A rehabilitation evaluation apparatus includes a sensor signal acquisition unit configured to acquire a sensor signal output from a detection sensor, a selection unit configured to select at least one myoelectric signal having a correlation with the sensor signal acquired by the sensor signal acquisition unit from among the plurality of second myoelectric signals on the second-side part acquired by the myoelectric-signal acquisition unit, and a similarity output unit configured to select a first myoelectric signal that has been output from a myoelectric sensor attached in a place that is left-right symmetric to a place of the myoelectric sensor that has output the second correlated myoelectric signal selected by the selection unit from among a plurality of first myoelectric signals on the first-side part acquired by the myoelectric-signal acquisition unit, calculate a similarity between these correlated myoelectric signals, and outputs the calculated similarity.

A system includes a minimally intrusive display system (MIDS) configured to be disposed on an eyewear. The MIDS includes a display system and a sensor system configured to provide for a sensor data. The MIDS further includes a processor configured to process the sensor data to derive a physiological measure. The processor is further configured to display, via the display system, the physiological measure, wherein the display system is disposed in the eyewear so that the physiological measure is only viewed when a user of the eyewear turns the user's pupil towards the display system at angle α from a forward direction.

A pulse sensor is capable of measuring a pulse rate of a wearer at a peripheral artery. In an embodiment, the pulse sensor includes a magnet supported to move responsive to an arterial pulse and a magnetometer configured to detect changes in a magnetic field produced by the magnet. The magnet may include a plurality of ferromagnetic particles disposed in or on a flexible substrate configured to be held adjacent to human skin subject to arterial palpation and a magnetic sensor configured to sense movement of the ferromagnetic particles. A system and method may measure hydration includes using a pulse sensor to measure pulse rate and modulation. The wearer is prompted when the pulse rate and pulse modulation indicate a response to dehydration of the wearer.

The walking training system includes: a treadmill; a determination unit configured to determine whether a walking of the trainee on the treadmill is an abnormal walking based on predetermined abnormal walking symptoms; a display unit configured to display a result of a determination of each of the abnormal walking symptoms; a reception unit configured receive a selection of at least one result of the determination from the results of the determinations, each of which displayed on the display unit, in which regarding pieces of advice about adjustment items for improving the abnormal walking symptoms in the result of the determination which the reception unit has received the selection, the display unit preferentially displays the pieces of advice that are common to pieces of advice about adjustment items for improving the abnormal walking symptoms in a result of another determination in which the determination unit determines the abnormal walking.

A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

A system for sensing true positive impacts may include a sensing device configured for secured coupling to a user. The sensing device may include a sensor configured for sensing accelerations of an impact and for generating a signal based on the impact. The sensing device may also include a control sensor for sensing when the sensing device is in position for sensing. The sensing device may also include a computer-readable storage medium having instructions stored thereon for receiving and capturing the signal from the sensor, and comparing first and second signals from the control sensor to determine if the signal is a true positive signal. The system may also include a processor for processing the instructions to capture the signal, perform the comparing, and identify the signal as a true positive signal. Method of sensing true positive impacts and of workload monitoring are also provided.

Methods, apparatus, systems, and articles of manufacture are disclosed for non-contact sensing of vital signs. An example electronic device to measure vital signs includes a camera to capture an image; a radar antenna to transmit and receive radar signals; and processing circuitry to: identify a subject in the image; identify a location of the subject in an environment; control the radar antenna to steer the radar signals toward the location; and determine a vital sign of the subject based on a reflected radar signal.

Aspects of the subject technology relate to communication device used as a power meter. The communication device includes circuitry to determine values of several forces and a processor. The processor determines a combined force by combining the determined values of the forces. The processor further determines a value of a power based on the s combined force, a speed and a loss factor. The communication device is used by a user to measure the power. The power is generated by the user when engaged in an activity, and the forces affect a movement of the user.

The embodiments of the present disclosure are capable of capturing a user's movement using inertial measurement units (IMUs) that are embedded in, or otherwise attached to, clothing. In one embodiment, a wearable system for capturing a user's bodily movements includes a wearable item mechanically coupled to an inertial measurement unit (IMU). The wearable item, when worn by a user, positions the IMU proximate to a body part of the user. The system further includes a processor communicatively coupled to the IMU and configured to receive the sensor data from the IMU, generate movement data based on the sensor data, and transmit the movement data to a device. The device includes a processor configured to receive the movement data, generate a kinematic chain model of the user, the model representing positions and orientations of one or more joints of the user at a given time, modify the kinematic chain model based on the movement data, determine a force experienced at a joint of the user using the kinematic chain model, and record the kinematic chain model and the force over a period of time.

A method and system for heterogeneous event detection. Sensor data is obtained and divided into discrete data windows. Each data window is defined by and corresponds to a time period of the sensor data. A time-frequency representation over the time period is calculated for each data window. A filter mask is calculated based on the data window corresponding to the time-frequency representation. The filter mask is applied for reverting the time-frequency representation to a time representation, resulting in filtered data. Features, such as extrema or other inflection points, are identified in the filtered data. The features define events, and transforming the time-frequency representation back into the time domain emphasizes differences between more and less prominent frequencies, facilitating identification of heterogeneous events. The method and system may be applied to body movements of people or animals, automaton movement, audio signals, light intensity, or any suitable time-dependent variable.