Title: Power analysis of EEG bands for diagnosis of Alzheimer disease

Authors: Sachin M. Elgandelwar; Vinayak K. Bairagi

Addresses: Department of E&TC, AISSMS Institute of Information Technology, Pune, Maharashtra, India; ZCOER, Pune, Maharashtra, India ' Department of E&TC, AISSMS Institute of Information Technology, Pune, Maharashtra, India

Abstract: Identifying the early and fundamental stages of Alzheimer disease (AD) called as mild cognitive impairment (MCI) is needed for better medical care. The basic goal of the current research is to evaluate the electroencephalography (EEG) for the diagnosis of AD and to separate the AD from the normal healthy subjects. The EEG signals has diverse frequency bands which reflect mental functions and memory performance of the humans. The EEG is non-invasive and measurable brain signal, which can be used for detecting the memory functions in the case of AD where there is significant slowdown of brain cognitive functions. The present study is based on analysis of power and frequency of EEG signals, which reflects the connection between specific EEG frequency bands and their relative power (RP). It is observed that relative power of few EEG signal bands is closely linked with the AD staging. Slowing of EEG signals is the main feature found in AD subjects. Such slowing down of EEG is increasing the relative power of delta and theta bands, along with the decrease in the power of alpha and beta bands of EEG. This paper shows the relative power analysis of each band in EEG signals to detect the severity of AD.

Keywords: Alzheimer disease; AD; mild cognitive impairment; MCI; electroencephalography; EEG; relative power; RP; bump modelling; frequency bands.

DOI: 10.1504/IJMEI.2021.117728

International Journal of Medical Engineering and Informatics, 2021 Vol.13 No.5, pp.376 - 385

Received: 10 Apr 2019
Accepted: 20 Nov 2019
Published online: 23 Sep 2021 *

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