{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T16:11:07Z","timestamp":1771517467556,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T00:00:00Z","timestamp":1655596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China Scholarship Council (CSC)","award":["[2018]3101"],"award-info":[{"award-number":["[2018]3101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To give people more specific information on the quality of their daily motion, it is necessary to continuously measure muscular activity during everyday occupations in an easy way. The traditional methods to measure muscle activity using a combination of surface electromyography (sEMG) sensors and optical motion capture system are expensive and not suitable for non-technical users and unstructured environment. For this reason, in our group we are researching methods to estimate leg muscle activity using non-contact wearable sensors, improving ease of movement and system usability. In a previous study, we developed a method to estimate muscle activity via only a single inertial measurement unit (IMU) on the shank. In this study, we describe a method to estimate muscle activity during walking via two IMU sensors, using an original sensing system and specifically developed estimation algorithms based on ANN techniques. The muscle activity estimation results, estimated by the proposed algorithm after optimization, showed a relatively high estimation accuracy with a correlation efficient of R2 = 0.48 and a standard deviation STD = 0.10, with a total system average delay of 192 ms. As the average interval between different gait phases in human gait is 250\u20131000 ms, a 192 ms delay is still acceptable for daily walking requirements. For this reason, compared with the previous study, the newly proposed system presents a higher accuracy and is better suitable for real-time leg muscle activity estimation during walking.<\/jats:p>","DOI":"10.3390\/s22124632","type":"journal-article","created":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T21:19:26Z","timestamp":1655673566000},"page":"4632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Development of a Non-Contacting Muscular Activity Measurement System for Evaluating Knee Extensors Training in Real-Time"],"prefix":"10.3390","volume":"22","author":[{"given":"Zixi","family":"Gu","sequence":"first","affiliation":[{"name":"Faculty of Science and Engineering, Waseda University, Tokyo 1690051, Japan"}]},{"given":"Shengxu","family":"Liu","sequence":"additional","affiliation":[{"name":"Faculty of Science and Engineering, Waseda University, Tokyo 1690051, Japan"}]},{"given":"Sarah","family":"Cosentino","sequence":"additional","affiliation":[{"name":"Faculty of Science and Engineering, Waseda University, Tokyo 1690051, Japan"},{"name":"Department of Modern Mechanical Engineering, Waseda University, Tokyo 1690051, Japan"}]},{"given":"Atsuo","family":"Takanishi","sequence":"additional","affiliation":[{"name":"Faculty of Science and Engineering, Waseda University, Tokyo 1690051, Japan"},{"name":"Department of Modern Mechanical Engineering, Waseda University, Tokyo 1690051, Japan"},{"name":"Humanoid Robotics Institute, Waseda University, Tokyo 1690051, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1111\/j.1532-5415.2007.01087.x","article-title":"Knee Extension Strength Cutpoints for Maintaining Mobility","volume":"55","author":"Manini","year":"2007","journal-title":"J. Am. Geriatr. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Casa\u00f1a, J., Calatayud, J., Silvestre, A., S\u00e1nchez-Frutos, J., Andersen, L.L., Jakobsen, M.D., Ezzatvar, Y., and Alakhdar, Y. (2021). Knee Extensor Muscle Strength Is More Important Than Postural Balance for Stair-Climbing Ability in Elderly Patients with Severe Knee Osteoarthritis. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18073637"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"229","DOI":"10.3138\/ptc.2012-04","article-title":"The Relationship of Knee-Extensor Strength and Rate of Torque Development to Sit-to-Stand Performance in Older Adults","volume":"65","author":"Crockett","year":"2013","journal-title":"Physiother. Can."},{"key":"ref_4","unstructured":"Schons, P., Fischer, G., da Rosa, R.G., Berriel, G.P., and Peyr\u00e9-Tartaruga, L.A. (2018). Correlations between the Strength of Knee Extensor and Flexor Muscles and Jump Performance in Volleyball Players: A Review. J. Phys. Educ., 29."},{"key":"ref_5","first-page":"1502","article-title":"Assessment of Isokinetic Knee Strength in Elite Young Female Basketball Players: Correlation with Vertical Jump","volume":"55","author":"Rouis","year":"2015","journal-title":"J Sports Med Phys Fit."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1088\/0967-3334\/33\/11\/1769","article-title":"Device-Based Monitoring in Physical Activity and Public Health Research","volume":"33","author":"Bassett","year":"2012","journal-title":"Physiol. Meas."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1016\/j.procs.2021.01.083","article-title":"A Review of Wearable Internet-of-Things Device for Healthcare","volume":"179","author":"Surantha","year":"2021","journal-title":"Procedia Comput. Sci."},{"key":"ref_8","first-page":"9","article-title":"Wearable Sensors for Monitoring Human Motion: A Review on Mechanisms, Materials, and Challenges","volume":"25","author":"Homayounfar","year":"2020","journal-title":"SLAS Technol. Transl. Life Sci. Innov."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Channa, A., Popescu, N., Skibinska, J., and Burget, R. (2021). The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review. Sensors, 21.","DOI":"10.3390\/s21175787"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"102074","DOI":"10.1016\/j.bspc.2020.102074","article-title":"A Review of the Key Technologies for SEMG-Based Human-Robot Interaction Systems","volume":"62","author":"Li","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.neucom.2011.05.033","article-title":"SEMG-Based Continuous Estimation of Joint Angles of Human Legs by Using BP Neural Network","volume":"78","author":"Zhang","year":"2012","journal-title":"Neurocomputing"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8235","DOI":"10.3390\/s140508235","article-title":"Design, Development and Testing of a Low-Cost SEMG System and Its Use in Recording Muscle Activity in Human Gait","volume":"14","author":"Supuk","year":"2014","journal-title":"Sensors"},{"key":"ref_13","unstructured":"Knutson, L.M., and Soderberg, G.L. (1995). EMG: Use and Interpretation in Gait. Gait Analysis Theory and Application, Mosby."},{"key":"ref_14","first-page":"77","article-title":"Kinesiological Use of the Surface EMG Signals","volume":"1","author":"Frigo","year":"1996","journal-title":"Eur. Act. Surf. Electromyogr. SENIAM"},{"key":"ref_15","unstructured":"Roberto, M., and Philip, P. (2004). Applications in Movement and Gait Analysis. Electromyography: Physiology, Engineering, and Noninvasive Applications, John Wiley & Sons, Inc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"125","DOI":"10.4103\/0974-8237.161594","article-title":"Scoliosis Curve Analysis with Milwaukee Orthosis Based on Open SIMM Modeling","volume":"6","author":"Karimi","year":"2015","journal-title":"J. Craniovertebral Junction Spine"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kong, W., Lin, J.-Y., Waaning, L., Sessa, S., Cosentino, S., Magistro, D., Zecca, M., Kawashima, R., and Takanishi, A. (2016, January 3\u20137). Comparison of Gait Event Detection from Shanks and Feet in Single-Task and Multi-Task Walking of Healthy Older Adults. Proceedings of the 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), Qingdao, China.","DOI":"10.1109\/ROBIO.2016.7866633"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kong, W., Sessa, S., Cosentino, S., Zecca, M., Saito, K., Wang, C., Imtiaz, U., Lin, Z., Bartolomeo, L., and Ishii, H. (2013, January 12\u201314). Development of a real-time IMU-Based Motion Capture System For Gait Rehabilitation. Proceedings of the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, China.","DOI":"10.1109\/ROBIO.2013.6739779"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Sessa, S., Saito, K., Zecca, M., Bartolomeo, L., Lin, Z., Cosentino, S., Ishii, H., Ikai, T., and Takanishi, A. (2013, January 4\u20137). Walking Assessment in the Phase Space by Using Ultra-Miniaturized Inertial Measurement Units. Proceedings of the 2013 IEEE International Conference on Mechatronics and Automation, Takamatsu, Japan.","DOI":"10.1109\/ICMA.2013.6618035"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.medengphy.2015.11.009","article-title":"Validity of an Inertial Measurement Unit to Assess Pelvic Orientation Angles during Gait, Sit\u2013Stand Transfers and Step-up Transfers: Comparison with an Optoelectronic Motion Capture System","volume":"38","author":"Bolink","year":"2016","journal-title":"Med. Eng. Phys."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1080\/03091902.2019.1609610","article-title":"Methodology of Surface Electromyography in Gait Analysis: Review of the Literature","volume":"43","author":"Papagiannis","year":"2019","journal-title":"J. Med. Eng. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.gaitpost.2020.01.021","article-title":"Adaptive Predictive Systems Applied to Gait Analysis: A Systematic Review","volume":"77","author":"Caldas","year":"2020","journal-title":"Gait Posture"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"78060","DOI":"10.1109\/ACCESS.2021.3083519","article-title":"Impact of EEG Parameters Detecting Dementia Diseases: A Systematic Review","volume":"9","year":"2021","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Imtiaz, U., Bartolomeo, L., Lin, Z., Sessa, S., Ishii, H., Saito, K., Zecca, M., and Takanishi, A. (2013, January 4\u20137). Design of a Wireless Miniature Low Cost EMG Sensor Using Gold Plated Dry Electrodes for Biomechanics Research. Proceedings of the 2013 IEEE International Conference on Mechatronics and Automation (ICMA), Takamatsu, Japan.","DOI":"10.1109\/ICMA.2013.6618044"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ruvalcaba, A., Altamirano, A., Toledo, C., Munoz, R., Vera, A., and Leija, L. (2015, January 24\u201327). Design and Measurement of the Standards of a Miniaturized SEMG Acquisition System with Dry Electrodes Integrated. Proceedings of the 2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE), Cuernavaca, Mexico.","DOI":"10.1109\/ICMEAE.2015.34"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Lopez, R., and Davies, T.C. (2016, January 29\u201331). The Effect of Surface Electromyography Placement on Muscle Activation Amplitudes and Timing. Proceedings of the 2016 IEEE EMBS International Student Conference (ISC), Ottawa, ON, Canada.","DOI":"10.1109\/EMBSISC.2016.7508618"},{"key":"ref_27","unstructured":"Vavrinsk\u00fd, E., Da\u0159\u00ed\u010dek, M., Donoval, M., Rendek, K., Hor\u00ednek, F., Horniak, M., and Donoval, D. (2011, January 7\u20138). Design of EMG Wireless Sensor System. Proceedings of the 2011 International Conference on Applied Electronics, Pilsen, Czech Republic."},{"key":"ref_28","unstructured":"Lin, Z., Zecca, M., Sessa, S., Bartolomeo, L., Ishii, H., and Takanishi, A. (September, January 30). Development of the Wireless Ultra-Miniaturized Inertial Measurement Unit WB-4: Preliminary Performance Evaluation. Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, Boston, MA, USA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1049\/htl.2014.0103","article-title":"Reliability of the Step Phase Detection Using Inertial Measurement Units: Pilot Study","volume":"2","author":"Sessa","year":"2015","journal-title":"Healthc. Technol. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chatterjee, S., Sadhu, S., and Ghoshal, T.K. (2015, January 7\u20138). Self Switched R-Adaptive Extended Kalman Filter Based State Estimation and Mode Determination for Nonlinear Hybrid Systems. Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT), Hooghly, India.","DOI":"10.1109\/C3IT.2015.7060209"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sessa, S., Zecca, M., Lin, Z., Bartolomeo, L., Itoh, K., Ishii, H., Mukaeda, Y., Suzuki, Y., and Takanishi, A. (2010, January 14\u201318). Ultra-Miniaturized WB-3 Inertial Measurement Unit: Performance Evaluation of the Attitude Estimation. Proceedings of the 2010 IEEE International Conference on Robotics and Biomimetics (ROBIO), Tianjin, China.","DOI":"10.1109\/ROBIO.2010.5723462"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s10846-012-9772-8","article-title":"A Methodology for the Performance Evaluation of Inertial Measurement Units","volume":"71","author":"Sessa","year":"2013","journal-title":"J Intell Robot Syst"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1017\/S0373463307004286","article-title":"Non-GPS Navigation for Security Personnel and First Responders","volume":"60","author":"Ojeda","year":"2007","journal-title":"J. Navig."},{"key":"ref_34","unstructured":"Kodama, T., Kasai, R., Gu, Z., Zhang, D., Kong, W., Cosentino, S., Sessa, S., Kawakami, Y., and Takanishi, A. (June, January 29). Stride Length Estimation in Self-Pace and Brisk Walking with a Single Inertial Measurement Unit on the Shank. Proceedings of the ICRA 2017 Workshop on Advances and Challenges on the Development, Testing and Assessment of Assistive and Rehabilitation Robots: Experiences from Engineering And Human Science Research, Marina Bay Sands, Singapore."},{"key":"ref_35","unstructured":"Liashchynskyi, P., and Liashchynskyi, P. (2019). Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS. arXiv."},{"key":"ref_36","first-page":"78","article-title":"A Review of Gait Cycle and Its Parameters","volume":"13","author":"Kharb","year":"2011","journal-title":"IJCEM Int. J. Comput. Eng. Manag."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Gu, Z., Maamari, M.S.A., Zhang, D., Kawakami, Y., Cosentino, S., and Takanishi, A. (2019, January 4\u20137). Design and Evaluation of a Training System to Increase Knee Extension Load During Walking. Proceedings of the 2019 IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China.","DOI":"10.1109\/ICMA.2019.8816555"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4632\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:35:09Z","timestamp":1760139309000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4632"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,19]]},"references-count":37,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22124632"],"URL":"https:\/\/doi.org\/10.3390\/s22124632","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,19]]}}}