Loading

Spectral Analysis of Polysomnograph
R.Chandrasekaran1, R.J.Hemalatha2, T.R.Thamizhvani3, A. Josephin Arockia Dhivya4, Anand Kumar.E5
1R.Chandrasekaran*,Assistant Professor-Department of Biomedical Engineering, Vels Institute of Science, Technology & Advanced Studies, Chennai, India.
2R.J.Hemalatha, head & Assistant Professor -Department of Biomedical Engineering,Vels Institute of Science, Technology & Advanced Studies, Chennai, India.
3T.R.Thamizhvani, Assistant Professor -Department of Biomedical Engineering,Vels Institute of Science, Technology & Advanced Studies, Chennai, India.
4Josephin Arockia Dhivya, Assistant Professor Department of Biomedical Engineering,Vels Institute of Science, Technology & Advanced Studies, Chennai, India.
5Anand Kumar.E, Student -Department of Biomedical Engineering,Vels Institute of Science, Technology & Advanced Studies, Chennai, India. 

Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12673-12678 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5402118419/2019©BEIESP | DOI: 10.35940/ijrte.D5402.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The Polysomnography (PSG) is the most commonly used test in the diagnosis of OSAS – Obstructive Sleep Apnea Syndrome. PSG signals consist of simultaneous recording of multiple physiological parameters related to sleep and wakefulness. PSG is used to evaluate abnor-malities of sleep and or wakefulness and other physiological disorders that have an impact on or related to sleep and or wakefulness. In this paper, we propped an idea of detection of insomnia based on frequency spectral analysis of PSG signals. The PSG signals consist of EMG of the chin, EEG taken from various lobes, respiratory signal, EOG signals, Temporary rectal signal and ECG signal. From all these physiological parameters, the Spectral analysis of EOG (horizontal), EEG FPZ-CZ and PZ-OZ [EEG 10-20 electrodes paced on midline FPZ,CZ,OZ channels]signals are analyzed and the mean, variance, standard deviation, RMS value and SNR features of the signal are extracted. The proposed methodology is applied to the male as well as female subjects at the age group of 30-40 years. The difference of the frequency range taken at respective intervals of time is noted and compared.
Keywords: OSAS-Obstructive Sleep Apnea; PSG-Polysomnography; RMS-Rootmeansquare; SNR-Signaltonoise Ratio.
Scope of the Article: Predictive Analysis.