Detection of Alzheimer’s Disease Using Optimized EEG Data Acquisition and its Effect on Reaction Time

In the elderly population Alzheimer's disease is a emergent health issue which seeks efficient early detection, that is still a challenge for scientist. This study focuses at establishing a low cost EEG based Alzheimer's disease detection system. This proposes EEG based wireless headset system, EMOTIV EPOC, for the detection of Alzheimer's disease and investigating its effect on reaction time. AD effect on EEG was investigated along with the cross check on response time. Approximate Entropy (ApEn) method was used to calculate reduced complexity of EEG signals to detect Alzheimer's disease. AD patients had significantly lower ApEn values than control subjects at electrodes F8, P7, P8 and T8 (p<;0.05). This study also investigated the response/reaction time of Alzheimer's patient and co relate the difference between dominant and non-dominant hand reactivity. As a result of stimulating the visual and auditory systems of AD patients the RT is increased as compared to healthy subjects which causes slow processing of different sensory and motor areas of brain consequently reducing their learning skills. Significant difference with p<; 0.05 was found between the dominant and non-dominant random interval of AD patients as compared to healthy subjects which causes imbalanced coordination of both left and right parts of body.