Systems and methods for facilitating exercise monitoring are provided. A representative method includes: using a processor, having processor circuitry, to: compute an orientation change of the single wearable device based on the motion readings; determine a current training type and a target status associated with the current training type based on the schedule of training types; select one of the computing models associated with the current training type; compare the set of matching orientation changes corresponding to the current training type and the orientation change of the single wearable device with respect to a determination threshold corresponding to the current training type until the target status associated with the current training type has been attained; and compute an exercise amount associated with the current training type based on the target status attained.

Systems and methods for facilitating exercise monitoring are provided. A representative method includes: using a processor, having processor circuitry, to: obtain motion readings reported from an inertial sensor of a wearable device and corresponding to a scheduled training types; receive the schedule and a target status of a target training count or a target training time corresponding to each of the training types; determine the current training type based on the schedule; select one of the computing models based on the current training type; compare the set of matching characteristics corresponding to the current training type and the motion readings until the target status has been attained for the current training type; select a next training type based on the schedule; select another one of the computing models based on the next training type; determine activity information associated with the schedule; and compute an exercise amount of the user based on the target status, the activity information, and the schedule.

Described herein is a method of operating an electronic device that includes collecting initial motion activity data from at least one sensor of the electronic device, and generating a initial probabilistic context of the electronic device relative to its surroundings from the initial collected motion activity data using a motion activity classifier function. The collected motion activity data is stored in a training data set, and the motion activity classifier function is updated using the training data set. The method also includes collecting subsequent motion activity data from the at least one sensor of the electronic device, and generating a subsequent probabilistic context of the electronic device relative to its surroundings from the subsequently collected motion activity data using the updated motion activity classifier function.

The subject of the invention is a sports physiological measuring system and method for the monitoring of the aerobic and anaerobic metabolic energy generating system and the autonomic nervous system, primarily during physical exercise.

A method of determining a CRF level for a user of a fitness tracking system includes receiving activity data from at least one activity sensor carried by the user during a number of workouts, the activity data including distance data for each of the number of workouts, and then generating workout data based on the activity data. The method further includes storing the workout data in a memory, the memory further including demographic data for the user. When the an attribute of the workout data is less than a threshold number, the method includes determining a first CRF level for the user based on a first CRF model. When the attribute of the workout data is greater than the threshold number, the method includes determining a second CRF level for the user based on a second CRF model, and displaying the first and second CRF levels.

The present disclosure is directed towards methods for calculating disease progression rates and sojourn times of solid tumors from metabolic markers and using this calculation to optimize patient-specific diagnosis, scheduling of screening procedures, and dosage or frequency of treatment.

A garment is made of flexible material that includes a first measurement electrode integrated into the garment at a first location, a second measurement electrode integrated into the garment at a second location different from the first location, and a measurement circuitry configured to measure bioimpedance by using the first measurement electrode and the second electrode and to transmit the measured bioimpedance and to measure electrocardiogram by using at least one of the first measurement electrode and the second electrode or another electrode. The garment is an upper body garment, in which the first measurement electrode is disposed above a heart level and the second measurement electrode is disposed below the heart level.

[Object] To provide an information processing method, an information processing apparatus, and an information processing terminal that can enhance care prevention.

[Solution] Provided is an information processing method including: acquiring, by an acquisition unit, measurement results of physical fitness measurement and a cognition function, life information, and a social participation score; learning, by a learning unit, correlation between a physical fitness value and a cognition function value that are based on the measurement results, and life information and a social participation score; and predicting, by a prediction unit, future physical fitness value and cognition function value of a user using the learned correlation on the basis of life information and a social participation score of the user.

A hydration and nutrition system includes a pressurized reservoir adapted to hold a quantity of fluid, a tube in fluid communication with the reservoir, a flow meter adapted to measure and collect flow data regarding the flow of fluid through the tube, one or more user performance sensors that provide performance data, and a database including a baseline requirements and a consumption plan. The baseline requirements are associated with a peak performance power output, and the consumption plan is based on a percentage of the baseline requirements for the peak performance power output. The system further includes a computerized nutritional calculator that performs the steps of receiving performance data, adjusting the consumption plan based on the performance data, calculating an actual caloric intake of fluid consumed, calculating a required caloric replenishment rate, and displaying a required caloric replenishment rate.

Computerized eyewear and corresponding methods measure a wearer's heart rate using a first optical sensor and a second optical sensor at least partially embedded in an eyewear temple. The first optical sensor transmits a first signal to a temple of the wearer and the second optical sensor transmits a second signal to the temple of the wearer. Reflections of the first signal are used to measure a raw heart rate delta and reflections of the second signal are used to measure a noise delta. The raw heart rate delta and the noise delta are used to determine a measured heart rate of the wearer of the computerized eyewear.