{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T11:54:32Z","timestamp":1769082872539,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T00:00:00Z","timestamp":1627603200000},"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>To facilitate the broader use of EMG signal whitening, we studied four whitening procedures of various complexities, as well as the roles of sampling rate and noise correction. We separately analyzed force-varying and constant-force contractions from 64 subjects who completed constant-posture tasks about the elbow over a range of forces from 0% to 50% maximum voluntary contraction (MVC). From the constant-force tasks, we found that noise correction via the root difference of squares (RDS) method consistently reduced EMG recording noise, often by a factor of 5\u201310. All other primary results were from the force-varying contractions. Sampling at 4096 Hz provided small and statistically significant improvements over sampling at 2048 Hz (~3%), which, in turn, provided small improvements over sampling at 1024 Hz (~4%). In comparing equivalent processing variants at a sampling rate of 4096 Hz, whitening filters calibrated to the EMG spectrum of each subject generally performed best (4.74% MVC EMG-force error), followed by one universal whitening filter for all subjects (4.83% MVC error), followed by a high-pass filter whitening method (4.89% MVC error) and then a first difference whitening filter (4.91% MVC error)\u2014but none of these statistically differed. Each did significantly improve from EMG-force error without whitening (5.55% MVC). The first difference is an excellent whitening option over this range of contraction forces since no calibration or algorithm decisions are required.<\/jats:p>","DOI":"10.3390\/s21155165","type":"journal-article","created":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T21:44:32Z","timestamp":1627854272000},"page":"5165","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMG\u03c3): Evaluation on Two Datasets"],"prefix":"10.3390","volume":"21","author":[{"given":"He","family":"Wang","sequence":"first","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kiriaki J.","family":"Rajotte","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haopeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenyun","family":"Dai","sequence":"additional","affiliation":[{"name":"Center for Biomedical Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziling","family":"Zhu","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0584-3448","authenticated-orcid":false,"given":"Xinming","family":"Huang","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0729-2523","authenticated-orcid":false,"given":"Edward A.","family":"Clancy","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1152\/japplphysiol.01070.2003","article-title":"The extraction of neural strategies from the surface EMG","volume":"96","author":"Farina","year":"2004","journal-title":"J. Appl. Physiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/0013-4694(52)90008-4","article-title":"Relation of human electromyogram to musculuar tension","volume":"4","author":"Inman","year":"1952","journal-title":"EEG Clin. Neurophysiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"576729","DOI":"10.3389\/fneur.2020.576729","article-title":"Analysis and biophysics of surface EMG for physiotherapists and kinesiologists: Toward a common language with rehabilitation engineers","volume":"11","author":"McManus","year":"2020","journal-title":"Front. Neurol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1109\/TNSRE.2016.2639443","article-title":"Comparison of constant-posture force-varying EMG-force dynamic models about the elbow","volume":"25","author":"Dai","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.jelekin.2019.04.003","article-title":"Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes","volume":"47","author":"Dai","year":"2019","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.jelekin.2009.08.005","article-title":"Methodological aspects of EMG recordings for force estimation\u2014A tutorial and review","volume":"20","author":"Staudenmann","year":"2010","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.jelekin.2011.10.012","article-title":"EMG-force modeling using parallel cascade identification","volume":"22","author":"Hashemi","year":"2012","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/TNSRE.2014.2325713","article-title":"Enhanced dynamic EMG-force estimation through calibration and PCI modeling","volume":"23","author":"Hashemi","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.jelekin.2007.03.006","article-title":"Effect of elbow joint angle on force-EMG relationships in human elbow flexor and extensor muscles","volume":"18","author":"Doheny","year":"2008","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jelekin.2019.02.001","article-title":"Single-trial estimation of quasi-static EMG-to-joint-mechanical-impedance relationship over a range of joint torques","volume":"45","author":"Dai","year":"2019","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1109\/TBME.1990.1438510","article-title":"Functional assessment of control systems for cybernetic elbow prosthesis\u2014Part I: Description of the technique","volume":"37","author":"Hogan","year":"1990","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1152\/jn.00584.2007","article-title":"A myokinetic arm model for estimating joint torque and stiffness from EMG signals during maintained posture","volume":"101","author":"Shin","year":"2009","journal-title":"J. Neurophysiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"205","DOI":"10.20965\/jrm.2012.p0205","article-title":"A power assist device based on joint equilibrium point estimation from EMG signals","volume":"24","author":"Kawase","year":"2012","journal-title":"J. Robot. Mechatron."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2604","DOI":"10.1109\/TBME.2012.2207895","article-title":"Model-based estimation of knee stiffness","volume":"59","author":"Pfeifer","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"35","DOI":"10.3389\/fncom.2017.00035","article-title":"Linear parametric varying identification of dynamic joint stiffness during time-varying voluntary contractions","volume":"11","author":"Golkar","year":"2017","journal-title":"Front. Comput. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1007\/s00221-003-1624-0","article-title":"A critical evaluation of the force control hypothesis in motor control","volume":"153","author":"Ostry","year":"2003","journal-title":"Exp. Brain Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"934","DOI":"10.3389\/fneur.2020.00934","article-title":"Surface EMG in clinical assessment and neurorehabilitation: Barriers limiting its use","volume":"11","author":"Campanini","year":"2020","journal-title":"Front. Neurol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/j.jelekin.2006.08.006","article-title":"Myoelectric signal processing for control of powered limb prostheses","volume":"16","author":"Parker","year":"2006","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1109\/TNSRE.2014.2305111","article-title":"The extraction of neural information from the surface EMG for the control of upper-limb prostheses: Emerging avenues and challenges","volume":"22","author":"Farina","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1016\/0003-9993(93)90033-7","article-title":"Quantitative assessment of four men using above-elbow prosthetic control","volume":"74","author":"Popat","year":"1993","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Merletti, R., and Parker, P.A. (2004). Applications in ergonomics. Electromyography: Physiology, Engineering, and Noninvasive Applications, IEEE Press\/Wiley-Interscience.","DOI":"10.1002\/0471678384"},{"key":"ref_22","unstructured":"Kumar, S., and Mital, A. (1996). Electromyography in Ergonomics, Taylor & Francis."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.clinbiomech.2008.08.003","article-title":"Surface electromyography and muscle force: Limits in sEMG-force relationship and new approaches for applications","volume":"24","author":"Rau","year":"2009","journal-title":"Clin. Biomech."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/S0268-0033(02)00183-3","article-title":"A clinically applicable EMG-force model to quantify active stabilization of the knee after a lesion of the anterior cruciate ligament","volume":"18","author":"Doorenbosch","year":"2003","journal-title":"Clin. Biomech."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"2328","DOI":"10.1109\/TNSRE.2019.2951081","article-title":"Optimal estimation of EMG standard deviation (EMG\u03c3) in additive measurement noise: Model-based derivations and their implications","volume":"27","author":"Wang","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1109\/10.844217","article-title":"Adaptive whitening of the electromyogram to improve amplitude estimation","volume":"47","author":"Clancy","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1109\/TBME.1980.326652","article-title":"Myoelectric signal processing: Optimal estimation applied to electromyography\u2014Part I: Derivation of the optimal myoprocessor","volume":"27","author":"Hogan","year":"1980","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/TBME.1980.326653","article-title":"Myoelectric signal processing: Optimal estimation applied to electromyography\u2014Part II: Experimental demonstration of optimal myoprocessor performance","volume":"27","author":"Hogan","year":"1980","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1109\/10.678614","article-title":"Influence of smoothing window length on electromyogram amplitude estimates","volume":"45","author":"Rancourt","year":"1998","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1109\/10.284927","article-title":"Single site electromyograph amplitude estimation","volume":"41","author":"Clancy","year":"1994","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1109\/TNSRE.2013.2243470","article-title":"Electromyogram whitening for improved classification accuracy in upper limb prosthesis control","volume":"21","author":"Liu","year":"2013","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1109\/10.634654","article-title":"Relating agonist-antagonist electromyograms to joint torque during isometric, quasi-isotonic, non-fatiguing contractions","volume":"44","author":"Clancy","year":"1997","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_34","unstructured":"Herberts, P., Kadefors, R., Magnusson, R., and Petersen, I. (1974). Adaptive Filter for EMG Control Signals. The Control of Upper-Extremity Prostheses and Orthoses, Charles C. Thomas."},{"key":"ref_35","unstructured":"Clancy, E.A. (1991). Stochastic Modeling of the Relationship Between the Surface Electromygram and Muscle Torque. [Ph.D. Thesis, Massachusetts Institute of Technology]."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1109\/TNSRE.2013.2283403","article-title":"Electromyogram bandwidth requirements when the signal is whitened","volume":"22","author":"Dasog","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.jelekin.2003.10.005","article-title":"Less is more: High pass filtering, to remove up to 99% of the surface EMG signal power, improves EMG-based biceps brachii muscle force estimates","volume":"14","author":"Potvin","year":"2004","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/0141-5425(81)90002-9","article-title":"Optimizing the acquisition and processing of surface electromyographic signals","volume":"3","author":"Harba","year":"1981","journal-title":"J. Biomech. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.cmpb.2014.06.013","article-title":"Feature extraction of the first difference of EMG time series for EMG pattern recognition","volume":"117","author":"Phinyomark","year":"2014","journal-title":"Comp. Meth. Prog. Biomed."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1109\/TBME.2019.2935182","article-title":"EMG-based real-time linear-nonlinear cascade regression decoding of shoulder, elbow, and wrist movements in able-bodied persons and stroke survivors","volume":"67","author":"Liu","year":"2020","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/10400435.1990.10132142","article-title":"Practical methods for controlling powered upper-extremity prostheses","volume":"2","year":"1990","journal-title":"Assist. Technol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1016\/j.jbiomech.2011.02.143","article-title":"Letter to the editor","volume":"44","author":"Hansson","year":"2011","journal-title":"J. Biomech."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Rajotte, K.J., Wang, H., Wang, H., Dai, C., Zhu, Z., Huang, X., and Clancy, E.A. (2020, January 20\u201324). Simplified optimal estimation of time-varying electromyogram standard deviation (EMG\u03c3). Proceedings of the 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montreal, QC, Canada.","DOI":"10.1109\/EMBC44109.2020.9175978"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1109\/10.764948","article-title":"Electromyogram amplitude estimation with adaptive smoothing window length","volume":"46","author":"Clancy","year":"1999","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1109\/TNSRE.2015.2405765","article-title":"Influence of joint angle on EMG-torque model during constant-posture, torque-varying contractions","volume":"23","author":"Liu","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1109\/10.341833","article-title":"Multiple site electromyograph amplitude estimation","volume":"42","author":"Clancy","year":"1995","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_47","unstructured":"Storn, R. (1996, January 20\u201322). Differential evolution design of an IIR-filter. Proceedings of the IEEE International Conference on Evolutionary Computation, Nagoya, Japan."},{"key":"ref_48","first-page":"1269","article-title":"Digital IIR filter design using differential evolution algorithm","volume":"8","author":"Karaboga","year":"2005","journal-title":"EURASIP J. Appl. Sig. Proc."},{"key":"ref_49","unstructured":"Wang, H. (2019). Advanced Electromyogram Signal Processing with an Emphasis on Simplified, Near-Optimal Whitening, Worcester Polytechnic Institute."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/TNSRE.2014.2331686","article-title":"Using the electromyogram to anticipate torques about the elbow","volume":"23","author":"Koirala","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1682\/JRRD.2011.10.0188","article-title":"Mechanical design and performance specifications of anthropomorphic prosthetic hands: A review","volume":"50","author":"Belter","year":"2013","journal-title":"J. Rehabil. Res. Devel."},{"key":"ref_52","first-page":"1637","article-title":"Response to letter to the editor","volume":"44","author":"Avin","year":"2011","journal-title":"J. Biomech."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/15\/5165\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:37:16Z","timestamp":1760164636000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/15\/5165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,30]]},"references-count":52,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["s21155165"],"URL":"https:\/\/doi.org\/10.3390\/s21155165","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,30]]}}}