Investigating effects of Levenshtein distance algorithm on accuracy performance in EEG based communication system

zIn our study, we investigated the effects of the Levenshtein distance algorithm on the eye-blink communication system that we developed based on EEG signals for people with severe motor disabilities, such as Amyotrophic Lateral Sclerosis, stroke, and locked-in syndrome.The developed system analyzes eye-blink signals to extract information and vocalize it.EEG signals were obtained from an electrode above the left eye using a NeuroSky MindWave Mobile device.Morse-coded eye-blink words were input to the system and feature vectors were extracted using the Wavelet Transform method.Support vector machines were trained with these vectors and the Levenshtein distance algorithm was used to reduce classification errors.Finally, the system was completed with a text-to-speech synthesis algorithm.The experiments, which used 20 words for self-expression, obtained highly successful results.almamzda, amyotrofik lateral skleroz, fel ve kilitli kalma sendromu gibi motor engeli olan kiiler iin, EEG sinyalleri kullanarak gelitirdiimiz gz-krpma iletiim sistemi zerinde Levenshtein mesafe algoritmasnn etkilerini aratrdk.Sistem, gz-krpma sinyallerini analiz ederek bilgi karmakta ve seslendirmektedir.EEG sinyalleri, kablosuz NeuroSky MindWave cihaz kullanlarak sol gzn zerine yerletirilmi bir elektrottan elde edilmitir.