Low complexity spectral analysis of heart-rate-variability through a wavelet based FFT
In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interesti...
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creator | Karakonstantis, G. Sankaranarayanan, A. Burg, A. |
description | In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system. |
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Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.</description><subject>Approximation algorithms</subject><subject>Approximation methods</subject><subject>Complexity theory</subject><subject>Discrete wavelet transforms</subject><subject>Heart rate variability</subject><subject>Kernel</subject><subject>Spectral analysis</subject><issn>0276-6574</issn><issn>2325-8853</issn><isbn>1467320765</isbn><isbn>9781467320764</isbn><isbn>9781467320757</isbn><isbn>9781467320771</isbn><isbn>1467320757</isbn><isbn>1467320773</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jMtKAzEUQOMLbGu_wE1-IJD3YynFUWHATXVbbqZ3bGTqlCS2zt-LqKuzOIdzRpbBeaGtU5I7487JTCppmPdGXZD5v7Dmksy4dJZZ4_Q1mZfyzrkIwZkZeW3HE-3G_WHAr1QnWg7Y1QwDhQ8YppIKHXu6Q8iVZajIjpATxDT8tHWXx8-3HQV6giMOWGmEglvaNOsbctXDUHD5xwV5ae7Xq0fWPj88re5aloQzlaECCdbHDnjQKARG8Oi87XUfIXArhTK90J3xkUfYbqOLMnitjVcRuejVgtz-fhMibg457SFPG6slV96qb6JlUPw</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Karakonstantis, G.</creator><creator>Sankaranarayanan, A.</creator><creator>Burg, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201209</creationdate><title>Low complexity spectral analysis of heart-rate-variability through a wavelet based FFT</title><author>Karakonstantis, G. ; Sankaranarayanan, A. ; Burg, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-e3a2a68bca094e11eba8e786f4fba9062135f14c58b0baddb7b29844583be01f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Approximation algorithms</topic><topic>Approximation methods</topic><topic>Complexity theory</topic><topic>Discrete wavelet transforms</topic><topic>Heart rate variability</topic><topic>Kernel</topic><topic>Spectral analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Karakonstantis, G.</creatorcontrib><creatorcontrib>Sankaranarayanan, A.</creatorcontrib><creatorcontrib>Burg, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Karakonstantis, G.</au><au>Sankaranarayanan, A.</au><au>Burg, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Low complexity spectral analysis of heart-rate-variability through a wavelet based FFT</atitle><btitle>2012 Computing in Cardiology</btitle><stitle>CiC</stitle><date>2012-09</date><risdate>2012</risdate><spage>285</spage><epage>288</epage><pages>285-288</pages><issn>0276-6574</issn><eissn>2325-8853</eissn><isbn>1467320765</isbn><isbn>9781467320764</isbn><eisbn>9781467320757</eisbn><eisbn>9781467320771</eisbn><eisbn>1467320757</eisbn><eisbn>1467320773</eisbn><abstract>In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.</abstract><pub>IEEE</pub><tpages>4</tpages></addata></record> |
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subjects | Approximation algorithms Approximation methods Complexity theory Discrete wavelet transforms Heart rate variability Kernel Spectral analysis |
title | Low complexity spectral analysis of heart-rate-variability through a wavelet based FFT |
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