A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan and a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session. The computer-implemented system may also include a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; write to an associated memory, for access by an artificial intelligence engine, the treatment data; receive, from the artificial intelligence engine, at least one prediction; identify a threshold corresponding to the at least one prediction; and, in response to a determination that the at least one prediction is outside of the range of the threshold, update the treatment data pertaining to the user to indicate the at least one prediction.

Provided is an exercise load control device including: a patient information input unit configured to input patient information which indicates whether a patient using an exercise therapy apparatus is an atrial fibrillation patient; a heart rate information acquisition unit configured to acquire heart rate information which indicates a heart rate of the patient using the exercise therapy apparatus; and a load control unit configured to control a magnitude of a load to be applied by the exercise therapy apparatus to the patient, based on the patient information input by the patient information input unit and the heart rate information acquired by the heart rate information acquisition unit.

A biological information measurement device which is capable of improving accuracy of detection of optimal exercise intensity, a biological information measurement method, and a biological information measurement program are provided. At the biological information measurement device, heart rate counting means measures an HR value indicating a heart rate on the basis of heart-rate data obtained by capturing heartbeats when a subject to be measured exercises, and analysis means performs power spectrum analysis on a heart rate variability frequency of the heart-rate data to calculate an LF value which is an integral value of low frequency components. Detection means then detects an HR/LF value by dividing the HR value with respect to exercise intensity of the subject to be measured by an LF value. Thus, by the biological information measurement device obtaining the HR/LF value as a new index indicating sympathetic nerve activity, it is possible to obtain biological information important for health management.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.

A method includes receiving data pertaining to a user that uses a treatment apparatus to perform a treatment plan. The data includes characteristics of the user, the treatment plan, and a result of the treatment plan. The method includes assigning the user to a cohort representing people having similarities to the characteristics of the user. The method includes receiving second data pertaining to a second user, the second data comprises characteristics of the second user. The method includes determining whether at least some of the characteristics of the second user match with at least some of the characteristics of the user, assigning the second user to the first cohort, and selecting, via a trained machine learning model, the treatment plan for the second user, and controlling, based on the treatment plan, the treatment apparatus while the second user uses the treatment apparatus.

In one embodiment, a method for generating a message to a friend of a user is provided, comprising: processing activity data of a first user measured by an activity monitoring device to update a value of an activity metric for the first user; identifying a change in an inequality relationship between the value of the activity metric for the first user and a value of the activity metric for a second user; in response to identifying the change in the inequality relationship, prompting the first user to generate a message to the second user.

In one embodiment, a method for generating a message to a friend of a user is provided, comprising: processing activity data of a first user measured by an activity monitoring device to update a value of an activity metric for the first user; identifying a change in an inequality relationship between the value of the activity metric for the first user and a value of the activity metric for a second user; in response to identifying the change in the inequality relationship, prompting the first user to generate a message to the second user.

Automated systems and methods are presented for determining the physiological response of human or suitable animal subjects to physical exertion. The methods and systems can include monitoring sensors that capture the motion of the subject along with corresponding physiological data, and can track such motion for the duration of a period of physical exertion. The system is able to acquire an initial stream of physiological data from the subject during a range of physical exertion activities that are representative of the events intended to be monitored with the proposed method and system, enabling a corresponding dynamic physiological response model to be created. The motion tracking system and physiological response model can then be used to predict the physiological response to physical exertion events under a prescribed framework, including applications during real-time event monitoring.

Wearable apparatus for monitoring various physiological and environmental factors are provided. Real-time, noninvasive health and environmental monitors include a plurality of compact sensors integrated within small, low-profile devices, such as earpiece modules. Physiological and environmental data is collected and wirelessly transmitted into a wireless network, where the data is stored and/or processed.

The invention relates to a method and a system for determining body's readiness to respond to physical exercise and for providing feedback to a user. In the method the user starts to perform an exercise, an earlier performance level is determined before starting a performance check having steps of: an instant performance level of the user is determined, the earlier performance level is compared to the instant performance level, a readiness index is determined according to the said comparison and optionally with background and/or training history of the user, a feedback is given according to the determined readiness index.