Under the control of a controller, a drive mechanism portion moves a massaging member and an ascent-descent mechanism moves up and down the massaging member together with the entire drive mechanism portion. During an ordinary kneading massage, the massaging member performs a relative motion to describe a reference locus in the shape of a closed curve. The controller controls to make the massaging member perform a relative reciprocating movement within a partial movement range corresponding to a partial segment of the reference locus and simultaneously controls to make the ascent-descent mechanism move the drive mechanism portion up and down. The relative reciprocating movement of the massaging member along the partial segment of the reference locus and the up-down movement of the entire drive mechanism portion are combined together to produce a new motion of the massaging member describing a locus different from the reference locus.

In one embodiment, a kinetic shape is designed by determining an applied force to be applied to an object that is to incorporate the kinetic shape, determining a reactive force that is desired to be produced in response to the applied force, inputting the applied force and the reactive force into a kinetic shape equation, and solving the equation to obtain the kinetic shape.

A body care apparatus capable of providing optimal therapeutic care for a body of a user is provided. The body care apparatus includes a wearable device worn on the body of the user so as to obtain activity data of the user, a massage chair performing a massage on each body part of the user while supporting the body of the user, a data analyzing unit inferring condition data for each body part of the user according to the activity data obtained from the wearable device, and a controller controlling an operation of the massage chair according to the condition data inferred by the data analyzing unit. The body care apparatus may infer the condition data by deep learning of an artificial intelligence algorithm or a sensor fusion.

A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

A psychosomatic state adjustment support device includes: a storage section that stores a target psychosomatic state for each destination of a moving body; a specification section that specifies a current psychosomatic state of an occupant of the moving body; an acquisition section that acquires a destination of the moving body; a deciding section that decides a vibration pattern based on the target psychosomatic state according to the destination and the current psychosomatic state; and a control section that applies a vibration stimulation to the occupant by causing a vibration applying section provided in a seat on which the occupant is seated to vibrate based on the vibration pattern.

A chair-type massage machine includes a seat portion, a backrest portion that is reclinable rearward of the seat portion, and a forearm treatment portion that treats each of forearms of a person to be treated. The forearm treatment portion is mounted to each of both left and right side surfaces of the backrest portion.

A steam physiotherapy mechanism includes a receptacle having a chamber formed in a housing, a steam pipe disposed in the housing, a steam generating device connected to the steam pipe for generating and supplying a steam into the chamber of the housing, a number of tiles disposed in the housing, and a number of retainers engaged with the tiles for anchoring the tiles in the housing, the tiles each include a number of casings each having a compartment, and one or more of the compartments of the casings are filled with an ore mud. The tiles each include a number of passages formed in the casings and communicating with the compartments of the casings.

A method for controlling a robotic walking assistant that includes a wheeled base having one or more wheels, two handles and a foldable seat that are coupled to the wheeled base, includes: detecting whether two hands of a user have held the two handles of the robotic walking assistant; receiving a command from the user to select an operation mode in response to detection of the two hands holding the two handles; controlling the wheeled base to move in response to a walking assistive mode being selected; providing resistance to at least one of the one or more wheels according to selection of the user, in response to a walking training mode being selected; and locking the one or more wheels in response to a static training mode being selected.

A robotic walking assistant includes a wheeled base having a base and one or more position adjustable wheels connected to the base, a body disposed in a vertical direction, positioned on the wheeled base and having a handle, and a control system that receives command instructions. Each of the one or more wheels is slidable with respect to the base between a retracted position and an extended position in a direction that is substantially parallel to a surface where the wheeled base moves. In response to the command instructions, the control system moves the one or more wheels between the retracted positions and the extended positions.

A method for optimizing at least one exercise. An exercise apparatus is configured to enable a user to perform the at least one exercise. The method includes receiving user data. The method includes generating, based on the user data, initial target data. The method includes receiving measurement data associated with one or more sensors. The method includes determining, differential data. The determining is based on one or more differences between the initial target data and the measurement data. The method includes receiving cohort data. The method includes generating, via an artificial intelligence engine and based on the differential data, a machine learning model trained to generate message data based on a difference between the differential data and the cohort data. The method includes transmitting, to an interface associated with a user, a message to the user based on the message data.