A system for providing a therapy to a user comprising one or more motion sensors configured to measure motion data during motion of the user, a mobile computing device, connected to or held by the user and connected to the motion sensor to receive motion data, comprising a sensory output device configured to direct the user in the performance of exercises and at least one processor configured to: (a) receive a therapy start signal, (b) receive a baseline user motion level, (c) adjust the sensitivity of the one or more motion sensors according to the baseline user motion level, (d) select an exercise having a difficulty level which matches the baseline user motion level, (e) cause the sensory output device to direct the user to perform the exercise, (f) receive user motion data measured during user performance of the exercise from the one or more motion sensors, (g) use the user motion data to establish a further user motion level, (h) compare the further user motion level with the baseline user motion level, (i) when the further user motion level is equal to or greater than the baseline user motion level, set the baseline user motion level to a higher user motion level and go to (k), (j) when the further user motion level is less than the baseline user motion level, set the baseline user motion level to a lower user motion level and go to (k), (k) when a therapy stop signal is not received, return to (d), (I) when a therapy stop signal is received, record the baseline user motion level and cause the sensory output device to direct the user to stop the therapy the method characterised by the steps of: (m) scanning the mobile computing device to determine the operating system of the mobile computing device, (n) determining whether each of the one or more sensors is an accelerometer sensor, a gyroscope sensor or a global positioning system sensor, (o) scanning the one or more sensors to determine which of the sensors are currently available to measure motion data of the user, and (p) using determinations from steps (m), (n) and (o) to further calibrate the sensitivity of the one or more motion sensors.

The disclosure provides a movement determination method, a movement determination device, and a computer-readable storage medium. The method includes the following. In response to determining that a user has presented an initial movement corresponding to a to-be-detected movement, an anchor joint point among multiple joint points of the user is decided based on the to-be-detected movement. A movable range of each of the anchor joint points is decided. In response to determining that each of the anchor joint points leaves the corresponding movable range, it is determined that the user has stopped performing the to-be-detected movement.

A method can include determining, by a head-mounted device based on first data received from a depth-sensing device included in the head-mounted device, that a first distance of the head-mounted device from a landmark is outside a completion range; outputting, based on the determination that the first distance of the head-mounted device from the landmark is outside the completion range from the landmark, an indication that a repetition has yet to be completed; determining, based on second data received from the depth-sensing device, that a second distance of head-mounted device from the landmark is within the completion range; and based on the determination that the second distance of the head-mounted device from the landmark is within the completion range, incrementing a repetition counter and outputting an indication that the repetition has been completed.

A system and method for evaluation, detection, conditioning, and treatment of neurological functioning and conditions which uses data obtained while a person is engaged in simultaneously in a range of primary physical tasks combined with defined types of secondary activity, such as listening, reading, speaking, mathematics, logic puzzles, navigation of a virtual environment, recall of past stimuli, etc. The data from the physical and secondary activities are combined to generate a composite functioning score visualization indicating the relative functioning of areas aspects of neurological functioning; including those in which deficiencies may be present, which are early indicators of possible neurological conditions. Through algorithmic recommendations combined with expert and user input, a conditioning regimen targeting neurological aspects of interest paired with periodic testing allows the user to track their progress in these areas over time.

A method of detecting and identifying postures and gestures of a human user generates a reference model from a reference image and obtains an image of action or gesture being performed. The image is of a user and his flexible and hand-held portable device, and the image comprises a second identification feature. A state of a second feature of the second identification feature in the reference model can generate posture identification. The state of the second feature comprises size, shape, and location of the second identification feature in the hands of the user. A portable device and a non-volatile storage medium of a computer are also disclosed.

An assistance system for guiding exercise postures in a live broadcast has a cloud server, at least one first electronic device, and a second electronic device. The cloud server stores a teaching video and multiple templates corresponding to different time segments in the teaching video. Each one of the templates has multiple preset skeleton checking points and multiple movement threshold values respectively corresponding to the multiple preset skeleton checking points. The at least one first electronic device records an image of a first user to generate a skeleton streaming data. In a live broadcast, the at least one first electronic device determines whether the skeleton streaming data is abnormal according to the multiple templates. When abnormal, the at least one first electronic device outputs an abnormality notification. The second electronic device receives the abnormality notification in the live broadcast and displays the abnormality notification and a corresponding message.

A plurality of control sequences is stored. A user state is detected. A next control sequence associated with the user is selected from the plurality of control sequences based at least in part on the user state.

Disclosed is an exercise rehabilitation system using a smart mirror. The exercise rehabilitation system is configured with a rehabilitation exercise motion information database, in which rehabilitation exercise motion information is pre-stored, a user rehabilitation progress information database, in which user rehabilitation progress information is cumulatively stored in real time, a smart mirror device having a display panel that displays rehabilitation exercise coaching information, a touch panel attached to a front surface of the display panel to receive a user's touch input, and a half mirror attached to a front surface of the touch panel to allow the user to view a rehabilitation exercise of the user with naked eyes, and an artificial intelligence (AI) rehabilitation exercise coaching control module that selects the rehabilitation exercise motion information pre-stored in the rehabilitation exercise motion information database on the basis of the user rehabilitation progress information cumulatively stored in the user rehabilitation progress information database using an AI engine, and controls to display the selected rehabilitation exercise motion information and corresponding rehabilitation exercise coaching information on the display panel of the smart mirror device in real time.

A femoral region supporter (2) supports a femoral region of a user (1) in a travel direction. A force detector (3) detects force received by the femoral region supporter (2) from the femoral region of the user (1). A walking motion estimator (4) estimates walking motion of the user (1) based on the force detected by the force detector (3). The video generator (5) generates a video to be presented to the user (1) based on the walking motion estimated by the walking motion estimator (4). The video presenter (6) presents the video generated by the video generator (5) to the user (1).

In some implementations, a method includes: while presenting a 3D environment, obtaining user profile and head pose information for a user; determining locations for visual cues within the 3D environment for a first portion of a guided stretching session based on the user profile and head pose information; presenting the visual cues at the determined locations within the 3D environment and a directional indicator; and in response to detecting a change to the head pose information: updating a location for the directional indicator based on the change to the head pose information; and in accordance with a determination that the change to the head pose information satisfies a criterion associated with a first visual cue among the visual cues, providing at least one of audio, haptic, or visual feedback indicating that the first visual cue has been completed for the first portion of the guided stretching session.