EEG-Based Demarcation of Yogic and Non-Yogic Sleep Patterns Using Power Spectral Analysis

EEG-Based Demarcation of Yogic and Non-Yogic Sleep Patterns Using Power Spectral Analysis

Basavaraj Hiremath, Natarajan Sriraam, B. R. Purnima, Nithin N. S., Suresh Babu Venkatasamy, Megha Narayanan
Copyright: © 2021 |Pages: 18
DOI: 10.4018/IJEHMC.20211101.oa2
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Abstract

Electroencephalogram (EEG) signals resulting from recordings of polysomnography play a significant role in determining the changes in physiology and behavior during sleep. This study aims at demarcating the sleep patterns of yogic and non-yogic subjects. Frequency domain features based on power spectral density methods were explored in this study. The EEG recordings were segmented into 1s and 0.5s. EEG patterns with four windowing scheme overlaps (0%, 50%, 60% and 75%) to ensure stationarity of the signal in order to investigate the effect of the pre-processing stage. In order to recognize the yoga and non-yoga group through N3 sleep stage, non-linear KNN classifier was introduced and performance was evaluated in terms of sensitivity and specificity. The experimental results show that modified covariance PSD estimate is the best method in classifying the sleep stage N3 of yogic and non-yogic subjects with 95% confidence interval, sensitivity, specificity and accuracy of 97.3%, 98% and 97%, respectively.
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Introduction

Sleep is a spontaneously occurring phase of mind and body, marked by changed state of cognizance, diminished sensory activity, inhibition of almost all voluntary muscles and minimized external encounters. During sleep, the brain uses considerably less energy than when awake, notably during non-rapid eye movement (NREM) sleep. Humans secrete growth hormone surges in slow-wave sleep. Sleep is broadly classified into: rapid eye movement (REM) sleep and NREM. NREM Stage 1(Wake) is focused on whether your eyes are closed or open. Alpha and beta waves, primarily beta waves, are active when awake with eye-opened. When people get dizzy and close eyes, the prevailing pattern is the alpha wave Getting up from Stage N1 is easy One spends at least less than 10 minutes in Stage N1 sleep in the first sleep cycle. It makes up about 5% of total sleep duration. Stage 2 sleep usually takes approximately 25 minutes in the immediate cycle and extends by each subsequent cycle, gradually about 50%. Stage 3 is the deepest sleep stage and is distinguished by relatively slow frequency with signals of higher magnitude termed as delta waves. It's the toughest level to wake up from. REM sleep is an active brain sleep cycle, but the body is immobilized. During REM sleep, intense dreams appear and the increase in the heart rate and breathing rate is observed (National Institute of Neurological Disorders and Stroke, 2019).

Yoga is a mind and body activity of ancient Indian tradition with a 5,000-year history. Specific yoga techniques incorporate physical asanas, methods of respiration, and meditation or relaxation. If people with insomnia practice yoga every day, they sleep longer, sleep quicker, and gets back to sleep quicker than normal if they got up in the middle of the night (The National Sleep Foundation, 2020). A national survey reported that more than 55 percent of yoga practitioners felt it assisted in getting better sleep (Alyson Ross, 2014). Research by Kalyan Maity et al. (2018) focused on examining the positive impacts of Sleep Special Technique (SST) on the quality of sleep, anxiety and well-being of fit young yoga practitioners. The experimental group received 1 month of (SST) training and there was no reference to SST from the control group. Substantial reductions in the global Pittsburgh sleep quality index (PQSI) value, perceived stress scale value and dramatic development in all Quality - of – life (QOL) scores were recorded after one month of SST practice. SST training of one month has a constructive influence on the entire quality of sleep, mental and physical health. Sarika Chaudhari et al. (2013) conducted a cross-sectional study to assess the influence of practicing yoga in the older people on quality of sleep and life quality. Overall PSQI score was less in yoga group than control group score. The Yoga group also had QOL scores than the control group. Practicing yoga for a long time by older people is aligned with little sleep disruptions and improved sleep quality and these findings are consistent with other studies involving only 180 days of yoga practice.

The research carried out by Li-Li Wang et al. (2016) was intended to assess EEG sleep efficiency from last night. Sleep trial was conducted to receive EEG signals from eight subjects under good, normal and poor sleep quality conditions. Taking into account the five different EEG frequency bands, the influence of sleep quality on the EEG expressed primarily in one or more frequency bands. The widely used EEG feature i.e., PSD was extracted in five frequency bands following the short-time Fourier transform. From the research observations, Gamma band is found to be the primary frequency band for determining sleep efficiency. Research by Rimpee Verma et al. (2018) helps people understand the sleep condition called a rapid eye behavior condition, the EEG signal's significance. The study allows the reader to have better information about sleep disorder, as well as its forms about EEG signals how it allows in sleep disorder diagnosis. The signal's PSD was determined by using Welch technique, whereupon the region contributing to delta, theta, alpha and beta bands were measured by using Trapezoidal Integration approach for evaluating average power. Power in the delta band has been reported to be greater for normal case however it is weakest in REM Sleep Behavior Disorders mostly during REM period.

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