Systems and methods for lean muscle mass monitoring of patients and for identifying and treating at least one of Cachexia or Sarcopenia are disclosed. The system may include a dynamometer provided to patients, the dynamometer being configured to perform remote monitoring. The dynamometer may be used and data may be collected by patients without the supervision of a healthcare professional. Using the collected data, lean muscle mass may be tracked over time, to provide fast and accurate assessment of conditions. Using such an assessment, early treatment options can be targeted to patients to avoid progression into various disease states, for examples, more severe states of at least one of Cachexia or Sarcopenia.

A method for an expert system to develop fitness training plans includes operating a dynamic exertion system to receive a rate of perceived exertion (RPE) through a user interface of a display device, combines the RPE with a movement, a movement load, and movement repetitions into movement set data, and operates a dynamic exertion algorithm. The method then displays an adjusted movement information display including the prescribed load and the prescribed movement repetitions through the user interface. The dynamic exertion algorithm generates a prescribed load and prescribed movement repetitions, determines a difference in RPE from the expected RPE through operation of a comparator, recalculates the one repetition maximum load value using the calibration and adjustment model when the difference in RPE is greater than an RPE threshold value, and generates a display control comprising the prescribed load and the prescribed movement repetitions.

An electromechanical device for rehabilitation includes pedals coupled to radially-adjustable couplings, an electric motor coupled to the pedals via the radially-adjustable couplings, and a control system including a processing device operatively coupled to the electric motor. The processing device configured to, responsive to a first trigger condition occurring, control the electric motor to operate in a passive mode by independently driving the radially-adjustable couplings rotationally coupled to the pedals. The processing device also configured to, responsive to a second trigger condition occurring, control the electric motor to operate in an active-assisted mode by measuring revolutions per minute of the radially-adjustable couplings, and cause the electric motor to drive the radially-adjustable couplings when the measured revolutions per minute satisfy a threshold condition, and responsive to a third trigger condition occurring, control the electric motor to operate in a resistive mode by providing resistance to rotation of the radially-adjustable couplings.

An apparatus for measuring an eyelid tension according to an embodiment of the present disclosure includes: an eyelid speculum configured to widen an interval between an upper eyelid and an lower eyelid; an eyelid tension measuring sensor attached to one side of the eyelid speculum and configured to measure the eyelid tension of a person to be measured and output eyelid tension data; a position sensor configured to measure the interval between the upper eyelid and the lower eyelid; and a communication module configured to transmit the eyelid tension data to an analysis device.

An apparatus for measuring an eyelid tension according to an embodiment of the present disclosure includes: an eyelid speculum configured to widen an interval between an upper eyelid and an lower eyelid; an eyelid tension measuring sensor attached to one side of the eyelid speculum and configured to measure the eyelid tension of a person to be measured and output eyelid tension data; a position sensor configured to measure the interval between the upper eyelid and the lower eyelid; and a communication module configured to transmit the eyelid tension data to an analysis device.

A jaw movement analysis system includes circuitry that is configured to acquire chewing information including time-series information that represents a jaw movement of a user chewing a bite of food, and to determine an attribute of the food having been chewed by the user based on the chewing information acquired and based on an analysis model. The analysis model is generated by machine learning based on training data including first information that includes time-series information indicating a past jaw movement during a chewing of a bite of food, and second information that indicates an attribute of the food chewed during the past jaw movement associated with the first information.

Measuring muscle load in athletic activities, and associated systems and methods are described herein. In an embodiment, a method for monitoring muscle load of an athlete includes: determining a muscle effort (ME) of the athlete by a wearable electromyography (EMG) sensor, and determining at least one inertial measurement unit (IMU) output of the athlete. The method further includes comparing the ME and the IMU output of the athlete, and, based on comparing, determining a performance of the athlete.

In a physical strength evaluation system, a reference storage stores a walking heart rate reference in which a correspondence relationship of a standard value of a relative heart rate with respect to a walking speed is defined for every gender and every age, a speed acquisition unit acquires a measured value of a walking speed of a subject, a heart rate acquisition unit acquires a measured value of the relative heart rate of the subject. A standard value derivation unit derives the standard value of the relative heart rate corresponding to the measured value of the walking speed that has been acquired, based on the walking heart rate reference. A level determination unit determines an evaluation value of a physical strength level of the subject, based on a difference between the measured value of the relative heart rate and the standard value of the relative heart rate.

Apparatus, systems, and methods are provided for measuring and analyzing movements of a body and for communicating information related to such body movements over a network. In certain embodiments, a system gathers biometric and biomechanical data relating to positions, orientations, and movements of various body parts of a user performed during sports activities, physical rehabilitation, or military or law enforcement activities. The biometric and biomechanical data can be communicated to a local and/or remote interface, which uses digital performance assessment tools to provide a performance evaluation to the user. The performance evaluation may include a graphical representation (e.g., a video), statistical information, and/or a comparison to another user and/or instructor. In some embodiments, the biometric and biomechanical data is communicated wirelessly to one or more devices including a processor, display, and/or data storage medium for further analysis, archiving, and data mining. In some embodiments, the device includes a cellular telephone.

Apparatus, systems, and methods are provided for measuring and analyzing movements of a body and for communicating information related to such body movements over a network. In certain embodiments, a system gathers biometric and biomechanical data relating to positions, orientations, and movements of various body parts of a user performed during sports activities, physical rehabilitation, or military or law enforcement activities. The biometric and biomechanical data can be communicated to a local and/or remote interface, which uses digital performance assessment tools to provide a performance evaluation to the user. The performance evaluation may include a graphical representation (e.g., a video), statistical information, and/or a comparison to another user and/or instructor. In some embodiments, the biometric and biomechanical data is communicated wirelessly to one or more devices including a processor, display, and/or data storage medium for further analysis, archiving, and data mining. In some embodiments, the device includes a cellular telephone.