| dc.description.abstract | In the past decades, stroke has been one of the world′s major diseases. Especially in the developed countries and aging society, with medical advances, an increasing elderly population, stroke problems are increasingly valued. In this study, we analyzed the different motor index for the stroke rehabilitation with upper extremity, try to find a new indicators information for therapists.
Study is divided into two parts, the first is to identify motor index that correspond to the movement of the system, and analyzed if the motor index would impact result of clinical assessment scale. The second, when found out the motor index, we used large number of patient′s data to classify groups with pattern recognition, like neural network or SVM. Unlike clinical assessment scale multiple tests must be carried out in order to know the patient′s level of classification, we can analyze the patient′s classification status can be obtained directly through the game′s outcome and the motor index of data with system.
The results of this study shows that part of the motor index for assessment scale have a considerable degree of influence. And after rehabilitation, the numerical of motor index also has definite progress. We used motor data that collected in system to establishing classification model also has a certain recognition rate. Thus establishing the classification model is a certain degree of feasibility.
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