Ocular Artifact Suppression in Multichannel EEG Using Dynamic Segmentation and Enhanced wICA

ABSTRACT

The artifacts such as ocular, muscle and certain electrical disturbances contaminate the Electroencephalogram (EEG). Wavelet enhanced independent component analysis (wICA) with static segmentation preserves little information of both spectral and coherent characteristics of neural activity. However, the considerable amount of valuable information can be preserved with novel automatic dynamic size segmentation of multichannel EEG signal with wICA. Most of the signal information lost in the threshold process (inappropriate threshold value) and this could be overcome with an adaptive threshold approach. It is assumed that the brain neural activity is a Gaussian random distribution with zero mean only for initial state.

The 16 channel EEG signals are acquired with Ocular Artifact (OA). The subject is instructed to blink an eye during the time of recording. A National Instrument (NI) data acquisition card is used to acquire the EEG data in MATLAB with sampling rate of 1024 Hz. Statistical parameters like Standard deviation, mean power (PSD), root mean square error (RMSE) are used for analysis and comparison. The proposed dynamic segmentation method is better for suppression of ocular artifacts which preserves the brain neural activity as compared with static segmentation. The artifacts related with eye blinking are removed completely and successfully preserve spectral and coherent characteristics of EEG activity of interest. It is proved that automatic dynamic segmentation is a key tool. The presented method is best suitable for suppression of OA and estimation of brain neural activity.

KEYWORDS:

• Adaptive threshold
• Independent components analysis
• Ocular artifacts
• Automatic segmentation
• Automatic partition

Additional information

Notes on contributors

K. P. Paradeshi

K P Paradeshi has completed his postgraduation in electronics engineering from Walchand college of Engineering, Shivaji University, Kolhapur, India. He has a total of 24 years of teaching experience. He is currently pursuing his PhD studies in the area of biomedical engineering. He is life member of IE, ISTE, and India. His research interest includes biomedical engineering, signal processing and control systems engineering.

U. D. Kolekar

Uttam Kolekar received his PhD degree in electronics engineering from Bharati Vidyapeeth, Pune, India in 2008. He has total 23 years of experience in the teaching. Currently, he is working as a principal of AP Shah Institute of Technology, Thane, Mumbai, India. He has shouldered various responsibilities like dean, director at various institutes in Mumbai University. He is working as research guide and currently five students are pursuing PhD under his guidance. He has published more than 15 research papers in international journals and conferences. He is the reviewer of international journals like IEEE transactions. He is fellow member of IETE and life member of ISTE and ISNT. His research interest includes wireless communication, cyber security, biomedical engineering, etc. Email: [email protected]