Systems and methods are provided for testing the ability of an individual to lift objects under various conditions. During standard lifting tests, the average acceleration and velocity of each lift, as well as the distribution of force between the hands and feet of the patient, are electronically measured and recorded. These objective factors can then be used to determine whether the patient is exerting maximal effort, and to assess a patient's condition and progress during a rehabilitation program. In example embodiments, one or more components of the system are adjustable so as to accommodate users of various posture, mechanics, size and movement capabilities.

A system for analysis of user gait and to provide correction in form of haptic and visual feedback. This system comprises a motion and force sensors and a haptic actuator embedded in the user shoe insoles in communication with a smart-phone based analysis application, configured to calculate motion and orientation of the user feet in relation to the value, location and distribution of ground reaction forces measured by sensors located in the shoe insoles and after analysis of said forces and motion, to provide haptic feedback to the user foot instructing about the location (and timing) of pressure the user must apply to achieve an optimal gait.

Devices, systems, and methods are provided for analyzing and treating learning disorders using software as a medical device. A method may include identifying, by a device, application-based cognitive musical training (CMT) exercises associated with performance of software; receiving a first user input to generate a first sequence of the application-based CMT exercises; presenting a first application-based CMT exercise of the application-based CMT exercises based on the first sequence; receiving, during the presentation of the first application-based CMT exercise, a second user input indicative of a user interaction with the first application-based CMT exercise; generating, based on a comparison of the second user input to a performance threshold, a second sequence of the application-based CMT exercises, the first sequence different than the second sequence; and presenting a second application-based CMT exercise of the application-based CMT exercises based on the second sequence.

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.

Disclosed herein are implementations of a method and apparatus for stroke self-detection. The method and apparatus may include a mobile platform for stroke detection. The method may include receiving sensor data. The method may include comparing the sensor data with a baseline test result to determine a test score. The method may include determining a passing test result based on a threshold. The method may include transmitting the results or an alert to one or more of an emergency contact, emergency medical services, a physician, or a telemedicine provider.

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.

Medical device systems and methods are disclosed herein for assessing motor symptoms in Parkinson's disease patients through passively and/or actively acquired sensor data of motor behaviors and generating motor system assessments. Passive movement data and/or active motor performance data collected from Parkinson's disease patients is representative of EQ-5D-5L, PDQ-39, and/or MDS-UPDRS health status measurement data to more accurately predict quality of life, health status, and disease severity of Parkinson's disease patients. The generated motor system assessment may be used to provide neurologists and other health professionals with more accurate treatment recommendations and disease management protocols rather than using patient surveys alone.

The abnormal data processing system is provided with: a storage unit for holding a multiple-subject DB in which data on multiple subjects are accumulated and individual-subject DB in which data on individual subjects are accumulated; an individual-subject DB divergence-degree calculation unit for calculating an individual-subject DB divergence degree which is the degree of divergence of the new data from the individual-subject DB; a multiple-subject DB divergence degree calculation unit for calculating a multiple-subject DB divergence degree which is the degree of divergence of the new data from the multiple-subject DB; and a composite divergence degree calculation unit for determining a composite divergence by compositing the individual-subject DB divergence degree and the multiple-subject DB divergence degree using the number of data instances in the individual-subject DB. The abnormal data processing system determines whether or not the new data is abnormal on the basis of the composite divergence degree.

A method and user device for providing a unified Parkinson's disease rating scale (UPDRS) value by a user device includes generating, by a sensor of the user device, sensor data based on a user of the user device manipulating the user device. The UPDRS value is determined based on the sensor data and a deep neural network (DNN) model. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

Provided is a technique that trains motor imagery to reinforce brain waves, and a guidance method for motor imagery displays virtual reality including a virtual body part corresponding to a user's real body part the user, detects a movement of the real body part through a motion sensor to track a motion, and visually displays the movement of the virtual body part through the virtual reality according to the tracked motion to induce an ownership feeling that makes the user mistake the virtual body part for the real body part.