A system 300 and method for biologically monitoring the fitness of an athlete, and providing a warning 338 when an overtraining condition is determined in order to reduce injury. Through implementation of an efficient system architecture, micro-artificial intelligence use is practical for mobile situations where internet coverage is deficient or non-existent.

An interchangeable smartwatch system includes a smartwatch body and a band including one or more sensors. The smartwatch body is removable from the band, which permits a user to continue to collect data, such as the user's heartrate, when the smartwatch body is removed from the band. The smartwatch body can receive a wireless charge when removed from the band, and then transfer a charge to the band when the smartwatch body is reconnected to the band.

The present disclosure generally relates to managing user interfaces associated with physical activities. The user interface displays a scrollable list of affordances associated with physical activities. The affordances may contain physical activity and heart rate information. A user can launch a physical activity tracking function or an interface to change a workout metric using an affordance. Users can also control the music that is played in response to selecting a workout. Further, the interface can be used to compose a reply message to a received message that contains workout information. The interfaces can show a graph that includes heart data when the user's heart rate meets a heart rate alert criteria.

Provided is a computer-implemented method of determining exercise parameters, such as heart rate thresholds, endurance, maximum heart rate and lactate threshold. The method comprises fitting a continuous curve to heart rate data obtained over time from the onset of exercise, the curve comprising a plurality of components that meet at transition points that join the components. The exercise parameters are obtained from the curve fitting of the heart rate data. Also provided is a system for determining exercise parameters, in particular a computer-implemented system that determines exercise parameters using the disclosed method.

Vital sign monitoring via remote sensing on stationary exercise equipment is provided. A new non-contact approach described herein uses radio frequency (RF) radar (e.g., ultra-wide band (UWB) radar) to remotely monitor vital sign information (such as heartbeat and breathing) and human activity information of subjects using stationary exercise equipment. In some embodiments, a radar sensor captures micro-scale chest motions (corresponding to the vital sign information) as well as macro-scale body motions (corresponding to movements from exercise). A signal processor receives radar signals from the radar sensor and processes the radar signals to reconstruct vital sign information from the micro-scale chest motions and/or human activity information from the macro-scale body motions using a joint vital sign-motion model, which can be trained using machine learning and other approaches.

An oral appliance for treating sleep apnea in a user includes a mouthpiece configured for being positioned in an oral cavity of the user, and at least one pulse oximeter attached to the mouthpiece. According to an aspect, the pulse oximeter is configured to monitor actual oxygen saturation levels of hemoglobin of the user when the oral appliance is positioned in the oral cavity of the user. The oral appliance may include an additional sensor attached to the mouthpiece that includes at least one of an airflow sensor, a pressure sensor, a noise detector, and an actigraphy sensor.

Multiple-sensor IoT devices are worn by users, each device containing one or more physiological and/or environmental sensors. The devices communicate with an external smart device that collects readings from the sensors. An algorithm module analyzes the readings and generates alerts to notify users if indices of the readings, and/or of parameters computed therefrom, are in potentially dangerous ranges.

Example embodiments may relate to a system, method, apparatus, and computer readable media configured for prompting a user to perform an exercise, monitoring form of the user while performing the exercise, and calculating an energy expenditure estimate for the user performing the exercise based on a type of the exercise and on the form of the user.

Example embodiments relate to systems, methods, apparatuses, and computer readable media relating to a user interface, that may for example, receive and/or process physical activity data and allow interaction with the received information in novel implementations.

Disclosed are devices and methods for non-invasively measuring arterial stiffness using pulse wave analysis of photoplethysmogram data. In some implementations, wearable biometric monitoring devices provided herein for measuring arterial stiffness have the ability to automatically and intelligently obtain PPG data under suitable conditions while the user is engaged in activities or exercises. In some implementations, wearable biometric monitoring devices are provided herein with the ability to remove PPG data variance caused by factors unrelated to arterial stiffness. In some implementations, wearable biometric monitoring devices have the ability to perform PWA while accounting for the user's activities, conditions, or status.