Intelligent model of rehabilitation training program for stroke

Abstract

In view of the uncertainty and complexity, the intelligent model of rehabilitation training program for stroke was proposed, combining with the case-based reasoning (CBR) and interval type-2 fuzzy reasoning (IT2FR). The model consists of two parts: the setting model based on CBR and the feedback compensation model based on IT2FR. The former presets the value of rehabilitation training program, and the latter carries on the feedback compensation of the preset value. Experimental results show that the average percentage error of two rehabilitation training programs is 0.074%. The two programs are made by the intelligent model and rehabilitation physician. That is, the two different programs are nearly identical. It means that the intelligent model can make a rehabilitation training program effectively and improve the rehabilitation efficiency.

Keywords

intelligent model / interval type-2 fuzzy reasoning / case-based reasoning / uncertainty / rehabilitation training program / stroke

References

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