{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T01:26:48Z","timestamp":1785288408406,"version":"3.55.0"},"reference-count":51,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union\u2019s Horizon 2020 Research and Innovation Program","doi-asserted-by":"publisher","award":["101017274"],"award-info":[{"award-number":["101017274"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Union\u2019s Horizon 2020 Research and Innovation Program","doi-asserted-by":"publisher","award":["871237"],"award-info":[{"award-number":["871237"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Union\u2019s Horizon 2020 Research and Innovation Program","doi-asserted-by":"publisher","award":["818 2017SB48FP"],"award-info":[{"award-number":["818 2017SB48FP"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"TIGHT: Tactile InteGration for Humans and arTificial systems","doi-asserted-by":"publisher","award":["101017274"],"award-info":[{"award-number":["101017274"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"TIGHT: Tactile InteGration for Humans and arTificial systems","doi-asserted-by":"publisher","award":["871237"],"award-info":[{"award-number":["871237"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"TIGHT: Tactile InteGration for Humans and arTificial systems","doi-asserted-by":"publisher","award":["818 2017SB48FP"],"award-info":[{"award-number":["818 2017SB48FP"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wearable sensing solutions have emerged as a promising paradigm for monitoring human musculoskeletal state in an unobtrusive way. To increase the deployability of these systems, considerations related to cost reduction and enhanced form factor and wearability tend to discourage the number of sensors in use. In our previous work, we provided a theoretical solution to the problem of jointly reconstructing the entire muscular-kinematic state of the upper limb, when only a limited amount of optimally retrieved sensory data are available. However, the effective implementation of these methods in a physical, under-sensorized wearable has never been attempted before. In this work, we propose to bridge this gap by presenting an under-sensorized system based on inertial measurement units (IMUs) and surface electromyography (sEMG) electrodes for the reconstruction of the upper limb musculoskeletal state, focusing on the minimization of the sensors\u2019 number. We found that, relying on two IMUs only and eight sEMG sensors, we can conjointly reconstruct all 17 degrees of freedom (five joints, twelve muscles) of the upper limb musculoskeletal state, yielding a median normalized RMS error of 8.5% on the non-measured joints and 2.5% on the non-measured muscles.<\/jats:p>","DOI":"10.3390\/s23073716","type":"journal-article","created":{"date-parts":[[2023,4,4]],"date-time":"2023-04-04T02:03:00Z","timestamp":1680573780000},"page":"3716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Multi-Modal Under-Sensorized Wearable System for Optimal Kinematic and Muscular Tracking of Human Upper Limb Motion"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7201-6632","authenticated-orcid":false,"given":"Paolo","family":"Bonifati","sequence":"first","affiliation":[{"name":"Research Center \u201cE. Piaggio\u201d, Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5724-4159","authenticated-orcid":false,"given":"Marco","family":"Baracca","sequence":"additional","affiliation":[{"name":"Research Center \u201cE. Piaggio\u201d, Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariangela","family":"Menolotto","sequence":"additional","affiliation":[{"name":"Research Center \u201cE. 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Sports, 7.","DOI":"10.3390\/sports7010028"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1109\/JSEN.2020.3019016","article-title":"Wearable sensors for real-time kinematics analysis in sports: A review","volume":"21","author":"Rana","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1561\/2300000052","article-title":"A survey of methods for safe human-robot interaction","volume":"5","author":"Lasota","year":"2017","journal-title":"Found. Trends Robot."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1177\/0278364919882089","article-title":"Human movement and ergonomics: An industry-oriented dataset for collaborative robotics","volume":"38","author":"Maurice","year":"2019","journal-title":"Int. J. Robot. Res."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ranavolo, A., Ajoudani, A., Cherubini, A., Bianchi, M., Fritzsche, L., Iavicoli, S., Sartori, M., Silvetti, A., Vanderborght, B., and Varrecchia, T. (2020). The Sensor-Based Biomechanical Risk Assessment at the Base of the Need for Revising of Standards for Human Ergonomics. Sensors, 20.","DOI":"10.3390\/s20205750"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Shafti, A., Ataka, A., Lazpita, B.U., Shiva, A., Wurdemann, H.A., and Althoefer, K. (2019, January 20\u201324). Real-time robot-assisted ergonomics. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8793739"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"033002","DOI":"10.1088\/2516-1091\/ac12c4","article-title":"Unifying system identification and biomechanical formulations for the estimation of muscle, tendon and joint stiffness during human movement","volume":"3","author":"Cop","year":"2021","journal-title":"Prog. Biomed. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1016\/j.jbiomech.2006.11.011","article-title":"Upper limb muscle volumes in adult subjects","volume":"40","author":"Holzbaur","year":"2007","journal-title":"J. Biomech."},{"key":"ref_10","unstructured":"Sengupta, A., and Cao, S. (2022). IEEE Transactions on Neural Networks and Learning Systems, IEEE."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhao, M., Li, T., Abu Alsheikh, M., Tian, Y., Zhao, H., Torralba, A., and Katabi, D. (2018, January 18\u201322). Through-wall human pose estimation using radio signals. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00768"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Filippeschi, A., Schmitz, N., Miezal, M., Bleser, G., Ruffaldi, E., and Stricker, D. (2017). Survey of motion tracking methods based on inertial sensors: A focus on upper limb human motion. Sensors, 17.","DOI":"10.3390\/s17061257"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kok, M., Hol, J.D., and Sch\u00f6n, T.B. (2017). Using Inertial Sensors for Position and Orientation Estimation. arXiv.","DOI":"10.1561\/9781680833577"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Rampichini, S., Vieira, T.M., Castiglioni, P., and Merati, G. (2020). Complexity analysis of surface electromyography for assessing the myoelectric manifestation of muscle fatigue: A review. Entropy, 22.","DOI":"10.3390\/e22050529"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1854","DOI":"10.1109\/JBHI.2017.2783849","article-title":"Weighted-cumulated S-EMG muscle fatigue estimator","volume":"22","author":"Rocha","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_16","unstructured":"Jebelli, H., and Lee, S. (2019). Advances in Informatics and Computing in Civil and Construction Engineering, Springer."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1109\/TMECH.2017.2715163","article-title":"Pervasive monitoring of motion and muscle activation: Inertial and mechanomyography fusion","volume":"22","author":"Woodward","year":"2017","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/TOH.2017.2689006","article-title":"Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives","volume":"10","author":"Pacchierotti","year":"2017","journal-title":"IEEE Trans. Haptics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2951","DOI":"10.1007\/s00221-021-06188-4","article-title":"One more time about motor (and non-motor) synergies","volume":"239","author":"Latash","year":"2021","journal-title":"Exp. Brain Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1097\/00003677-200404000-00007","article-title":"Prehension synergies","volume":"32","author":"Zatsiorsky","year":"2004","journal-title":"Exerc. Sport Sci. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Latash, M.L. (2008). Neurophysiological Basis of Movement, Human Kinetics.","DOI":"10.1093\/acprof:oso\/9780195333169.003.0007"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.3389\/fphys.2019.01231","article-title":"A comprehensive spatial mapping of muscle synergies in highly variable upper-limb movements of healthy subjects","volume":"10","author":"Scano","year":"2019","journal-title":"Front. Physiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1109\/TNSRE.2019.2918311","article-title":"On the time-invariance properties of upper limb synergies","volume":"27","author":"Averta","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2836","DOI":"10.1080\/09638288.2019.1578421","article-title":"Lower limb muscle synergies during walking after stroke: A systematic review","volume":"42","author":"Vermeulen","year":"2020","journal-title":"Disabil. Rehabil."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"12237","DOI":"10.1523\/JNEUROSCI.6344-11.2012","article-title":"Voluntary and reactive recruitment of locomotor muscle synergies during perturbed walking","volume":"32","author":"Chvatal","year":"2012","journal-title":"J. Neurosci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1177\/0278364913518998","article-title":"Adaptive synergies for the design and control of the Pisa\/IIT SoftHand","volume":"33","author":"Catalano","year":"2014","journal-title":"Int. J. Robot. Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1177\/0278364909105606","article-title":"Hand posture subspaces for dexterous robotic grasping","volume":"28","author":"Ciocarlie","year":"2009","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12984-020-00680-8","article-title":"Exploiting upper-limb functional principal components for human-like motion generation of anthropomorphic robots","volume":"17","author":"Averta","year":"2020","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ficuciello, F., Palli, G., Melchiorri, C., and Siciliano, B. (2011, January 25\u201330). Experimental evaluation of postural synergies during reach to grasp with the UB Hand IV. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6094671"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1177\/0278364912474078","article-title":"Synergy-based hand pose sensing: Reconstruction enhancement","volume":"32","author":"Bianchi","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1177\/0278364912474079","article-title":"Synergy-based hand pose sensing: Optimal glove design","volume":"32","author":"Bianchi","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ciotti, S., Battaglia, E., Carbonaro, N., Bicchi, A., Tognetti, A., and Bianchi, M. (2016). A synergy-based optimally designed sensing glove for functional grasp recognition. Sensors, 16.","DOI":"10.3390\/s16060811"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e1415","DOI":"10.1002\/wics.1415","article-title":"Estimation of covariance and precision matrix, network structure, and a view toward systems biology","volume":"9","author":"Kuismin","year":"2017","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1109\/THMS.2022.3163184","article-title":"Optimal Reconstruction of Human Motion From Scarce Multimodal Data","volume":"52","author":"Averta","year":"2022","journal-title":"IEEE Trans.-Hum.-Mach. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Ramsay, J.O., Hooker, G., and Graves, S. (2009). Functional Data Analysis with R and MATLAB, Springer Science & Business Media.","DOI":"10.1007\/978-0-387-98185-7"},{"key":"ref_36","unstructured":"Peppoloni, L., Filippeschi, A., Ruffaldi, E., and Avizzano, C.A. (2013). Proceedings of the 2013 IEEE 11th International Symposium on Intelligent Systems and Informatics (SISY), IEEE."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40648-020-00185-y","article-title":"Pose estimation by extended Kalman filter using noise covariance matrices based on sensor output","volume":"7","author":"Saito","year":"2020","journal-title":"Robomech J."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"giab043","DOI":"10.1093\/gigascience\/giab043","article-title":"U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions","volume":"10","author":"Averta","year":"2021","journal-title":"GigaScience"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"M\u00fcller, M. (2007). Information Retrieval for Music and Motion, Springer.","DOI":"10.1007\/978-3-540-74048-3"},{"key":"ref_40","unstructured":"Tedaldi, D., Pretto, A., and Menegatti, E. (2014). Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1109\/TAES.2011.5751259","article-title":"Geometric approach to strapdown magnetometer calibration in sensor frame","volume":"47","author":"Vasconcelos","year":"2011","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_42","unstructured":"Bleser, G., Hendeby, G., and Miezal, M. (2011). Proceedings of the 2011 10th IEEE International Symposium on Mixed and Augmented Reality, IEEE."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1109\/RBME.2022.3164797","article-title":"A Review of Techniques for Surface Electromyography Signal Quality Analysis","volume":"16","author":"Farago","year":"2022","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4880","DOI":"10.1038\/s41467-021-25152-y","article-title":"Ultra-conformal skin electrodes with synergistically enhanced conductivity for long-time and low-motion artifact epidermal electrophysiology","volume":"12","author":"Zhao","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_45","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_46","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1109\/TBME.2015.2403368","article-title":"Human joint angle estimation with inertial sensors and validation with a robot arm","volume":"62","author":"McNames","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1109\/TBME.2021.3103201","article-title":"An open-source and wearable system for measuring 3D human motion in real-time","volume":"69","author":"Slade","year":"2021","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1750031","DOI":"10.1142\/S0219519417500312","article-title":"Shoulder and elbow joint angle estimation for upper limb rehabilitation tasks using low-cost inertial and optical sensors","volume":"17","author":"Alizadegan","year":"2017","journal-title":"J. Mech. Med. Biol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative adversarial networks","volume":"63","author":"Goodfellow","year":"2020","journal-title":"Commun. ACM"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Liu, H., Hartmann, Y., and Schultz, T. (2022, January 9\u201311). A Practical Wearable Sensor-based Human Activity Recognition Research Pipeline. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, Online.","DOI":"10.5220\/0010937000003123"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Hartmann, Y., Liu, H., and Schultz, T. (2022, January 21\u201325). Interactive and Interpretable Online Human Activity Recognition. Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Pisa, Italy.","DOI":"10.1109\/PerComWorkshops53856.2022.9767207"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/7\/3716\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:09:27Z","timestamp":1760123367000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/7\/3716"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,3]]},"references-count":51,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["s23073716"],"URL":"https:\/\/doi.org\/10.3390\/s23073716","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,3]]}}}