Outlier Pulse Detection and Feature Extraction for Wrist Pulse Analysis
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Outlier Pulse Detection and Feature Extraction for Wrist Pulse Analysis

Authors: Bhaskar Thakker, Anoop Lal Vyas

Abstract:

Wrist pulse analysis for identification of health status is found in Ancient Indian as well as Chinese literature. The preprocessing of wrist pulse is necessary to remove outlier pulses and fluctuations prior to the analysis of pulse pressure signal. This paper discusses the identification of irregular pulses present in the pulse series and intricacies associated with the extraction of time domain pulse features. An approach of Dynamic Time Warping (DTW) has been utilized for the identification of outlier pulses in the wrist pulse series. The ambiguity present in the identification of pulse features is resolved with the help of first derivative of Ensemble Average of wrist pulse series. An algorithm for detecting tidal and dicrotic notch in individual wrist pulse segment is proposed.

Keywords: Wrist Pulse Segment, Ensemble Average, Dynamic Time Warping (DTW), Pulse Similarity Vector.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332620

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[1] V. Dattatray Lad "Secrets of the Pulse The Ancient Art of Ayurvedic Pulse Diagnosis" Motilal Banarasidas Publishers INDIA,2005.
[2] S. Upadhyaya "Nadi Vijyaya Ancient Pulse Science" Chaukhamba Publishers, INDIA 2005
[3] B. Flaws "The Secrets of Chinese Pulse Diagnosis", 1995 Blue Poppy Press.
[4] C. Xia, Y. Li, J. Yan, Y. Wang, H. Yan, R. Guo, F. Li "Wrist Pulse Waveform Feature Extraction and Dimension Reduction with Feature Variability Analysis" International Conference on Bioinformatics and Biomedical Engineering, 2008.
[5] H. Wang, Y. Cheng "A Quantitative system for pulse diagnosis in Traditiona Chinese Medicine" Proceedings of IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai,China, 2005.
[6] C. Xia, Y. Li, J. Yan, Y. Wang, H. Yan, R. Guo, F. Li " A Practical Approach to Wrist Pulse Segmentation and Signle-period Average Waveform Estimation" Internacional Conference on BioMedical Engineering and Informatics , 2008
[7] L. Wang, K. Wang, L. Xu "Recognizing Wrist Pulse Waveforms with Improved Dynamic Time Warping Algorithm " Third International Conference on Machine Learning and Cybernetics, Shanghai, 2004
[8] J. Shu, Y. Sun "Developing classification indices for Chinese pulse diagnosis"Complementary Therapies in Medicine 2007, Elsevier
[9] P. Zhang, H.Wang "A Framework for Automatic Time-Domain Characteristic Parameters Extraction of Human Pulse Signal" EURASIP Journal on Advances in Signal Processing, 2008
[10] R. Rangayyan "Biomedical Signal Analysis" A Case-Study Approach, Wiley-Interscience , 2004