{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T13:57:59Z","timestamp":1780408679681,"version":"3.54.1"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,15]],"date-time":"2021-01-15T00:00:00Z","timestamp":1610668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A new algorithm based on singular value decomposition (SVD) to remove cardiac contamination from trunk electromyography (EMG) is proposed. Its performance is compared to currently available algorithms at different signal-to-noise ratios (SNRs). The algorithm is applied on individual channels. An experimental calibration curve to adjust the number of SVD components to the SNR (0\u201320 dB) is proposed. A synthetic dataset is generated by the combination of electrocardiography (ECG) and EMG to establish a ground truth reference for validation. The performance is compared with state-of-the-art algorithms: gating, high-pass filtering, template subtraction (TS), and independent component analysis (ICA). Its applicability on real data is investigated in an illustrative diaphragm EMG of a patient with sleep apnea. The SVD-based algorithm outperforms existing methods in reconstructing trunk EMG. It is superior to the others in the time (relative mean squared error &lt; 15%) and frequency (shift in mean frequency &lt; 1 Hz) domains. Its feasibility is proven on diaphragm EMG, which shows a better agreement with the respiratory cycle (correlation coefficient = 0.81, p-value &lt; 0.01) compared with TS and ICA. Its application on real data is promising to non-obtrusively estimate respiratory effort for sleep-related breathing disorders. The algorithm is not limited to the need for additional reference ECG, increasing its applicability in clinical practice.<\/jats:p>","DOI":"10.3390\/s21020573","type":"journal-article","created":{"date-parts":[[2021,1,20]],"date-time":"2021-01-20T03:34:25Z","timestamp":1611113665000},"page":"573","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1231-9372","authenticated-orcid":false,"given":"Elisabetta","family":"Peri","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5777-1496","authenticated-orcid":false,"given":"Lin","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Ciccarelli","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nele L.","family":"Vandenbussche","sequence":"additional","affiliation":[{"name":"Center for Sleep Medicine, Kempenhaeghe, P.O. Box 61, 5590 AB Heeze, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongji","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9505-1270","authenticated-orcid":false,"given":"Xi","family":"Long","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6445-9836","authenticated-orcid":false,"given":"Sebastiaan","family":"Overeem","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"},{"name":"Center for Sleep Medicine, Kempenhaeghe, P.O. Box 61, 5590 AB Heeze, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6188-2973","authenticated-orcid":false,"given":"Johannes P.","family":"van Dijk","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"},{"name":"Center for Sleep Medicine, Kempenhaeghe, P.O. Box 61, 5590 AB Heeze, The Netherlands"},{"name":"Department of Orthodontics, University of Ulm, 89081 Ulm, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1179-5385","authenticated-orcid":false,"given":"Massimo","family":"Mischi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,15]]},"reference":[{"key":"ref_1","first-page":"321","article-title":"Comparison of pleural pressure and transcutaneous diaphragmatic electromyogram in obstructive sleep apnea syndrome","volume":"28","author":"Stoohs","year":"2005","journal-title":"Sleep"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.smrv.2014.12.006","article-title":"Assessment of respiratory effort during sleep: Esophageal pressure versus noninvasive monitoring techniques","volume":"24","author":"Vandenbussche","year":"2015","journal-title":"Sleep Med. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S1050-6411(01)00033-5","article-title":"Sampling, noise-reduction and amplitude estimation issues in surface electromyography","volume":"12","author":"Clancy","year":"2002","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.jelekin.2007.07.001","article-title":"Effect of electrocardiographic contamination on surface electromyography assessment of back muscles","volume":"19","author":"Hu","year":"2009","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.jelekin.2005.07.003","article-title":"Elimination of electrocardiogram contamination from electromyogram signals: An evaluation of currently used removal techniques","volume":"16","author":"Drake","year":"2006","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1152\/jappl.1979.46.1.152","article-title":"Spectral analysis of human inspiratory diaphragmatic electromyograms","volume":"46","author":"Schweitzer","year":"1979","journal-title":"J. Appl. Physiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1898","DOI":"10.1152\/jappl.1996.80.6.1898","article-title":"Analysis of diaphragm EMG signals: Comparison of gating vs. subtraction for removal of ECG contamination","volume":"80","author":"Bartolo","year":"1996","journal-title":"J. Appl. Physiol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1152\/jappl.1986.60.3.1073","article-title":"Description and validation of an ECG removal procedure for EMGdi power spectrum analysis","volume":"60","author":"Levine","year":"1986","journal-title":"J. Appl. Physiol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Merletti, R., Parker, P.A., and Parker, P.J. (2004). Electromyography: Physiology, Engineering, and Non-Invasive Applications, John Wiley & Sons.","DOI":"10.1002\/0471678384"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/S0268-0033(05)80009-9","article-title":"High-pass filtering to remove electrocardiographic interference from torso EMG recordings","volume":"8","author":"Redfern","year":"1993","journal-title":"Clin. Biomech."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Xu, L., Peri, E., Vullings, R., Rabotti, C., Van Dijk, J.P., and Mischi, M. (2020). Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography. Sensors, 20.","DOI":"10.3390\/s20174890"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1152\/jappl.1983.55.2.619","article-title":"Subtraction of electrocardiographic signal from respiratory electromyogram","volume":"55","author":"Bloch","year":"1983","journal-title":"J. Appl. Physiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/BF02637025","article-title":"Description and validation of a technique for the removal of ECG contamination from diaphragmatic EMG signal","volume":"34","author":"Bartolo","year":"1996","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_14","first-page":"33","article-title":"Removing ECG artifact from the surface EMG signal using adaptive subtraction technique","volume":"4","author":"Abbaspour","year":"2014","journal-title":"J. Biomed. Phys. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2009","DOI":"10.1109\/5.720250","article-title":"Blind signal separation: Statistical principles","volume":"86","author":"Cardoso","year":"1998","journal-title":"Proc. IEEE"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.jelekin.2012.01.001","article-title":"Removing ECG contamination from EMG recordings: A comparison of ICA-based and other filtering procedures","volume":"22","author":"Willigenburg","year":"2012","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1016\/j.medengphy.2010.05.007","article-title":"An automated ECG-artifact removal method for trunk muscle surface EMG recordings","volume":"32","author":"Mak","year":"2010","journal-title":"Med. Eng. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/10.553712","article-title":"Fetal ECG extraction from single-channel maternal ECG using singular value decomposition","volume":"44","author":"Kanjilal","year":"1997","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1109\/TUFFC.2020.2975483","article-title":"Blind Source Separation for Clutter and Noise Suppression in Ultrasound Imaging: Review for Different Applications","volume":"67","author":"Wildeboer","year":"2020","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1137\/17M1117732","article-title":"The singular value decomposition: Anatomy of optimizing an algorithm for extreme scale","volume":"60","author":"Dongarra","year":"2018","journal-title":"SIAM Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"20150202","DOI":"10.1098\/rsta.2015.0202","article-title":"Principal component analysis: A review and recent developments","volume":"374","author":"Jolliffe","year":"2016","journal-title":"Philos. Trans. R. Soc. A Math. Phys. Eng. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1007\/s13042-012-0131-7","article-title":"Principal component analysis using QR decomposition","volume":"4","author":"Sharma","year":"2013","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ouali, M.A., and Chafaa, K. (2013, January 20\u201322). SVD-based method for ECG denoising. Proceedings of the IEEE 2013 International Conference on Computer Applications Technology (ICCAT), Sousse, Tunisia.","DOI":"10.1109\/ICCAT.2013.6522051"},{"key":"ref_24","first-page":"2109","article-title":"ECG denoising using singular value decomposition","volume":"4","author":"Bandarabadi","year":"2010","journal-title":"Aust. J. Basic Appl. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S0893-6080(00)00026-5","article-title":"Independent component analysis: Algorithms and applications","volume":"13","author":"Oja","year":"2000","journal-title":"Neural Netw."},{"key":"ref_26","unstructured":"Junior, J.C., Ferreira, D., Nadal, J., and de S\u00e1, A.M. (September, January 31). Reducing electrocardiographic artifacts from electromyogram signals with independent component analysis. Proceedings of the 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina."},{"key":"ref_27","unstructured":"Hu, Y., Li, X., Xie, X., Pang, L., Cao, Y., and Luk, K. (2006, January 17\u201318). Applying independent component analysis on ECG cancellation technique for the surface recording of trunk electromyography. Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Alty, S.R., Man, W.D.C., Moxham, J., and Lee, K.C. (2008, January 20\u201325). Denoising of diaphragmatic electromyogram signals for respiratory control and diagnostic purposes. Proceedings of the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada.","DOI":"10.1109\/IEMBS.2008.4650474"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1186\/s12938-016-0196-8","article-title":"FastICA peel-off for ECG interference removal from surface EMG","volume":"15","author":"Chen","year":"2016","journal-title":"Biomed. Eng. Online"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1088\/0967-3334\/27\/12\/005","article-title":"Eliminating cardiac contamination from myoelectric control signals developed by targeted muscle reinnervation","volume":"27","author":"Zhou","year":"2006","journal-title":"Physiol. Meas."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1016\/j.jelekin.2009.07.007","article-title":"A wavelet-based adaptive filter for removing ECG interference in EMGdi signals","volume":"20","author":"Zhan","year":"2010","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.jelekin.2004.10.001","article-title":"Adaptive filtering for ECG rejection from surface EMG recordings","volume":"15","author":"Marque","year":"2005","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1284","DOI":"10.1109\/TNSRE.2015.2493358","article-title":"Analysis of vibration exercise at varying frequencies by different fatigue estimators","volume":"24","author":"Xu","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1109\/TNSRE.2016.2632755","article-title":"Towards real-time estimation of muscle-fiber conduction velocity using delay-locked loop","volume":"25","author":"Xu","year":"2016","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"066001","DOI":"10.1088\/1741-2552\/aadc43","article-title":"Does vibration superimposed on low-level isometric contraction alter motor unit recruitment strategy?","volume":"15","author":"Xu","year":"2018","journal-title":"J. Neural Eng."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"S\u00f6rnmo, L., and Laguna, P. (2006). Electrocardiogram (ECG) signal processing. Wiley Encyclopedia of Biomedical Engineering, John Wiley & Sons, Inc.","DOI":"10.1002\/9780471740360.ebs1482"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"van Gilst, M.M., van Dijk, J.P., Krijn, R., Hoondert, B., Fonseca, P., van Sloun, R.J., Arsenali, B., Vandenbussche, N., Pillen, S., and Maass, H. (2019). Protocol of the SOMNIA project: An observational study to create a neurophysiological database for advanced clinical sleep monitoring. BMJ Open, 9.","DOI":"10.1136\/bmjopen-2019-030996"},{"key":"ref_39","unstructured":"Silva, I., Behar, J., Sameni, R., Zhu, T., Oster, J., Clifford, G.D., and Moody, G.B. (2013, January 22\u201325). Noninvasive fetal ECG: The PhysioNet\/computing in cardiology challenge 2013. Proceedings of the Computing in Cardiology 2013, Zaragoza, Spain."},{"key":"ref_40","unstructured":"Moon, T.K., and Stirling, W.C. (2000). Mathematical Methods and Algorithms for Signal Processing, Prentice Hall."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/72.761722","article-title":"Fast and robust fixed-point algorithms for independent component analysis","volume":"10","author":"Hyvarinen","year":"1999","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/0167-2789(92)90103-T","article-title":"Singular-spectrum analysis: A toolkit for short, noisy chaotic signals","volume":"58","author":"Vautard","year":"1992","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2752","DOI":"10.1016\/j.nonrwa.2011.03.020","article-title":"Singular spectrum analysis based on the perturbation theory","volume":"12","author":"Hassani","year":"2011","journal-title":"Nonlinear Anal. Real World Appl."},{"key":"ref_44","first-page":"399","article-title":"Extracting fetal heart signal from noisy maternal ECG by singular spectrum analysis","volume":"3","author":"Ghodsi","year":"2010","journal-title":"J. Stat. Its Interface Spec. Issue Appl. SSA"},{"key":"ref_45","unstructured":"Lv, Q., Zhang, X.D., and Jia, Y. (2005, January 18\u201323). Kalman filtering algorithm for blind source separation. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP\u201905), Philadelphia, PA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/2\/573\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:11:25Z","timestamp":1760159485000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/2\/573"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,15]]},"references-count":45,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["s21020573"],"URL":"https:\/\/doi.org\/10.3390\/s21020573","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,15]]}}}