Evaluating the Lower-Body Electromyogram Signal Acquired From the Feet As a Noise Reference for Standing Ballistocardiogram Measurements
The ballistocardiogram (BCG) is a measure of the reaction force of the body to cardiac ejection of blood. A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives:...
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| description | The ballistocardiogram (BCG) is a measure of the reaction force of the body to cardiac ejection of blood. A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives: low cost, small size, unobtrusiveness, and familiarity to the user; one disadvantage is that the subject must stand during the recording, rather than sit or lay supine, resulting in a higher susceptibility to motion artifacts in the measured signal. This paper evaluates the electromyogram (EMG) signal acquired from the feet of the subject during BCG recording as a noise reference for standing BCG measurements. As a subject moves while standing on the scale, muscle contractions in the feet are detected by the EMG signal, and used to flag segments of the BCG signal that are corrupted by elevated noise. For the purposes of evaluating this method, estimates of the BCG noise-to-signal ratio (NSR) were independently calculated with an ensemble average method, using the R-wave of a simultaneously-acquired chest ECG as a timing reference. The linear correlation between EMG power alone and BCG NSR from 14 subjects was found to be moderate ( r = 0.58, F -statistic p -value |
| doi_str_mv | 10.1109/TITB.2010.2044185 |
| format | Article |
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A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives: low cost, small size, unobtrusiveness, and familiarity to the user; one disadvantage is that the subject must stand during the recording, rather than sit or lay supine, resulting in a higher susceptibility to motion artifacts in the measured signal. This paper evaluates the electromyogram (EMG) signal acquired from the feet of the subject during BCG recording as a noise reference for standing BCG measurements. As a subject moves while standing on the scale, muscle contractions in the feet are detected by the EMG signal, and used to flag segments of the BCG signal that are corrupted by elevated noise. For the purposes of evaluating this method, estimates of the BCG noise-to-signal ratio (NSR) were independently calculated with an ensemble average method, using the R-wave of a simultaneously-acquired chest ECG as a timing reference. The linear correlation between EMG power alone and BCG NSR from 14 subjects was found to be moderate ( r = 0.58, F -statistic p -value <; 0.05); combined with body-mass index (BMI), multiple linear regression yielded a stronger correlation ( r = 0.73, F -statistic p -value = 0.01). Additionally, an example usage of the lower-leg EMG for improving BCG measurement robustness is provided.</description><identifier>ISSN: 1089-7771</identifier><identifier>ISSN: 2168-2194</identifier><identifier>EISSN: 1558-0032</identifier><identifier>EISSN: 2168-2208</identifier><identifier>DOI: 10.1109/TITB.2010.2044185</identifier><identifier>PMID: 20371416</identifier><identifier>CODEN: ITIBFX</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Adult ; Ballistocardiogram (BCG) ; Ballistocardiography - methods ; Blood ; Costs ; electromyogram (EMG) ; Electromyography ; Electromyography - methods ; Feet ; Female ; Foot - physiology ; Force measurement ; Humans ; Linear Models ; Male ; motion artifacts ; Motion measurement ; Movement ; Muscles ; Noise ; Noise measurement ; noninvasive cardiovascular monitoring ; Particle measurements ; Posture ; Signal Processing, Computer-Assisted ; Signal to noise ratio ; Size measurement ; SNR estimation</subject><ispartof>IEEE journal of biomedical and health informatics, 2010-09, Vol.14 (5), p.1188-1196</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Sep 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c494t-554154d9a8084f4f023cf21a56808d2418684fa24358565235bf2c14a3a01a7d3</citedby><cites>FETCH-LOGICAL-c494t-554154d9a8084f4f023cf21a56808d2418684fa24358565235bf2c14a3a01a7d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5443605$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5443605$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20371416$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Inan, O T</creatorcontrib><creatorcontrib>Kovacs, G T A</creatorcontrib><creatorcontrib>Giovangrandi, L</creatorcontrib><title>Evaluating the Lower-Body Electromyogram Signal Acquired From the Feet As a Noise Reference for Standing Ballistocardiogram Measurements</title><title>IEEE journal of biomedical and health informatics</title><addtitle>TITB</addtitle><addtitle>IEEE Trans Inf Technol Biomed</addtitle><description>The ballistocardiogram (BCG) is a measure of the reaction force of the body to cardiac ejection of blood. A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives: low cost, small size, unobtrusiveness, and familiarity to the user; one disadvantage is that the subject must stand during the recording, rather than sit or lay supine, resulting in a higher susceptibility to motion artifacts in the measured signal. This paper evaluates the electromyogram (EMG) signal acquired from the feet of the subject during BCG recording as a noise reference for standing BCG measurements. As a subject moves while standing on the scale, muscle contractions in the feet are detected by the EMG signal, and used to flag segments of the BCG signal that are corrupted by elevated noise. For the purposes of evaluating this method, estimates of the BCG noise-to-signal ratio (NSR) were independently calculated with an ensemble average method, using the R-wave of a simultaneously-acquired chest ECG as a timing reference. The linear correlation between EMG power alone and BCG NSR from 14 subjects was found to be moderate ( r = 0.58, F -statistic p -value <; 0.05); combined with body-mass index (BMI), multiple linear regression yielded a stronger correlation ( r = 0.73, F -statistic p -value = 0.01). Additionally, an example usage of the lower-leg EMG for improving BCG measurement robustness is provided.</description><subject>Adult</subject><subject>Ballistocardiogram (BCG)</subject><subject>Ballistocardiography - methods</subject><subject>Blood</subject><subject>Costs</subject><subject>electromyogram (EMG)</subject><subject>Electromyography</subject><subject>Electromyography - methods</subject><subject>Feet</subject><subject>Female</subject><subject>Foot - physiology</subject><subject>Force measurement</subject><subject>Humans</subject><subject>Linear Models</subject><subject>Male</subject><subject>motion artifacts</subject><subject>Motion measurement</subject><subject>Movement</subject><subject>Muscles</subject><subject>Noise</subject><subject>Noise measurement</subject><subject>noninvasive cardiovascular monitoring</subject><subject>Particle measurements</subject><subject>Posture</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Signal to noise ratio</subject><subject>Size measurement</subject><subject>SNR estimation</subject><issn>1089-7771</issn><issn>2168-2194</issn><issn>1558-0032</issn><issn>2168-2208</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqFkc9u1DAQxi0EoqXwAAgJWeqhp5Txv8Q57la7UGkBiS7nyHUmi6skbm0HtG_Qx8Zhlx64cBrPzO_7JM9HyFsGl4xB_WF7vV1ecsgtBymZVs_IKVNKFwCCP89v0HVRVRU7Ia9ivANgUjHxkpxwEBWTrDwlj6ufpp9McuOOph9IN_4XhmLp2z1d9WhT8MPe74IZ6I3bjaanC_swuYAtXefVH8kaMdFFpIZ-8S4i_YYdBhwt0s4HepPM2M7uS9P3LiZvTWjdwfIzmjgFHHBM8TV50Zk-4ptjPSPf16vt1adi8_Xj9dViU1hZy1QoJZmSbW00aNnJDriwHWdGlXnQ8nyEMs8Nl0JpVSou1G3HLZNGGGCmasUZuTj43gf_MGFMzeCixb43I_opNpWueKlrUP8nlQTGa11m8vwf8s5PIV8rNgxmAmpgmWIHygYfY8CuuQ9uMGGfoWbOs5nzbOY8m2OeWfP-6DzdDtg-Kf4GmIF3B8Ah4tNaSSnK_IXfzIajDg</recordid><startdate>201009</startdate><enddate>201009</enddate><creator>Inan, O T</creator><creator>Kovacs, G T A</creator><creator>Giovangrandi, L</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201009</creationdate><title>Evaluating the Lower-Body Electromyogram Signal Acquired From the Feet As a Noise Reference for Standing Ballistocardiogram Measurements</title><author>Inan, O T ; Kovacs, G T A ; Giovangrandi, L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c494t-554154d9a8084f4f023cf21a56808d2418684fa24358565235bf2c14a3a01a7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adult</topic><topic>Ballistocardiogram (BCG)</topic><topic>Ballistocardiography - methods</topic><topic>Blood</topic><topic>Costs</topic><topic>electromyogram (EMG)</topic><topic>Electromyography</topic><topic>Electromyography - methods</topic><topic>Feet</topic><topic>Female</topic><topic>Foot - physiology</topic><topic>Force measurement</topic><topic>Humans</topic><topic>Linear Models</topic><topic>Male</topic><topic>motion artifacts</topic><topic>Motion measurement</topic><topic>Movement</topic><topic>Muscles</topic><topic>Noise</topic><topic>Noise measurement</topic><topic>noninvasive cardiovascular monitoring</topic><topic>Particle measurements</topic><topic>Posture</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Signal to noise ratio</topic><topic>Size measurement</topic><topic>SNR estimation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Inan, O T</creatorcontrib><creatorcontrib>Kovacs, G T A</creatorcontrib><creatorcontrib>Giovangrandi, L</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE journal of biomedical and health informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Inan, O T</au><au>Kovacs, G T A</au><au>Giovangrandi, L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluating the Lower-Body Electromyogram Signal Acquired From the Feet As a Noise Reference for Standing Ballistocardiogram Measurements</atitle><jtitle>IEEE journal of biomedical and health informatics</jtitle><stitle>TITB</stitle><addtitle>IEEE Trans Inf Technol Biomed</addtitle><date>2010-09</date><risdate>2010</risdate><volume>14</volume><issue>5</issue><spage>1188</spage><epage>1196</epage><pages>1188-1196</pages><issn>1089-7771</issn><issn>2168-2194</issn><eissn>1558-0032</eissn><eissn>2168-2208</eissn><coden>ITIBFX</coden><abstract>The ballistocardiogram (BCG) is a measure of the reaction force of the body to cardiac ejection of blood. A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives: low cost, small size, unobtrusiveness, and familiarity to the user; one disadvantage is that the subject must stand during the recording, rather than sit or lay supine, resulting in a higher susceptibility to motion artifacts in the measured signal. This paper evaluates the electromyogram (EMG) signal acquired from the feet of the subject during BCG recording as a noise reference for standing BCG measurements. As a subject moves while standing on the scale, muscle contractions in the feet are detected by the EMG signal, and used to flag segments of the BCG signal that are corrupted by elevated noise. For the purposes of evaluating this method, estimates of the BCG noise-to-signal ratio (NSR) were independently calculated with an ensemble average method, using the R-wave of a simultaneously-acquired chest ECG as a timing reference. The linear correlation between EMG power alone and BCG NSR from 14 subjects was found to be moderate ( r = 0.58, F -statistic p -value <; 0.05); combined with body-mass index (BMI), multiple linear regression yielded a stronger correlation ( r = 0.73, F -statistic p -value = 0.01). Additionally, an example usage of the lower-leg EMG for improving BCG measurement robustness is provided.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>20371416</pmid><doi>10.1109/TITB.2010.2044185</doi><tpages>9</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adult Ballistocardiogram (BCG) Ballistocardiography - methods Blood Costs electromyogram (EMG) Electromyography Electromyography - methods Feet Female Foot - physiology Force measurement Humans Linear Models Male motion artifacts Motion measurement Movement Muscles Noise Noise measurement noninvasive cardiovascular monitoring Particle measurements Posture Signal Processing, Computer-Assisted Signal to noise ratio Size measurement SNR estimation |
| title | Evaluating the Lower-Body Electromyogram Signal Acquired From the Feet As a Noise Reference for Standing Ballistocardiogram Measurements |
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