A hippotherapy device includes a saddle for receiving a person thereon, a programmable movement control, and an automatic movement device for automatically moving the saddle according to a movement pattern program. The program specifies a sequence of target values of positions and orientations of the saddle in the locality of the movement device in order to execute the movement pattern. The hippotherapy device further includes a person securing device having a main support on which a body strap is mounted, at least one sensor for detecting at least one physical variable characterizing the body posture of the person on the saddle, and an auxiliary control device configured to compare expected values of the physical variable with current values of the physical variable detected by the sensor, and to trigger an associated safety function, if a deviation of the current values from the expected values exceeds a predetermined tolerance threshold.

An athlete wearing footwear measures jump heights with a motion sensor mounted on the footwear over toes of the athlete. By sensing vertical jump start motions the sensor detects jump start and finish times of −4 g start and −4 g landing. The sensor, a body wearable mems sensor developed by JAWKU, L.L.C., has a previously installed generic factory scale calibration factor. The athlete replaces this calibration factor with a new calibration scale factor selecting an “absolute” external reference device which measures jump height. This device measures several jump heights then inputted to an algorithm app in the sensor to calculate the new calibration scale factor customized to the actual athlete. The motion sensor has built in programming apps to periodically receive an upgraded factory scale calibration factor which upgrade is based on an ever increasing data pool of jump heights. The updated factory calibration factor is then again replaced by the athlete personally taking several new measured jumps which jump heights are in turn inputted to the sensor. The progress made in evolving jumping skills based on training and specific conditioning exercises can thus be motion sensor evaluated.

Multiple circuits in a computing device can share one or more conductive elements. The use of the conductive element can vary by circuit, such as an antenna radiator for a radio frequency (RF) circuit or an electrode for an electrocardiography (ECG) circuit. The circuitry sharing a conductive element can utilize signals obtained over different frequency ranges. Those ranges can be used to select decoupling circuitry, or elements, that can enable the respective circuits to obtain signals over a respective frequency range, excluding signals over one or more other frequency ranges corresponding to other circuitry sharing the circuit. Such an approach allows for concurrent independent operation of the circuitry sharing a conductive element.

A detection system includes an acquisition unit, a calculation unit, a determination unit and a correction unit. The acquisition unit acquires measurement information from a load distribution sensor that detects a distribution of a load received from a sole of a subject. The calculation unit calculates a total load value of a sole region corresponding to the position of a sole of one leg of the subject, based on the measurement information. The determination unit determines an action state of the one leg based on the total load value. The correction unit starts to offset the total load value using an offset filter that decreases an offset amount with time elapse, in response to a determination that the action state is a first action state where the total load value tends to increase and is equal to or larger than a preset determination value.

In a physical strength evaluation system, a reference storage stores a walking heart rate reference in which a correspondence relationship of a standard value of a relative heart rate with respect to a walking speed is defined for every gender and every age, a speed acquisition unit acquires a measured value of a walking speed of a subject, a heart rate acquisition unit acquires a measured value of the relative heart rate of the subject. A standard value derivation unit derives the standard value of the relative heart rate corresponding to the measured value of the walking speed that has been acquired, based on the walking heart rate reference. A level determination unit determines an evaluation value of a physical strength level of the subject, based on a difference between the measured value of the relative heart rate and the standard value of the relative heart rate.

A device comprising a piece of planar substrate embedded with two sensors and two emitters. The substrate has a generally planar surface for application onto the wearer's body part. The emitters and sensors are shown to be arranged in such a way that no subset of any two emitters and one sensor, or subset of any two emitters and one sensor, forms a straight line, which prevents the two sensors from detecting the same noise caused by the same wearer movements.

Techniques for music selection based on exercise detection are disclosed. In one aspect, a method of operating a wearable device may involve determining, based on output of one or more biometric sensors, that a user of the wearable device has started an exercise and playing music for the user of the wearable device in response to determining the start of the exercise. For example, playing the music may involve turning on a music player based on the start of the exercise. In another example, the wearable device includes the music player.

A thermal control unit for controlling a patient's temperature includes a fluid outlet for delivering temperature-controlled fluid to a patient, a pump, a heat exchanger, and a controller that automatically pauses thermal treatment of the patient prior the patient reaching a target temperature. During the pause, the controller assesses a reaction of the patient and changes a temperature of the fluid only inside the thermal control unit if the patient is likely to reach the target temperature without further thermal treatment. However, if the patient is unlikely to reach the target temperature without further thermal treatment, the controller restarts the thermal treatment. The controller may pause thermal treatment again prior to reaching the target temperature and assess the patient's reaction. In some embodiments, the controller may selectively include and exclude a fluid reservoir in a circulation channel within the thermal control unit.

A mixed reality (MR) training system includes an identification algorithm (ML1) that identifies incidents of concern (IOCs) based on an incident report data set and related contextual data. Each IOC occurs in the data set with a frequency at least equal to a pre-determined threshold or the resulting consequence is at least equal to a different pre-determined threshold. The system also includes a prediction algorithm (ML2) configured to identify predicted changes in the frequency or contextual data of incidents, an experience generation algorithm (ML3) configured to generate an MR training experience based on IOCs identified by ML1 and the predictions of ML2. A fourth algorithm (ML4) tailors and optimizes MR generated training experiences based, in part, on (i) changes in the incident report data or contextual data or (ii) performance data or biometric response data received during or after a user's interaction with the MR training experience.

Methods, systems, and devices for heart rate detection are described. A method for measuring heart rate for a user may include receiving physiological data associated with the user, wherein the physiological data may include photoplethysmogram (PPG) data and motion data collected throughout a first time interval via a wearable device associated with the user. The method may include determining a set of candidate heart rate measurements within the first time interval based at least in part on the PPG data, selecting a first heart rate measurement from the set of candidate heart rate measurements based on the received motion data, and determining a first heart rate for the user within the first time interval based on the selected first heart rate measurement.