An isometric, dynamic isotonic concentric and dynamic isotonic eccentric motorized guidance exercise apparatus for human muscle development is provided. The exercise apparatus comprises a frame, an electric motor, the electric motor including an output shaft and secured to the frame, a drive guidance assembly, the drive guidance assembly secured to the frame and connected to the output shaft; at least one tactile feedback interface member, the at least one tactile feedback interface member secured to the drive guidance assembly; a weight plate, the weight plate secured to a limb of the human body, the limb positioned at the at least one tactile feedback interface member and wherein energizing the electric motor actuates the drive guidance assembly, the drive guidance assembly induces a motion in the at least one tactile feedback interface member, the limb engages the at least one tactile feedback interface member and the limb actuates the weight plate.

A folding exercise bike can be easily assembled and disassembled/folded for storage and/or transportation. The exercise bike can include a telescoping seat, a telescoping stem, a fold to stow handlebar and fold down locking legs. Various configurations for the exercise bike can be used. The exercise bike can include a wireless transmitter to transmit cycling data to a user's portable electronic device.

A method for protecting healthcare information associated with an individual may include receiving at least a first electronic medical record associated with the individual and generating a patient identifier associated with the individual. The method may also include generating, using the patient identifier and at least a portion of the first electronic medical record, at least one protected electronic medical record corresponding to the first electronic medical record. The patient identifier may be associated with at least one characteristic of the individual. The method may also include providing, at least at a healthcare provider interface, at least one of the patient identifier and at least a portion of the at least one protected electronic medical record.

Disclosed are systems and methods for a computerized framework that leverages artificial intelligence (AI)/machine learning (ML) mechanisms to assign selected individuals to military operations. The disclosed framework comparatively analyzes an ops sheet of a military operation and profile data related to a user(s), and automatically determines user(s) who are optimal for the operation. The determined user or users possess the physical and/or intellectual capabilities to accurately and efficiently, with respect to real-world and electronic resources, perform and complete the operation. The disclosed framework provides a computerized platform that selects users for highly specific tasks based on the users' analyzed skill sets, and based on computerized determinations of how such users are predicted to perform using those skill sets, securely and/or confidentially provides the users access to information related to the operation.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a cardiovascular health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the cardiovascular health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. Wherein a machine learning model is used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

A method includes receiving data pertaining to a user that uses a treatment apparatus to perform a treatment plan. The data includes characteristics of the user, the treatment plan, and a result of the treatment plan. The method includes assigning the user to a cohort representing people having similarities to the characteristics of the user. The method includes receiving second data pertaining to a second user, the second data comprises characteristics of the second user. The method includes determining whether at least some of the characteristics of the second user match with at least some of the characteristics of the user, assigning the second user to the first cohort, and selecting, via a trained machine learning model, the treatment plan for the second user, and controlling, based on the treatment plan, the treatment apparatus while the second user uses the treatment apparatus.

A stride emulator device for efficiently utilizing human leg power for transference to a rotary drive system including a pair of levers, at least two gears, at least two crankshafts having crank arms, and where each lever includes a cam and cam track.

Provided are apparatuses for augmenting human speed, human-driven compliant mechanisms, artificial limbs to augment human movement, and the like. The apparatuses can include variable stiffness mechanisms including springs that can be configured to selectively store and subsequently release energy generated by human movement. The apparatuses can selectively release the captured energy supplied by the human to provide force and power output beyond the physical capability of the human.

A device for therapy or exercise includes a frame, a base at least partially supporting and extending from the frame, a user support moveably coupled to the base and positioned adjacent the frame, a foot crank system coupled to the frame, a hand crank system coupled to the frame, and a motor coupled to at least one of the foot crank system and the hand crank system. The motor selectively powers the foot crank system and the hand crank system and is operable in an active mode and a passive mode.

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.