A data processing method for a care-giving robot and an apparatus comprises receiving data from a target object comprising a capability parameter of the target object, generating a growing model capability parameter matrix of the target object that includes the capability parameter, a capability parameter adjustment value, and a comprehensive capability parameter that is calculated based on the capability parameter; adjusting the capability parameter adjustment value in the growing model capability parameter matrix, to determine an adjusted capability parameter adjustment value; determining whether the adjusted capability parameter adjustment value exceeds a preset threshold; and sending the adjusted capability parameter adjustment value to a machine learning engine when the adjusted capability parameter adjustment value is within a range of the preset threshold.

Provided are display screens for electronic devices and methods for displaying content on electronic devices, that are particularly suitable for users who are suffering from or recovering from a concussion or mild traumatic brain injury (MTBI), migraine, or computer vision syndrome. Embodiments comprise a component that modifies at least one parameter of content that is displayed on the display screen, wherein the modified displayed content reduces, minimizes, or eliminates negative side effects of users. Embodiments may include computer executable programmed instructions stored on a non-transitory computer readable storage medium that direct a processor to modify at least one parameter of content that is displayed on a display screen of an electronic device, and/or to implement a simplified graphical user interface. One embodiment is implemented using an e-paper display screen.

A system, method, and apparatus are provided for a robotic system effecting autonomous therapy or treatment of a body having soft and/or hard tissue. A system, method, and apparatus are provided for a robotic control system having a fused sensing stream for predicting the deformation of a robotic end effector and the tissue that the end effector is in contact with using, e.g., a Finite Element Analysis (FEA) model. The model updates provide adjustment parameters for the control system to compensate for changes in the mechanical nature of the robotic end effector and the characteristics and/or movement of the tissue being treated by the robotic end effector.

A system, method, and apparatus for a robot system that manipulates the surface of an object effect programmed manipulation goals such as reaching specific locations on the surface of the object, displacing the surface of the object, applying a predetermined force and torque to the surface of the object, dynamically changing the contact point between the robot and the object, and applying force to structures below the surface of the object. The system and method determine the state of the object through a sensing method that includes, without limitation: torque and force measurement, visible light sensors, range and depth sensors, ultrasound sensors, thermographic sensors, and worktable force measurement.

An actuator has a linear driving mechanism, an output member, and an elastic member. The linear driving mechanism has a stepping motor, a thread rod assembly, and a linearly moveable member. The threaded rod assembly is connected with the stepping motor. The linearly moveable member is located at a side of the stepping motor and is connected with and driven by the thread rod assembly to reciprocatively move along a power input axis. The output member is disposed on a side of the linearly moveable member and has a capability of linearly moving along a power output axis that is co-axial with the power input axis. The elastic member is connected between the linearly moveable member and the output member to provide an elastic force along the power input axis.

A rehabilitation system for rehabilitation of a subject including at least one end-effector for interacting with the subject, the end-effector having at least two degrees of freedom of motion, at least one actuator for actuating the at least one end-effector, at least one sensor for measuring at least the position and the speed of the at least one end-effector; at least one sensor for measuring the interaction force between the subject and the end-effector; a memory including at least two initial coefficients and a session including at least one exercise including at least one reference trajectory to be carried out by the subject through actuation of the end effector; and an actuator controlling unit. The memory delivers the initial coefficients and the session, the sensors deliver measurement signals to the controlling unit, and the controlling unit provides a force-controlled feedback based on the initial coefficients.

A system, method, and apparatus for a robot system that manipulates the surface of an object effect programmed manipulation goals such as reaching specific locations on the surface of the object, displacing the surface of the object, applying a predetermined force and torque to the surface of the object, dynamically changing the contact point between the robot and the object, and applying force to structures below the surface of the object. The system and method determine the state of the object through a sensing method that includes, without limitation: torque and force measurement, visible light sensors, range and depth sensors, ultrasound sensors, thermographic sensors, and worktable force measurement.

A system, method, and apparatus are provided for a robotic system effecting autonomous therapy or treatment of a body having soft and/or hard tissue. A system, method, and apparatus are provided for a robotic control system having a fused sensing stream for predicting the deformation of a robotic end effector and the tissue that the end effector is in contact with using, e.g., a Finite Element Analysis (FEA) model. The model updates provide adjustment parameters for the control system to compensate for changes in the mechanical nature of the robotic end effector and the characteristics and/or movement of the tissue being treated by the robotic end effector.

Disclosed is a rehabilitation robot training system for monitoring and suppressing the compensatory movement of a hemiplegic upper limb. The system includes an upper computer control center, an interaction display screen, a force feedback glove, a position tracker, upper limb rehabilitation robot tail end connectors, an upper limb rehabilitation robot, a base and a pressure cushion. One upper limb rehabilitation robot tail end connector is mounted on a tail end of each of two robotic arms of the upper limb rehabilitation robot, and the upper limb rehabilitation robot tail end connectors are respectively worn on an upper arm and a forearm of a patient to drive an arm to move; the upper computer control center stores and processes data, collected by the position tracker, the force feedback glove and the pressure cushion in real time, of the patient, and monitors and analyses whether the patient does a compensatory gesture.

A holding mechanism holds a care-receiver, a traction mechanism that is connected to the holding mechanism, and the traction mechanism pulls the holding mechanism so that the holding mechanism draws a predetermined path. On the basis of a position of the holding mechanism detected by a position sensor and a force detected by a force sensor, if the position of the holding mechanism is not on the predetermined path, a controller controls the traction mechanism so that the holding mechanism draws the predetermined path by changing the position of the holding mechanism to a position on the predetermined path at a time after the time at which the position is detected.