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Parallel support vector architectures for taxonomy of radial pulse morphology

DSpace at IIT Bombay

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Title Parallel support vector architectures for taxonomy of radial pulse morphology
 
Creator KARAMCHANDANI, SH
DESAI, UB
MERCHANT, SN
JINDAL, GD
 
Subject Impedance plethysmography
Radial pulse
Heart rate variability
Reaction diffusion transform
Morphology index
Peripheral pulse analyzer
IMPEDANCE PLETHYSMOGRAPHY
BLOOD-FLOW
MACHINES
PRESSURE
 
Description Application of impedance plethysmography (IP) for impedance measurement is the paradigm in assessment of central and peripheral blood flow. We propose the expediency of IP to unearth hidden patterns from Plethysmographic observations on a radial pulse. The variability analysis in one thousand control and disease subjects evolves an archetype of eight different morphological patterns. The peripheral pulse waveforms not only characterize the physiology of control subjects, but also define the morphology of patients suffering from Myocardial Infarction, cirrhosis of liver, and disorder of lungs. Diverse parallel support vector machine (pSVM) topologies are designed as an aid to the physician for multiclass pattern recognition problem. Besides a lowest confusion coefficient (0.133), the PCA-based pSVM classifier offers a comparatively higher generalized correlation coefficient and kappa value of 0.6586 and 0.8407, respectively. However, the ROC characteristics and the benchmark parameters suggest that wavelet-based pSVM is the optimum classifier with a sensitivity of 85.33 %, an elevated MCC (0.69), and a least upper bound on the expected error. pSVM stands out as a model classifier as compared with identified indices such as, Fishers Ratio, Morphology Index, and Heart rate variability.
 
Publisher SPRINGER LONDON LTD
 
Date 2014-10-16T06:56:11Z
2014-10-16T06:56:11Z
2013
 
Type Article
 
Identifier SIGNAL IMAGE AND VIDEO PROCESSING, 7(5)975-990
http://dx.doi.org/10.1007/s11760-012-0287-3
http://dspace.library.iitb.ac.in/jspui/handle/100/15489
 
Language en