Title :
Steady-State Visual Evoked Potential based Brain controlled wheelchair system
Author :
Omar, Trigui ; Wassim, Zouch ; Mohamed, Ben Messaoud
Author_Institution :
Adv. Technol. for Med. & Signals `ATMS, Sfax Univ., Sfax, Tunisia
Abstract :
Brain controlled wheelchair system is a Brain-computer interface (BCI) allowing people with severe neuromuscular disorder to control the navigation by themselves. Indeed, it replaces muscular activities by neurophysiological ones. The advantages of the Steady State Visual Evoked Potential (SSVEP) make it a favorable choice to be used in the BCI. The aim of the present study is to design a brain controlled wheelchair system which is cheap and easy to use. Two signal processing methods for SSVEP frequencies detection are presented and discussed. The first method is based on the calculation of the normalized amplitude spectrum. The second method is based on the comparison between the signals´ signal to noise ratio calculated on specific frequencies. A comparison of the accuracy of these methods with a frequency resolution of 0.1Hz allows the identification of the most precise method among them both. Results show that by using the second method, the system can reach for 97% of the four directions´ navigation´s accuracy.
Keywords :
brain-computer interfaces; electric vehicles; electroencephalography; feature extraction; handicapped aids; medical control systems; medical disorders; medical signal detection; medical signal processing; muscle; neurophysiology; noise; position control; signal resolution; visual evoked potentials; wheelchairs; BCI; SSVEP frequency detection accuracy; brain controlled wheelchair system design; brain-computer interface; cheap brain controlled wheelchair system; direction navigation accuracy; easy-to-use; frequency resolution; muscular activity; navigation control; neuromuscular disorder; neurophysiological activity; normalized amplitude spectrum calculation; signal processing; signal-to-noise-ratio calculation; signal-to-noise-ratio comparison; steady-state visual evoked potential; Accuracy; Electrodes; Electroencephalography; Harmonic analysis; Light emitting diodes; Noise; Power harmonic filters; Brain-Computer Interface; Steady State Visual Evoked Potential; frequency discrimination; principal component analysis;
Conference_Titel :
Image Processing, Applications and Systems Conference (IPAS), 2014 First International
Print_ISBN :
978-1-4799-7068-1
DOI :
10.1109/IPAS.2014.7043311