Synchronous brain machine interface design using focused time delay networks
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Ramachandran, Nagarajan, Prof. Dr.
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Focused time delay neural network based design for a four-state Brain Machine Interface (BMI) to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively using two bipolar electrodes are used in the study. The performance of the proposed dynamic classifier is compared with a static feed forward neural classifier. Data collected from 10 subjects is used in this study. Average classification performance in the range of 93% to 100% is achievable. Experiment results show that the focused time delay neural network model is suitable for a four-state BMI design.