An exercise rating and improvement system comprising: a feature amount extraction unit for extracting, from information obtained from a subject, a feature amount about exercise efficiency; an rating unit for rating exercise efficiency of the subject by comparing the extracted feature amount and a feature amount to be compared; and an improvement information providing unit for providing, on the basis of the rating result, information such that the feature amount of the subject approaches the feature amount to be compared.

In one embodiment, an apparatus (12) that samples a signal obtained or derived from an accelerometer, filters the samples, accumulates the filtered samples, and determines which limb the apparatus is associated with based on a comparison of the filtered accumulated samples and a threshold set.

A system is disclosed herein for providing a kinetic assessment and preparation of a prosthetic joint comprising one or more prosthetic components. The system comprises a prosthetic component including sensors and circuitry configured to measure load, position of load on a curved surface, joint stability, range of motion, and impingement. In one embodiment, the system is for a ball and socket joint of a musculoskeletal system. The system further includes a computer having a display configured to graphical display quantitative measurement data to support rapid assimilation of the information. The kinetic assessment measures joint alignment under loading that will be similar to that of a final joint installation. The kinetic assessment can use trial or permanent prosthetic components. Furthermore, adjustments can be made to the applied load magnitude, position of load, and joint alignment by various means to fine-tune an installation.

Fall detection systems and methods use radar chips to scan monitored regions such that data obtained by the scanning radar chip are processed to identify targets within the monitored region. Targets are tracked and profiled indicating their posture and fall detection rules are applied. Standard energy profiles and time dependent energy profiles are generated for various segments of the monitored region and compared to the current energy profile for each target segment of the monitored region. Anomalies are detected, false fall alerts filtered out and verified fall alerts are generated.

A sports injury sensing system and method are provided. The sports injury sensing system includes a sports injury sensing apparatus. The apparatus receives a plurality of inertial sensing data of a user, and each of the inertial sensing data corresponds to a body part of the user. The apparatus determines an exercising body part of the user based on the inertial sensing data. The apparatus receives a thermal image sensing datum corresponding to the exercising body part, wherein the thermal image sensing datum indicates a body temperature state of the user. The apparatus analyzes a temperature change of surrounding muscles of the exercising body part based on the thermal image sensing datum. The apparatus calculates a sports injury assessment based on the inertial sensing data and the temperature change of surrounding muscles.

According to one embodiment, a proficiency determination apparatus includes a processing circuit. The processing circuit acquires first time-series data about biological information of a worker in a predetermined period. The processing circuit calculates second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data. The processing circuit calculates an appearance condition of the physiological index by analyzing the second time-series data. The processing circuit determines a proficiency of the worker based on the appearance condition of the physiological index.

A system and method for human motion detection and tracking are disclosed. In one embodiment, an optical sensing instrument monitors a stage. A memory is accessible to a processor and communicatively coupled to the optical sensing instrument. The system captures a depth frame from the optical sensing instrument. The depth frame may include at each image element first coordinate values including a point related to a distance from the optical sensing instrument. The depth frame is converted into a designated depth frame format, which includes at each image element second coordinate values relative to the depth frame. Probability distribution models are applied to the designated depth frame format to identify a respective plurality of body parts. The position of each of the respective plurality of body parts in the designated depth frame is calculated as is the position of each of the plurality of body parts in the depth frame.

A recognition method executed by a processor, includes: acquiring positional relation between a plurality of sensors each of which senses a distance to an object; provisionally classifying an orientation of the object relative to each individual sensor included in the sensors into one of a plurality of classifications based on sensing data acquired by the individual sensor; calculating likelihood of each combination corresponding to the positional relation between the sensors based on a result of provisional classification of the orientation of the object relative to the individual sensor; and classifying the orientation of the object corresponding to each individual sensor in accordance with the calculated likelihood of each combination.

This disclosure relates generally to breathing analysis of a subject. Breathing analysis on a regular basis allows early detection for the onset of diseases, thus saving resources and cost in treatments. The existing state of art techniques require specialized devices to collect-infer the breathing and are mostly limited to analyzing breathing rate. The disclosure enables breathing analysis using a personal digital assistant (PDA). The breathing analysis includes (a) estimating exhale period-inhale period, (b) estimating the breathing rate and (c) determining the type of breathing. A PDA such as a smartphone is used receive accelerometer data from a subject. The received data is pre-processed in several steps including estimating a plurality of parameters, identifying a plurality of breathing cycles. The breathing cycles of the subject are further analyzed at real time based on the plurality of parameters to provide the breathing analysis of a subject.

A system for monitoring exercise activity in a gym environment includes an image-based monitoring arrangement, a storage device, and a replay device. The monitoring arrangement generates a time series of 3D representations of an individual, with each 3D representation defining a pose of the individual and comprising 3D positions of a plurality of predefined feature points of the individual. The storage device receives and stores an exercise sequence, which comprises at least part of the time series of 3D representations and corresponds to an exercise performed by the individual. The replay device retrieves the exercise sequence from the storage device, renders an animation of the individual when performing the exercise based on the exercise sequence, and provides the animation for display. The system enables a user to review the exercise at any desirable viewing angle and/or magnification.