EEG Wheelchair for People of Determination
This provides a communication bridge for people with paralysis, but it is incremental as it uses established methods like SVM and DWT on existing hardware.
The paper tackled the problem of enabling mobility for paralyzed individuals by designing an EEG-based brain-controlled wheelchair, achieving control for basic movement commands through signal processing and classification.
The aim of this paper is to design and construct an electroencephalograph (EEG) based brain-controlled wheelchair to provide a communication bridge from the nervous system to the external technical device for people of determination or individuals suffering from partial or complete paralysis. EEG is a technique that reads the activity of the brain by capturing brain signals non-invasively using a special EEG headset. The signals acquired go through pre-processing, feature extraction and classification. This technique allows human thoughts alone to be converted to control the wheelchair. The commands used are moving to the right, left, forward, and backward and stop. The brain signals are acquired using the Emotiv Epoc headset. Discrete Wavelet Transform is used for feature extraction and Support Vector Machine (SVM) is used for classification.