{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:00:32Z","timestamp":1775743232471,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"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>Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics.<\/jats:p>","DOI":"10.3390\/s21217186","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:24:22Z","timestamp":1635805462000},"page":"7186","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0620-594X","authenticated-orcid":false,"given":"Samanta","family":"Rosati","sequence":"first","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7626-1563","authenticated-orcid":false,"given":"Marco","family":"Ghislieri","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0004-0243","authenticated-orcid":false,"given":"Gregorio","family":"Dotti","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7856-9518","authenticated-orcid":false,"given":"Daniele","family":"Fortunato","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5887-1499","authenticated-orcid":false,"given":"Valentina","family":"Agostini","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5396-5103","authenticated-orcid":false,"given":"Marco","family":"Knaflitz","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2717-648X","authenticated-orcid":false,"given":"Gabriella","family":"Balestra","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.gaitpost.2011.03.027","article-title":"Efficacy of clinical gait analysis: A systematic review","volume":"34","author":"Wren","year":"2011","journal-title":"Gait Posture"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2255","DOI":"10.3390\/s120202255","article-title":"Gait Analysis Using Wearable Sensors","volume":"12","author":"Tao","year":"2012","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1097\/01.bpo.0000229970.55694.5c","article-title":"Effectiveness of Instrumented Gait Analysis in Children with Cerebral Palsy\u2014Comparison of Outcomes","volume":"26","author":"Chang","year":"2006","journal-title":"J. Pediatr. Orthop."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1123\/jab.13.2.135","article-title":"The Use of Surface Electromyography in Biomechanics","volume":"13","year":"1997","journal-title":"J. Appl. Biomech."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0966-6362(03)00005-5","article-title":"Surface electromyography analysis for variable gait","volume":"18","author":"Roetenberg","year":"2003","journal-title":"Gait Posture"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Frigo, C., and Crenna, P. (2009). Multichannel SEMG in Clinical Gait Analysis: A Review and State-of-the-Art, Elsevier.","DOI":"10.1016\/j.clinbiomech.2008.07.012"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.3389\/fneur.2020.573616","article-title":"A Survey on the Use and Barriers of Surface Electromyography in Neurorehabilitation","volume":"11","author":"Manca","year":"2020","journal-title":"Front. Neurol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Agostini, V., Rosati, S., Castagneri, C., Balestra, G., and Knaflitz, M. (2017, January 22\u201325). Clustering analysis of EMG cyclic patterns: A validation study across multiple locomotion pathologies. Proceedings of the 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Turin, Italy.","DOI":"10.1109\/I2MTC.2017.7969746"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.bspc.2016.09.017","article-title":"Muscle activation patterns during gait: A hierarchical clustering analysis","volume":"31","author":"Rosati","year":"2017","journal-title":"Biomed. Signal. Process. Control."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Rosati, S., Castagneri, C., Agostini, V., Knaflitz, M., and Balestra, G. (2017). Muscle contractions in cyclic movements: Optimization of CIMAP algorithm. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, 58\u201361.","DOI":"10.1109\/EMBC.2017.8036762"},{"key":"ref_11","first-page":"3337","article-title":"Gait impairment score: A fuzzy logic-based index for gait assessment","volume":"12","author":"Rosati","year":"2017","journal-title":"Int. J. Appl. Eng. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1109\/TNSRE.2019.2903687","article-title":"Asymmetry Index in Muscle Activations","volume":"27","author":"Castagneri","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1109\/TNSRE.2013.2291907","article-title":"Segmentation and classification of gait cycles","volume":"22","author":"Agostini","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1109\/10.661154","article-title":"A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait","volume":"45","author":"Bonato","year":"1998","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Agostini, V., Knaflitz, M., Nascimberi, A., and Gaffuri, A. (2014, January 11\u201312). Gait measurements in hemiplegic children: An automatic analysis of foot-floor contact sequences and electromyographic patterns. Proceedings of the IEEE MeMeA 2014\u2014IEEE International Symposium on Medical Measurements and Applications, Lisboa, Portugal.","DOI":"10.1109\/MeMeA.2014.6860061"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1016\/j.clinbiomech.2015.07.010","article-title":"Multiple gait patterns within the same Winters class in children with hemiplegic cerebral palsy","volume":"30","author":"Agostini","year":"2015","journal-title":"Clin. Biomech."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.jelekin.2015.07.004","article-title":"Assessment of the variability of vastii myoelectric activity in young healthy females during walking: A statistical gait analysis","volume":"25","author":"Maranesi","year":"2015","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1428","DOI":"10.1016\/j.jelekin.2013.05.011","article-title":"Assessment of the activation modalities of gastrocnemius lateralis and tibialis anterior during gait: A statistical analysis","volume":"23","author":"Ghetti","year":"2013","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.jelekin.2012.06.011","article-title":"Statistical analysis of surface electromyographic signal for the assessment of rectus femoris modalities of activation during gait","volume":"23","author":"Fioretti","year":"2013","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1186\/1743-0003-9-64","article-title":"Self-reported gait unsteadiness in mildly impaired neurological patients: An objective assessment through statistical gait analysis","volume":"9","author":"Benedetti","year":"2012","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.gaitpost.2010.06.024","article-title":"Normative EMG activation patterns of school-age children during gait","volume":"32","author":"Agostini","year":"2010","journal-title":"Gait Posture"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/0013-4694(87)90003-4","article-title":"EMG profiles during normal human walking: Stride-to-stride and inter-subject variability","volume":"67","author":"Winter","year":"1987","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_23","first-page":"1525","article-title":"How to Improve Robustness in Muscle Synergy Extraction","volume":"2019","author":"Ghislieri","year":"2019","journal-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1109\/TNSRE.2020.2965179","article-title":"Muscle Synergies Extracted Using Principal Activations: Improvement of Robustness and Interpretability","volume":"28","author":"Ghislieri","year":"2020","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Mazzetta, I., Zampogna, A., Suppa, A., Gumiero, A., Pessione, M., and Irrera, F. (2019). Wearable Sensors System for an Improved Analysis of Freezing of Gait in Parkinson\u2019s Disease Using Electromyography and Inertial Signals. Sensors, 19.","DOI":"10.3390\/s19040948"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, M., Villagra, F., Castellote, J.M., and Pastor, M.A. (2018). Kinematic and kinetic patterns related to free-walking in parkinson\u2019s disease. Sensors, 18.","DOI":"10.3390\/s18124224"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Khoury, N., Attal, F., Amirat, Y., Oukhellou, L., and Mohammed, S. (2019). Data-driven based approach to aid Parkinson\u2019s disease diagnosis. Sensors, 19.","DOI":"10.3390\/s19020242"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1109\/TITB.2009.2022927","article-title":"Automatic Recognition of Gait Patterns Exhibiting Patellofemoral Pain Syndrome Using a Support Vector Machine Approach","volume":"13","author":"Lai","year":"2009","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Alaqtash, M., Sarkodie-Gyan, T., Yu, H., Fuentes, O., Brower, R., and Abdelgawad, A. (September, January 30). Automatic classification of pathological gait patterns using ground reaction forces and machine learning algorithms. Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, USA.","DOI":"10.1109\/IEMBS.2011.6090063"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2479","DOI":"10.1109\/TBME.2006.883697","article-title":"Support Vector Machines and Other Pattern Recognition Approaches to the Diagnosis of Cerebral Palsy Gait","volume":"53","author":"Kamruzzaman","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1016\/j.patcog.2008.09.025","article-title":"Gait classification in children with cerebral palsy by Bayesian approach","volume":"42","author":"Zhang","year":"2009","journal-title":"Pattern Recognit."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1109\/TNSRE.2018.2811415","article-title":"Simultaneous Recognition and Assessment of Post-Stroke Hemiparetic Gait by Fusing Kinematic, Kinetic, and Electrophysiological Data","volume":"26","author":"Cui","year":"2018","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2488","DOI":"10.1109\/TNSRE.2020.3028203","article-title":"Automatic diagnosis of cerebral palsy gait using computational intelligence techniques: A low-cost multi-sensor approach","volume":"28","author":"Chakraborty","year":"2020","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.gaitpost.2008.05.001","article-title":"The gait deviation index: A new comprehensive index of gait pathology","volume":"28","author":"Schwartz","year":"2008","journal-title":"Gait Posture"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0966-6362(99)00047-8","article-title":"An index for quantifying deviations from normal gait","volume":"11","author":"Schutte","year":"2000","journal-title":"Gait Posture"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.gaitpost.2009.05.020","article-title":"The Gait Profile Score and Movement Analysis Profile","volume":"30","author":"Baker","year":"2009","journal-title":"Gait Posture"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Kugler, P., Jaremenko, C., Schlachetzki, J., Winkler, J., Klucken, J., and Eskofier, B. (2013, January 3\u20137). Automatic recognition of Parkinson\u2019s disease using surface electromyography during standardized gait tests. Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan.","DOI":"10.1109\/EMBC.2013.6610865"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.jneumeth.2011.04.030","article-title":"Quantification of dynamic EMG patterns during gait in children with cerebral palsy","volume":"198","author":"Bojanic","year":"2011","journal-title":"J. Neurosci. Methods"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Infarinato, F., Romano, P., Goffredo, M., Ottaviani, M., Galafate, D., Gison, A., Petruccelli, S., Pournajaf, S., and Franceschini, M. (2021). Functional Gait Recovery after a Combination of Conventional Therapy and Overground Robot-Assisted Gait Training Is Not Associated with Significant Changes in Muscle Activation Pattern: An EMG Preliminary Study on Subjects Subacute Post Stroke. Brain Sci., 11.","DOI":"10.3390\/brainsci11040448"},{"key":"ref_40","first-page":"835","article-title":"Computer algorithms to characterize individual subject EMG profiles during gait","volume":"73","author":"Bogey","year":"1992","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_41","first-page":"99","article-title":"Statistical gait analysis","volume":"Volume II","author":"Agostini","year":"2012","journal-title":"Distributed Diagnosis and Home Healthcare (D2H2)"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1016\/j.arth.2013.12.018","article-title":"Gait parameters and muscle activation patterns at 3, 6 and 12 months after total hip arthroplasty","volume":"29","author":"Agostini","year":"2014","journal-title":"J. Arthroplast."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/21\/7186\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:22:25Z","timestamp":1760167345000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/21\/7186"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,29]]},"references-count":42,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21217186"],"URL":"https:\/\/doi.org\/10.3390\/s21217186","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,29]]}}}