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1.
Biomed Mater Eng ; 28(2): 105-116, 2017.
Article in English | MEDLINE | ID: mdl-28372264

ABSTRACT

BACKGROUND: Clinical scales such as Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) are widely used to evaluate stroke patient's motor performance. However, there are several limitations with these assessment scales such as subjectivity, lack of repeatability, time-consuming and highly depend on the ability of the physiotherapy. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessments are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear. OBJECTIVE: This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest. METHODS: Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS. RESULTS: Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score. CONCLUSION: There is a potential of using iRest, a non-motorized device in predicting MAS score.


Subject(s)
Hand/physiopathology , Robotics/instrumentation , Stroke Rehabilitation , Stroke/physiopathology , Biomechanical Phenomena , Equipment Design , Female , Humans , Male , Middle Aged , Movement , Recovery of Function , Stroke/diagnosis , Stroke Rehabilitation/instrumentation , Treatment Outcome
2.
IEEE Trans Neural Syst Rehabil Eng ; 25(10): 1864-1873, 2017 10.
Article in English | MEDLINE | ID: mdl-28410110

ABSTRACT

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot's portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects' wrist and forearm movement.


Subject(s)
Hand/physiopathology , Robotics , Stroke Rehabilitation/instrumentation , Stroke Rehabilitation/methods , Wrist , Aged , Aged, 80 and over , Female , Forearm/physiopathology , Games, Experimental , Humans , Male , Middle Aged , Muscle Strength , Patient Safety , Patient Satisfaction , Physical Education and Training , Range of Motion, Articular , Stroke/physiopathology , Stroke Rehabilitation/adverse effects , Treatment Outcome , Virtual Reality
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