ALIVECOR, INC.

Embodiments of the present disclosure provide a small form factor ECG monitoring device that can acquire 3 standard ECG leads including a V-lead, does not require the use of adhesives for electrodes, and provides ECG data for a user on a near instantaneous basis. The ECG monitoring device can acquire leads I, II, and V 2 (or any other V lead). The addition of a V-lead not only provides an additional channel of ECG data, but also adds another orthogonal cardiac field plane (the horizontal plane) thanks to the reference point formed by leads I and II. The ECG monitoring device may derive the augmented limb leads and subsequently generate a full 12-lead ECG. The ECG monitoring device may generate one or more diagnoses based on the full 12-lead set. The ECG monitoring device may provide an easy and non-invasive way for a person to take an ECG on the fly.

Described herein are devices, systems, and methods for sensing, generating, and time aligning one or more of the 12 leads of a standard ECG. A set of electrodes may be used to perform an electrocardiogram (ECG) of a user to generate a set of limb leads including a first lead I. A Wilson's Central Terminal (WCT) value may be determined using a subset of the set of limb leads. In response to an electrode of the set of electrodes contacting the user's chest, a precordial lead may be generated based on electric potentials sensed by the electrode while contacting the user's chest and the WCT value. As the precordial lead is generated, a corresponding second lead I is simultaneously generated. The corresponding second lead I is used to time align the set of limb leads and the precordial lead.

A personal monitoring device has a sensor assembly configured to sense physiological signals upon contact with a user's skin. The sensor assembly produces electrical signals representing the sensed physiological signals. A converter assembly, integrated with, and electrically connected to the sensor assembly, converts the electrical signals generated by the sensor assembly to a frequency modulated physiological audio signal having a carrier frequency in the range of from about 6 kHz to about 20 kHz.

Described herein are software platforms (or “platforms”), systems, devices, and methods for providing effective healthcare to a patient while increasing the efficiency of the healthcare provider. A platform provides effective healthcare to a patient through, but not limited to, monitoring of the physical parameters and therapeutic objectives of the patient. In addition, a platform is further configured to provide a communication link between a patient and a healthcare provider. The platform may be implemented by a system comprising one or more computing devices that interact with or run one or more applications of the platform.

Described herein are devices, systems, and methods for sensing and generating a one or more of the 12 leads of a standard ECG with a mobile computing device. In some embodiments, three electrodes are positioned on a mobile computing device so that an individual may comfortably contact all three sensors at once to generate a six lead ECG which may be displayed on a display of said mobile computing device. In some embodiments, analysis carried out further comprises determining a QRS axis and QRST angle.

Described herein are methods, systems, and software for monitoring blood pressure. In some embodiments, a using a mobile device is used. The blood pressure monitoring system utilizes heart rate measurements at two separate locations on the body to calculate a differential pulse arrival time which is used to estimate blood pressure. The heart rate measurements can be taken simultaneously, or they can be taken sequentially while simultaneously taking ECG measurement. If taken sequentially, the heart rate measurements are aligned with the ECG to determine the differential. Accurate, inexpensive, and discreet blood pressure monitoring is thus provided.

Devices, systems, and methods for measuring and monitoring biometric or physiological parameters in a user-friendly and convenient manner are disclosed. Relevant physiological parameters of the user may be measured as the user normally operates a computing device or other hand-operated or hand-held device. These parameters are measured using an accessory of the device such as a laptop case, a tablet computer case, a smartphone case, or a smart watch or smart armband. The accessory may include at least two or three electrodes for taking an electrocardiogram or other physiological parameters. The measured parameters are transmitted to the computing device. The computing device can be normally used while a physiological parameter monitoring and measurement application loaded onto the computing device operates in the background to receive the measured parameters.

Software applications, devices, systems, and methods are provided for monitoring, recording, and tracking cardiac health related metrics using an associated computing device. The software applications may monitor, record, and track physiological data such as cardiac electrical activity, heart rate, and blood pressure. Data transmission between a patient and a healthcare provider may also be enabled via the software applications disclosed herein.

Described herein are methods, systems, and software for monitoring blood pressure. In some embodiments, a using a mobile device is used. The blood pressure monitoring system utilizes heart rate measurements at two separate locations on the body to calculate a differential pulse arrival time which is used to estimate blood pressure. The heart rate measurements can be taken simultaneously, or they can be taken sequentially while simultaneously taking ECG measurement. If taken sequentially, the heart rate measurements are aligned with the ECG to determine the differential. Accurate, inexpensive, and discreet blood pressure monitoring is thus provided.

Embodiments of the present disclosure provide a mobile electrocardiogram (ECG) sensor comprising an electrode assembly comprising electrodes, wherein the electrode assembly senses heart-related signals when in contact with a body of a user, and produces electrical signals representing the sensed heart-related signals. The ECG sensor further comprises a processing device, operatively coupled to the electrode assembly, the processing device to provide the sensed heart-related signals to a machine learning module trained to predict a twelve-lead QT interval (QTc) value from the mobile ECG sensor comprising less than twelve leads. The ECG sensor also comprises a housing containing the electrode assembly and the processing device.