Rhythms-Based Coherence Analysis Between Brain and Heart of Sleep Disorder Samples using MSC

Rhythms-Based Coherence Analysis Between Brain and Heart of Sleep Disorder Samples using MSC
  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-6
Year of Publication : 2022
Authors : Polepogu Rajesh, Vaegae Naveen Kumar
DOI : 10.14445/22315381/IJETT-V70I6P230

How to Cite?

Polepogu Rajesh, Vaegae Naveen Kumar, "Rhythms-Based Coherence Analysis Between Brain and Heart of Sleep Disorder Samples using MSC," International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 287-299, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I6P230

Abstract
62% of adults suffer from sleep problems all over the world, and the incidence of these illnesses is anticipated to grow. Unfortunately, many of these problems in scientific practice may go unnoticed and untreated. It has been widely observed in the diagnosis and scientific applications of various sleep disorders that a diligent and fundamental function of watching the heart and brain functions is required. Sleep problems can be studied using various techniques, mainly polysomnography, Electroencephalogram, MSLT, etc. In this work, we propose a new technique for estimating the relationship between cardiology and neurology for identifying cardiac and cerebrovascular anomalies of sleep disorder patients using ECG and EEG rhythms. Sleep problems based on ECG and EEG rhythms are utilized for the analysis and clinical treatment of difficulties associated with heart and brain-related issues. This paper investigated the magnitude squared coherence (MSC) between the ECG and EEG rhythms through a nonparametric power spectrum density estimation (PSDE) using the Welch method in the typical frequency band of 0-35 Hz. All signals are acquired from sleep apnea samples aged 20 to 50, with a sampling rate of thousand samples per second, using physioNet. For each signal, 1000 samples are used for MSC analysis. The MSC between the ECG and EEG rhythms are plotted, and their mean values are computed. ECG and EEG rhythms of two subjects were reported among the 25 subjects investigated. The measurement shows that in sleep apnea sample 1, the value of MSC between the ECG and EEG rhythms are 0.13954, 0.13017, 0.12599, and 0.12197 at beta (β)band, alpha (α)band, theta (θ) and Delta (δ) of EEG rhythms.
Similarly, in sleep apnea sample 2, the value of MSC is 0.13970, 1.3540, 0.13404, and 0.13092 at the beta (β) band, alpha (α) band, theta (θ) band, and delta (δ) band of EEG rhythms respectively. Finally, in the first sample, the MSC value is higher in the beta and the second-highest in the alpha rhythm. In the second, the highest MSC rating and the second-highest MSC value are obtained by the beta rhythm and alpha rhythm, respectively. In sleep apnea, the patient’s brain and heart are closely associated with beta rhythm and the second highest in the alpha rhythms.

Keywords
Electrocardiogram (ECG), Electroencephalogram (EEG), Rapid eye movement, non-Rapid eye movement, Power Spectrum Density Estimation, Cross Power Spectral Density, Magnitude Squared Coherence (MSC).

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