{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T20:18:30Z","timestamp":1784751510898,"version":"3.55.0"},"reference-count":69,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFB4704600"],"award-info":[{"award-number":["2023YFB4704600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.bspc.2026.110863","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T12:05:36Z","timestamp":1782216336000},"page":"110863","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Dynamic muscle deformation as a novel biomechanical marker for load-induced neuromuscular fatigue assessment"],"prefix":"10.1016","volume":"126","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6152-7323","authenticated-orcid":false,"given":"Jiahao","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2073-7125","authenticated-orcid":false,"given":"Hongmiao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bspc.2026.110863_b1","series-title":"Skeletal Muscle: Form and Function","author":"MacImstosh","year":"2005"},{"key":"10.1016\/j.bspc.2026.110863_b2","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.rehab.2011.01.001","article-title":"Neuromuscular fatigue in healthy muscle: Underlying factors and adaptation mechanisms","volume":"54","author":"Boyas","year":"2011","journal-title":"Ann. Phys. Rehabil. Med."},{"key":"10.1016\/j.bspc.2026.110863_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108134","article-title":"Complex network properties analysis of upper trunk muscle fatigue in firefighters carrying self-contained breathing apparatus","volume":"110","author":"Xie","year":"2025","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110863_b4","doi-asserted-by":"crossref","first-page":"56","DOI":"10.3390\/safety10030056","article-title":"Assessing the short-term effects of dual back-support exoskeleton within logistics operations","volume":"10","author":"Cardoso","year":"2024","journal-title":"Safety"},{"key":"10.1016\/j.bspc.2026.110863_b5","series-title":"European working conditions survey 2015","year":"2016"},{"key":"10.1016\/j.bspc.2026.110863_b6","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1136\/bjsm.7.3-4.332","article-title":"Quantification of muscle fatigue\u2014an overview","volume":"7","author":"Heyward","year":"1973","journal-title":"Br. J. Sports Med."},{"key":"10.1016\/j.bspc.2026.110863_b7","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1007\/s40279-019-01203-9","article-title":"Quantification of neuromuscular fatigue: What do we do wrong and why?","volume":"50","author":"Place","year":"2020","journal-title":"Sports Med."},{"key":"10.1016\/j.bspc.2026.110863_b8","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1109\/TNSRE.2024.3393132","article-title":"Exploration and application of a muscle fatigue assessment model based on NMF for multi-muscle synergistic movements","volume":"32","author":"Yu","year":"2024","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.bios.2025.117616","article-title":"A battery-free wearable sweat lactate sensing patch for assessing muscle fatigue and recovery","volume":"286","author":"Zhu","year":"2025","journal-title":"Biosens. Bioelectron."},{"key":"10.1016\/j.bspc.2026.110863_b10","doi-asserted-by":"crossref","first-page":"16835","DOI":"10.1109\/JIOT.2021.3056126","article-title":"sEMG-based dynamic muscle fatigue classification using SVM with improved whale optimization algorithm","volume":"8","author":"Liu","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.bspc.2026.110863_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.jelekin.2019.102360","article-title":"Perceived physical exertion is a good indicator of neuromuscular fatigue for the core muscles","volume":"49","author":"Cruz-Montecinos","year":"2019","journal-title":"J. Electromyogr. Kinesiol."},{"key":"10.1016\/j.bspc.2026.110863_b12","doi-asserted-by":"crossref","DOI":"10.1186\/s13102-023-00620-8","article-title":"Validity of using perceived exertion to assess muscle fatigue during back squat exercise","volume":"15","author":"Zhao","year":"2023","journal-title":"BMC Sport. Sci. Med. Rehabil."},{"key":"10.1016\/j.bspc.2026.110863_b13","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1093\/occmed\/kqx063","article-title":"The borg rating of perceived exertion (RPE) scale","volume":"67","author":"Williams","year":"2017","journal-title":"Occup. Med."},{"key":"10.1016\/j.bspc.2026.110863_b14","doi-asserted-by":"crossref","DOI":"10.1136\/bmjsem-2016-000164","article-title":"Misinterpretation of the borg\u2019s rating of perceived exertion scale by patients with panic disorder during ergospirometry challenge","volume":"3","author":"Muotri","year":"2017","journal-title":"BMJ Open Sport. Exerc. Med."},{"key":"10.1016\/j.bspc.2026.110863_b15","doi-asserted-by":"crossref","first-page":"e1","DOI":"10.1016\/j.rehab.2017.07.017","article-title":"Reliability of the rating of perceived exertion (Borg Scale) in post-stroke during 2 tasks of daily life","volume":"60","author":"Compagnat","year":"2017","journal-title":"Ann. Phys. Rehabil. Med."},{"key":"10.1016\/j.bspc.2026.110863_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2020.103381","article-title":"Effects of physical fatigue on the induction of mental fatigue of construction workers: A pilot study based on a neurophysiological approach","volume":"120","author":"Xing","year":"2020","journal-title":"Autom. Constr."},{"key":"10.1016\/j.bspc.2026.110863_b17","doi-asserted-by":"crossref","first-page":"4175","DOI":"10.1109\/TCYB.2021.3123842","article-title":"A product fuzzy convolutional network for detecting driving fatigue","volume":"53","author":"Du","year":"2023","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.bspc.2026.110863_b18","doi-asserted-by":"crossref","DOI":"10.1186\/s40779-023-00502-7","article-title":"The applied principles of EEG analysis methods in neuroscience and clinical neurology","volume":"10","author":"Zhang","year":"2023","journal-title":"Military Med. Res."},{"key":"10.1016\/j.bspc.2026.110863_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.108466","article-title":"FFTNet: fNIRS-based frequency-enhanced patch network for driving fatigue detection","volume":"196","author":"Li","year":"2026","journal-title":"Neural Netw."},{"key":"10.1016\/j.bspc.2026.110863_b20","doi-asserted-by":"crossref","first-page":"3580","DOI":"10.1109\/TVCG.2025.3549581","article-title":"Investigating virtual reality for alleviating human-computer interaction fatigue: A multimodal assessment and comparison with flat video","volume":"31","author":"Wang","year":"2025","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"key":"10.1016\/j.bspc.2026.110863_b21","doi-asserted-by":"crossref","first-page":"1517","DOI":"10.4103\/1673-5374.387970","article-title":"Functional near-infrared spectroscopy in non-invasive neuromodulation","volume":"19","author":"Huo","year":"2024","journal-title":"Neural Regen. Res."},{"key":"10.1016\/j.bspc.2026.110863_b22","doi-asserted-by":"crossref","first-page":"2371","DOI":"10.1016\/j.clinph.2021.05.036","article-title":"Removal of physiological artifacts from simultaneous EEG and fMRI recordings","volume":"132","author":"Daly","year":"2021","journal-title":"Clin. Neurophysiol."},{"key":"10.1016\/j.bspc.2026.110863_b23","doi-asserted-by":"crossref","first-page":"1770","DOI":"10.1109\/TIM.2016.2608479","article-title":"Independent vector analysis applied to remove muscle artifacts in EEG data","volume":"66","author":"Chen","year":"2017","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.bspc.2026.110863_b24","doi-asserted-by":"crossref","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":"10.1016\/j.bspc.2026.110863_b25","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.bspc.2016.04.002","article-title":"Dynamic modeling of sEMG\u2013force relation in the presence of muscle fatigue during isometric contractions","volume":"28","author":"Asefi","year":"2016","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110863_b26","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1016\/j.bbe.2021.06.003","article-title":"Characterization of muscle fatigue in the lower limb by sEMG and angular position using the WFD protocol","volume":"41","author":"Chaparro-C\u00e1rdenas","year":"2021","journal-title":"Biocybern. Biomed. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b27","first-page":"153","article-title":"Locality preserving projections","author":"He","year":"2003","journal-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)"},{"key":"10.1016\/j.bspc.2026.110863_b28","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1162\/089976603321780317","article-title":"Laplacian eigenmaps for dimensionality reduction and data representation","volume":"15","author":"Belkin","year":"2003","journal-title":"Neural Comput."},{"key":"10.1016\/j.bspc.2026.110863_b29","first-page":"1","article-title":"UaBMA-OLPP: A novel manifold-inspired technique for sEMG-based hand movement and object grasp recognition","author":"Ghosh","year":"2025","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"10.1016\/j.bspc.2026.110863_b30","article-title":"Detection, identification and removing of artifacts from sEMG signals: Current studies and future challenges","volume":"186","author":"Yous","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.bspc.2026.110863_b31","article-title":"Surface-level muscle deformation as a correlate for joint torque","volume":"9","author":"Alvarez","year":"2024","journal-title":"Adv. Mater. Technol."},{"key":"10.1016\/j.bspc.2026.110863_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106647","article-title":"Recognizing and predicting muscular fatigue of biceps brachii in motion with novel fabric strain sensors based on machine learning","volume":"96","author":"Wang","year":"2024","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110863_b33","doi-asserted-by":"crossref","first-page":"3407","DOI":"10.1113\/JP271400","article-title":"Mechanisms of in vivo muscle fatigue in humans: investigating age-related fatigue resistance with a computational model","volume":"594","author":"Callahan","year":"2016","journal-title":"J. Physiol."},{"key":"10.1016\/j.bspc.2026.110863_b34","doi-asserted-by":"crossref","DOI":"10.3389\/fbioe.2020.00308","article-title":"Predicting perturbed human arm movements in a neuro-musculoskeletal model to investigate the muscular force response","volume":"8","author":"Stollenmaier","year":"2020","journal-title":"Front. Bioeng. Biotechnol."},{"key":"10.1016\/j.bspc.2026.110863_b35","doi-asserted-by":"crossref","DOI":"10.1186\/s12984-025-01596-x","article-title":"Abnormal activity in the brainstem affects gait in a neuromusculoskeletal model","volume":"22","author":"Ichimura","year":"2025","journal-title":"J. Neuroeng. Rehabil."},{"key":"10.1016\/j.bspc.2026.110863_b36","doi-asserted-by":"crossref","first-page":"2024","DOI":"10.1145\/3648679","article-title":"Non-invasive techniques for muscle fatigue monitoring: A comprehensive survey","volume":"56","author":"Li","year":"2024","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.bspc.2026.110863_b37","doi-asserted-by":"crossref","DOI":"10.1016\/j.sna.2023.114892","article-title":"Continuously monitoring of muscle fatigue based on a wearable micromachined ultrasonic transducer probe","volume":"365","author":"Qu","year":"2024","journal-title":"Sens. Actuators A: Phys."},{"key":"10.1016\/j.bspc.2026.110863_b38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2023.3330221","article-title":"Adaptive learning against muscle fatigue for A-mode ultrasound-based gesture recognition","volume":"72","author":"Zeng","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.bspc.2026.110863_b39","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1177\/01617346211013473","article-title":"Acoustic-field beamforming for low-power portable ultrasound","volume":"43","author":"Hu","year":"2021","journal-title":"Ultrason. Imaging"},{"key":"10.1016\/j.bspc.2026.110863_b40","doi-asserted-by":"crossref","first-page":"159436,","DOI":"10.1016\/j.cej.2025.159436","article-title":"Flexible dual-mode epidermal sensor for time-sharing muscle fatigue monitoring and photothermal therapy","volume":"505","author":"Li","year":"2025","journal-title":"Chem. Eng. J."},{"key":"10.1016\/j.bspc.2026.110863_b41","doi-asserted-by":"crossref","DOI":"10.1002\/smtd.202100819","article-title":"Muscle fatigue sensor based on ti3c2tx mxene hydrogel","volume":"5","author":"Lee","year":"2021","journal-title":"Small Methods"},{"key":"10.1016\/j.bspc.2026.110863_b42","doi-asserted-by":"crossref","DOI":"10.1016\/j.snb.2024.136717","article-title":"Novel bioelectrode for sweat lactate sensor based on platinum nanoparticles\/reduced graphene oxide modified carbonized silk cocoon","volume":"423","author":"Phamonpon","year":"2025","journal-title":"Sens. Actuators B: Chem."},{"key":"10.1016\/j.bspc.2026.110863_b43","doi-asserted-by":"crossref","first-page":"4380","DOI":"10.1021\/acssensors.4c00604","article-title":"Advancements in textile-based sEMG sensors for muscle fatigue detection: A journey from material evolution to technological integration","volume":"9","author":"Medagedara","year":"2024","journal-title":"ACS Sens."},{"key":"10.1016\/j.bspc.2026.110863_b44","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s40846-023-00782-3","article-title":"Normalization of EMG signals: Optimal MVC positions for the lower limb muscle groups in healthy subjects","volume":"43","author":"Avdan","year":"2023","journal-title":"J. Med. Biol. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b45","article-title":"European recommendations for surface electromyography: Results of the SENlAM project","author":"Hermens","year":"1999","journal-title":"Roessingh Res. Dev."},{"key":"10.1016\/j.bspc.2026.110863_b46","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1519\/JSC.0000000000004769","article-title":"Time course of neuromuscular fatigue during different resistance exercise loadings in power athletes, strength athletes, and nonathletes","volume":"38","author":"Kotikangas","year":"2024","journal-title":"J. Strength Cond. Res."},{"key":"10.1016\/j.bspc.2026.110863_b47","doi-asserted-by":"crossref","DOI":"10.1186\/s13102-023-00620-8","article-title":"Validity of using perceived exertion to assess muscle fatigue during back squat exercise","volume":"15","author":"Zhao","year":"2023","journal-title":"BMC Sport. Sci. Med. Rehabil."},{"key":"10.1016\/j.bspc.2026.110863_b48","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2025.103422","article-title":"A comprehensive review of sEMG-IMU sensor fusion for upper limb movements pattern recognition","volume":"125","author":"Zhang","year":"2026","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.bspc.2026.110863_b49","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiol. Hear. Circ. Physiol."},{"key":"10.1016\/j.bspc.2026.110863_b50","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1123\/ijspp.2020-0552","article-title":"Maximal strength in relation to force and velocity patterns during countermovement jumps","volume":"17","author":"Haischer","year":"2021","journal-title":"Int. J. Sport. Physiol. Perform."},{"key":"10.1016\/j.bspc.2026.110863_b51","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1136\/bjsm.2007.035113","article-title":"Does plyometric training improve vertical jump height? A meta-analytical review","volume":"41","author":"Markovic","year":"2007","journal-title":"Br. J. Sports Med."},{"key":"10.1016\/j.bspc.2026.110863_b52","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/978-3-662-66786-6_8","article-title":"One-way analysis of variance (ANOVA)","author":"Janczyk","year":"2023","journal-title":"Underst. Inferent. Stat."},{"key":"10.1016\/j.bspc.2026.110863_b53","doi-asserted-by":"crossref","first-page":"g7327","DOI":"10.1136\/bmj.g7327","article-title":"Spearman\u2019s rank correlation coefficient","volume":"349","author":"Sedgwick","year":"2014","journal-title":"BMJ"},{"key":"10.1016\/j.bspc.2026.110863_b54","article-title":"Principal component analysis","volume":"100","author":"Greenacre","year":"2022","journal-title":"Nat. Rev. Methods Prim. 2"},{"key":"10.1016\/j.bspc.2026.110863_b55","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":"10.1016\/j.bspc.2026.110863_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.sna.2025.117127","article-title":"Wearable multimodal sensing platform for contraction and fatigue transition monitoring of biceps in motion using machine learning","volume":"396","author":"Chen","year":"2025","journal-title":"Sens. Actuators A: Phys."},{"key":"10.1016\/j.bspc.2026.110863_b57","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1016\/j.jelekin.2011.05.002","article-title":"EMG-based muscle fatigue assessment during dynamic contractions using principal component analysis","volume":"21","author":"Rogers","year":"2011","journal-title":"J. Electromyogr. Kinesiol."},{"key":"10.1016\/j.bspc.2026.110863_b58","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1519\/JSC.0000000000000622","article-title":"Effect of acute fatigue and training adaptation on countermovement jump performance in elite snowboard cross athletes","volume":"29","author":"Gathercole","year":"2015","journal-title":"J. Strength Cond. Res."},{"key":"10.1016\/j.bspc.2026.110863_b59","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1123\/ijspp.3.3.359","article-title":"Neuromuscular and endocrine responses of elite players to an Australian rules football match","volume":"3","author":"Cormack","year":"2008","journal-title":"Int. J. Sport. Physiol. Perform."},{"key":"10.1016\/j.bspc.2026.110863_b60","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1123\/ijspp.6.1.82","article-title":"Concurrent fatigue and potentiation in endurance athletes","volume":"6","author":"Boullosa","year":"2011","journal-title":"Int. J. Sport. Physiol. Perform."},{"key":"10.1016\/j.bspc.2026.110863_b61","article-title":"Three-dimensional geometrical changes of the human tibialis anterior muscle and its central aponeurosis measured with three-dimensional ultrasound during isometric contractions","volume":"28","author":"Raiteri","year":"2016","journal-title":"PeerJ"},{"key":"10.1016\/j.bspc.2026.110863_b62","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1109\/TBME.2007.909538","article-title":"Continuous monitoring of sonomyography, electromyography and torque generated by normal upper arm muscles during isometric contraction: Sonomyography assessment for arm muscles","volume":"55","author":"Shi","year":"2008","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b63","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/TNSRE.2024.3511267","article-title":"Stimulation-induced muscle deformation measured with A-mode ultrasound correlates with muscle fatigue","volume":"33","author":"Alvarez","year":"2025","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b64","doi-asserted-by":"crossref","first-page":"103225,","DOI":"10.1016\/j.ijhcs.2024.103225","article-title":"The role of individual differences in human-automated vehicle interaction","volume":"185","author":"Fisher","year":"2024","journal-title":"Int. J. Hum.-Comput. Stud."},{"key":"10.1016\/j.bspc.2026.110863_b65","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/0360-8352(89)90135-6","article-title":"Individual differences in human-computer interaction","volume":"17","author":"Aykin","year":"1989","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.bspc.2026.110863_b66","doi-asserted-by":"crossref","DOI":"10.1016\/j.neulet.2021.136101","article-title":"Changes in synchronization of the motor unit in muscle fatigue condition during the dynamic and isometric contraction in the biceps brachii muscle","volume":"761","author":"Liu","year":"2021","journal-title":"Neurosci. Lett."},{"key":"10.1016\/j.bspc.2026.110863_b67","doi-asserted-by":"crossref","unstructured":"K. Gokcesu, M. Ergeneci, E. Ertan, A.Z. Alkilani, P. Kosmas, An sEMG-based method to adaptively reject the effect of contraction on spectral analysis for fatigue tracking, in: Proc. ACM Int. Symp. Wearable Comput, ISWC \u201918, New York, NY, USA, 2018, pp. 80\u201387.","DOI":"10.1145\/3267242.3267292"},{"key":"10.1016\/j.bspc.2026.110863_b68","first-page":"135","article-title":"The neurophysiology of central and peripheral fatigue during sub-maximal lower limb isometric contractions","volume":"15","author":"Berchicci","year":"2013","journal-title":"Front. Hum. Neurosci."},{"key":"10.1016\/j.bspc.2026.110863_b69","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1016\/j.jelekin.2008.08.003","article-title":"A bi-dimensional index for the selective assessment of myoelectric manifestations of peripheral and central muscle fatigue","volume":"19","author":"Mesin","year":"2009","journal-title":"J. Electromyogr. Kinesiol."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426014175?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426014175?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T19:38:08Z","timestamp":1784749088000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426014175"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":69,"alternative-id":["S1746809426014175"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110863","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic muscle deformation as a novel biomechanical marker for load-induced neuromuscular fatigue assessment","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110863","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"110863"}}