Single Channel EOG Signal Processing and Features Extraction using Virtual Instrumentation

International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue IV, April 2018 | ISSN 2321–2705

Single Channel EOG Signal Processing and Features Extraction using Virtual Instrumentation

 Vrushali Ratne¹, M.S.Panse²

 ¹Student M. Tech Electronics, ²Professor
Department of Electrical Engineering, VJTI, Mumbai, India

Abstract— Patient is aware and awake but body movements are restricted except for eyes, for persons suffering from severe neurological disorders. Bioelectric signals like EEG, EMG, EOG can be used by such patients to communicate with the outside world. The current research paper focuses on EOG signal acquisition using portable Myon biofeedback device and its analysis. EOG signal acquisition was carried with electrodes placed around the eye of 10 different volunteers. Pre-processing is done using cascaded stages of the notch, bandpass filters. After band-limiting the signal, 10 different features are extracted using LabVIEW software.

Index Terms— neurological disorders, EOG, electrodes, LabVIEW, Features Extraction.

I. INTRODUCTION

In our daily life activity, communication is essential for human beings to interact with the society. Differentially abled people are on the increase, thereby causes requirement of rehabilitative devices to assist these individuals to communicate with the outside world. Those suffering from severe neuromuscular disorders are perturbed from living a good quality of life. A substitute for communication without speech and hand movements is paramount to increase the quality of life for these individuals.

The eye can be considered as a rich source of information to retrieve information related to the user’s activities and their cognitive processes. Huang et al. developed a system which controlled wheelchair based on electro-oculography (EOG) signal by detecting one type of eye movement(blink). Single Vertical channel with three wet electrodes was used for EOG acquisition. The System had a sampling rate of 250 Hz. DC level and 50 Hz power line noise was removed using differential approach. Several Features such as the peak value of the sub-segment and the duration of the blink were extracted. Thirteen different commands were generated. Thresholding algorithm was used to process these signals.[1] He et al. developed a single-channel EOG-based asynchronous speller. Three electrodes were used for EOG acquisition with 8 healthy subjects. The EOG signals were acquired using a NuAmps device. The data acquisition system had a sampling rate of 250 Hz.

Read More