{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T08:29:58Z","timestamp":1767774598573,"version":"build-2238731810"},"reference-count":37,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2014,5,7]],"date-time":"2014-05-07T00:00:00Z","timestamp":1399420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Sensors"],"abstract":"<jats:p>Surface electromyography (sEMG) is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the system is 1,000 Hz. Since real measured EMG signals are usually corrupted by various types of noises (motion artifacts, white noise and electromagnetic noise present at 50 Hz and higher harmonics), we have tested several denoising techniques, both on artificial and measured EMG signals. Results showed that a wavelet\u2014based technique implementing Daubechies5 wavelet and soft sqtwolog thresholding is the most appropriate for EMG signals denoising. To test the system performance, EMG activities of six dominant muscles of ten healthy subjects during gait were measured (gluteus maximus, biceps femoris, sartorius, rectus femoris, tibialis anterior and medial gastrocnemius). The obtained EMG envelopes presented against the duration of gait cycle were compared favourably with the EMG data available in the literature, suggesting that the proposed system is suitable for a wide range of applications in biomechanics.<\/jats:p>","DOI":"10.3390\/s140508235","type":"journal-article","created":{"date-parts":[[2014,5,7]],"date-time":"2014-05-07T10:41:54Z","timestamp":1399459314000},"page":"8235-8258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Design, Development and Testing of a Low-Cost sEMG System and Its Use in Recording Muscle Activity in Human Gait"],"prefix":"10.3390","volume":"14","author":[{"given":"Tamara","family":"Supuk","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,  Laboratory of Biomechanics and Automatic Control Systems, R. Boskovica 32, Split 21000, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana","family":"Skelin","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,  Laboratory of Biomechanics and Automatic Control Systems, R. Boskovica 32, Split 21000, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maja","family":"Cic","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,  Laboratory of Biomechanics and Automatic Control Systems, R. 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Image Underst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2776","DOI":"10.1016\/j.jbiomech.2008.06.024","article-title":"Systematic accuracy and precision analysis of video motion capturing systems-exemplified on the Vicon-460 system","volume":"41","author":"Windolf","year":"2008","journal-title":"J. Biomech."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1016\/j.jbiomech.2006.01.017","article-title":"Accuracy of an optical active-marker system to track the relative motion of rigid bodies","volume":"40","author":"Maletsky","year":"2007","journal-title":"J. Biomech."},{"key":"ref_6","unstructured":"Motion Lab Systems, Inc. Available online: http:\/\/www.motion-labs.com\/."},{"key":"ref_7","unstructured":"BTS Bioengineering. Available online: http:\/\/www.btsbioengineering.com\/products\/surface-emg\/."},{"key":"ref_8","unstructured":"Delsys. Available online: https:\/\/www.delsys.com\/index.html."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"12431","DOI":"10.3390\/s130912431","article-title":"Surface electromyography signal processing and classification techniques","volume":"13","author":"Chowdhury","year":"2013","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/RBME.2012.2183586","article-title":"Accessing the neural drive to muscle and translation to neurorehabilitation technologies","volume":"5","author":"Farina","year":"2012","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"11100","DOI":"10.3390\/s101211100","article-title":"Man-machine interface system for neuromuscular training and evaluation based on EMG and MMG signals","volume":"10","author":"Alonso","year":"2010","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Naik, G.R. (2012). EMG decomposition and artefact removal. Computational Intelligence in Electromyography Analysis\u2014A Perspective on Current Applications and Future Challenges, InTech.","DOI":"10.5772\/3315"},{"key":"ref_13","unstructured":"Surface electromyography: Detection and recording. Available online: http:\/\/www.delsys.com\/Attachments_pdf\/WP_SEMGintro.pdf."},{"key":"ref_14","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_15","doi-asserted-by":"crossref","unstructured":"Malboubi, M., Razzazi, F., and Aliyari, S.M. (2010, January 7\u201310). Elimination of power line noise from EMG signals using an efficient adaptive laguerre Filter. Gliwice, Poland.","DOI":"10.1109\/ICBME.2010.5704932"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1055\/s-0038-1633419","article-title":"Surface EMG crosstalk evaluated from experimental recordings and simulated signals. Reflections on crosstalk interpretation, quantification and reduction","volume":"43","author":"Farina","year":"2004","journal-title":"Methods Inf. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1016\/j.medengphy.2009.09.005","article-title":"A method to estimate EMG crosstalk between two muscles based on the silent period following an H-reflex","volume":"31","author":"Mezzarane","year":"2009","journal-title":"Med. Eng. Phys."},{"key":"ref_18","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_19","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/S1050-6411(98)00023-6","article-title":"Optimal rejection of movement artefacts from myoelectric signals by means of a wavelet filtering procedure","volume":"9","author":"Conforto","year":"1999","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.bspc.2006.03.003","article-title":"EMG signal filtering based on empirical mode decomposition","volume":"1","author":"Andrade","year":"2006","journal-title":"Biomed. Signal Process Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1016\/j.ins.2007.12.013","article-title":"The application of the hilbert spectrum to the analysis of electromyographic signals","volume":"178","author":"Andrade","year":"2008","journal-title":"Inf. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"13123","DOI":"10.3390\/s131013123","article-title":"Programmable gain amplifiers with DC suppression and low output offset for bioelectric sensors","volume":"13","author":"Carrera","year":"2013","journal-title":"Sensors"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/BF02512527","article-title":"Amplifiers for bioelectric events: A design with a minimal number of parts","volume":"32","author":"MettingVanRijn","year":"1994","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1049\/iet-smt.2012.0157","article-title":"Design, development, and evaluation of optical motion-tracking system based on active white light markers","volume":"7","author":"Panjkota","year":"2013","journal-title":"IET Sci. Meas. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1016\/j.measurement.2012.09.010","article-title":"Improved structured light 3D scanner with application to anthropometric parameter estimation","volume":"46","author":"Zanchi","year":"2013","journal-title":"Measurement"},{"key":"ref_26","unstructured":"AD621 data sheet. Available online: http:\/\/www.analog.com\/static\/imported-files\/data_sheets\/AD621.pdf."},{"key":"ref_27","unstructured":"OP07 data sheet. Available online: http:\/\/www.analog.com\/static\/imported-files\/data_sheets\/OP07.pdf."},{"key":"ref_28","unstructured":"NI 6034E data sheet. Available online: http:\/\/sites.fas.harvard.edu\/\u223cphys191r\/Bench_Notes\/A7\/6034e.pdf."},{"key":"ref_29","unstructured":"Winter, D.A. (1991). Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological, University of Waterloo Press. [2nd ed.]."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Strang, G., and Nguyen, T. (1996). Wavelets and Filter Banks, Wellesley Cambridge Press.","DOI":"10.1093\/oso\/9780195094237.003.0002"},{"key":"ref_31","unstructured":"Polikar, R. The Wavelet Tutorial, 1996. Available online: http:\/\/users.rowan.edu\/\u223cpolikar\/WAVELETS\/WTtutorial.html."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/18.382009","article-title":"De-noising by Soft-Thresholding","volume":"41","author":"Donoho","year":"1995","journal-title":"IEEE Trans. Inf Theory"},{"key":"ref_33","unstructured":"Donoho, D.L., and Johnstone, I.M. (1994). Ideal Denoising in An Orthonormal Basis Chosen from A Library of Bases, Department of Statistics, Stanford University. Technical Report 461."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1109\/10.764945","article-title":"Decomposition of multiunit electromyographic signals","volume":"46","author":"Fang","year":"1999","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_35","unstructured":"Misiti, M., Misiti, Y., Oppenheim, G., and Poggi, J.M. (2004). Wavelet Toolbox User's Guide, The Mathworks, Inc. [3rd ed.]."},{"key":"ref_36","unstructured":"Vaughan, C.L., Davis, B.L., and O'Connor, J.C. (1992). Dynamics of Human Gait, Kiboho Publishers. [2nd ed.]."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"489","DOI":"10.3390\/s120100489","article-title":"A wireless sEMG recording system and its application to muscle fatigue detection","volume":"12","author":"Chang","year":"2012","journal-title":"Sensors"}],"updated-by":[{"DOI":"10.3390\/s140815639","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2014,5,7]],"date-time":"2014-05-07T00:00:00Z","timestamp":1399420800000}}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/5\/8235\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,4]],"date-time":"2025-08-04T07:49:18Z","timestamp":1754293758000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/5\/8235"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,5,7]]},"references-count":37,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2014,5]]}},"alternative-id":["s140508235"],"URL":"https:\/\/doi.org\/10.3390\/s140508235","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,5,7]]}}}