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 leg muscle strength estimation system includes: an obtainer that obtains an image including a user that is walking as a subject of the image; and an estimator that estimates a leg muscle strength of the user based on the obtained image.

A muscle contraction detection sensor for detecting a muscle contraction that includes: a substrate to be mounted facing a muscle to be detected; at least two pressing members that are disposed on the substrate and are to be pressed against the muscle; and at least two reaction force detection units configured to detect respective reaction forces received by the pressing members, wherein the pressing members include a first pressing member and a second pressing member, the reaction force detection units include a first reaction force detection unit and a second reaction force detection unit, a muscle contraction is detected based on a change in a difference between, or a change in ratios of, the reaction force received by the first pressing member detected by the first reaction force detection unit and the reaction force received by the second pressing member detected by the second reaction force detection unit.

A muscle contraction detection sensor for detecting a muscle contraction that includes: a substrate to be mounted facing a muscle to be detected; at least two pressing members that are disposed on the substrate and are to be pressed against the muscle; and at least two reaction force detection units configured to detect respective reaction forces received by the pressing members, wherein the pressing members include a first pressing member and a second pressing member, the reaction force detection units include a first reaction force detection unit and a second reaction force detection unit, a muscle contraction is detected based on a change in a difference between, or a change in ratios of, the reaction force received by the first pressing member detected by the first reaction force detection unit and the reaction force received by the second pressing member detected by the second reaction force detection unit.

A wearable device utilizing flexible electronics is disclosed. The wearable device may comprise a flexible matrix material and may include sensors for measuring biometric measurements of an individual, an accelerometer for measuring an acceleration of a body part to which the wearable device is attached, a wireless transmitter, a flexible power source, and a microcontroller. During an activity, the microcontroller may receive signals from the sensors including the biometric measurements, and signals from the accelerometer including acceleration and force measurements associated with the individual. The microcontroller may convert the signals into digital signals and transmit the signals to a computing device for analysis. The computing device may analyze the digital signals to determine a performance metric for the individual. The performance metric may be compared to baseline data for the individual to determine a fatigue level, injury risk, or an adjustment to be made by the individual during the activity.

A wearable device utilizing flexible electronics is disclosed. The wearable device may comprise a flexible matrix material and may include sensors for measuring biometric measurements of an individual, an accelerometer for measuring an acceleration of a body part to which the wearable device is attached, a wireless transmitter, a flexible power source, and a microcontroller. During an activity, the microcontroller may receive signals from the sensors including the biometric measurements, and signals from the accelerometer including acceleration and force measurements associated with the individual. The microcontroller may convert the signals into digital signals and transmit the signals to a computing device for analysis. The computing device may analyze the digital signals to determine a performance metric for the individual. The performance metric may be compared to baseline data for the individual to determine a fatigue level, injury risk, or an adjustment to be made by the individual during the activity.

Embodiments generally relate to a device for monitoring air pressure in the body of a patient. The device comprises a tube comprising a feeding lumen; a sensor lumen positioned parallel to the feeding lumen; at least one sensor positioned in the sensor lumen; and at least one perforation positioned to expose the at least one sensor to an air pressure within the body of a patient when the device is positioned at least partially in the airway of the patient. The at least one sensor is configured to generate data related to the pressure to which the sensor has been exposed.

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 system for determining a physical status of a subject, the system including a computing device configured to store a parameter classifier, the parameter classifier configured to classify biological extractions to physiological status parameters of subjects wherein the physiological status parameters include a nutrition parameter, an endurance parameter, and a strength parameter, receive biological extraction data of a subject, classify subject biological extraction to subject physiological parameters as a function of the stored parameter classifier, assign values to subject physiological status parameters as a function of the biological extraction data, indicate the physical status of the subject as a function of the subject physiological parameters, generate a physical guidance for the subject as a function of the physical status, and output the physical guidance.

A handgrip device has a palm rest operable to engage with a palm of a user, a grip bar moveably coupled with the palm rest and operable to engage with one or more fingers of a user. One or more force transducers can be disposed between the palm rest and the grip bar to measure a compression rate and the return rate of the grip bar relative to the palm rest, and a data connection operable to communicate the compression rate and the return rate.