Alivecor, Inc.

Iman Abuzeid

David E Albert

Euan Thomson

Nupur Srivastava

Fei Wang

Omar Dawood

Ravi Gopalakrishnan

Lev Korzinov

Frank Losasso Petterson

Conner Daniel Cross Galloway

Alexander Vainius Valys

Bruce Richard Satchwell

A smart watch to detect a presence of an arrhythmia of a user is disclosed. The smart watch comprising: a processing device and a photoplethysmography ('PPG') sensor operatively coupled to the processing device, an ECG sensor comprising two or more ECG electrodes and operatively coupled to the processing device, a display operatively coupled to the processing device, and a memory, operatively coupled to the processing device. The memory may have instructions stored thereon that, when executed by the processing device, cause the processing device to: receive PPG data from the PPG sensor, receive ECG data from the ECG sensor, detect, based on the PPG data and the ECG data simultaneously, the presence of an arrhythmia, and provide one or more recommendations to the user based on the PPG data and the ECG data.

Methods and systems for arrhythmia tracking and scoring

Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator ('other-factors') to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.

Continuous monitoring of a user's health with a mobile device

Described herein are systems, devices, and methods for cardiac monitoring. In particular, the systems, devices, and methods described herein may be used to conveniently sense the presence of an intermittent arrhythmia in an individual. The systems, devices, and methods described herein may be further configured to sense an electrocardiogram.

Discordance monitoring

Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator ('other-factors') to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.

Machine learning health analysis with a mobile device

A dashboard centered around arrhythmia or atrial fibrillation tracking is provided. The dashboard includes a heart or cardiac health score that can be calculated in response to data from the user such as their ECG and other personal information and cardiac health influencing factors. The dashboard also provides to the user recommendations or goals, such as daily goals, for the user to meet and thereby improve their heart or cardiac health score. These goals and recommendations may be set by the user or a medical professional and routinely updated as his or her heart or cardiac health score improves or otherwise changes. The dashboard is generally displayed from an application provided on a smartphone or tablet computer of the user.

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.

Growing community of inventors

San Francisco, CA, United States of America

Iman Abuzeid