A hybrid platform based on EOG and EEG signals to restore communication for patients afflicted with progressive motor neuron diseases.

A. B. Usakli, S. Gurkan, F. Aloise, G. Vecchiato, F. Babiloni

Research output: Contribution to journalArticlepeer-review

Abstract

An efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amiotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. Often, such diseases leave the ocular movements preserved for a relatively long time. The aim of this study is to present a new approach for the hybrid system which is based on the recognition of electrooculogram (EOG) and electroencephalogram (EEG) measurements for efficient communication and control. As a first step we show that the EOG-based side of the system for communication and controls is useful for patients. The EOG side of the system has been equipped with an interface including a speller to notify of messages. A comparison of the performance of the EOG-based system has been made with a BCI system that uses P300 waveforms. As a next step, we plan to integrate EOG and EEG sides. The final goal of the project is to realize a unique noninvasive device able to offer the patient the partial restoration of communication and control abilities with EOG and EEG signals.

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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