A method can include receiving (1) images of at least one subject and (2) at least one total mass value for the at least one subject. The method can further include executing a first machine learning model to identify joints of the at least one subject. The method can further include executing a second machine learning model to determine limbs of the at least one subject based on the joints and the images. The method can further include generating three-dimensional (3D) representations of a skeleton based on the joints and the limbs. The method can further include determining a torque value for each limb, based on at least one of a mass value and a linear acceleration value, or a torque inertia and an angular acceleration value. The method can further include generating a risk assessment report based on at least one torque value being above a predetermined threshold.

A training apparatus is capable of generating and presenting a suitable training menu for finger exercise to maintain or improve a cognitive function and/or an exercise function of a human and supporting training of the human. The training apparatus includes a measuring apparatus and a terminal device. Analysis evaluating data based on measurement of the finger exercise including finger tapping is obtained, and the analysis evaluating data contains an evaluation value of an index item related to an exercise function of a user. A training menu for the user is generated based on the analysis evaluating data and contains a training item for the finger exercise. The index item includes at least one of an amount of exercise, endurance, rhythmicity, cooperativeness of both sides, or marker trackability. The training item includes an exercise to carry out the finger tapping in accordance with teaching information, stimulation, or a marker.

A positioning method of functional rotation center of shoulder based on rigid upper arm model includes: step 1: abstracting a human upper arm into a cylinder with FRCS as a center of top surface; step 2: determining a reference axis vector of the cylinder; step 3: determining an axis vector of the cylinder and a displacement from the reference axis vector to the axis vector; step 4: correcting a central axis direction of the cylinder; step 5: determining a height compensation of the cylinder, and positioning the FRCS. The method has higher accuracy for the positioning result of FRCS, the positioning result of FRCS has better stability relative to the upper arm and trunk, and can be used to establish a more accurate human digital dynamic model and predict more accurate human posture.

A device or system including an assessment device with a body with a top surface ruled with a pattern to or instruct students in their parts during a physical position or movement between different positions, such as may be learned in a class or virtual class. The rulings include vertical lines and horizontal lines at various spaces, spacings, and intersections.

A method for providing an auditory program according to an embodiment of the present disclosure may include: decoding, by a processor, first audiovisual data including a target sound to be aurally perceived by a user and an ambient sound reflecting a real-life environment, and playing back the first audiovisual data through a display and a speaker; receiving, by the processor, the user's input based on the result of aural perception of the target sound from the user through a user interface; and changing, by the processor, at least one of parameters of the audiovisual data, based on the user's input, and playing back the audiovisual data through the speaker or the display, or determining a fitting parameter of an assistive listening device, based on the user's input.

An estimation method includes: transmitting transmission signals using M transmission antenna elements; receiving reception signals by N reception antenna elements; calculating, from the reception signals, a first matrix whose components are complex transfer functions indicating propagation characteristics between the transmission antenna elements and the reception antenna elements; estimating, using the first matrix, a position and an orientation of a living body relative to an estimation device; when the estimated position is in a first identification region and the estimated orientation is in a predetermined range from a first direction, identifying the living body based on time waveforms of the reception signals and a first training signal which is obtained in advance in the first identification region and corresponds to the living body; and adding, as an identification region for identifying the first living body identified, a new identification region based on an estimated position of the first living body identified.

Embodiments of the instant invention relate to applying motor learning to promote remyelination following demyelination in a subject having a condition or disease. In certain embodiments, applying motor learning alone or in combination with vagus nerve stimulation (VNS) induces the production of new and preserves surviving oligodendrocytes. In accordance with certain embodiments of the disclosure, motor learning, when properly timed, enhances oligodendrogenesis after injury and recruits mature oligodendrocytes to participate in remyelination through the generation of new myelin sheaths. In other aspects of the disclosure, VNS paired with motor learning enhances remyelination following demyelination.

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.

The present invention relates to a system for neuromuscular rehabilitation of a patient having an affected limb comprising: a feedback member arranged to give real-time visual feedback; a plurality of electrodes arranged to acquire an electric signal corresponding to an intent to move said affected limb; a control unit configured to: perform pattern recognition of said electric signals, wherein at least one feature in said electric signal is used to predict motion intent of said affected limb adjacent to at least one joint, such aggregated motions of said affected limb are predicted; based on output signals from said performed pattern recognition, control said feedback member to perform actions corresponding to said motions, whereby said actions of said feedback member are individually and simultaneously controlled by said patient via said intended motions.

The present disclosure relates to a method and a system for detecting a neurological disease and an eye gaze-pattern abnormality related to the neurological disease of a user. The method comprises displaying stimulus videos on a screen of an electronic device and simultaneously filming with a camera of the electronic device to generate a video of the user's face for each one of the stimulus videos, each one of the stimulus videos corresponding to a task. The method further comprises providing a machine learning model for gaze predictions, generating the gaze predictions for each video frame of the recorded video, and determining features for each task to detect the neurological disease using a pre-trained machine learning model.