Virtual reality is widely applied in rehabilitation robot to help post-stoke patients complete rehabilitation training for the body function recovery. Most of virtual rehabilitation training systems lack scientific assessment standards and doctors don’t usually use quantitative examinations but qualitative observation and conversation with patients to evaluate the motor function of limb. Based on this situation, a virtual rehabilitation training and assessment system is designed, which contains two rehabilitation training games and one assessment system. The virtual system can attract patient attention and decrease the boredom of rehabilitation training and assessment. Compared with the existing rehabilitation assessment methods, the proposed virtual assessment system can give the assessment results similar to Fugl-Meyer Assessment, which is more quantitative, interesting and convenient. Five volunteers participate in the study of assessment system and the experimental results confirm the effectiveness of assessment system.
In recent years, according to American Heart Association, stroke is the leading cause of serious long-term disability in the US and about 795,000 people suffer from a stroke each year . China is also facing the same problem. The stroke is the first leading cause of death. Every year, 2.4 million people suffer from stroke . Fortunately, about 60-75 percent of those can survive. However, about 65 percent of them still remain severely handicapped because of the neurological damage caused by stroke, for example, movement disorders, hemiparesis and so on , . Those sequelae have an effect on body movement function, especially arm and hand function , . The lost of hand movement function will affect the Activities of Daily Living (ADLs), which will decrease the quality of life .[…]
via A Virtual Reality based Training and Assessment System for Hand Rehabilitation – IEEE Conference Publication
In recent years, the robotic devices have been used in hand rehabilitation training practice. The majority of existing robotic devices for rehabilitation belong to the rigid exoskeleton. However, rigid exoskeletons may have some limitations such as heavy weight, un-safety and inconvenience. This paper presents a device designed to help post-stroke patients to stretch their spastic hands. This hand rehabilitation device actuator is fabricated by soft material, powered with fluid pressure, and embedded in one glove surface. The distinguished features of this device are: safety, low cost, light weight, convenience and pneumatic actuation. In clinical practice, rehabilitation therapists should help the post-stroke patients to stretch fingers to a desired joint position. Therefore, the control objective of the proposed hand rehabilitation device is to drive the patient’s finger bending angle to a predesigned position. To this end, curvature sensors embedded in the glove are used to measure the finger’s bending angle. A commercial data glove is used to collect the actual finger’s bending angle for calibrating the curvature sensors based on a three-layer back-propagation (BP) neural network. Then the error between the designed joint position and the actual joint position can be calculated. An error proportional control strategy is adopted for the positioning control objective (the controller’s input is the pump speed). Finally, experiments are conducted to validate the effectiveness of control method and the capacity of the proposed hand rehabilitation device.
Source: Preliminary study on the design and control of a pneumatically-actuated hand rehabilitation device – IEEE Xplore Document