Hinge Health, Inc.

Neuromodulation devices and methods of their use are described in which a therapeutic device is configured to generate a treatment for treating pain such as the reduction of the symptoms of chronic and acute pain as well as for treating other conditions. The neuromodulation device generates an output electrical signal in the form of pulses with a fast rise-time spike waveform followed by a longer-duration, lower amplitude primary phase waveform. The output signal includes a broad range of frequency components, with time constants tuned so as to interact with specific cell membrane or cellular components. The output signal may be conducted to the patient via electrodes. The pulses are triggered at variable intervals which prevent habituation.

Introduced here is an approach to allowing a computer-implemented model to learn its own ordering scheme by applying an appropriate loss function during training. More generally, the present disclosure pertains to computer programs and associated computer-implemented techniques for estimating pose of a living body through simultaneous analysis of multiple visualizations. For example, joint type heatmaps—where a given heatmap includes every visible joint of the corresponding type across all visible persons—can be combined with joint person heatmaps—where a given heatmap includes every visible joint of the corresponding person—to better understand the relationship between joints visible in a digital image and people included in the digital image.

A computing device may include a display mechanism configured to display an interface that presents, to a user, a series of visualizations to guide performance of a series of physical exercises. A computing device may include an image sensor configured to generate digital images of the user as the series of physical exercises are performed. A computing device may include a processor configured to: receive, from the user, input that specifies (i) an anatomical region in which pain is felt, (ii) a functional task, or (iii) an ability level, determine, based on the input, appropriate physical exercises and an appropriate order in which to perform the appropriate physical exercises; and cause the appropriate physical exercises to be presented, in the appropriate order, to the user as the series of physical exercises.

Introduced here are computer programs that are able to generate computer vision data through local analysis of image data (also referred to as “raw data” or “input data”). The image data may be representative of one or more digital images that are generated by an image sensor. Also introduced here are apparatuses for generating and handling the image data and computer vision data.

Systems and methods for generating synthetic training data for pose estimators based on volumetric video data are described herein. For example, the system may obtain volumetric videos of individuals. The system may generate multiple sets of view parameters. The system may generate 2 D renderings of the volumetric videos in multiple volumetric scenes. The system may generate transformed 2 D representations from renderings of the volumetric videos in a virtual studio. The system may provide a training dataset to a machine learning algorithm to produce a machine learning model.

A neuromodulation device including a first electrode via which an electrical signal is applied to the skin of a living body. The device further includes a second electrode at which the electrical signal is received and a gel pad that is electrically connected with the first and second electrodes. The device further includes a controller configured to generate the electrical signal that is applied to the skin of the living body at the first location via the first electrode, measure the electrical signal received at the second electrode and produce an analog output that is representative of the measured electrical signal, establish a change in resistance between the first and second electrodes, determine whether the gel pad is being removed from the skin of the living body based on the change in resistance, and halt generation of the electrical signal.

Introduced here are computer-implemented platforms (also referred to as “therapy platforms”) that are designed to improve adherence to, and success of, exercise therapy programs\assigned to patients for completion. As part of an exercise therapy program, a patient may be requested to engage with a therapy platform. An exercise therapy program normally comprises a number of exercise therapy sessions in which the patient is instructed to perform physical activities. For example, the patient may be instructed to perform a series of exercises over the course of an exercise therapy session. The therapy platform can assist the patient by actively guiding her through the exercise therapy session.

An apparatus is provided to generate mechanical index maps for mesh rigging. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of an object. The apparatus further includes a memory storage unit to store the raw data. In addition, the apparatus includes a pre-processing engine to generate a segmentation map from the raw data. The segmentation map is to outline the object. Furthermore, the apparatus includes a neural network engine to generate a mechanical heatmap for a predefined key-point connector based on the segmentation map. The mechanical heatmap includes a mechanical weight index of the predefined key-point connector for each pixel.

An apparatus is provided. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of a first object and a second object. The apparatus further includes a memory storage unit to store the raw data. In addition, the apparatus includes a neural network engine to receive the raw data. The neural network engine is to generate a segmentation map and a boundary map. The apparatus also includes a post-processing engine to identify the first object and the second object based on the segmentation map and the boundary map.