Qualitative Analysis of Brain and Heart Signals using DWT
Revati Shriram1, Nivedita Daimiwal2
1Dr. Revati Shriram, Dept of Instrumentation and Control, MKSSS’s Cummins College of Engineering for Womrn, Pune, India.
2Dr. Nivedita Daimiwal, Dept of Instrumentation and Control, MKSSS’s Cummins College of Engineering for Womrn, Pune, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5647-5652 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8527118419/2019©BEIESP | DOI: 10.35940/ijrte.D8527.118419
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© 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: Bio-signal processing is a widely carried out by the researchers for better understating of complex biological processes. Instead of studying complete biosignal; a decomposed biosignals gives better and more accurate information about the various dynamics involved in the process. Wavelet is one of the powerful transform which is applicable to time and frequency domain. While dealing with various types of physiological signals it is a tedious task to choose the correct or accurate wavelet for the given biosignal analysis. Electrical brain and heart signal along with peripheral pressure signal for 120 subjects is studied by the authors. Authors have checked various quality metrics decide suitability of various Wavelets for EEG, ECG, PP and PPG signal decomposition and reconstruction. The methodology was applied to normal as well as diseased subjects. Our results based on performance parameters like Mean Square Error, Mean Approximate Error, Signal to Error Ratio, PRMSD shows that orthogonal and biorthogonal wavelets are more suitable for bio-signal decomposition and reconstruction. This shows that selection of wavelet should not always be based on similarity between the mother wavelet and the nature of bio-signal.
Keywords: Decomposition, Reconstruction, Electroencephalogram, Pressure Pulse, Electrocardiogram, Photo plethys mogram, Wavelet, Performance Parameters.
Scope of the Article: Measurement & Performance Analysis.