Enhancing Signal Processing Measurement for Pulse Rate Variability by Novel Algorithm and Regression Technique

Authors

  • Saravanan Velusamy Research Scholar,Department of ECE,Kalasalingam Academy of Research and Education Krishnankoil, Tamilnadu, India
  • Pallikonda Rajasekaran Murugan Department of Electronics and Communication Engineering, Kalasalingam Academy of Researchand Education Krishnankoil, Tamilnadu, India
  • G. Vishnuvarthanan Associate Professor,Data Science – Division School of Computing Science and Engineering VIT Bhopal University, Kothrikalan, Sehore Madhya Pradesh – 466114, India.
  • Arunprasath Thiyagarajan Department of Biomedical Engineering,Kalasalingam Academy of Research, and Education Krishnankoil, Tamilnadu, India
  • Kottaimalai Ramaraj Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education Krishnankoil, Tamilnadu, India
  • Vidyavathi Kamalakkannan Department of Electronics and Communication Engineering, Selvam College of Technology Namakkal, Tamilnadu, India

Keywords:

Autonomous nervous system, Heart Rate Variability, ECG, Denoising, UWFR filtering

Abstract

The researchers looked into the relationship connected with magnetic element and sunlight, further the overall duration & delays of parasympathetic nervous method reactions to variation in sunlight and magnetic activity. Heart Rate Variability (HRV) measures were connected with sunlight and magnetic parameters utilizing a multi-element linear regression model with Bonferroni correction of multi-comparison tests after removing the circadian impacts of both information.Changes in sunlight radiation intensity were linked to changes in Pulse rates, which we interpret as a physiologic reaction to stress. Solar radiation elevation, gravitational wave fluxes, and Schumann's resonance amplitude were related to higher parasympathetic and HRV activity.HRV spectrograms were calculated for every participant utilizing Short Term Fourier Transform (STFT). A P-shift unfiltered fractional frequency response filter has utilized here, which gets smoother at P0. The filter is intended to provide a configurable median threshold that is excellent for slow ECG action and worse for rapid excursions. From the signal generator standpoint, it has been demonstrated that the flexible Unified Write Filter (UWFR) methodology in this technique provides optimal information extraction. In such a typical ECG signal sequence, the approach is necessary to track the T-wave, P-wave, and QRS-complex durations.

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Published

29.01.2024

How to Cite

Velusamy, S. ., Murugan, P. R. ., Vishnuvarthanan, G. ., Thiyagarajan, A. ., Ramaraj, K. ., & Kamalakkannan, V. . (2024). Enhancing Signal Processing Measurement for Pulse Rate Variability by Novel Algorithm and Regression Technique. International Journal of Intelligent Systems and Applications in Engineering, 12(13s), 207–219. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4588

Issue

Vol. 12 No. 13s (2024)

Section

Research Article

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