Two signal-processing algorithms have been developed to detect the head movements from a human subject. The head movement was measured by two signals from a gyroscope (representing x-and y-axis) integrated in an EEG headset (EEG neuroheadset, Emotiv Syste ms). These signals were acquired into a PC wirelessly to determine four possible head movements: left, right, up, and down using two different algorithms based on cross-correlation and clipping. A series of tests was conducted with three subjects to evaluate the performance of both algorithms. The results showed that the cross-correlation method detected head movements with 75% accuracy while the clipping method performed slightly better than the cross-correlation method with 81% accuracy. The clipping method was further enhanced with the application of filters to achieve better accuracy. These algorithms will be further improved and integrated with a brain-computer interface for the purpose of assisting people with disabilities.
Sicheng Wang, originally from Mianyang, China, is a junior Electrical and Computer Engineering major at Lafayette College. He is actively involved in the brain-computer interface research team led by Dr. Yih-Choung Yu and Dr. Lisa Gabel at Lafayette College. He has previously externed at Cisco Inc.. He plans to merge his interest in signal processing with technologies in communication networks. In addition to his research work, Sicheng is the President of the math club and the head peer adviser of the international Student Association at Lafayette College.