Development and Assist-As-Needed Control of an End-Effector Upper Limb Rehabilitation Robot
Source abstract
Abstract
Robot-assisted rehabilitation therapy has been proven to effectively improve upper limb motor function and daily behavior of patients with motor dysfunction, and the demand has increased at every stage of the rehabilitation recovery. According to the motor relearning program theory, upper limb motor dysfunction can be restored by a certain amount of repetitive training. Robotics devices can be an approach to accelerate the rehabilitation process by maximizing the patients’ training intensity. This paper develops a new end-effector upper limb rehabilitation robot (EULRR) first and then presents a controller that is suitable for the assist-as-needed (AAN) training of the patients when performing the rehabilitation training. The AAN controller is a strategy that helps the patient’s arm to stay close to the given trajectory while allowing for spatial freedom. This controller enables the patient’s arm to have spatial freedom by constructing a virtual channel around the predetermined training trajectory. Patients could move their arm freely in the allowed virtual channel during rehabilitation training while the robot provides assistance when deviating from the virtual channel. The AAN controller is preliminarily tested with a healthy male subject in different conditions based on the EULRR. The experimental results demonstrate that the proposed AAN controller could provide assistance when moving out of the virtual channel and provide no assistance when moving along the trajectory within the virtual channel. In the close future, the controller is planned to be used in elderly volunteers and help to increase the intensity of the rehabilitation therapy by assisting the arm movement and by provoking active participation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Stroke Rehabilitation and Recovery · Prosthetics and Rehabilitation Robotics · Muscle activation and electromyography studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200444, China
Funding
National Natural Science Foundation of China · National Key Research and Development Program of China · Science and Technology Commission of Shanghai Municipality
References (40)
Show source-provided references
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