The present disclosure relates to method and system for signal processing rehabilitation exercise signals. The method comprises the step of receiving a first and a second motion signals associated with movements of a body part, wherein the motion signals comprise temporal data of the movements. The method further comprises the step of segmenting each of the first and second motion signals into a plurality of segmented signals based on gradients of the motion signals, wherein each segmented signal has consistent gradient. The method further comprises the step of automatically modifying the segmented signals to form multiple combinations of matching signals with similar gradients between the first and second motion signals, such that the first and second motion signals are in one-to-one correspondence. The method further comprises the step of extracting corresponding time intervals of the matching signals in the correspondences.

An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

A muscle training apparatus with muscle strength detecting function includes a first supporting shell, a plurality of membrane pressure-sensing units, an arithmetic processing unit and an elastic covering unit. The first support shell is spherical and has a first outer surface and a first containing space. The membrane pressure-sensing unit is disposed on the first outer surface of the first support shell. The arithmetic processing unit is disposed in the first containing space and electrically connected to the membrane pressure-sensing unit. The elastic covering unit covers the first support shell.

An athletic garment includes sensors at different locations of the garment. The sensors are electrically coupled to a processing unit and/or a power source via one or more conduits that are printed onto the garment. The conduits are designed for improved flexibility to accommodate stretching in the garment that occurs as a user wearing the garment performs an exercise and for improved durability to resist corrosion due to friction, sweat, or washing of the garment. In one embodiment, the conduits are designed for decreased stress concentrations at seams of the garment. In one embodiment, the conduits are designed to create a conductive pathway between different surfaces of the garment to electrically couple sensors on a first side (skin side) of the garment and a processing unit and/or a power source on a second side (outer side) of the garment.

Described herein are systems and methods of guiding a user to achieve musculoskeletal counterpulsation. A method may include receiving a cardiovascular cycle signal from a first sensor; determining a heart rate of the user based on the cardiovascular cycle signal; receiving a rhythmic musculoskeletal activity timing signal from a second sensor; determining an actual musculoskeletal activity cycle (MSKC) to cardiovascular cycle (CC) timing relationship; comparing the actual MSKC to CC timing relationship to a target MSKC to CC timing relationship; providing a recurrent prompt to the user as a timing indication for performance of a rhythmic musculoskeletal activity to guide the user to achieve a musculoskeletal activity cycle rate (MSKR) that approaches the target MSKC to CC timing relationship; and altering a feature of the recurrent prompt based on a determined alignment between the actual MSKC to CC timing relationship and the target MSKC to CC timing relationship.

Presented is an Isokinetic exercise system having a base, a pedestal, a vertical member, a height adjustable vertical column for resting a rotary actuator on top, a resistance control valve unit with rotatable dials connected to the actuator, wherein the rotatable dials are selectively used to rotatably set a range of resistances for opposing movements to accommodate varying exerted forces by a user performing an intended exercise. The system further includes an electronics module to detect angle and pressure related data (as a measure of voltages) associated with the actuator, an A to D converter to convert the detected voltages in a digital form, a display unit embodying a program product for receiving, and processing the detected voltages to generate and display a muscular performance assessment report, store the received voltages for future comparison and enable printing the muscular performance assessment report, enable configuring next intended exercise.

There is described an integrated unweighted gait training system having an unweighting system comprising a computer controller; a gait measurement system in communication with the controller; and a display in communication with the computer controller adapted and configured to provide real-time feedback to a user of the integrated unweighting gait training system. The unweighting system may be a differential air pressure (DAP) unweighting system or a non-DAP unweighting system.

An Internet of Thing (IoT) device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

A pelvic floor muscle training device includes a pelvic floor muscle training device, an intelligent terminal, a cloud server, a VR device, and one or more application programs. The user does Kegel exercise wearing the training device, with the help of the VR device and scene induction, synergistic or independently, thus enhancing pelvic floor muscle function.