Abstract:

In health monitoring and neurology Wearable electroencephalography (EEG) systems have been observed in human-computer interaction. In such systems, signal processing strategies have been simplified in this paper so as to consider issues of data quality, real time processing and noise interference. Preprocessing, feature extraction, and facial recognition algorithm are improved in the proposed plan. The results show that they are more accurate in classification, are quicker and are less sensitive to noise. The superior algorithms performed better than the state-of-the-art, and offered more reliable EEG data. Despite this being improved, computational complexity and the need of additional validation is noted in the paper. Future research would focus on improving newer technologies and improving such limits by improving wearable EEG devices