Abstrait

Brain Computer Interface Systems To Assist Patients Using EEG Signals

Thejaswini S, Sumathi M S , Manasa C , Raashi Saxena , Tarun R Prasad, Akash Tiwari

Brain computer interface (BCI) facilitates a connection between the human brain and external device like computer and is used for assisting the physically disabled and impaired people. The BCI system can be used for analysis and classification of EEG signals corresponding to different emotions, including self-report, startle response, behavioral response, autonomic measurement, and neurophysiologic measurement. The EEG signals can play an important role in detecting the emotional states for developing the BCI based analysis and classification of emotions. Since the BCI based on emotion detection can be useful in many areas like as entertainment, education, and health care. Here in this project we have proposed a prototype embedded controller based model to assist patients which can control home appliances. We have used DWT algorithms for feature extraction and features like energy, entropy, mean are computed. The KNN classifier is used to classify EEG signal into two states through which the controller controls the home appliances. The two applications namely switch on/off bulb and turns on/off dc motor are implemented successfully