Synchronous brain machine interface design using focused time delay networks
Date
2012-02-27Author
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Ramachandran, Nagarajan, Prof. Dr.
Metadata
Show full item recordAbstract
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.