An exercise sensing method, an exercise sensing apparatus and an exercise sensing system are provided. The exercise sensing system includes a computing device, a storage device and at least one biophysical quantity sensor disposed on at least one muscle portion of a user. In the method, a current muscle strength of the muscle portion when the user performs an exercise is monitored by the biophysical quantity sensor. An exercise history of the user is accessed to obtain a muscle strength reference value of the muscle portion when the user previously performed the exercise. The current muscle strength is compared with the muscle strength reference value so as to adjust an exercise intensity of the exercise.

A system and method for controlling a device, such as a virtual reality (VR) and/or a prosthetic limb are provided. A biomimetic controller of the system comprises a signal processor and a musculoskeletal model. The signal processor processes M biological signals received from a residual limb to transform the M biological signals into N activation signals, where M and N are integers and M is less than N. The musculoskeletal model transforms the N activation signals into intended motion signals. A prosthesis controller transforms the intended motion signals into three or more control signals that are outputted from an output port of the prosthesis controller. A controlled device receives the control signals and performs one or more tasks in accordance with the control signals.

A system for ankle rehabilitation includes a motorized platform arranged to hold an ankle of a subject to be rehabilitated; a first sensor module arranged to detect signals representing movement intention of the ankle on the motorized platform; a second sensor module arranged to detect signals representing actual movement of the ankle on the motorized platform; and a processor arranged to process the signals detected by the first sensor module and the signals detected by the second sensor module, for control of movement of the motorized platform.

A display apparatus includes a controller for obtaining image information using an image obtainer; obtaining body images of a user based on the received image information; receiving menu information of at least one of a somatotype mode or an exercise purpose through an inputter; obtaining parameters for each part of a body based on the obtained body image; adjusting at least one of the obtained parameters for each part of the body based on the received menu information; changing an image for each part of the body among the body images based on the adjusted parameter; and displaying the changed image through a screen.

A weight training apparatus includes an electrical hoist and a cable coupled to the electrical hoist. A first end of the cable is coupled to the electrical hoist and a second end is configured to attach to a barbell assembly. A sensor is configured to output a signal indicative of a lift position of the barbell assembly. A controller is programmed to compare the lift position to an predetermined vertical locations and activate the electrical hoist to change the lift position of the barbell assembly based at least in part on at least one of the lift position or vertical lift velocity relative to the predetermined vertical locations.

The present invention relates to systems and methods for physical therapy in augmented reality (AR) comprising: at least one projector; at least one motion capture sensor; at least one surface EMG sensor, balance sensing unit; a computer in connection to said at least one projector, at least one motion capture sensor, and at least one surface EMG sensor and balance sensing unit. Wherein, movement and actions instructions are provided to a patient in visual and cues projected on a surface in patient's vicinity; and further wherein, data regarding patient's movements and actions are collected by said at least one motion capture sensor and at least one surface EMG sensor and balance sensing unit. It is within the provision of the invention that said data is processed and analyzed into a representation of patient's status and progress, further providing suitable therapy and exercise plans.

Provided is an artificial intelligence (AI) workout guide apparatus including a personal maximum weight (PMW) estimator configured to estimate PMW.sub.estimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data, and a PMW guider configured to provide PMW.sub.individual for the fitness equipment by complementing the PMW.sub.estimation with an individual objectification index of the user.

A device for rehabilitating patients especially with peripheral nervous system paralysis. The rehabilitation device comprising a remote control terminal, a base, an arm mounted to a column with adjustable height containing an motor propelling the arm and at least two electrodes of the electromyography (EMG) sensor according to the disclosure is characterized in that the actuator (7) enables the extension (4) to move within the angular range of 360°, while the EMG signal from the sensor connected to the muscle or muscles of the patient is transmitted to the network of the motor controlling module (2) and then further by radio or cable connection to a remote control terminal (1).

An upper-limb rehabilitation assisting device includes first and second handles coupled to first and second rotating shafts and rotationally operated by hands on a paralytic limb side and a healthy limb side; first and second biosignal detecting parts that detect first and second biosignals corresponding to the paralytic limb side and the healthy limb side; first and second drive parts that drive the first and second rotating shafts; and a control part that performs a cooperative control of the first rotating shaft and the second rotating shaft. The control part controls the torques of the first and second drive parts at the time of the cooperative control of the first and second rotating shafts the basis of the degree of cooperation between the first and second biosignals.

Aspects of the present disclosure are directed toward apparatuses and methods for rendering haptic environments, such as may be used in rehabilitation. As may be implemented in accordance with one or more embodiments, haptic rehabilitative movement is effected by providing feedback signals characterizing sensed engagement of a user's lower extremity with a crank coupled to a shaft that is driven by a motor, and controlling movement of the crank in response to the feedback signals. Force may be provided by the motor and shaft, by applying control inputs to the motor that cause the motor and crank to render respective haptic environments while engaged with the user's lower extremity, via rotation of the shaft. The haptic environments may include one or both of impedance-based haptic environments and admittance-based haptic environments.