User Specific Efficiency Parameters for Brain Computer Interface (BCI) based Upper Limb Stroke Rehabilitation System

Abstract

Rehabilitation after stroke through conventional manner is not quite successful due to a number of patient related issues including lack of interest in lengthy exercises, cost of therapy and dependency on healthcare professionals. In addition, around 50% of stroke survivors worldwide belong to the low and middle income countries that are unable to afford expensive rehabilitation systems. Advancements in Brain Computer Interface (BCI) technology enabling the researchers to design and develop BCI based strokerehabilitation systems by exploiting neural plasticity. This is achieved via Electroencephalogram (EEG) based computer gaming rehabilitation exercises through Motor Imagery (MI) to achieve successful neural plasticity. However, current research is largelybased on expensive bio-signal amplifiers and processing hardware that are beyond the affordability of a large population of stroke patients living in low and middle-income countries. Moreover, the efficiency of BCI based stroke rehabilitation systems thatare generally considered as the accuracy of EEG signal classifications is not the only parameter to rate the efficiency.Since the requirements of BCI based rehabilitation therapy are highly subject specific, efficiency of such systems also depends on many user specific features related to cost and performance.This paper describes a research that proposes a number of parameters for cost and efficiency along with their weightage set by the domestic users to determine the overall efficiency of the system.Inputs from different groups of users were obtained that are classified as deserving class, middle class and rich class. Results indicated that the users of different groups are giving different weights to different performance and cost parameters. The overall efficiency requirements are therefore having different meanings for different classes of users