measurable reduction in thermal stress markers over sessions provides objective evidence of progress.

[0089] In some embodiments, Exercise-induced mood enhancement is optimized by preventing overexertion. Achievement and mastery experiences from well-calibrated challenge counter anhedonia. Session logging provides objective progress evidence that counters negative self-assessment.

[0090]In various embodiments, controlled stress exposure with thermal safety monitoring enables immediate difficulty reduction if stress markers spike. Non-verbal monitoring is critical for trauma populations who may not self-report accurately. At the clinical camera tiers (Boson 640, A500/A700), the spatial resolution is sufficient for fine-grained stress detection that could detect early onset of a trauma response before it reaches conscious intensity.

[0091] In still other embodiments, cognitive training under physical load supports neuroplasticity. Thermal monitoring prevents overstimulation that could exacerbate symptoms. Objective tracking of cognitive performance over the rehabilitation course, via session-over-session comparison of thermal response patterns, provides quantifiable evidence of progress. Non-verbal assessment is valuable for patients with communication difficulties. Clinical camera tiers enable integration with clinical protocols and reporting via GigE Vision interfaces and FLIR Research Studio.

[0092] Dual-task training has been shown to benefit cognitive reserve. Thermal monitoring ensures safety and prevents distress. Engaging virtual environments increase compliance. Caregiver/clinician dashboards enabled by clinical camera tiers provide progress monitoring. Early detection of thermal stress patterns may indicate cognitive decline.

[0093] In various other embodiments, progressive exposure to controlled stressors, combined with the biofeedback loop (where the user can observe their thermal stress response), trains the user to maintain performance under stress. Applications include athletes, first responders, and military personnel.

Example Technical Platforms

[0094] Aspects of the present disclosure may be implemented in various ways, including as computer program products that comprise articles of manufacture. Such computer program products may include one or more software components including, for example, software objects, methods, data structures, and/or the like. A software component may be coded in any of a variety of programming languages. An illustrative programming language may be a lower-level programming language such as an assembly language associated with a particular hardware architecture and/or operating system platform. A software component comprising assembly language instructions may require conversion into executable machine code by an assembler prior to execution by the hardware architecture and/or platform. Another example programming language may be a higher-level programming language that may be portable across multiple architectures. A software component comprising higher-level programming language instructions may require conversion to an intermediate representation by an interpreter or a compiler prior to execution.

[0095] Other examples of programming languages include, but are not limited to, a macro language, a shell or command language, a job control language, a script language, a database query, or search language, and/or a report writing language. In one or more example aspects, a software component comprising instructions in one of the foregoing examples of programming languages may be executed directly by an operating system or other software component without having to be first transformed into another form. A software component may be stored as a file or other data storage construct. Software components of a similar type or functionally related may be stored together such as, for example, in a particular directory, folder, or library. Software components may be static (e.g., pre-established, or fixed) or dynamic (e.g., created or modified at the time of execution).

[0096] A computer program product may include a non-transitory computer-readable storage medium storing applications, programs, program modules, scripts, source code, program code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like (also referred to herein as executable instructions, instructions for execution, computer program products, program code, and/or similar terms used herein interchangeably). Such non-transitory computer-readable storage media include all computer-readable media (including volatile and non-volatile media).

[0097] In some aspects, a non-volatile computer-readable storage medium may include a floppy disk, flexible disk, hard disk, solid-state storage (SSS) (e.g., a solid-state drive (SSD), solid state card (SSC), solid state module (SSM)), enterprise flash drive, magnetic tape, or any other non-transitory magnetic medium, and/or the like. A non-volatile computer-readable storage medium may also include a punch card, paper tape, optical mark sheet (or any other physical medium with patterns of holes or other optically recognizable indicia), compact disc read only memory (CD-ROM), compact disc-rewritable (CD-RW), digital versatile disc (DVD), Blu-ray disc (BD), any other non-transitory optical medium, and/or the like. Such a non-volatile computer-readable storage medium may also include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory (e.g., Serial, NAND, NOR, and/or the like), multimedia memory cards (MMC), secure digital (SD) memory cards, SmartMedia cards, CompactFlash (CF) cards, Memory Sticks, and/or the like. Further, a non-volatile computer-readable storage medium may also include conductive-bridging random access memory (CBRAM), phase-change random access memory (PRAM), ferroelectric random-access memory (FeRAM), non-volatile random-access memory (NVRAM), magnetoresistive random-access memory (MRAM), resistive random-access memory (RRAM), Silicon-Oxide-Nitride-Oxide-Silicon memory (SONOS), floating junction gate random access memory (FJG RAM), Millipede memory, racetrack memory, and/or the like.

[0098]In some aspects, a volatile computer-readable storage medium may include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), fast page mode dynamic random access memory (FPM DRAM), extended data-out dynamic random access memory (EDO DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), double data rate type two synchronous dynamic random access memory (DDR2 SDRAM), double data rate type three synchronous dynamic random access memory (DDR3 SDRAM), Rambus dynamic random access memory (RDRAM), Twin Transistor RAM (TTRAM), Thyristor RAM (T-RAM), Zero-capacitor (Z-RAM), Rambus in-line memory module (RIMM), dual in-line memory module (DIMM), single in-line memory module (SIMM), video random access memory (VRAM), cache memory (including various levels), flash memory, register memory, and/or the like. It will be appreciated that where various aspects are described to use a computer-readable storage medium, other types of computer-readable storage media may be substituted for or used in addition to the computer-readable storage media described above.

[0099] Various aspects of the present disclosure may also be implemented as methods, apparatuses, systems, computing devices, computing entities, and/or the like. As such, various aspects of the present disclosure may take the form of a data structure, apparatus, system, computing device, computing entity, and/or the like executing instructions stored on a computer-readable storage medium to perform certain steps or operations. Thus, various aspects of the present disclosure also may take the form of entirely hardware, entirely computer program product, and/or a combination of computer program product and hardware performing certain steps or operations.

[0100] Various aspects of the present disclosure are described below with reference to block diagrams and flowchart illustrations. Thus, each block of the block diagrams and flowchart illustrations may be implemented in the form of a computer program product, an entirely hardware aspect, a combination of hardware and computer program products, and/or apparatuses, systems, computing devices, computing entities, and/or the like carrying out instructions, operations, steps, and similar words used interchangeably (e.g., the executable instructions, instructions for execution, program code, and/or the like) on a computer-readable storage medium for execution. For example, retrieval, loading, and execution of code may be performed sequentially such that one instruction is retrieved, loaded, and executed at a time. In some examples of aspects, retrieval, loading, and/or execution may be performed in parallel such that multiple instructions are retrieved, loaded, and/or executed together. Thus, such aspects can produce specially configured machines performing the steps or operations specified in the block diagrams and flowchart illustrations. Accordingly, the block diagrams and flowchart illustrations support various combinations of aspects for performing the specified instructions, operations, or steps.

Example System Architecture

[0101]FIG. 9 is a block diagram of an example of a system architecture that can be used for adapting exercise systems based on user context as described herein. As may be understood from FIG. 9, the system architecture in some aspects may include an adaptive exercise system 100 that comprises one or more servers 1102 and a data repository 140. The data repository 140 may be made up of computing components such as servers, routers, data storage, networks, and/or the like that are used on the adaptive exercise system 100 to store user data, context data, and gaming data.

[0102] As previously noted, the adaptive exercise system 100may provide gaming environment access over one or more networks 150. Here, a user may access the service via a user device 120. For example, the context-based gaming modification computing system 100 may provide the service through a website that is accessible to the user device 120 or exercise device 1000 via the one or more networks 150.

[0103] The server(s) 1102 may execute the various system modules as described herein. Further, according to particular aspects, the server(s) 1102 may provide one or more graphical user interfaces (e.g., one or more webpages, webform, and/or the like through the website) through which users can interact with the adaptive exercise system 100. Furthermore, the server(s) 1102 may provide one or more interfaces that allow context-based gaming modification computing system 100 to communicate with third-party computing system(s) 130 such as one or more suitable application programming interfaces (APIs), direct connections, and/or the like.

Example Computing Hardware

[0104]FIG. 10 illustrates a diagrammatic representation of a computing hardware device 1800 that may be used in accordance with various aspects. For example, the hardware device 1800 may be computing hardware such as a server 1102 as described in FIG. 9. According to particular aspects, the hardware device 1800 may be connected (e.g., networked) to one or more other computing entities, storage devices, and/or the like via one or more networks such as, for example, a LAN, an intranet, an extranet, and/or the Internet. As noted above, the hardware device 1800 may operate in the capacity of a server and/or a client device in a client-server network environment, or as a peer computing device in a peer-to-peer (or distributed) network environment. In some aspects, the hardware device 1800 may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a mobile device (smartphone), a web appliance, a server, a network router, a switch or bridge, or any other device capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that device. Further, while only a single hardware device 1800 is illustrated, the term “hardware device,” “computing hardware,” and/or the like shall also be taken to include any collection of computing entities that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

[0105] A hardware device 1800 includes a processor 1802, a main memory 1804 (e.g., read-only memory (ROM), flash memory, dynamic random-access memory (DRAM) such as synchronous DRAM (SDRAM), Rambus DRAM (RDRAM), and/or the like), a static memory 1806 (e.g., flash memory, static random-access memory (SRAM), and/or the like), and a data storage device 1818, that communicate with each other via a bus 1832.

[0106]The processor 1802 may represent one or more general-purpose processing devices such as a microprocessor, a central processing unit, and/or the like. According to some aspects, the processor 1802 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, a processor implementing other instruction sets, processors implementing a combination of instruction sets, and/or the like. According to some aspects, the processor 1802 may be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, and/or the like. The processor 1802 can execute processing logic 1826 for performing various operations and/or steps described herein.

[0107]The hardware device 1800 may further include a network interface device 1808, as well as a video display unit 1810 (e.g., a liquid crystal display (LCD), a cathode ray tube (CRT), and/or the like), an alphanumeric input device 1812 (e.g., a keyboard), a cursor control device11814 (e.g., a mouse, a trackpad), and/or a signal generation device 1816 (e.g., a speaker). The hardware device 1800 may further include a data storage device 1818. The data storage device 1818 may include a non-transitory computer-readable storage medium 1830 (also known as a non-transitory computer-readable storage medium or a non-transitory computer-readable medium) on which is stored one or more modules 1822 (e.g., sets of software instructions) embodying any one or more of the methodologies or functions described herein. For instance, according to particular aspects, the modules 1822 include any suitable module described herein. The one or more modules 1822 may also reside, completely or at least partially, within main memory 1804 and/or within the processor 1802 during execution thereof by the hardware device 1800 - main memory 1804 and processor 1802 also constituting computer-accessible storage media. The one or more modules 1822 may further be transmitted or received over a network 150 via the network interface device 1808.

[0108] While the computer-readable storage medium 1830 is shown to be a single medium, the terms “computer-readable storage medium” and “machine-accessible storage medium” should be understood to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” should also be understood to include any medium that is capable of storing, encoding, and/or carrying a set of instructions for execution by the hardware device 1800 and that causes the hardware device 1800 to perform any one or more of the methodologies of the present disclosure. The term “computer-readable storage medium” should accordingly be understood to include, but not be limited to, solid-state memories, optical and magnetic media, and/or the like.

System Operation

[0109]The logical operations described herein may be implemented (1) as a sequence of computer implemented acts or one or more program modules running on a computing system and/or (2) as interconnected machine logic circuits or circuit modules within the computing system. The implementation is a matter of choice dependent on the performance and other requirements of the computing system. Accordingly, the logical operations described herein are referred to variously as states, operations, steps, structural devices, acts, or modules. These states, operations, steps, structural devices, acts, and modules may be implemented in software, in firmware, in special purpose digital logic, and any combination thereof. Greater or fewer operations may be performed than shown in the figures and described herein. These operations also may be performed in a different order than those described herein.

Additional System Components and Features

[0110] As may be understood in light of this disclosure, a treadmill system 1000 may include a treadmill 800, which may, for example, include a display device 210 and one or more imaging devices 900 (e.g., and/or any suitable input device or combination of input devices, such as an infrared imaging device).

[0111]The treadmill configuration may provide a constrained imaging geometry that simplifies thermal capture compared to unconstrained research settings: the user's mean distance and angle relative to the camera remain fixed throughout the session, eliminating the tracking challenges associated with subjects who move freely through space, turn away from the sensor, or exit the field of view entirely. However, gait-induced motion — vertical oscillation of approximately 5–10 cm per stride at running pace, along with lateral sway and head rotation — introduces frame-to-frame positional variation that must be addressed. Thermal cameras in the relevant performance tiers (Lepton 3.5 at 9 Hz, Boson 320/640 at 9–60 Hz, FLIR A500/A700 at up to 30 Hz) lack optical image stabilization, and frame rates at the lower end of this range capture only a few samples per gait cycle. Accordingly, the system employs software-based frame registration, using head position data from the skeletal tracking subsystem to maintain consistent alignment of facial regions of interest across frames. This computational stabilization, combined with the fixed mean imaging geometry, enables reliable sub-ROI thermal analysis despite gait-induced motion — an approach that would be substantially more difficult to implement in settings where the subject's gross position is unconstrained.

[0112] In particular embodiments, the treadmill 800 may include any suitable treadmill, which may, for example, comprise any suitable belt-driven simulated running surface.

Virtual Terrain Simulation Systems

[0113]In particular embodiments, any treadmill system described herein (e.g., as discussed herein) may be integrated into a virtual terrain simulation system. As may be understood in light of the systems described herein, a treadmill system may provide one or more system inputs and system outputs to the virtual terrain simulation system by, for example: (1) providing system input to the virtual terrain simulation system such as requests for changes in speed, direction, incline, etc.; and (2) provide one or more system outputs by, for example, modifying a belt speed, belt angle, etc. in response to one or more conditions within the virtual terrain simulation systems.

[0114]In particular embodiments, the virtual terrain simulation system may include a mixed reality system in which a user of the treadmill system may interact with a virtual environment by providing input to the system and experiencing physical feedback through manipulation of one or more treadmill mechanisms while the user is using the treadmill. In particular embodiments, the user may view the virtual terrain system while on the treadmill using a suitable display screen, virtual reality headset, etc. In various embodiments, the system may provide a more engaging, realistic user experience for a user of a treadmill (e.g., in contrast with a traditional exercise class). In particular embodiments, a virtual camera may travel through the virtual environment based on both: (1) user inputs (direction change); and (2) treadmill settings (e.g., such as speed) such that the system displays (e.g., on the display screen 210) a substantially first-person view as the virtual camera traverses the virtual terrain. In this way, a user of the treadmill may experience a realistic walking and/or running through the virtual terrain.

[0115]FIGS. 11 depicts a treadmill system 1000 according to various embodiments. In various embodiments, the treadmill 800 may include a tread that extends between one or more front and rear rollers. In such embodiments, the system may enable a runner to run along the tread surface. In particular embodiments, the system is configured to substantially automatically speed up and slowdown in response to identifying a change in running speed of the runner. The system may, for example, determine a change in distance of the runner/rider from the front of the device and speed up and/or slow down the belt in order to maintain the runner in a desired location in the belt (e.g., as the runner is running). In this way, the system may be configured to avoid having to require a user to manually modify a speed of the belt. The system may, for example, use software to keep the runner in the center of the belt, by identifying a slowdown in the user’s gait (e.g., using one or more imaging devices, such as a Microsoft Kinect).

[0116] In particular embodiments, the treadmill may include one or more lifting mechanisms. In some embodiments, the one or more lifting mechanisms are configured to incline and/or decline a front or rear of the tread (e.g., and/or both the front and the rear) in order to modify an angle of the tread in order to simulate uphill and/or downhill walking/running. In particular embodiments, the system is configured to modify an incline and/or decline level of the treadmill based on one or more changes in terrain of a virtually generated terrain while the system is displaying the terrain on a display screen. For example, as a user’s avatar encounters a virtual terrain that has a particular incline level, the system may be configured to automatically modify an incline of the treadmill in response (i.e., the system may be configured to automatically modify the incline based on the incline of the virtual terrain). In this way, the system may be configured to simulate, via physical manipulation of the tread, a running/walking/jogging experience that substantially mirrors the terrain as a user’s avatar is traversing through the virtual terrain (e.g., and the system displays a first-person view of the movement through the terrain on the display screen).

Terrain Simulation System

[0117] Various functionality of the exercise device 1000 and system 100 may be implemented via various system modules. The system, when executing certain steps of such modules, may be configured to receive terrain and sensor data and, in response, send one or more control signals to one or more system components in order to manipulate a position, height, angle, or other orientation of an exercise device (e.g., treadmill). The system may perform the operations described in an order other than those in which they are presented in the various embodiments described herein. Various other embodiments of the system modules may perform steps in addition to those described or omit one or more of the described steps.

[0118]FIG. 12 depicts an overview of various operations performed by the treadmill system 1000 when executing a terrain simulation module 400. In particular embodiments, the system is configured to control one or more operations of a treadmill 800, such as the treadmill 800 shown in FIG. 11 (e.g., or other exercise device). In particular embodiments, such as the embodiment shown in FIG. 12, the system begins at Step 410 by receiving terrain data. The system may, for example, receive the terrain data from one or more terrain generation systems that includes, for example, physical terrain data such as altitude, angle, incline, terrain type, etc. In various embodiments, the system is configured to receive terrain data that corresponds to one or more real-world locations. In still other embodiments, the system is configured to generate a custom terrain, which may, for example, be based on a desired difficulty level of a user. In particular embodiments, the system is configured to determine slope data for the virtual terrain (e.g., slope data corresponding to a current position and direction of an avatar positioned within the virtual terrain) using any suitable technique. This may include for example, determining the slope data based on a grid, raster, digital elevation model, and or other suitable technique. In still other embodiments, the terrain data may include position data of an avatar within the virtual terrain and the physical terrain data may be based on the position data.

[0119]The system continues, at Step 420, by receiving one or more pieces of sensor data and/or user input data. The one or more pieces of sensor data may, for example, include one or more pieces of sensor data related to a position of one or more components of a bicycle ridden by a rider on a bicycle riding device. For example, the system may use one or more encoders, accelerometers, gyroscopes, or other suitable sensors/devices to determine, for example: (1) running speed; (2) angle of the rider/runner relative to the exercise device; (3) handlebar angle (e.g., in embodiments in which the exercise device includes a bicycle); (4) pose of the rider/runner; (5) tilt of a bicycle relative to the bicycle riding device (e.g., in embodiments in which the exercise device comprises a bicycle); and/or (6) any other suitable sensor data.

[0120] In various embodiments, the one or more pieces of sensor data, may, for example, include image data (e.g., received from one or more imaging devices). In particular embodiments, the treadmill system is configured to enable a user to control one or more features of the system using one or more physical gestures (i.e., as opposed to providing physical input via one or more physical controls such as buttons, knobs, levers, etc.). For example, the system may be configured to identify particular user gestures and perform one or more actions in response to an identified gesture. In various embodiments, the system may be configured to associate particular actions with respective gestures and to perform the associated action in response to identifying the respective gesture. In some embodiments, the particular actions may include, for example: (1) speeding up the tread; (2) slowing down the tread; (3) changing an orientation of an avatar relative to a virtually generated terrain (e.g., as discussed more fully herein); (4) causing the avatar to turn to the left and/or right; (5) causing the avatar to avoid one or more obstacles on the virtual terrain; (6) etc.

[0121]In various embodiments, gestures that may be associated with particular actions may include, for example: (1) raising or lowering a user’s hand; (2) placing one of the user’s limbs in a particular orientation; (3) changing the user’s position relative to a width of the tread (e.g., moving side to side); (4) jumping; (5) lifting a user’s knee; (6) increasing or decreasing the user’s running speed; and/or (7) any other suitable action which the system may be configured to identify.

[0122] In particular embodiments, as described herein, the treadmill system comprises one or more imaging devices 900 configured to generate a skeletal mapping (e.g., a substantially instantaneous skeletal map) of a user in order to identify one or more gestures performed by the user (e.g., based at least in part on a pose of the skeletal mapping). In various embodiments the one or more imaging devices may include any imaging device configured to identify key points in order to generate a skeletal mapping of a user (e.g., a Microsoft Kinect, Intel Realsense, iPhone, iPad, etc.). In other embodiments, the imaging device may be placed to track a particular user feature (e.g., foot, ankle, knee, leg, etc.). In some embodiments, the system is configured to determine user body positioning data based on one or more images (e.g., video images), one or more infrared images, etc. As may be understood from FIG. 13, the system may be configured to generate the skeletal mapping to determine a pose of the user.

[0123] Gesture inputs are inherently ambiguous when interpreted in isolation. The present system can resolve this ambiguity by interpreting gesture intent in the context of the user's concurrent thermal state. For example, a dismissive gesture from a user whose thermal signature indicates relaxed engagement is interpreted as a navigation command to skip or change content. The same dismissive gesture from a user exhibiting thermal indicators of psychological stress—such as perinasal cooling—is interpreted as a distress signal, prompting the system to reduce stimulation intensity or initiate a calming intervention rather than simply cycling to the next content option. This thermal-contextualized gesture interpretation is particularly valuable for cognitively impaired users who may instinctively gesture to push an experience away but lack the capacity to verbally articulate that they are overwhelmed. The fusion of gesture and thermal data enables the system to infer user intent beyond what either modality provides alone.

[0124]FIG. 13 depicts an example skeletal mapping of a user that may be generated from the one or more imaging devices 900. In various embodiments, The system may be configured to identify a variety of joints, bones, or other portions of an individual’s body such as, for example: (1) each of the user’s hands; (2) each of the user’s forearms; (3) each elbow; (4) each bicep; (5) each shoulder; (6) each hip; (7) each thigh; (8) each knee; (9) each foot; (10) the head; (11) the torso; (12) the top and bottom of the spine; (13) the waist; etc. In particular embodiments, the system is configured to identify and track additional points and features such as, for example: (1) individual bones; (2) joints of the fingers or toes; (3) individual features of the face, such as the nose and eyes; etc.

[0125] In various embodiments, the system is configured to enable the user to create gestures by performing particular movements. In some embodiments, a gesture may comprise a motion or pose by a user that the system is configured to capture as image data and parse for meaning. In various embodiments, particular gestures may include dynamic gestures, which may, for example, comprise a motion (e.g., lifting an arm at a particular speed, nodding a head, etc.). In still other embodiments, a gesture may include a static gesture, such as holding an arm up at a ninety-degree angle (e.g., to indicate a desire to stop the treadmill). In particular embodiments, a gesture may comprise more than one body part, such as clapping the hands together. In various embodiments, the system is configured to interpret any particular gesture as any particular user input (e.g., a first gesture may be associated with a first input type or action, a second gesture may be associated with a second input type or action, etc.). In particular embodiments, the system is configured to enable a user to assign particular action types or inputs to particular gestures.

[0126] In particular embodiments, the system is configured to interpret particular gestures as a system input. Gestures may be used for input in a general computing context. For example, as discussed above, particular gestures may correspond to particular movements of a user’s avatar within a game (i.e., virtual terrain). Still other movements and/or gestures may correspond to particular settings or changes to settings for the treadmill or other exercise device (e.g., speed, elevation/incline, etc.).

[0127] In still other embodiments, the system may utilize one or more additional components in order to track one or more aspects of a user’s body (i.e., movement, positioning, etc.) in order to determine one or more user actions (e.g., using one or more additional sensors or combination of sensors). The system may, for example, provide one or more tracking devices (e.g., comprising one or more accelerometers, gyroscopes, etc.) for placement on a particular portion of the user’s body (i.e., one or more wrists, one or more ankles, around the user’s chest, etc.). The one or more tracking devices may be configured to communicate with the system using any suitable wireless protocol (e.g., Bluetooth, zigbee, wireless LAN, NFC, etc.)

[0128] In various embodiments, each of the one or more motion trackers are configured to determine motion data for a respective portion of the user’s body on which the respective device is placed and relays the motion data to the system. The system may be configured to receive the motion data from the trackers and, in response, cause the treadmill system to modify one or more settings based on the motion data (e.g., an incline level of the treadmill, a speed of the treadmill, etc.). In still other embodiments, the system is configured to receive the motion data from the trackers and, in response, provide input to a connected gaming environment in which an avatar representing the user is traversing a virtual terrain (e.g., by modifying a direction of the avatar within the virtual terrain, causing the avatar to take one or more actions within the virtual terrain, etc.).

[0129] In particular embodiments the system is configured to use motion data received from one or more tracking devices in combination with other data (e.g., imaging data, pressure data from one or more pressure sensors, etc.) in order to determine one or more responsive actions (e.g., one or more responsive actions to cause the treadmill or other device to take or to use as one or more inputs in a virtual game).

[0130]In some embodiments, the system may include one or more force sensors (e.g., one or more accelerometers, one or more pressure sensitive resistors, etc.) embedded in a deck of the treadmill. In this way, the system may be configured to triangulate a position of a user’s foot upon impact of the treadmill’s belt. The system may use impact data for each foot to determine, for example: (1) foot position; (2) stride length; (3) foot pressure (e.g., impact pressure); (4) etc. In various embodiments, the system may be configured to monitor pressure changes in each foot, for example, in order to monitor physical therapy progress, muscle imbalances, etc.

[0131] In some embodiments, the treadmill may include one or more pressure sensors on the belt, which may, for example, be configured to determine user gait information related to a position of a user’s foot while walking/running. The system may, for example, be determined to identify a weight distribution of a user’s foot on the tread. This may, for example, enable a user to trial a pair of footwear and otherwise determine which of one or more different types of footwear are most suitable based on the user’s gait (e.g., based on different levels of arch support, different cushioning, etc.).

[0132] In various embodiments, the system is configured to merge data received from one or more cameras in addition to one or more pressure sensors and/or one or more tracking bands. For example, the system may be configured to determine a body angle based on data received from one or more sensors. As may be understood by one skilled in the art, as a user’s running speed increases, the user may modify an angle of their body (e.g., such that their legs impart more thrust against the support surface at a more severe angle than while walking). In particular embodiments, the system is configured to determine stride length, in addition to ‘hang time’ (e.g., an amount of time in the air between foot falls). In various embodiments, the system may use hang time data to identify inefficiencies in a user’s running motion (e.g., because too much time between steps may indicate a loss of efficiency).

[0133] In particular embodiments, the system is configured to track a respective position (e.g., and/or change in position) of each of the user’s feet as the user is running/walking on the treadmill. The system may, for example, track the change in position and/or impact of each foot on the belt based on feedback from the one or more motion tracking devices and/or force sensors worn by the user. The system may then be configured to substantially automatically adjust a belt speed of the treadmill (e.g., on-the-fly) as the user increases or decreases their speed. For example, the system may be configured to monitor a change in position of each foot and cause the motor driving the belt to advance a distance based on the user’s instantaneous stride length (i.e., of each leg). In this way, the system may be configured to enable a user to adjust to any changes in terrain (i.e., incline, etc.) that the user may encounter while using the treadmill without having to provide any input to increase or decrease the belt speed (e.g., gesture input, button input, etc.). As the user’s stride length increases, for example, the system may automatically increase the speed of the treadmill. In response to measuring a decrease in the user’s stride length, the system may be configured to decrease the speed of the treadmill.

[0134] Returning to Step 430, the system is configured to analyze the terrain and sensor data. The system may, for example, be configured to analyze the data to determine a position of an avatar that represents the rider (e.g., runner) within the terrain (e.g., a substantially instantaneous position). The system may further analyze the terrain and sensor data to manipulate a location of an avatar (e.g., and/or virtual camera indicating what the avatar is viewing from a first person perspective) within the terrain. The system may then display a current image from the virtual camera on the display device.

[0135] At Step 440, the system is configured for, in response to analyzing the terrain and sensor data, determine a desired orientation of the exercise device based on the terrain and sensor data. The system may, for example, determine the desired orientation based on the physical terrain data and one or more sensor-determined aspects of the exercise device (e.g., or the user on the exercise device). For example, the system may determine a desired orientation of the exercise device (e.g., treadmill) based on an orientation that most closely simulates the terrain.

[0136]FIG. 13 depicts a diagram indicating the system tracking a user’s stride length and gait. As may be understood from this disclosure, the system may be configured to determine, based on the skeletal mapping discussed herein: (1) a user’s gait width; (2) a users’ stride length (e.g., based on the distance between the landing of the user’s feet and a distance of belt travel between footsteps; (3) a velocity of each respective foot, etc.).

[0137] In particular embodiments, as part of the analysis, the system is configured to record information about a user’s gait characteristics, cadence, etc. in order to identify changes over time. For example, a user rehabilitating a leg injury may initially walk with a limp. The system may be configured to identify, based on the user’s skeletal mapping, one or more characteristics of the user’s limp such as: (1) the user favoring one particular leg over another; (2) the user leaning to one side; (3) one or more limits to the user’s speed or ability to navigate certain levels of incline, etc. In various embodiments, the system may be able to track improvements to the user’s gait over time in order to identify completion of a user’s rehabilitation from an injury that caused the limp.

[0138] In particular embodiments, the system is configured to track a respective position of each of the user’s feet as the user is running/walking on the treadmill. The system may then be configured to substantially automatically adjust a belt speed of the treadmill (e.g., on-the-fly) as the user increases or decreases their speed. For example, the system may be configured to monitor a change in position of each foot and cause the motor driving the belt to advance a distance based on the user’s instantaneous stride length (i.e., of each leg). In this way, the system may be configured to enable a user to adjust to any changes in terrain (i.e., incline, etc.) that the user may encounter while using the treadmill without having to provide any input to increase or decrease the belt speed (e.g., gesture input, button input, etc.). As the user’s stride length increases, for example, the system may automatically increase the speed of the treadmill. In response to measuring a decrease in the user’s stride length (e.g., at a higher incline level), the system may be configured to decrease the speed of the treadmill.

[0139] In some embodiments, user gait data may be used to biometrically authenticate a user during a virtual gaming session such as described herein.

[0140] In particular embodiments, the instantaneous speed adjustments may provide the user with more control over the experience, without having to provide any system input. The system may, for example, be configured to determine a real-time movement speed based in response to completion of a first step as the user drives off of a particular foot. The system may, for example, identify a new forward motion based on a lifting of a knee and/or foot, which may, for example, signal a new forward step by the user. In some embodiments, the system is configured to track user-specific characteristics in order to predict and/or identify a single stride length (e.g., knee position, hand position, arm pumping speed, etc.). In some embodiments, the system may similarly identify other actions by the user such as reversing (i.e., walking/running backwards), crouching, exaggerated longer strides to avoid obstacles, bunny hops to clear certain obstacles, etc.

[0141] In still other embodiments, the system is configured to automatically adjust a belt speed in response to a change in incline caused in response to position change within a virtual terrain. For example, the system may automatically reduce a belt speed as the incline of the treadmill increases. In still other embodiments, the system may comprise one or more mechanical breaks (e.g., electromagnetic breaks) configured to prevent slipping of the belt during incline and/or decline. For example, one or more rotors and/or motors may include one or more suitable breaking mechanisms.

[0142] In some embodiments, the treadmill may include one or more pressure sensors on the belt, which may, for example, be configured to determine user gait information related to a position of a user’s foot while walking/running. The system may, for example, be determined to identify a weight distribution of a user’s foot on the tread. This may, for example, enable a user to trial a pair of footwear and otherwise determine which of one or more different types of footwear are most suitable based on the user’s gait (e.g., based on different levels of arch support, different cushioning, etc.).

[0143] Next, at Step 450, the system is configured to send one or more control systems to one or more exercise device components (e.g., treadmill components) based on the determined orientation. The system may, for example, activate one or more motors to adjust a belt speed of the treadmill. In still other embodiments, the system is configured to modify a position of a rider’s avatar within a displayed version of the terrain based on the runner’s inputs, lean, etc. The system may be further configured to cause the runner’s avatar to traverse the terrain based on the sensor data (e.g., by turning, etc.) which may, in turn, adjust the terrain based on where the runner travels within the terrain. In this way, the system may be configured to enable the runner to ‘freely’ move within the terrain, while the treadmill (e.g., exercise device) adjusts the simulated terrain that the runner experiences based on the runner’s position and orientation within the terrain, as well as the turning, leaning, etc. that the runner performs (e.g., and is determined by the sensor data or user input data). In other embodiments, the system may automatically activate a lifting mechanism configured to adjust an incline of the exercise device (e.g., the treadmill) to substantially match (e.g., correspond to) a level of incline based on a current position of a user’s avatar within a virtual terrain.

[0144] In particular embodiments, the treadmill may include one or more lifting mechanisms. In some embodiments, the one or more lifting mechanisms are configured to incline and/or decline a front or rear of the tread (e.g., and/or both the front and the rear) in order to modify an angle of the tread in order to simulate uphill and/or downhill walking/running. In certain embodiments, such as those shown in FIG. 7, the treadmill is configured to pivot about a point positioned adjacent a rear of the treadmill (e.g., by adjusting and/or lifting or lowering a front portion of the treadmill using any suitable lifting mechanism). In particular embodiments, the system is configured to modify an incline and/or decline level of the treadmill based on one or more changes in terrain of a virtually generated terrain while the system is displaying the terrain on a display screen. The system may, for example, activate the lifting mechanism to adjust an incline of the treadmill’s running surface (e.g., upward or downward).

Exercise Devices According to Various Embodiments

Treadmill

[0145] In particular embodiments, a treadmill may comprise one or more lifting mechanisms configured to lift and lower a treadmill belt (e.g., adjust an angle of the treadmill belt relative to a support surface) by adjusting a height of the front and rear of the treadmill about a pivot point. In particular embodiments, the pivot point may be positioned in any suitable location between the front and rear of the treadmill (e.g., positioned somewhat centered along a length of the belt). In the embodiment shown in these figures, the treadmill includes a safety handrail and bar in front of and to either side of the runner. In the embodiment shown in this figure, the treadmill does not include a console with input controls. As discussed more fully herein, the system may employ gesture control through one or more imaging devices. In this way, the system may provide a safer experience by not requiring a user to look down in order to press a button to control a speed or incline of the treadmill. In this way, the user may continue looking ahead to make such setting adjustments, which can avoid unsafe situations resulting from a user looking down or struggling to find a desired button to press (e.g., which is particularly unsafe at an incline or when running at higher speeds).

[0146]FIG. 15 depicts an exemplary embodiment of a treadmill in a “see-saw” design in which a pivot point for inclining and/or declining the treadmill is somewhat centrally positioned (e.g., centrally positioned) between a front and rear of the treadmill. As may be understood from this disclosure, although the “see-saw” treadmill will generally be described as having a central pivot point, it should be understood that various other embodiments may include a pivot point at any other suitable location between a front and rear of the treadmill (e.g., positioned approximately ¼ from the front end, 1/3 from the front end, 2/3^rd from the front end, 3/4^th from the front end, etc.).

[0147] In particular embodiments, a seesaw arrangement may provide a central pivot point, providing a moment arm to the motor while decreasing a moment arm caused by the load (e.g., the runner). In this way, an apparent load on a motor providing incline and decline to the running surface may be reduced by the system.

[0148]As shown in FIG. 15, a treadmill may include, for example, a belt 705(e.g., running surface), one or more supports 720, one or more pulleys 740 (e.g., one or more sprockets), one or more motors 730, and one or more chains/cables. In particular embodiments, a respective motor 730 (and/or gearbox) may be configured to adjust a length of cable 710 (e.g., chain, link, rigid or semi-rigid connector, etc.) that attaches to a front or rear portion of the treadmill (e.g., a support structure for the belt 705) via a suitable pulley 740. In a particular embodiment, the treadmill includes at least one worm gearbox or other gearbox configured to provide holding torque to the cable (e.g., or other connector). In such embodiments, the gearbox may be configured to provide a holding torque to the cable in the instance of a power loss to one or more motors (e.g., which may enable the system to maintain a particular incline level in the case of power loss, thereby avoiding an unsafe condition for a user stemming from an unpredictable rapid incline or decline). In still other embodiments, a worm gear or other gearbox may be configured to provide holding torque the enables the system to operate more efficiently, as a motor may only draw current to drive the motion of an angle change for the treadmill running surface. In such embodiments, the system does not require power to the motor to maintain the treadmill at a particular incline level. In various other embodiments, the system may include any other suitable geared and/or braking system capable of holding a cable or other connection mechanism while the motor is off or has lost power. In particular embodiments, one or more controllers may be configured to control each of the one or more motors 730 to cooperate to adjust a length of the respective cables to adjust an incline/decline of the belt.

[0149] In various embodiments the cable may further include a chain tensioner or other mechanism for integrating the cable with one or more lengths of chain. In particular embodiments, each of the one or more motors are configured to release and/or pull the cable as necessary to enable the respective cable portions to hold the belt at a desired angle with sufficient force to support a runner on the surface of the belt 705 while the belt is running and maintained at the desired angle.

[0150] In particular embodiments, the see-saw arrangement described herein may provide a faster change in angle for the belt (e.g., faster than traditional systems which rely on one or more linear actuators to lift a front portion of the treadmill). In particular embodiments, the treadmill system comprises a system of one or more cables, chains, combination of cables and chains, or other suitable mechanism configured to cooperate to cause an incline and/or decline of a running platform (e.g., belt).

[0151] In various embodiments, the position of the pivot point 708 may reduce a load on the one or more motors while the belt 705 is in an incline or decline position. In a particular embodiment, the pivot point 708 may be positioned at least about 2/3^rd of the length of the belt from a front end of the treadmill.

[0152] In particular embodiments, a position of the pivot point and the load of the runner are configured to minimize a load on one or more motors that are causing the running platform to maintain a particular position (e.g., angle relative to the support surface). In particular embodiments, a position of the pivot point may be adjusted to modify a motor load and an effect on a lever arm created by a runner’s position with respect to the pivot point. The system may, for example, be configured to utilize different pivot point positions for different applications (e.g., treadmill, rowing machine, etc.). In still other embodiments, the pivot point (e.g., position of the pivot point) is adjustable. FIG. 16 depicts a treadmill with a centralized pivot in various embodiments.

[0153] In particular embodiments, the treadmill system is designed such that a runner using the treadmill would have his or her weight substantially centered above the pivot point while running. In a particular embodiment, a drive motor for the belt may be configured to transfer rotation (e.g., via one or more belts) to a shaft at the pivot point, which may then be configured to transfer rotation to either the front roller or a back roller to drive a rotation of the running surface belt (e.g., treadmill surface). FIG. 15 depicts an embodiment in which a drive belt from a drive motor transfers rotational energy to a pivot shaft, which in turn, transfers energy to a rear roller which drives the running belt. The drive belt design described immediately above (e.g., with the drive belt initially driving rotation of a pivot shaft) may, for example, reduce a strain of driving a rear or front roller directly via a stationary motor, as a lifting or lowering of the front or rear of treadmill may exert additional tension on a drive belt in such embodiments. In still other embodiments, one or more motors may be mounted to the bed itself such that the one or more motors provide a direct drive to the belt. Such embodiments may, for example, limit a number of rotating elements and transmission belts and act as a counterweight to improve the efficiency of the lifting mechanism.

CONCLUSION

[0154] While this specification contains many specific aspect details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features that may be specific to particular aspects of particular inventions. Certain features that are described in this specification in the context of separate aspects also may be implemented in combination in a single aspect. Conversely, various features that are described in the context of a single aspect also may be implemented in multiple aspects separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination may in some cases be excised from the combination, and the claimed combination may be a sub-combination or variation of a sub-combination.

[0155] Similarly, while operations are described in a particular order, this should not be understood as requiring that such operations be performed in the particular order described or in sequential order, or that all described operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various components in the various aspects described above should not be understood as requiring such separation in all aspects, and the described program components (e.g., modules) and systems may be integrated together in a single software product or packaged into multiple software products.

[0156] Many modifications and other aspects of the disclosure will come to mind to one skilled in the art to which this disclosure pertains having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the disclosure is not to be limited to the specific aspects disclosed and that modifications and other aspects are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for the purposes of limitation.