A kinesitherapy apparatus includes a measuring instrument, a pedaled rotational mechanism, a rotating electrical machine configured to apply an assist load, which is a regenerative load or a power running load, to the pedaled rotational mechanism, and a motion control device. The motion control device performs power running operation of the rotating electrical machine so that a minus assist load is generated in a warm-up period. In a ramp loading period following the warm-up period, the motion control device raises the assist load from the minus assist load, and calculates an anaerobic threshold based on time-series data of oxygen uptake and carbon dioxide emission that are obtained via the measuring instrument.

A computer-implemented system for a remote examination is disclosed. The computer-implemented system includes a treatment device, a master console, a user interface, and a control system. The treatment device comprises one or more slave sensors and a slave pressure system, the treatment device configured to be manipulated while a patient performs a treatment plan. The master console comprises a master device. The user interface comprises an output device configured to present telemedicine information associated with a telemedicine session. The control system comprises one or more processing devices operatively coupled to the master console and the treatment device. The one or more processing devices are configured to receive slave sensor data from the one or more slave sensors, use a manipulation of the master device to generate a manipulation instruction, transmit the manipulation instruction, and during the telemedicine session, use the manipulation instruction to cause the slave pressure system to activate.

An electromechanical device for rehabilitation includes a motor and a control system including one or more processing devices operatively coupled to the motor. The one or more processing devices are configured to, responsive to a first trigger condition occurring, control the motor to operate in a passive mode, responsive to a second trigger condition occurring, control the motor to operate in an active-assisted mode, and responsive to a third trigger condition occurring, control the motor, by providing resistance, to operate in a resistive mode.

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.

A method for optimizing at least one exercise is provided. The method includes receiving user data. The user data includes biometric attribute data associated with a user of an exercise device. The method includes generating at least one interval, the at least one interval including at least duration data and target power data each associated with the exercise. The method includes during the at least one interval, receiving measurement data associated with at least one of the user and the exercise device. The method includes calculating, based on the measurement data and the user data, energy data associated with an expended energy of the user during the at least one interval, the energy data including quantity data and source information each associated with at least one energy source. The method includes generating, via an artificial intelligence engine, a machine learning model trained to identify the at least one energy source.

A disorder detection system includes: a pair of left and right footrests configured so that left and right feet of a user are respectively placed thereon to perform an exercise of legs therewith; a pair of left and right slide mechanisms for enabling the footrests to slide in a front/rear direction with respect to a sitting part, the slide mechanisms including a resistance part for applying a resistance to the sliding; a moving mechanism for enabling the left and right slide mechanisms and the footrests to move independently of each other; an angle detection unit for detecting angles of joints of left and right lower legs of the user around a roll axis, a yaw axis, and a pitch axis; and a display unit for displaying the detected angles of the joints of the left and right lower legs of the user around the roll, yaw, and pitch axes.

A method provides for optimizing at least one exercise. The method includes receiving first image data. The first image data includes first pixel data associated with the user performing the exercise at a first time. The method includes receiving second image data. The second image data includes second pixel data associated with the user performing the exercise at a second time. The method includes determining, based on a difference between the first pixel data and the second pixel data, deviation data associated with a profile of the user. The method includes generating outline data based on the deviation data and corresponding to a frontal area of the user. The method may also include determining drag coefficient data based on the frontal area of the user. The method includes determining, based on the outline data and the drag coefficient data, drag force data associated with the user using the exercise device.

A system for rehabilitation is disclosed. The system for rehabilitation includes one or more electronic devices comprising one or more memory devices storing instructions, one or more network interface cards, and one or more sensors, wherein the one or more electronic devices are coupled to a user. The system for rehabilitation further includes one or more processing devices operatively coupled to the one or more memory devices, the one or more network interface cards, and the one or more sensors. The one or more processing devices are configured to execute the instructions to receive information from the one or more sensors. The one or more processing devices are further configured to execute the instructions to transmit the information to a computing device controlling an electromechanical device, via the one or more network interface cards.

A weight training method, a weight training apparatus and a weight training system are provided. In the method, a weight of a load of a user operating the weight training apparatus is detected by a load sensor, a motion of the load is detected by an activity sensor, and thereby an operation power of the weight training apparatus is calculated. A force applied by the muscle portion when the user operates the weight training apparatus is detected by at least one biophysical quantity sensor disposed on at least one muscle portion of the user and used to calculate an energy power consumed by the user. An exercise efficiency value of the user is calculated by using the energy power and the operation power, and the user is prompted to adjust an operation performed on the weight training apparatus when the exercise efficiency value drops beyond a preset ratio.

A computer-implemented system for a remote examination is disclosed. The computer-implemented system includes a treatment device, a master console, a user interface, and a control system. The treatment device comprises one or more slave sensors and a slave pressure system, the treatment device configured to be manipulated while a patient performs a treatment plan. The master console comprises a master device. The user interface comprises an output device configured to present telemedicine information associated with a telemedicine session. The control system comprises one or more processing devices operatively coupled to the master console and the treatment device. The one or more processing devices are configured to receive slave sensor data from the one or more slave sensors, use a manipulation of the master device to generate a manipulation instruction, transmit the manipulation instruction, and during the telemedicine session, use the manipulation instruction to cause the slave pressure system to activate.