Attention Level Measurement During Exoskeleton Rehabilitation Through a BMI System
Brain-Machine Interfaces based on wearable robots’ control have been proposed in the research field for rehabilitation purposes. The combination of both systems allow the performance of more natural movements and a higher level of involvement of patients on their therapy. Studies focused on this topic should face several issues related to the integration of these systems. The current work is meant to test the accuracy of a real time Brain-Machine Interface based on the detection of gait attention during lower limb exoskeletal rehabilitation. Four users performed the experiment wearing an ankle exoskeleton. The system provides a coefficient between 0 and 1 depending on the level of attention experienced by the subject. These results show good similitude between real and decoded attention level.
KeywordsLinear Discriminant Analysis Gamma Band Attention Level Dual Task Paradigm Power Line Interference
The authors would like to thank Marta Moltedo, Tomislav Bacek and Dirk Lefeber for their support in the work on the MACCEPA actuator used in these experiments. We also thank Maria del Carmen Sánchez , Guillermo Asín-Prieto, José González and Juan Camilo Moreno for the mechanical design and fitting of the ankle exoskeleton.
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