An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation
In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-w...
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| Published in | Medical & biological engineering & computing Vol. 46; no. 2; pp. 147 - 158 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer-Verlag
01.02.2008
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0140-0118 1741-0444 1741-0444 |
| DOI | 10.1007/s11517-007-0302-y |
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| Abstract | In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (
r
2
> 0.8) with the signal acquired from the chest-belt respiration sensor. |
|---|---|
| AbstractList | In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r super(2) > 0.8) with the signal acquired from the chest-belt respiration sensor. In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r(2) > 0.8) with the signal acquired from the chest-belt respiration sensor. In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r2 > 0.8) with the signal acquired from the chest-belt respiration sensor. [PUBLICATION ABSTRACT] In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r2 > 0.8) with the signal acquired from the chest-belt respiration sensor. In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation ( r 2 > 0.8) with the signal acquired from the chest-belt respiration sensor. In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r(2) > 0.8) with the signal acquired from the chest-belt respiration sensor.In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r(2) > 0.8) with the signal acquired from the chest-belt respiration sensor. |
| Author | Yoon, Hyoung-Ro Noh, Yeon-Sik Park, Sung-Jun Park, Sung-Bin |
| Author_xml | – sequence: 1 givenname: Sung-Bin surname: Park fullname: Park, Sung-Bin email: babypjs@hotmail.com organization: Department of Biomedical Engineering, Yonsei University – sequence: 2 givenname: Yeon-Sik surname: Noh fullname: Noh, Yeon-Sik organization: Department of Biomedical Engineering, Yonsei University – sequence: 3 givenname: Sung-Jun surname: Park fullname: Park, Sung-Jun organization: Department of Biomedical Engineering, Yonsei University – sequence: 4 givenname: Hyoung-Ro surname: Yoon fullname: Yoon, Hyoung-Ro organization: Department of Biomedical Engineering, Yonsei University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/18210178$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_3390_s21155245 crossref_primary_10_1063_5_0156340 crossref_primary_10_1152_ajpheart_00039_2014 crossref_primary_10_1088_0967_3334_36_7_1497 crossref_primary_10_1002_advs_202203460 crossref_primary_10_1016_j_cmpb_2018_05_026 crossref_primary_10_1016_j_compbiomed_2015_04_015 crossref_primary_10_1088_0967_3334_33_10_R47 crossref_primary_10_1109_TBCAS_2017_2688339 crossref_primary_10_1186_1471_230X_12_60 crossref_primary_10_1016_j_bspc_2017_08_016 crossref_primary_10_1155_2010_926305 crossref_primary_10_1016_j_bspc_2022_103716 crossref_primary_10_1016_j_bspc_2012_06_001 crossref_primary_10_3390_s16101573 crossref_primary_10_1016_j_bspc_2019_02_004 crossref_primary_10_1109_ACCESS_2018_2865487 crossref_primary_10_3390_s150511295 crossref_primary_10_1109_TBME_2013_2244892 crossref_primary_10_1109_RBME_2017_2763681 crossref_primary_10_3390_e24040471 crossref_primary_10_1016_j_bspc_2018_05_025 crossref_primary_10_1016_j_compbiomed_2016_12_005 crossref_primary_10_1016_j_measurement_2024_114978 crossref_primary_10_1109_TAFFC_2017_2781732 crossref_primary_10_1186_s12938_015_0054_0 crossref_primary_10_1016_j_sna_2012_06_031 crossref_primary_10_1038_s41598_020_62624_5 crossref_primary_10_1098_rsos_182001 crossref_primary_10_1109_JBHI_2019_2898273 crossref_primary_10_1109_JSYST_2014_2336372 crossref_primary_10_14326_abe_6_28 crossref_primary_10_3389_fpsyg_2014_00805 crossref_primary_10_1109_JSEN_2020_3012697 crossref_primary_10_1016_j_bspc_2015_04_006 |
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| Copyright | The Author(s) 2008 International Federation for Medical and Biological Engineering 2008 |
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| Keywords | Conductive textile electrodes in bed Hilbert transform ECG-derived respiration Instantaneous frequency Home healthcare |
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| References | O’BrienCHeneghanCA comparison of algorithms for estimation of a respiratory signal from the surface electrocardiogramComput Biol Med20073730531410.1016/j.compbiomed.2006.02.002 MietusDetection of obstructive sleep apnea from cardiac interbeat interval time seriesComput Cardiol200027753756 IshijimaMCardiopulmonary monitoring by textile electrodes without subject-awareness of being monitoredMed Biol Eng Comput19973568569010.1007/BF02510978 Ogawa M, Togawa T (2000) Attempts at monitoring health status in home. IEEE EMBS. 1st annual international conference. pp 552–556 MoodyGBMarkRGBumpMAWeinsteinJSClinical validation of ECG-derived respiration techniqueComput Cardiol198613507510 Bebehani K, Burk J, Lucas E (2002) ECG derived respiratory rhythms for improved diagnosis of sleep apnea, United States Patent US 6415174 B1 Chou TC (1996) Electrocardiography in clinical practice—adult and pediatric. Saunders 3–22 Smithers CR, Hill N (1999) Options for wireless technology in telemedicine and telecare applications. Telemedicine and telecare on 1999. p 138 Urrusti JL, Tompkins WJ (1993) Performance evaluation of an ECG QRS complex detection algorithm. EMBS. In: Proceedings of the 15th annual international conference of the IEEE. pp 800–801 Yi WJ, Park KS (2002) Derivation of respiration from ECG Measured without subject’s awareness using wavelet transform. IEEE EMBS/BMES Conference. pp 130–131 IshijimaMMonitoring of electrocardiograms in bed without utilizing surface electrodesIEEE Trans Biomed Eng19934059359410.1109/10.237680 Tom F, Alan AM, James B, Jo P (2003) Quality of care for elderly residents in nursing homes and elderly people living at home: controlled observational study. BMJ 326–580, doi:10.1136/bmj;326.7389.580 MazzantiBLambertiCBieJValiation of an ECG-derived respiration monitoring methodComput Cardiol20033061361610.1109/CIC.2003.1291230 Caggiano D, Reisman S (1996) Respiration derived from electrocardiogram: a quantitative comparison of three different methods. In: Proceedings of the IEEE 22nd annual international conference. pp 103–104 MoodyGBMarkRGZoccolaAManteroSDerivation of respiration signals from multi-lead ECGsComput Cardiol198512113116 Bebehani K, Vijendra S, Burk J, Lucas E (2002) An investigation of the mean electrical axis angle and respiration during sleep. In: Proceedings of the 2nd joint EMBS/BMES conference, TX, USA KrishnaPSahambiJSClassification of ECG arrhythmias using multi-resolution analysis and neural networksIEEE Trans Biomed Eng20031227231 PinciroliFRossiRVerganiLDetection of electrical axis variation for extraction of respiration informationComput Cardiol19852499502 Juan PM, Rute A, Salvador O, Ana PR, Pablo L (2004) A wavelet-based ECG delineator: evaluation on standard databases, IEEE Trans Biomed Eng 51(4) ReillyAFrazerGBoashashBAnalytic signal generation—tips and trapsIEEE Trans Signal Process199442113241324510.1109/78.330385 Cuiwei L, Chongxun Z, Changfeng T (1995) Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng 42(1) Ishijima M (1996) Long-term cardiopulmonary monitoring in bed without subject awareness. IEEE EMB. 18th annual international conference. pp 65–66 B Mazzanti (302_CR11) 2003; 30 302_CR20 M Ishijima (302_CR6) 1993; 40 GB Moody (302_CR14) 1986; 13 302_CR4 302_CR3 P Krishna (302_CR10) 2003; 1 302_CR2 302_CR22 302_CR1 302_CR21 302_CR7 302_CR16 F Pinciroli (302_CR17) 1985; 2 A Reilly (302_CR18) 1994; 42 302_CR5 GB Moody (302_CR13) 1985; 12 302_CR19 302_CR9 C O’Brien (302_CR15) 2007; 37 M Ishijima (302_CR8) 1997; 35 Mietus (302_CR12) 2000; 27 8262542 - IEEE Trans Biomed Eng. 1993 Jun;40(6):593-4 16777085 - Comput Biol Med. 2007 Mar;37(3):305-14 7851927 - IEEE Trans Biomed Eng. 1995 Jan;42(1):21-8 15072211 - IEEE Trans Biomed Eng. 2004 Apr;51(4):570-81 12637404 - BMJ. 2003 Mar 15;326(7389):580 9538546 - Med Biol Eng Comput. 1997 Nov;35(6):685-90 |
| References_xml | – reference: Tom F, Alan AM, James B, Jo P (2003) Quality of care for elderly residents in nursing homes and elderly people living at home: controlled observational study. BMJ 326–580, doi:10.1136/bmj;326.7389.580 – reference: IshijimaMMonitoring of electrocardiograms in bed without utilizing surface electrodesIEEE Trans Biomed Eng19934059359410.1109/10.237680 – reference: MietusDetection of obstructive sleep apnea from cardiac interbeat interval time seriesComput Cardiol200027753756 – reference: MoodyGBMarkRGZoccolaAManteroSDerivation of respiration signals from multi-lead ECGsComput Cardiol198512113116 – reference: IshijimaMCardiopulmonary monitoring by textile electrodes without subject-awareness of being monitoredMed Biol Eng Comput19973568569010.1007/BF02510978 – reference: KrishnaPSahambiJSClassification of ECG arrhythmias using multi-resolution analysis and neural networksIEEE Trans Biomed Eng20031227231 – reference: MazzantiBLambertiCBieJValiation of an ECG-derived respiration monitoring methodComput Cardiol20033061361610.1109/CIC.2003.1291230 – reference: O’BrienCHeneghanCA comparison of algorithms for estimation of a respiratory signal from the surface electrocardiogramComput Biol Med20073730531410.1016/j.compbiomed.2006.02.002 – reference: Yi WJ, Park KS (2002) Derivation of respiration from ECG Measured without subject’s awareness using wavelet transform. IEEE EMBS/BMES Conference. pp 130–131 – reference: Bebehani K, Vijendra S, Burk J, Lucas E (2002) An investigation of the mean electrical axis angle and respiration during sleep. In: Proceedings of the 2nd joint EMBS/BMES conference, TX, USA – reference: PinciroliFRossiRVerganiLDetection of electrical axis variation for extraction of respiration informationComput Cardiol19852499502 – reference: Ogawa M, Togawa T (2000) Attempts at monitoring health status in home. IEEE EMBS. 1st annual international conference. pp 552–556 – reference: Smithers CR, Hill N (1999) Options for wireless technology in telemedicine and telecare applications. Telemedicine and telecare on 1999. p 138 – reference: Cuiwei L, Chongxun Z, Changfeng T (1995) Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng 42(1) – reference: ReillyAFrazerGBoashashBAnalytic signal generation—tips and trapsIEEE Trans Signal Process199442113241324510.1109/78.330385 – reference: Caggiano D, Reisman S (1996) Respiration derived from electrocardiogram: a quantitative comparison of three different methods. In: Proceedings of the IEEE 22nd annual international conference. pp 103–104 – reference: Chou TC (1996) Electrocardiography in clinical practice—adult and pediatric. Saunders 3–22 – reference: MoodyGBMarkRGBumpMAWeinsteinJSClinical validation of ECG-derived respiration techniqueComput Cardiol198613507510 – reference: Bebehani K, Burk J, Lucas E (2002) ECG derived respiratory rhythms for improved diagnosis of sleep apnea, United States Patent US 6415174 B1 – reference: Juan PM, Rute A, Salvador O, Ana PR, Pablo L (2004) A wavelet-based ECG delineator: evaluation on standard databases, IEEE Trans Biomed Eng 51(4) – reference: Ishijima M (1996) Long-term cardiopulmonary monitoring in bed without subject awareness. IEEE EMB. 18th annual international conference. pp 65–66 – reference: Urrusti JL, Tompkins WJ (1993) Performance evaluation of an ECG QRS complex detection algorithm. EMBS. In: Proceedings of the 15th annual international conference of the IEEE. pp 800–801 – ident: 302_CR22 doi: 10.1109/IEMBS.2002.1134420 – ident: 302_CR19 – ident: 302_CR20 doi: 10.1136/bmj;326.7389.580 – ident: 302_CR1 – volume: 35 start-page: 685 year: 1997 ident: 302_CR8 publication-title: Med Biol Eng Comput doi: 10.1007/BF02510978 – volume: 37 start-page: 305 year: 2007 ident: 302_CR15 publication-title: Comput Biol Med doi: 10.1016/j.compbiomed.2006.02.002 – ident: 302_CR2 doi: 10.1109/IEMBS.2002.1106531 – volume: 1 start-page: 227 year: 2003 ident: 302_CR10 publication-title: IEEE Trans Biomed Eng – ident: 302_CR4 – volume: 27 start-page: 753 year: 2000 ident: 302_CR12 publication-title: Comput Cardiol – ident: 302_CR5 doi: 10.1109/10.362922 – ident: 302_CR9 doi: 10.1109/TBME.2003.821031 – ident: 302_CR7 – ident: 302_CR21 doi: 10.1109/IEMBS.1993.978840 – volume: 13 start-page: 507 year: 1986 ident: 302_CR14 publication-title: Comput Cardiol – volume: 42 start-page: 3241 issue: 11 year: 1994 ident: 302_CR18 publication-title: IEEE Trans Signal Process doi: 10.1109/78.330385 – volume: 12 start-page: 113 year: 1985 ident: 302_CR13 publication-title: Comput Cardiol – ident: 302_CR3 doi: 10.1109/NEBC.1996.503238 – volume: 40 start-page: 593 year: 1993 ident: 302_CR6 publication-title: IEEE Trans Biomed Eng doi: 10.1109/10.237680 – ident: 302_CR16 doi: 10.1109/MMB.2000.893845 – volume: 2 start-page: 499 year: 1985 ident: 302_CR17 publication-title: Comput Cardiol – volume: 30 start-page: 613 year: 2003 ident: 302_CR11 publication-title: Comput Cardiol doi: 10.1109/CIC.2003.1291230 – reference: 15072211 - IEEE Trans Biomed Eng. 2004 Apr;51(4):570-81 – reference: 7851927 - IEEE Trans Biomed Eng. 1995 Jan;42(1):21-8 – reference: 12637404 - BMJ. 2003 Mar 15;326(7389):580 – reference: 16777085 - Comput Biol Med. 2007 Mar;37(3):305-14 – reference: 9538546 - Med Biol Eng Comput. 1997 Nov;35(6):685-90 – reference: 8262542 - IEEE Trans Biomed Eng. 1993 Jun;40(6):593-4 |
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| Snippet | In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system... |
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| SubjectTerms | Adhesives Algorithms Biomedical and Life Sciences Biomedical Engineering and Bioengineering Biomedicine Computer Applications Electrocardiography Electrocardiography - instrumentation Electrocardiography - methods Electrodes Health care Hilbert space Home Care Services Human Physiology Humans Imaging Male Medical research Methods Original Original Article Radiology Respiration Respiratory Mechanics Signal processing Signal Processing, Computer-Assisted Studies Textiles |
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| Title | An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation |
| URI | https://link.springer.com/article/10.1007/s11517-007-0302-y https://www.ncbi.nlm.nih.gov/pubmed/18210178 https://www.proquest.com/docview/211499714 https://www.proquest.com/docview/20595823 https://www.proquest.com/docview/70264422 https://pubmed.ncbi.nlm.nih.gov/PMC2668578 https://link.springer.com/content/pdf/10.1007/s11517-007-0302-y.pdf |
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