{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:11:33Z","timestamp":1772262693492,"version":"3.50.1"},"reference-count":87,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. U21A20121"],"award-info":[{"award-number":["Grant No. U21A20121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. 52027806"],"award-info":[{"award-number":["Grant No. 52027806"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s11517-025-03465-0","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T14:01:29Z","timestamp":1761314489000},"page":"493-511","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A physiologically inspired meta-pattern generator bridging intention and motor primitives for human voluntary locomotion"],"prefix":"10.1007","volume":"64","author":[{"given":"Miao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6295-6583","authenticated-orcid":false,"given":"Ronglei","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyue","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"key":"3465_CR1","volume-title":"Principles of Neural Science","author":"ER Kandel","year":"2021","unstructured":"Kandel ER, Koester JD, Mack SH, Siegelbaum SA (2021) Principles of Neural Science, 6th edn. McGraw-Hill Education, New York","edition":"6"},{"key":"3465_CR2","doi-asserted-by":"crossref","unstructured":"Hug F, Avrillon S, Ibanez J, Farina D (2023) Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation. J Physiology-London 601(1):11\u201320","DOI":"10.1113\/JP283698"},{"key":"3465_CR3","doi-asserted-by":"crossref","unstructured":"Israely S, Leisman G, Carmeli E (2018) Neuromuscular synergies in motor control in normal and poststroke individuals. Rev Neurosci 29(6):593\u2013612","DOI":"10.1515\/revneuro-2017-0058"},{"key":"3465_CR4","doi-asserted-by":"crossref","unstructured":"Aoi S, Ohashi T, Bamba R, Fujiki S, Tamura D, Funato T, Senda K, Ivanenko Y, Tsuchiya K (2019) Neuromusculoskeletal model that walks and runs across a speed range with a few motor control parameter changes based on the muscle synergy hypothesis. Sci Reports 9","DOI":"10.1038\/s41598-018-37460-3"},{"key":"3465_CR5","doi-asserted-by":"crossref","unstructured":"Sun T, Gao Z, Chang Z, Zhao K (2021) Brain-like intelligent decision-making based on basal ganglia and its application in automatic car-following. J Bionic Eng 18(6):1439\u20131451","DOI":"10.1007\/s42235-021-00113-9"},{"key":"3465_CR6","doi-asserted-by":"crossref","unstructured":"Pei D, Patel V, Burns M, Chandramouli R, Vinjamuri R (2019) Neural decoding of synergy-based hand movements using electroencephalography. IEEE Access 7:18\u00a0155\u201318\u00a0163","DOI":"10.1109\/ACCESS.2019.2895566"},{"key":"3465_CR7","doi-asserted-by":"crossref","unstructured":"Giszter SF (2015) Motor primitives - new data and future questions. Curr Opin Neurobiol 33:156\u2013165","DOI":"10.1016\/j.conb.2015.04.004"},{"key":"3465_CR8","doi-asserted-by":"crossref","unstructured":"Zandvoort CS, van Dieen JH, Dominici N, Daffertshofer A (2019) The human sensorimotor cortex fosters muscle synergies through cortico-synergy coherence. NeuroImage 199:30\u201337","DOI":"10.1016\/j.neuroimage.2019.05.041"},{"key":"3465_CR9","doi-asserted-by":"crossref","unstructured":"Blanco-Diaz CF, Guerrero-Mendez CD, de\u00a0Andrade RM, Badue C, De\u00a0Souza AF, Delisle-Rodriguez D, Bastos-Filho T (2024) Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and eeg. Med Biol Eng Comput 62(12):3763\u20133779","DOI":"10.1007\/s11517-024-03147-3"},{"key":"3465_CR10","doi-asserted-by":"crossref","unstructured":"Scano A, Mira RM, d\u2019Avella A (2022) Mixed matrix factorization: a novel algorithm for the extraction of kinematic-muscular synergies. J Neurophys 127(2):529\u2013547","DOI":"10.1152\/jn.00379.2021"},{"key":"3465_CR11","doi-asserted-by":"crossref","unstructured":"d\u2019Avella A, Giese M, Ivanenko YP, Schack T, Flash T (2015) Editorial: Modularity in motor control: from muscle synergies to cognitive action representation. Front Comput Neurosci 9","DOI":"10.3389\/fncom.2015.00126"},{"key":"3465_CR12","doi-asserted-by":"crossref","unstructured":"Rybak IA, Shevtsova NA, Lafreniere-Roula M, McCrea DA (2006) Modelling spinal circuitry involved in locomotor pattern generation: insights from deletions during fictive locomotion. J Physiology-London 577(2):617\u2013639","DOI":"10.1113\/jphysiol.2006.118703"},{"key":"3465_CR13","doi-asserted-by":"crossref","unstructured":"Rybak IA, Stecina K, Shevtsova NA, McCrea DA (2006) Modelling spinal circuitry involved in locomotor pattern generation: insights from the effects of afferent stimulation. J Physiology-London 577(2):641\u2013658","DOI":"10.1113\/jphysiol.2006.118711"},{"key":"3465_CR14","doi-asserted-by":"crossref","unstructured":"Wang Y, Xue X, Chen B (2020) Matsuoka\u2019s cpg with desired rhythmic signals for adaptive walking of humanoid robots. IEEE Trans Cybernet 50(2):613\u2013626","DOI":"10.1109\/TCYB.2018.2870145"},{"issue":"6","key":"3465_CR15","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1007\/BF00449593","volume":"52","author":"K Matsuoka","year":"1985","unstructured":"Matsuoka K (1985) Sustained oscillations generated by mutually inhibiting neurons with adaptation. Biol Cybern 52(6):367\u201376","journal-title":"Biol Cybern"},{"key":"3465_CR16","doi-asserted-by":"crossref","unstructured":"Gutierrez GJ, O\u2019Leary T, Marder E (2013) Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators. Neuron 77(5):845\u2013858","DOI":"10.1016\/j.neuron.2013.01.016"},{"key":"3465_CR17","doi-asserted-by":"crossref","unstructured":"Drion G, Franci A, Sepulchre R (2019) Cellular switches orchestrate rhythmic circuits. Biol Cybernet 113(1\u20132):71\u201382. workshop on Control Theory in Biology and Medicine. Ohio State Univ, Math Biosciences Inst, Columbus, OH, DEC, p 2017","DOI":"10.1007\/s00422-018-0778-6"},{"key":"3465_CR18","doi-asserted-by":"crossref","unstructured":"Dougherty KJ, Ha NT (2019) The rhythm section: an update on spinal interneurons setting the beat for mammalian locomotion. Curr Opin Physiol 8","DOI":"10.1016\/j.cophys.2019.01.004"},{"key":"3465_CR19","doi-asserted-by":"crossref","unstructured":"Lodi M, Shilnikov AL, Storace M (2020) Design principles for central pattern generators with preset rhythms. IEEE Trans Neural Netw Learn Syst 31(9):3658\u20133669","DOI":"10.1109\/TNNLS.2019.2945637"},{"key":"3465_CR20","doi-asserted-by":"crossref","unstructured":"Turk AZ, Bishop M, Adeck A, SheikhBahaei S (2022) Astrocytic modulation of central pattern generating motor circuits. Glia 70(8):1506\u20131519","DOI":"10.1002\/glia.24162"},{"key":"3465_CR21","doi-asserted-by":"crossref","unstructured":"Yu J, Tan M, Chen J, Zhang J (2014) A survey on cpg-inspired control models and system implementation. IEEE Trans Neural Netw Learn Syst 25(3):441\u2013456","DOI":"10.1109\/TNNLS.2013.2280596"},{"key":"3465_CR22","doi-asserted-by":"crossref","unstructured":"Kiehn O (2016) Decoding the organization of spinal circuits that control locomotion. Nat Rev Neurosci 17(4):224\u2013238","DOI":"10.1038\/nrn.2016.9"},{"key":"3465_CR23","doi-asserted-by":"crossref","unstructured":"Shen X, Wu Y, Lou X, Li Z, Ma L, Bian X (2023) Central pattern generator network model for the alternating hind limb gait of rats based on the modified van der pol equation. Med Biol Eng Comput 61(2):555\u2013566","DOI":"10.1007\/s11517-022-02734-6"},{"key":"3465_CR24","doi-asserted-by":"crossref","unstructured":"Ivanenko YP, Poppele RE, Lacquaniti F (2006) Motor control programs and walking. The Neuroscientist 12(4):339\u2013348","DOI":"10.1177\/1073858406287987"},{"key":"3465_CR25","doi-asserted-by":"crossref","unstructured":"Cheung VCK, Seki K (2021) Approaches to revealing the neural basis of muscle synergies: a review and a critique. J Neurophys 125(5):1580\u20131597","DOI":"10.1152\/jn.00625.2019"},{"key":"3465_CR26","doi-asserted-by":"crossref","unstructured":"Singh RE, Iqbal K, White G, Hutchinson TE (2018) A systematic review on muscle synergies: From building blocks of motor behavior to a neurorehabilitation tool. Appl Bionics Biomech 2018","DOI":"10.1155\/2018\/3615368"},{"key":"3465_CR27","doi-asserted-by":"crossref","unstructured":"Liu Y-X, Gutierrez-Farewik EM (2023) Joint kinematics, kinetics and muscle synergy patterns during transitions between locomotion modes. IEEE Trans Biomed Eng 70(3):1062\u20131071","DOI":"10.1109\/TBME.2022.3208381"},{"key":"3465_CR28","doi-asserted-by":"crossref","unstructured":"La\u00a0Scaleia V, Ivanenko YP, Zelik KE, Lacquaniti F (2014) Spinal motor outputs during step-to-step transitions of diverse human gaits. Front Human Neurosci 8","DOI":"10.3389\/fnhum.2014.00305"},{"key":"3465_CR29","doi-asserted-by":"crossref","unstructured":"Takei T, Confais J, Tomatsu S, Oya T, Seki K (2017) Neural basis for hand muscle synergies in the primate spinal cord. Proc Natl Acad Sci U S A 114(32):8643\u20138648","DOI":"10.1073\/pnas.1704328114"},{"key":"3465_CR30","doi-asserted-by":"crossref","unstructured":"Santuz A, Ekizos A, Janshen L, Mersmann F, Bohm S, Baltzopoulos V, Arampatzis A (2018) Modular control of human movement during running: An open access data set. Front Phys 9","DOI":"10.3389\/fphys.2018.01509"},{"key":"3465_CR31","doi-asserted-by":"crossref","unstructured":"Pan B, Huang Z, Wu J, Shen Y (2021) Primitive muscle synergies reflect different modes of coordination in upper limb motions. Med Biol Eng Comput 59(10):2153\u20132163","DOI":"10.1007\/s11517-021-02429-4"},{"key":"3465_CR32","doi-asserted-by":"crossref","unstructured":"Zhao K, Zhang Z, Wen H, Wang Z, Wu J (2019) Modular organization of muscle synergies to achieve movement behaviors. J Healthcare Eng 2019","DOI":"10.1155\/2019\/8130297"},{"key":"3465_CR33","doi-asserted-by":"crossref","unstructured":"Moiseev SA, Ivanov SM, Gorodnichev RM (2022) The motor synergies\u2019 organization features at different levels of motor control during high coordinated human\u2019s movement. J Evol Biochem Physiol 58(2):610\u2013622","DOI":"10.1134\/S0022093022020272"},{"key":"3465_CR34","doi-asserted-by":"crossref","unstructured":"Ferreira CL, Barroso FO, Torricelli D, Pons JL, Politti F, Garcia\u00a0Lucareli PR (2020) Women with patellofemoral pain show altered motor coordination during lateral step down. J Biomech 110","DOI":"10.1016\/j.jbiomech.2020.109981"},{"key":"3465_CR35","doi-asserted-by":"crossref","unstructured":"Taleshi M, Yeung D, Negro F, Vujaklija I (2022) Muscle synergy-driven motor unit clustering for human-machine interfacing. In Annual international conference of the IEEE engineering in medicine and biology society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol 2022, pp 4147\u20134150","DOI":"10.1109\/EMBC48229.2022.9871356"},{"key":"3465_CR36","doi-asserted-by":"crossref","unstructured":"Ivanenko Y, Cappellini G, Dominici N, Poppele R, Lacquaniti F (2005) Coordination of locomotion with voluntary movements in humans. J Neurosci 25(31):7238\u20137253","DOI":"10.1523\/JNEUROSCI.1327-05.2005"},{"key":"3465_CR37","doi-asserted-by":"crossref","unstructured":"Ivanenko Y, Poppele R, Lacquaniti F (2006) Spinal cord maps of spatiotemporal alpha-motoneuron activation in humans walking at different speeds. J Neurophys 95(2):602\u2013618","DOI":"10.1152\/jn.00767.2005"},{"key":"3465_CR38","doi-asserted-by":"crossref","unstructured":"Cappellini G, Ivanenko YP, Poppele RE, Lacquaniti F (2006) Motor patterns in human walking and running. J Neurophys 95(6):3426\u20133437","DOI":"10.1152\/jn.00081.2006"},{"key":"3465_CR39","doi-asserted-by":"crossref","unstructured":"Ivanenko YP, Cappellini G, Poppele RE, Lacquaniti F (2008) Spatiotemporal organization of $$\\alpha $$-motoneuron activity in the human spinal cord during different gaits and gait transitions. Eur J NeuroSci 27(12):3351\u20133368","DOI":"10.1111\/j.1460-9568.2008.06289.x"},{"key":"3465_CR40","doi-asserted-by":"crossref","unstructured":"Cappellini G, Ivanenko YP, Dominici N, Poppele RE, Lacquaniti F (2010) Motor patterns during walking on a slippery walkway. J Neurophys 103(2):746\u2013760","DOI":"10.1152\/jn.00499.2009"},{"key":"3465_CR41","doi-asserted-by":"crossref","unstructured":"Afzal T, Iqbal K, White G, Wright AB (2017) A method for locomotion mode identification using muscle synergies. IEEE Trans Neural Syst Rehabil Eng 25(6):608\u2013617","DOI":"10.1109\/TNSRE.2016.2585962"},{"key":"3465_CR42","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1109\/TNSRE.2021.3087135","volume":"29","author":"Y-X Liu","year":"2021","unstructured":"Liu Y-X, Wang R, Gutierrez-Farewik EM (2021) A muscle synergy-inspired method of detecting human movement intentions based on wearable sensor fusion. IEEE Trans Neural Syst Rehabil Eng 29:1089\u20131098","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"3465_CR43","doi-asserted-by":"crossref","unstructured":"Rasool G, Iqbal K, Bouaynaya N, White G (2016) Real-time task discrimination for myoelectric control employing task-specific muscle synergies. IEEE Trans Neural Syst Rehabil Eng 24(1):98\u2013108","DOI":"10.1109\/TNSRE.2015.2410176"},{"key":"3465_CR44","doi-asserted-by":"crossref","unstructured":"Hagio S, Fukuda M, Kouzaki M (2015) Identification of muscle synergies associated with gait transition in humans. Front Human Neurosci 9","DOI":"10.3389\/fnhum.2015.00048"},{"key":"3465_CR45","doi-asserted-by":"crossref","unstructured":"Saito A, Tomita A, Ando R, Watanabe K, Akima H (2018) Muscle synergies are consistent across level and uphill treadmill running. Sci Reports 8","DOI":"10.1038\/s41598-018-24332-z"},{"key":"3465_CR46","doi-asserted-by":"crossref","unstructured":"Cruz-Montecinos C, Garcia-Masso X, Maas H, Cerda M, Ruiz-del Solar J, Tapia C (2023) Detection of intermuscular coordination based on the causality of empirical mode decomposition. Med Biol Eng Comput 61(2):497\u2013509","DOI":"10.1007\/s11517-022-02736-4"},{"key":"3465_CR47","doi-asserted-by":"crossref","unstructured":"Madarshahian S, Letizi J, Latash ML (2021) Synergic control of a single muscle: The example of flexor digitorum superficialis. J Physiology-London 599(4):1261\u20131279","DOI":"10.1113\/JP280555"},{"key":"3465_CR48","doi-asserted-by":"crossref","unstructured":"Hug F, Avrillon S, Sarcher A, Del\u00a0Vecchio A, Farina D (2023) Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task. J Physiology-London 601(15):3201\u20133219","DOI":"10.1113\/JP283040"},{"key":"3465_CR49","doi-asserted-by":"crossref","unstructured":"Zhang M, Sun R (2020) Generation of human-like gait adapted to environment based on a kinematic model. In 2020 IEEE\/ASME International conference on advanced intelligent mechatronics (AIM), ser. IEEE ASME international conference on advanced intelligent mechatronics, 2020, proceedings paper, pp 747\u2013752, iEEE\/ASME international conference on advanced intelligent mechatronics (AIM), ELECTR NETWORK","DOI":"10.1109\/AIM43001.2020.9158864"},{"key":"3465_CR50","doi-asserted-by":"crossref","unstructured":"Huang B, Xiong C, Chen W, Liang J, Sun B-Y, Gong X (2021) Common kinematic synergies of various human locomotor behaviours. Royal Soc Open Sci 8(4)","DOI":"10.1098\/rsos.210161"},{"key":"3465_CR51","doi-asserted-by":"crossref","unstructured":"Huang B, Chen W, Liang J, Cheng L, Xiong C (2022) Characterization and categorization of various human lower limb movements based on kinematic synergies. Front Bioeng Biotechnol 9","DOI":"10.3389\/fbioe.2021.793746"},{"issue":"3","key":"3465_CR52","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1113\/jphysiol.1996.sp021539","volume":"494","author":"NA Borghese","year":"1996","unstructured":"Borghese NA, Bianchi L, Lacquaniti F (1996) Kinematic determinants of human locomotion. J Physiology-London 494(3):863\u2013879","journal-title":"J Physiology-London"},{"key":"3465_CR53","doi-asserted-by":"crossref","unstructured":"Ivanenko YP, Cappellini G, Dominici N, Poppele RE, Lacquaniti F (2007) Modular control of limb movements during human locomotion. J Neurosci 27(41):11\u00a0149\u201311\u00a0161","DOI":"10.1523\/JNEUROSCI.2644-07.2007"},{"key":"3465_CR54","doi-asserted-by":"crossref","unstructured":"Barliya A, Omlor L, Giese MA, Flash T (2009) An analytical formulation of the law of intersegmental coordination during human locomotion. Exp Brain Res 193(3):371\u2013385","DOI":"10.1007\/s00221-008-1633-0"},{"key":"3465_CR55","doi-asserted-by":"crossref","unstructured":"Peng C, Yang D, Ge Z, Liu H (2023) Wrist autonomy based on upper-limb synergy: a pilot study. Med Biol Eng Comput 61(5):1149\u20131166","DOI":"10.1007\/s11517-023-02783-5"},{"key":"3465_CR56","doi-asserted-by":"crossref","unstructured":"Turpin NA, Uriac S, Dalleau G (2021) How to improve the muscle synergy analysis methodology? Eur J Appl Physiol 121(4):1009\u20131025","DOI":"10.1007\/s00421-021-04604-9"},{"key":"3465_CR57","doi-asserted-by":"crossref","unstructured":"Mukovskiy A, Vassallo C, Naveau M, Stasse O, Soueres P, Giese MA (2017) Adaptive synthesis of dynamically feasible full-body movements for the humanoid robot hrp-2 by flexible combination of learned dynamic movement primitives. Robot Auton Syst 91:270\u2013283","DOI":"10.1016\/j.robot.2017.01.010"},{"key":"3465_CR58","doi-asserted-by":"crossref","unstructured":"Chiovetto E, Giese MA (2013) Kinematics of the coordination of pointing during locomotion. Plos One 8(11)","DOI":"10.1371\/journal.pone.0079555"},{"key":"3465_CR59","doi-asserted-by":"crossref","unstructured":"Gasparri GM, Manara S, Caporale D, Averta G, Bonilla M, Marino H, Catalano M, Grioli G, Bianchi M, Bicchi A, Garabini M (2018) Efficient walking gait generation via principal component representation of optimal trajectories: Application to a planar biped robot with elastic joints. IEEE Robot Autom Lett 3(3):2299\u20132306","DOI":"10.1109\/LRA.2018.2807578"},{"key":"3465_CR60","doi-asserted-by":"crossref","unstructured":"Sproewitz AT, Ajallooeian M, Tuleu A, Ijspeert AJ (2014) Kinematic primitives for walking and trotting gaits of a quadruped robot with compliant legs. Front Comput Neurosci 8","DOI":"10.3389\/fncom.2014.00027"},{"key":"3465_CR61","doi-asserted-by":"crossref","unstructured":"Sano H, Wada T (2017) Knee motion generation method for transfemoral prosthesis based on kinematic synergy and inertial motion. IEEE Trans Neural Syst Rehabil Eng 25(12):2387\u20132397","DOI":"10.1109\/TNSRE.2017.2759818"},{"key":"3465_CR62","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1523\/JNEUROSCI.02-11-01527.1982","volume":"2","author":"AP Georgopoulos","year":"1982","unstructured":"Georgopoulos AP, Kalaska JF, Caminiti R, Massey JT (1982) On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. J Neurosci Official J Soc Neurosci 2:1527\u201337","journal-title":"J Neurosci Official J Soc Neurosci"},{"key":"3465_CR63","doi-asserted-by":"crossref","unstructured":"Schwartz A, Moran D (2000) Arm trajectory and representation of movement processing in motor cortical activity. Eur J Neurosci 12(6):1851\u20131856","DOI":"10.1046\/j.1460-9568.2000.00097.x"},{"key":"3465_CR64","doi-asserted-by":"crossref","unstructured":"Li K, Zhang J, Wang L, Zhang M, Li J, Bao S (2020) A review of the key technologies for semg-based human-robot interaction systems. Biomed Signal Process Control 62","DOI":"10.1016\/j.bspc.2020.102074"},{"key":"3465_CR65","doi-asserted-by":"crossref","unstructured":"Lambert-Shirzad N, Van\u00a0der Loos HFM (2017) On identifying kinematic and muscle synergies: a comparison of matrix factorization methods using experimental data from the healthy population. J Neurophys 117(1):290\u2013302","DOI":"10.1152\/jn.00435.2016"},{"key":"3465_CR66","doi-asserted-by":"crossref","unstructured":"Tresch M, Cheung V, d\u2019Avella A (2006) Matrix factorization algorithms for the identification of muscle synergies: Evaluation on simulated and experimental data sets. J Neurophys 95(4):2199\u20132212","DOI":"10.1152\/jn.00222.2005"},{"key":"3465_CR67","doi-asserted-by":"crossref","unstructured":"Steele KM, Tresch MC, Perreault EJ (2015) Consequences of biomechanically constrained tasks in the design and interpretation of synergy analyses. J Neurophys 113(7):2102\u20132113","DOI":"10.1152\/jn.00769.2013"},{"key":"3465_CR68","doi-asserted-by":"crossref","unstructured":"Rabbi MF, Pizzolato C, Lloyd DG, Carty CP, Devaprakash D, Diamond LE (2020) Non-negative matrix factorisation is the most appropriate method for extraction of muscle synergies in walking and running. Sci Reports 10(1)","DOI":"10.1038\/s41598-020-65257-w"},{"key":"3465_CR69","doi-asserted-by":"crossref","unstructured":"Xie P, Chang Q, Zhang Y, Dong X, Yu J, Chen X (2022) Estimation of time-frequency muscle synergy in wrist movements. Entropy 24(5)","DOI":"10.3390\/e24050707"},{"key":"3465_CR70","doi-asserted-by":"crossref","unstructured":"Meng M, Zhou G, Ma Y, Xi X (2023) Continuous estimation of multi-dof movement from semg based on non-negative matrix factorization and l2 regulation. Med Biol Eng Comput 61(7):1675\u20131686","DOI":"10.1007\/s11517-023-02807-0"},{"key":"3465_CR71","doi-asserted-by":"crossref","unstructured":"Brambilla C, Atzori M, Muller H, d\u2019Avella A, Scano A (2023) Spatial and temporal muscle synergies provide a dual characterization of low-dimensional and intermittent control of upper-limb movements. Neuroscience 514:100\u2013122","DOI":"10.1016\/j.neuroscience.2023.01.017"},{"key":"3465_CR72","doi-asserted-by":"crossref","unstructured":"Esmaeili S, Karami H, Baniasad M, Shojaeefard M, Farahmand F (2022) The association between motor modules and movement primitives of gait: A muscle and kinematic synergy study. J Biomech 134","DOI":"10.1016\/j.jbiomech.2022.110997"},{"key":"3465_CR73","doi-asserted-by":"crossref","unstructured":"Patel V, Burns M, Vinjamuri R (2016) Effect of visual and tactile feedback on kinematic synergies in the grasping hand. Med Biol Eng Comput 54(8):1217\u20131227","DOI":"10.1007\/s11517-015-1424-2"},{"key":"3465_CR74","doi-asserted-by":"crossref","unstructured":"Xu L, Fu Q (2020) Design and development of a rayleigh oscillator-based reference angle generator for motion control of smart prosthetic knees. IEEE Access 8:32\u00a0421\u201332\u00a0431","DOI":"10.1109\/ACCESS.2020.2973858"},{"key":"3465_CR75","doi-asserted-by":"crossref","unstructured":"Wang Y, Cheng X, Jabban L, Sui X, Zhang D (2022) Motion intention prediction and joint trajectories generation toward lower limb prostheses using emg and imu signals. IEEE Sensors J 22(11):10\u00a0719\u201310\u00a0729","DOI":"10.1109\/JSEN.2022.3167686"},{"key":"3465_CR76","doi-asserted-by":"crossref","unstructured":"Liang F-Y, Gao F, Liao W-H (2021) Synergy-based knee angle estimation using kinematics of thigh. Gait & Posture 89:25\u201330","DOI":"10.1016\/j.gaitpost.2021.06.015"},{"key":"3465_CR77","doi-asserted-by":"crossref","unstructured":"Xiong Q, Wan J, Jiang S, Liu Y (2022) Age-related differences in gait symmetry obtained from kinematic synergies and muscle synergies of lower limbs during childhood. Biomed Eng Online 21(1)","DOI":"10.1186\/s12938-022-01034-2"},{"key":"3465_CR78","doi-asserted-by":"crossref","unstructured":"Olikkal P, Pei D, Adali T, Banerjee N, Vinjamuri R (2022) Data fusion-based musculoskeletal synergies in the grasping hand. Sensors 22(19)","DOI":"10.3390\/s22197417"},{"key":"3465_CR79","doi-asserted-by":"crossref","unstructured":"Mazlan MH, Abu\u00a0Osman NA, Abas WABW (2011) Hip 3d joint mechanics analysis of normal and obese individuals\u2019 gait. In 5th Kuala Lumpur international conference on biomedical engineering 2011 (Biomed 2011), ser. IFMBE Proceedings, vol 35, pp 161+","DOI":"10.1007\/978-3-642-21729-6_43"},{"key":"3465_CR80","doi-asserted-by":"crossref","unstructured":"Tagliabue M, Ciancio AL, Brochier T, Eskiizmirliler S, Maier MA (2015) Differences between kinematic synergies and muscle synergies during two-digit grasping. Front Human Neurosci 9","DOI":"10.3389\/fnhum.2015.00165"},{"key":"3465_CR81","doi-asserted-by":"crossref","unstructured":"Olikkal P, Pei D, Adali T, Banerjee N, Vinjamuri R (2022) Musculoskeletal synergies in the grasping hand. In Annual international conference of the IEEE engineering in medicine and biology society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol 2022, pp 3649\u20133652","DOI":"10.1109\/EMBC48229.2022.9871023"},{"key":"3465_CR82","doi-asserted-by":"crossref","unstructured":"Dwivedi SK, Ngeo J, Shibata T (2020) Extraction of nonlinear synergies for proportional and simultaneous estimation of finger kinematics. IEEE Trans Biomed Eng 67(9):2646\u20132658","DOI":"10.1109\/TBME.2020.2967154"},{"key":"3465_CR83","doi-asserted-by":"crossref","unstructured":"Hirai H, Miyazaki F, Naritomi H, Koba K, Oku T, Uno K, Uemura M, Nishi T, Kageyama M, Krebs HI (2015) On the origin of muscle synergies: invariant balance in the co-activation of agonist and antagonist muscle pairs. Front Bioeng Biotechnol 3","DOI":"10.3389\/fbioe.2015.00192"},{"key":"3465_CR84","doi-asserted-by":"crossref","unstructured":"Alessandro C, Delis I, Nori F, Panzeri S, Berret B (2013) Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives. Frontiers Comput Neurosci 7","DOI":"10.3389\/fncom.2013.00043"},{"key":"3465_CR85","doi-asserted-by":"crossref","unstructured":"Chvatal SA, Torres-Oviedo G, Safavynia SA, Ting LH (2011) Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors. J Neurophys 106(2):999\u20131015","DOI":"10.1152\/jn.00549.2010"},{"key":"3465_CR86","doi-asserted-by":"crossref","unstructured":"Ting L, Macpherson J (2005) A limited set of muscle synergies for force control during a postural task. J Neurophys 93(1):609\u2013613","DOI":"10.1152\/jn.00681.2004"},{"key":"3465_CR87","doi-asserted-by":"crossref","unstructured":"Ngeo J, Tamei T, Ikeda K, Shibata T (2015) Modeling dynamic high-dof finger postures from surface emg using nonlinear synergies in latent space representation. In 2015 37th Annual international conference of the IEEE engineering in medicine and biology society (EMBC), ser. IEEE Engineering in medicine and biology society conference proceedings, 2015, proceedings paper, pp 2095\u20132098, 37th Annual international conference of the IEEE-engineering-in-medicine-and-biology-society (EMBC), Milan, ITALY, AUG 25-29,","DOI":"10.1109\/EMBC.2015.7318801"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-025-03465-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-025-03465-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-025-03465-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:26:31Z","timestamp":1772252791000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-025-03465-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":87,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["3465"],"URL":"https:\/\/doi.org\/10.1007\/s11517-025-03465-0","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"4 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"None.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}]}}