{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T02:28:22Z","timestamp":1775096902790,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,6]],"date-time":"2018-04-06T00:00:00Z","timestamp":1522972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of education and science of Russia","award":["14.Y26.31.0022"],"award-info":[{"award-number":["14.Y26.31.0022"]}]},{"name":"Spanish Ministry of Economy and Competitiveness","award":["FIS2017-82900-P"],"award-info":[{"award-number":["FIS2017-82900-P"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recent advances in recording and real-time analysis of surface electromyographic signals (sEMG) have fostered the use of sEMG human\u2013machine interfaces for controlling personal computers, prostheses of upper limbs, and exoskeletons among others. Despite a relatively high mean performance, sEMG-interfaces still exhibit strong variance in the fidelity of gesture recognition among different users. Here, we systematically study the latent factors determining the performance of sEMG-interfaces in synthetic tests and in an arcade game. We show that the degree of muscle cooperation and the amount of the body fatty tissue are the decisive factors in synthetic tests. Our data suggest that these factors can only be adjusted by long-term training, which promotes fine-tuning of low-level neural circuits driving the muscles. Short-term training has no effect on synthetic tests, but significantly increases the game scoring. This implies that it works at a higher decision-making level, not relevant for synthetic gestures. We propose a procedure that enables quantification of the gestures\u2019 fidelity in a dynamic gaming environment. For each individual subject, the approach allows identifying \u201cproblematic\u201d gestures that decrease gaming performance. This information can be used for optimizing the training strategy and for adapting the signal processing algorithms to individual users, which could be a way for a qualitative leap in the development of future sEMG-interfaces.<\/jats:p>","DOI":"10.3390\/s18041122","type":"journal-article","created":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T13:06:08Z","timestamp":1523365568000},"page":"1122","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Latent Factors Limiting the Performance of sEMG-Interfaces"],"prefix":"10.3390","volume":"18","author":[{"given":"Sergey","family":"Lobov","sequence":"first","affiliation":[{"name":"Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, 603950 Nizhny Novgorod, Russia"}]},{"given":"Nadia","family":"Krilova","sequence":"additional","affiliation":[{"name":"Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, 603950 Nizhny Novgorod, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6050-4356","authenticated-orcid":false,"given":"Innokentiy","family":"Kastalskiy","sequence":"additional","affiliation":[{"name":"Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, 603950 Nizhny Novgorod, Russia"}]},{"given":"Victor","family":"Kazantsev","sequence":"additional","affiliation":[{"name":"Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, 603950 Nizhny Novgorod, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8789-7532","authenticated-orcid":false,"given":"Valeri","family":"Makarov","sequence":"additional","affiliation":[{"name":"Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, 603950 Nizhny Novgorod, Russia"},{"name":"Department of Applied Mathematics, Instituto de Matem\u00e1tica Interdisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,6]]},"reference":[{"key":"ref_1","unstructured":"Basmajian, J.V., and De Luca, C.J. (1985). Muscles Alive: Their Functions Revealed by Electromyography, Williams & Wilkins."},{"key":"ref_2","first-page":"5","article-title":"Electromyogram recording, processing, and normalization: Procedures and considerations","volume":"1","author":"Winter","year":"1991","journal-title":"J. Hum. Muscle Perform"},{"key":"ref_3","first-page":"61","article-title":"Considerations for the use of surface electromyography","volume":"11","author":"Bishop","year":"2004","journal-title":"Phys. Theor. Korea"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1212\/WNL.55.2.171","article-title":"Clinical utility of surface EMG. Report of the therapeutics and technology assessment subcommittee of the American Academy of Neurology","volume":"55","author":"Pullman","year":"2000","journal-title":"Neurology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1152\/japplphysiol.zdg-8232-pcpcomm.2008","article-title":"Spectral properties of the surface EMG can characterize motor unit recruitment strategies","volume":"105","author":"Wakeling","year":"2008","journal-title":"J. Appl. Physiol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gopura, R.A.R.C., Kiguchi, K., and Li, Y. (2009, January 10\u201315). SUEFUL-7: A 7DOF upper-limb exoskeleton robot with muscle-model-oriented EMG-based control. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5353935"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TSMCB.2012.2185843","article-title":"An EMG-based control for an upper-limb power-assist exoskeleton robot","volume":"42","author":"Kiguchi","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"ref_8","unstructured":"(2016, May 26). MyoTM Gesture Control Armband\u2014Wearable Technology by Thalmic Labs. Available online: www.myo.com."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"27894","DOI":"10.3390\/s151127894","article-title":"A spiking neural network in sEMG feature extraction","volume":"15","author":"Lobov","year":"2015","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chakrabarti, A., and Prakash, R.V. (2013). Muscle computer interface: A review. ICoRD\u201913, Lect. Notes Mechan. Eng., Springer.","DOI":"10.1007\/978-81-322-1050-4"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/s40137-013-0044-8","article-title":"Prosthetic myoelectric control strategies: A clinical perspective","volume":"2","author":"Roche","year":"2014","journal-title":"Curr. Surg. Rep."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1109\/TNSRE.2014.2305520","article-title":"Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control","volume":"22","author":"Hahne","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1152\/jn.01128.2011","article-title":"Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton","volume":"109","author":"Gordon","year":"2013","journal-title":"J. Neurophysiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1007\/978-3-319-26561-2_51","article-title":"Myoelectric control system of lower limb exoskeleton for re-training motion deficiencies","volume":"9492","author":"Mironov","year":"2015","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1682\/JRRD.2010.08.0161","article-title":"Myoelectric forearm prostheses: State of the art from a user-centered perspective","volume":"48","author":"Peerdeman","year":"2011","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1109\/TBME.2006.883695","article-title":"A real-time EMG pattern recognition system based on linear-nonlinear feature projection for a multifunction myoelectric hand","volume":"53","author":"Chu","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"435","DOI":"10.4028\/www.scientific.net\/AMR.701.435","article-title":"Analysis of surface electromyography for on-off control","volume":"701","author":"Chan","year":"2013","journal-title":"Adv. Mater. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1109\/TBME.2003.813539","article-title":"A robust, real-time control scheme for multifunction myoelectric control","volume":"50","author":"Englehart","year":"2003","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1109\/TBME.2004.828048","article-title":"Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals","volume":"51","author":"Farina","year":"2004","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1109\/TBME.2005.856295","article-title":"A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses","volume":"52","author":"Huang","year":"2005","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1109\/TBME.2006.870220","article-title":"Fatigue estimation with a multivariable myoelectric mapping function","volume":"53","author":"MacIsaac","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kiguchi, K., Imada, Y., and Liyanage, M. (2007, January 22\u201326). EMG-based neuro-fuzzy control of a 4DOF upper-limb power-assist exoskeleton. Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France.","DOI":"10.1109\/IEMBS.2007.4352969"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1109\/TBME.2007.909536","article-title":"Online electromyographic control of a robotic prosthesis","volume":"55","author":"Shenoy","year":"2008","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/1743-0003-8-25","article-title":"Influence of the training set on the accuracy of surface EMG classification in dynamic contractions for the control of multifunction prostheses","volume":"8","author":"Lorrain","year":"2011","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1109\/TNSRE.2012.2196711","article-title":"Control of upper limb prostheses: Terminology and proportional myoelectric control\u2014A review","volume":"20","author":"Fougner","year":"2012","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1186\/1743-0003-11-91","article-title":"A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts\u2019 law style assessment procedure","volume":"11","author":"Wurth","year":"2014","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"58","DOI":"10.3389\/fnins.2016.00058","article-title":"Dual window pattern recognition classifier for improved partial-hand prosthesis control","volume":"10","author":"Earley","year":"2016","journal-title":"Front. Neurosci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"114","DOI":"10.3389\/fnins.2016.00114","article-title":"A novel percutaneous electrode implant for improving robustness in advanced myoelectric control","volume":"10","author":"Hahne","year":"2016","journal-title":"Front. Neurosci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1186\/1743-0003-9-42","article-title":"EMG-based simultaneous and proportional estimation of wrist\/hand kinematics in uni-lateral trans-radial amputees","volume":"9","author":"Jiang","year":"2012","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1109\/TBME.2006.889192","article-title":"A comparison of surface and intramuscular myoelectric signal classification","volume":"54","author":"Hargrove","year":"2007","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_31","first-page":"30","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 Arch."},{"key":"ref_32","unstructured":"Mann, P.S. (2006). Introductory Statistics, John Wiley and Sons."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Rumelhart, D.E., Hinton, G.E., and Williams, R.J. (1985). Learning internal representations by error propagation. Parallel Distributed Processing, California Univ.","DOI":"10.21236\/ADA164453"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1109\/TNSRE.2007.910282","article-title":"An analysis of EMG electrode configuration for targeted muscle reinnervation based neural machine interface","volume":"16","author":"Huang","year":"2008","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_35","first-page":"30","article-title":"Combined use of command-proportional control of external robotic devices based on electromyography signals","volume":"7","author":"Lobov","year":"2015","journal-title":"Mod. Technol. Med."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lobov, S., Krilova, N., Kastalskiy, I., Kazantsev, V., and Makarov, V.A. (2016, January 7\u20138). Human-computer interface based on electromyography command-proportional control. Proceedings of the 4th International Congress on Neurotechnology, Electronics and Informatics, Porto, Portugal.","DOI":"10.5220\/0006033300570064"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sammut, C., and Webb, G.I. (2010). Encyclopedia of Machine Learning, Springer.","DOI":"10.1007\/978-0-387-30164-8"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"6884","DOI":"10.1073\/pnas.1016507108","article-title":"How simple rules determine pedestrian behaviour and crowd disasters","volume":"108","author":"Moussaid","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s00422-015-0644-8","article-title":"Prediction-for-CompAction: Navigation in social environments using generalized cognitive maps","volume":"109","author":"Calvo","year":"2015","journal-title":"Biol. Cybern."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1650012","DOI":"10.1142\/S0219525916500120","article-title":"Waves in isotropic totalistic cellular automata: Application to real-time robot navigation","volume":"19","author":"Calvo","year":"2016","journal-title":"Adv. Complex Syst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1007\/s10827-009-0206-y","article-title":"Disentanglement of local field potential sources by independent component analysis","volume":"29","author":"Makarov","year":"2010","journal-title":"J. Comput. Neurosci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.neuroscience.2015.09.054","article-title":"New uses of LFPs: Pathway-specific threads obtained through spatial discrimination","volume":"310","author":"Herreras","year":"2015","journal-title":"Neuroscience"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"e16658","DOI":"10.7554\/eLife.16658","article-title":"The right hippocampus leads the bilateral integration of gamma-parsed lateralized information","volume":"5","author":"Benito","year":"2016","journal-title":"eLife"},{"key":"ref_44","first-page":"53","article-title":"An electromyographic study on the development of optimal tactics of botulinum toxin type a injections in children with spastic forms of cerebral palsy","volume":"113","author":"Kurenkov","year":"2013","journal-title":"Zhurnal Nevrologii i Psihiatrii"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2205","DOI":"10.1109\/TBME.2013.2250502","article-title":"Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface","volume":"60","author":"Matsubara","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Tyukin, I., Gorban, A.N., Calvo, C., Makarova, J., and Makarov, V.A. (2018). High-dimensional brain: A tool for encoding and rapid learning of memories by single neurons. Bull. Math. Biol.","DOI":"10.1007\/s11538-018-0415-5"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"10895","DOI":"10.3390\/s140610895","article-title":"The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases","volume":"14","author":"Khalil","year":"2014","journal-title":"Sensors"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"S116","DOI":"10.4100\/jhse.2012.7.Proc1.13","article-title":"The neurofeedback successfulness of sportsmen","volume":"7","author":"Cherapkina","year":"2012","journal-title":"J. Hum. Sport Exerc."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.neuroscience.2017.07.059","article-title":"Exercise-related cognitive effects on sensory-motor control in athletes and drummers compared to non-athletes and other musicians","volume":"360","author":"Bianco","year":"2017","journal-title":"Neuroscience"},{"key":"ref_50","first-page":"414","article-title":"Motor imagery based brain computer interface with vibrotactile interaction","volume":"67","author":"Liburkina","year":"2017","journal-title":"Zhurnal vysshey nervnoy deyatel\u2019nosti im. I.P. Pavlova"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1122\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:59:51Z","timestamp":1760194791000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1122"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,6]]},"references-count":50,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["s18041122"],"URL":"https:\/\/doi.org\/10.3390\/s18041122","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201804.0044.v1","asserted-by":"object"}]},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,6]]}}}