Continuous Joint Angle Estimation of an Index Finger Exoskeleton using Online EEG Signal

This paper deals with the continuous joint angle estimation of the index finger exoskeleton for flexion and extension movements based on online EEG signal. The human subject's intention for index finger movement is extracted by recording the online EEG signal from primary motor cortex and supplementary motor cortex regions through LabView platform. The Hjorth parameters such as activity, mobility and complexity are computed as input features of the online recorded signal and are fed to a multilayered neural network for mapping the flexion and extension movement of the index finger exoskeleton. From the experimental results, it is observed that both the extension and flexion motions of index finger exoskeleton with different angle positions are estimated successfully through the human intention.