{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T21:18:58Z","timestamp":1788902338846,"version":"build-2803163510"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004233","name":"Universitat Polit\u00e8cnica de Val\u00e8ncia","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004233","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["GeroScience"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to investigate neuromuscular adaptations in individuals with pre\/sarcopenia during postural balance perturbations, using surface electromyography (sEMG) signal features as potential functional biomarkers of early motor decline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Twenty-eight older adults (14 pre\/sarcopenic, 14 controls) were subjected to a series of forward balance perturbations while standing on a force platform. sEMG signals were recorded from four lower limb muscles and analyzed across five defined postural epochs established by the perturbation. Six sEMG features were extracted to capture amplitude, frequency, shape, and complexity characteristics of the signals. Linear mixed-effects models were used to evaluate group differences and trial-by-trial adaptation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The Post-stab epoch (350\u20132350\u00a0ms post-perturbation) revealed the most pronounced differences between groups. The pre\/sarcopenic group exhibited significantly lower amplitude and complexity values. Additionally, shape analysis showed a distribution more closely resembling a Laplacian profile in the pre\/sarcopenic group, indicative of increased motor unit synchronization and diminished recruitment variability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study identifies specific sEMG-derived features, particularly signal shape and complexity metrics, as potential non-invasive biomarkers for neuromuscular decline in sarcopenia. The Post-stab epoch emerges as a sensitive window for detecting deficits in motor control, supporting the use of perturbation-based tasks and sEMG analysis for early detection, monitoring, and intervention planning in aging populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s11357-025-01841-0","type":"journal-article","created":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T19:36:55Z","timestamp":1756409815000},"page":"3025-3044","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Assessment of surface EMG biomarkers in sarcopenic motor dysfunction during postural stabilization"],"prefix":"10.1007","volume":"48","author":[{"given":"I.","family":"Junquera-Godoy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. L.","family":"Martinez-De-Juan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G. Gonz\u00e1lez","family":"Lorente","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"I. C.","family":"Vendramini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. M.","family":"Scheeren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9362-5055","authenticated-orcid":false,"given":"G.","family":"Prats-Boluda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,28]]},"reference":[{"key":"1841_CR1","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1093\/ageing\/afy169","volume":"48","author":"AJ Cruz-Jentoft","year":"2019","unstructured":"Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruy\u00e8re O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16\u201331. https:\/\/doi.org\/10.1093\/ageing\/afy169.","journal-title":"Age Ageing"},{"key":"1841_CR2","doi-asserted-by":"publisher","first-page":"160","DOI":"10.3390\/cells11010160","volume":"11","author":"J Bilski","year":"2022","unstructured":"Bilski J, Pierzchalski P, Szczepanik M, Bonior J, Zoladz J. Multifactorial mechanism of sarcopenia and sarcopenic obesity. Role of Physical Exercise. Microbiota and Myokines Cells. 2022;11:160. https:\/\/doi.org\/10.3390\/cells11010160.","journal-title":"Microbiota and Myokines. Cells"},{"key":"1841_CR3","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1002\/jcsm.12901","volume":"13","author":"C Li","year":"2022","unstructured":"Li C, Yu K, Shyh-Chang N, Jiang Z, Liu T, Ma S, et al. Pathogenesis of sarcopenia and the relationship with fat mass: descriptive review. J Cachexia Sarcopenia Muscle. 2022;13:781\u201394. https:\/\/doi.org\/10.1002\/jcsm.12901.","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"1841_CR4","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1152\/physrev.00061.2017","volume":"99","author":"L Larsson","year":"2019","unstructured":"Larsson L, Degens H, Li M, Salviati L, Lee YI, Thompson W, et al. Sarcopenia: aging-related loss of muscle mass and function. Physiol Rev. 2019;99:427\u2013511. https:\/\/doi.org\/10.1152\/physrev.00061.2017.","journal-title":"Physiol Rev"},{"key":"1841_CR5","doi-asserted-by":"publisher","first-page":"7","DOI":"10.14283\/jfa.2018.35","volume":"8","author":"BC Clark","year":"2019","unstructured":"Clark BC. Neuromuscular changes with aging and sarcopenia. J Frailty Aging. 2019;8:7\u20139. https:\/\/doi.org\/10.14283\/jfa.2018.35.","journal-title":"J Frailty Aging."},{"key":"1841_CR6","doi-asserted-by":"publisher","first-page":"2289","DOI":"10.1007\/s00421-011-2200-0","volume":"112","author":"KF Reid","year":"2012","unstructured":"Reid KF, Doros G, Clark DJ, Patten C, Carabello RJ, Cloutier GJ, et al. Muscle power failure in mobility-limited older adults: preserved single fiber function despite lower whole muscle size, quality and rate of neuromuscular activation. Eur J Appl Physiol. 2012;112:2289\u2013301. https:\/\/doi.org\/10.1007\/s00421-011-2200-0.","journal-title":"Eur J Appl Physiol"},{"key":"1841_CR7","doi-asserted-by":"publisher","first-page":"1194889","DOI":"10.3389\/fphys.2023.1194889","volume":"14","author":"M N\u00f9\u00f1ez-Lisboa","year":"2023","unstructured":"N\u00f9\u00f1ez-Lisboa M, Valero-Breton M, Dewolf AH. Unraveling age-related impairment of the neuromuscular system: exploring biomechanical and neurophysiological perspectives. Front Physiol. 2023;14:1194889. https:\/\/doi.org\/10.3389\/fphys.2023.1194889.","journal-title":"Front Physiol"},{"key":"1841_CR8","doi-asserted-by":"publisher","first-page":"955","DOI":"10.2147\/CIA.S104674","volume":"12","author":"EV Papa","year":"2017","unstructured":"Papa EV, Dong X, Hassan M. Resistance training for activity limitations in older adults with skeletal muscle function deficits: a systematic review. Clin Interv Aging. 2017;12:955\u201361. https:\/\/doi.org\/10.2147\/CIA.S104674.","journal-title":"Clin Interv Aging"},{"key":"1841_CR9","doi-asserted-by":"publisher","first-page":"155533","DOI":"10.1016\/j.metabol.2023.155533","volume":"144","author":"S Yuan","year":"2023","unstructured":"Yuan S, Larsson SC. Epidemiology of sarcopenia: prevalence, risk factors, and consequences. Metabolism. 2023;144:155533. https:\/\/doi.org\/10.1016\/j.metabol.2023.155533.","journal-title":"Metabolism"},{"key":"1841_CR10","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1007\/s13539-010-0014-2","volume":"1","author":"S von Haehling","year":"2010","unstructured":"von Haehling S, Morley JE, Anker SD. An overview of sarcopenia: facts and numbers on prevalence and clinical impact. J Cachexia Sarcopenia Muscle. 2010;1:129\u201333. https:\/\/doi.org\/10.1007\/s13539-010-0014-2.","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"1841_CR11","doi-asserted-by":"publisher","first-page":"2636","DOI":"10.1016\/S0140-6736(19)31138-9","volume":"393","author":"AJ Cruz-Jentoft","year":"2019","unstructured":"Cruz-Jentoft AJ, Sayer AA. Sarcopenia. The Lancet. 2019;393:2636\u201346. https:\/\/doi.org\/10.1016\/S0140-6736(19)31138-9.","journal-title":"The Lancet"},{"key":"1841_CR12","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s00223-018-0478-1","volume":"104","author":"R Pinedo-Villanueva","year":"2019","unstructured":"Pinedo-Villanueva R, Westbury LD, Syddall HE, Sanchez-Santos MT, Dennison EM, Robinson SM, et al. health care costs associated with muscle weakness: a UK population-based estimate. Calcif Tissue Int. 2019;104:137\u201344. https:\/\/doi.org\/10.1007\/s00223-018-0478-1.","journal-title":"Calcif Tissue Int"},{"key":"1841_CR13","doi-asserted-by":"publisher","first-page":"1046","DOI":"10.1038\/ejcn.2016.73","volume":"70","author":"AS Sousa","year":"2016","unstructured":"Sousa AS, Guerra RS, Fonseca I, Pichel F, Ferreira S, Amaral TF. Financial impact of sarcopenia on hospitalization costs. Eur J Clin Nutr. 2016;70:1046\u201351. https:\/\/doi.org\/10.1038\/ejcn.2016.73.","journal-title":"Eur J Clin Nutr"},{"key":"1841_CR14","first-page":"91","volume":"10","author":"A Ungar","year":"2013","unstructured":"Ungar A, Rafanelli M, Iacomelli I, Brunetti MA, Ceccofiglio A, Tesi F, et al. Fall prevention in the elderly. Clin Cases Miner Bone Metab. 2013;10:91\u20135.","journal-title":"Clin Cases Miner Bone Metab"},{"key":"1841_CR15","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1093\/ageing\/afq034","volume":"39","author":"AJ Cruz-Jentoft","year":"2010","unstructured":"Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis. Age Ageing. 2010;39:412\u201323. https:\/\/doi.org\/10.1093\/ageing\/afq034.","journal-title":"Age Ageing"},{"key":"1841_CR16","unstructured":"Criswell Eleanor, Cram JR. Cram\u2019s introduction to surface electromyography. Jones and Bartlett; 2011."},{"key":"1841_CR17","doi-asserted-by":"publisher","first-page":"105151","DOI":"10.1016\/j.archger.2023.105151","volume":"116","author":"T Hirono","year":"2024","unstructured":"Hirono T, Takeda R, Nishikawa T, Okudaira M, Kunugi S, Yoshiko A, et al. Motor unit firing patterns in older adults with low skeletal muscle mass. Arch Gerontol Geriatr. 2024;116:105151. https:\/\/doi.org\/10.1016\/j.archger.2023.105151.","journal-title":"Arch Gerontol Geriatr"},{"key":"1841_CR18","doi-asserted-by":"publisher","first-page":"2721","DOI":"10.3390\/s22072721","volume":"22","author":"A Leone","year":"2022","unstructured":"Leone A, Rescio G, Manni A, Siciliano P, Caroppo A. Comparative analysis of supervised classifiers for the evaluation of sarcopenia using a sEMG-based platform. Sensors. 2022;22:2721. https:\/\/doi.org\/10.3390\/s22072721.","journal-title":"Sensors"},{"key":"1841_CR19","doi-asserted-by":"publisher","first-page":"2901","DOI":"10.3934\/mbe.2024129","volume":"21","author":"KS Kumar","year":"2024","unstructured":"Kumar KS, Lee D, Jamsrandoj A, Soylu NN, Jung D, Kim J, et al. sEMG-based Sarcopenia risk classification using empirical mode decomposition and machine learning algorithms. Math Biosci Eng. 2024;21:2901\u201321. https:\/\/doi.org\/10.3934\/mbe.2024129.","journal-title":"Math Biosci Eng"},{"key":"1841_CR20","doi-asserted-by":"publisher","first-page":"e24116","DOI":"10.1016\/j.heliyon.2024.e24116","volume":"10","author":"T Zhang","year":"2024","unstructured":"Zhang T, Huo Y, Yin W, Xiang J. Postural balance disorders in sarcopenia based on surface electromyography. Heliyon. 2024;10:e24116. https:\/\/doi.org\/10.1016\/j.heliyon.2024.e24116.","journal-title":"Heliyon"},{"key":"1841_CR21","doi-asserted-by":"publisher","first-page":"2122","DOI":"10.3390\/s25072122","volume":"25","author":"A Leone","year":"2025","unstructured":"Leone A, Carluccio AM, Caroppo A, Manni A, Rescio G. A systematic review of surface electromyography in sarcopenia: muscles involved, signal processing techniques, significant features, and artificial intelligence approaches. Sensors. 2025;25:2122. https:\/\/doi.org\/10.3390\/s25072122.","journal-title":"Sensors"},{"key":"1841_CR22","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1093\/gerona\/glac143","volume":"78","author":"L Imrani","year":"2023","unstructured":"Imrani L, Boudaoud S, Lahaye C, Moreau C, Ghezal M, Ben Manaa S, et al. High-density surface electromyography as biomarker of muscle aging. The Journals of Gerontology: Series A. 2023;78:25\u201333. https:\/\/doi.org\/10.1093\/gerona\/glac143.","journal-title":"The Journals of Gerontology: Series A"},{"key":"1841_CR23","doi-asserted-by":"crossref","unstructured":"Ma Y, Yang B, Zan P, Zhang Y. Comparative analysis of classification methods for diagnosing myasthenia gravis based on lumbar electromyography. Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition, Qingdao, China: 2023, p. 65\u201371.","DOI":"10.1145\/3633637.3633647"},{"key":"1841_CR24","doi-asserted-by":"publisher","first-page":"5490","DOI":"10.3390\/s23125490","volume":"23","author":"JH Sung","year":"2023","unstructured":"Sung JH, Baek S-H, Park J-W, Rho JH, Kim B-J. Surface electromyography-driven parameters for representing muscle mass and strength. Sensors. 2023;23:5490. https:\/\/doi.org\/10.3390\/s23125490.","journal-title":"Sensors"},{"key":"1841_CR25","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1186\/s12938-024-01310-3","volume":"23","author":"H He","year":"2024","unstructured":"He H, Wu X, Li N, Jiang Y, He J, Jiang N. Multi-channel EMG manifestations of upper-extremity muscle coordination imbalance among community-dwelling sarcopenic seniors. Biomed Eng Online. 2024;23:115. https:\/\/doi.org\/10.1186\/s12938-024-01310-3.","journal-title":"Biomed Eng Online"},{"key":"1841_CR26","doi-asserted-by":"publisher","unstructured":"Junquera-Godoy I, Gomis-Tena J, Saiz J, Martinez-de-Juan JL, Carot-Sierra JM, Prats-Boluda G. Evaluation of surface electromyography parameters as possible biomarkers for the assessment of sarcopenia. 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE), IEEE; 2023, p. 285\u201391. https:\/\/doi.org\/10.1109\/BIBE60311.2023.00053.","DOI":"10.1109\/BIBE60311.2023.00053"},{"key":"1841_CR27","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1186\/s12984-024-01369-y","volume":"21","author":"N Li","year":"2024","unstructured":"Li N, Ou J, He H, He J, Zhang L, Peng Z, et al. Exploration of a machine learning approach for diagnosing sarcopenia among Chinese community-dwelling older adults using sEMG-based data. J Neuroeng Rehabil. 2024;21:69. https:\/\/doi.org\/10.1186\/s12984-024-01369-y.","journal-title":"J Neuroeng Rehabil"},{"key":"1841_CR28","doi-asserted-by":"publisher","unstructured":"Hung Y-T, Liu B, Lin Y-C. AI classification system on sarcopenia for elderly. 2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), IEEE; 2023, p. 123\u20136. https:\/\/doi.org\/10.1109\/ECBIOS57802.2023.10218530.","DOI":"10.1109\/ECBIOS57802.2023.10218530"},{"key":"1841_CR29","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1113\/JP275520","volume":"596","author":"M Piasecki","year":"2018","unstructured":"Piasecki M, Ireland A, Piasecki J, Stashuk DW, Swiecicka A, Rutter MK, et al. Failure to expand the motor unit size to compensate for declining motor unit numbers distinguishes sarcopenic from non-sarcopenic older men. J Physiol. 2018;596:1627\u201337. https:\/\/doi.org\/10.1113\/JP275520.","journal-title":"J Physiol"},{"key":"1841_CR30","doi-asserted-by":"publisher","unstructured":"Dimitrova NA, Dimitrov GV. Amplitude-related characteristics of motor unit and M-wave potentials during fatigue. A simulation study using literature data on intracellular potential changes found in vitro. Journal of Electromyography and Kinesiology 2002;12:339\u201349. https:\/\/doi.org\/10.1016\/S1050-6411(02)00046-9.","DOI":"10.1016\/S1050-6411(02)00046-9"},{"key":"1841_CR31","doi-asserted-by":"publisher","first-page":"102937","DOI":"10.1016\/j.jelekin.2024.102937","volume":"79","author":"S Muceli","year":"2024","unstructured":"Muceli S, Merletti R. Tutorial. Frequency analysis of the surface EMG signal: best practices. Journal of Electromyography and Kinesiology. 2024;79:102937. https:\/\/doi.org\/10.1016\/j.jelekin.2024.102937.","journal-title":"Journal of Electromyography and Kinesiology"},{"key":"1841_CR32","doi-asserted-by":"publisher","unstructured":"Rampichini S, Vieira TM, Castiglioni P, Merati G. Complexity analysis of surface electromyography for assessing the myoelectric manifestation of muscle fatigue: a review. Entropy (Basel) 2020;22. https:\/\/doi.org\/10.3390\/e22050529.","DOI":"10.3390\/e22050529"},{"key":"1841_CR33","doi-asserted-by":"publisher","unstructured":"Boudaoud S, Ayachi F, Marque C. Shape analysis and clustering of Surface EMG Data. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, IEEE; 2010, p. 4703\u20136. https:\/\/doi.org\/10.1109\/IEMBS.2010.5626378.","DOI":"10.1109\/IEMBS.2010.5626378"},{"key":"1841_CR34","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/s40846-023-00808-w","volume":"43","author":"IC Vendramini","year":"2023","unstructured":"Vendramini IC, Papcke C, da Veiga Neto PS, dos Santos CF, de Pinho RA, Scheeren EM. Older adults with pre-sarcopenia\/sarcopenia have increased gastrocnemius muscle activity to maintain upright postural control at stance perturbation. J Med Biol Eng. 2023;43(4):437\u201345. https:\/\/doi.org\/10.1007\/s40846-023-00808-w.","journal-title":"J Med Biol Eng"},{"key":"1841_CR35","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1080\/00222895.2024.2360515","volume":"56","author":"C Papcke","year":"2024","unstructured":"Papcke C, Manffra EF, Teixeira LA, Nohama P, Scheeren EM. Reciprocal inhibition and coactivation of ankle muscles in low- and high-velocity forward and backward perturbations. J Mot Behav. 2024;56:655\u201364. https:\/\/doi.org\/10.1080\/00222895.2024.2360515.","journal-title":"J Mot Behav"},{"key":"1841_CR36","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.jbmt.2020.07.022","volume":"24","author":"AR Pawlack","year":"2020","unstructured":"Pawlack AR, Papcke C, Scheeren EM. Changes in the range of angular variation of the ankle, knee, hip and neck joints related to the awareness of an impending perturbation. J Bodyw Mov Ther. 2020;24:24\u20138. https:\/\/doi.org\/10.1016\/j.jbmt.2020.07.022.","journal-title":"J Bodyw Mov Ther"},{"key":"1841_CR37","doi-asserted-by":"publisher","unstructured":"de Fran\u00e7a NA, do Nascimento LZN, Papcke C, Scheeren EM. Reactive response of older tennis practitioners and healthy young people in relation to balance perturbations. Journal of Science in Sport and Exercise 2022;4:82\u201390. https:\/\/doi.org\/10.1007\/s42978-021-00130-4.","DOI":"10.1007\/s42978-021-00130-4"},{"key":"1841_CR38","doi-asserted-by":"publisher","first-page":"1179","DOI":"10.1152\/jappl.1986.60.4.1179","volume":"60","author":"T Moritani","year":"1986","unstructured":"Moritani T, Muro M, Nagata A. Intramuscular and surface electromyogram changes during muscle fatigue. J Appl Physiol. 1986;60:1179\u201385. https:\/\/doi.org\/10.1152\/jappl.1986.60.4.1179.","journal-title":"J Appl Physiol"},{"key":"1841_CR39","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1007\/s11517-014-1170-x","volume":"52","author":"FS Ayachi","year":"2014","unstructured":"Ayachi FS, Boudaoud S, Marque C. Evaluation of muscle force classification using shape analysis of the sEMG probability density function: a simulation study. Med Biol Eng Comput. 2014;52:673\u201384. https:\/\/doi.org\/10.1007\/s11517-014-1170-x.","journal-title":"Med Biol Eng Comput"},{"key":"1841_CR40","doi-asserted-by":"publisher","unstructured":"Korner-Nievergelt F, Roth T, von Felten S, Gu\u00e9lat J, Almasi B, Korner-Nievergelt P. Linear mixed effects models. Bayesian data analysis in ecology using linear models with R, BUGS, and STAN, Elsevier; 2015, p. 95\u2013114. https:\/\/doi.org\/10.1016\/B978-0-12-801370-0.00007-1.","DOI":"10.1016\/B978-0-12-801370-0.00007-1"},{"key":"1841_CR41","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.jspi.2003.09.017","volume":"128","author":"G Shieh","year":"2005","unstructured":"Shieh G. On power and sample size calculations for Wald tests in generalized linear models. J Stat Plan Inference. 2005;128:43\u201359. https:\/\/doi.org\/10.1016\/j.jspi.2003.09.017.","journal-title":"J Stat Plan Inference"},{"key":"1841_CR42","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1111\/bmsp.12085","volume":"70","author":"OLO Astivia","year":"2017","unstructured":"Astivia OLO, Zumbo BD. Population models and simulation methods: the case of the Spearman rank correlation. Br J Math Stat Psychol. 2017;70:347\u201367. https:\/\/doi.org\/10.1111\/bmsp.12085.","journal-title":"Br J Math Stat Psychol"},{"key":"1841_CR43","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.exger.2016.07.007","volume":"83","author":"RKA Sayed","year":"2016","unstructured":"Sayed RKA, de Leonardis EC, Guerrero-Mart\u00ednez JA, Rahim I, Mokhtar DM, Saleh AM, et al. Identification of morphological markers of sarcopenia at early stage of aging in skeletal muscle of mice. Exp Gerontol. 2016;83:22\u201330. https:\/\/doi.org\/10.1016\/j.exger.2016.07.007.","journal-title":"Exp Gerontol"},{"key":"1841_CR44","doi-asserted-by":"publisher","unstructured":"Snijders T, Verdijk LB, van Loon LucJC. The impact of sarcopenia and exercise training on skeletal muscle satellite cells. Ageing Res Rev 2009;8:328\u201338. https:\/\/doi.org\/10.1016\/j.arr.2009.05.003.","DOI":"10.1016\/j.arr.2009.05.003"},{"key":"1841_CR45","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s10354-018-0618-2","volume":"169","author":"K Keller","year":"2019","unstructured":"Keller K. Sarcopenia. Wien Med Wochenschr. 2019;169:157\u201372. https:\/\/doi.org\/10.1007\/s10354-018-0618-2.","journal-title":"Wien Med Wochenschr"},{"key":"1841_CR46","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.rehab.2011.01.001","volume":"54","author":"S Boyas","year":"2011","unstructured":"Boyas S, Gu\u00e9vel A. Neuromuscular fatigue in healthy muscle: underlying factors and adaptation mechanisms. Ann Phys Rehabil Med. 2011;54:88\u2013108. https:\/\/doi.org\/10.1016\/j.rehab.2011.01.001.","journal-title":"Ann Phys Rehabil Med"},{"key":"1841_CR47","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1016\/j.jelekin.2012.02.019","volume":"22","author":"M Gonz\u00e1lez-Izal","year":"2012","unstructured":"Gonz\u00e1lez-Izal M, Malanda A, Gorostiaga E, Izquierdo M. Electromyographic models to assess muscle fatigue. J Electromyogr Kinesiol. 2012;22:501\u201312. https:\/\/doi.org\/10.1016\/j.jelekin.2012.02.019.","journal-title":"J Electromyogr Kinesiol"},{"key":"1841_CR48","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1007\/s00223-014-9915-y","volume":"96","author":"WR Frontera","year":"2015","unstructured":"Frontera WR, Ochala J. Skeletal muscle: a brief review of structure and function. Calcif Tissue Int. 2015;96:183\u201395. https:\/\/doi.org\/10.1007\/s00223-014-9915-y.","journal-title":"Calcif Tissue Int"},{"key":"1841_CR49","doi-asserted-by":"publisher","unstructured":"Arjunan SP, Wheeler K, Shimada H, Kumar D. Age related changes in the complexity of surface EMG in biceps: a model based study. 2013 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC), IEEE; 2013, p. 1\u20134. https:\/\/doi.org\/10.1109\/BRC.2013.6487547.","DOI":"10.1109\/BRC.2013.6487547"},{"key":"1841_CR50","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1016\/j.exger.2010.04.001","volume":"45","author":"EE Carter","year":"2010","unstructured":"Carter EE, Thomas MM, Murynka T, Rowan SL, Wright KJ, Huba E, et al. Slow twitch soleus muscle is not protected from sarcopenia in senescent rats. Exp Gerontol. 2010;45:662\u201370. https:\/\/doi.org\/10.1016\/j.exger.2010.04.001.","journal-title":"Exp Gerontol"},{"key":"1841_CR51","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1002\/jum.16082","volume":"42","author":"Z Wang","year":"2023","unstructured":"Wang Z, Lyu G, Zhong H, Yan L, Xu Z. Shear wave elastography for detecting calf muscle stiffness: an effective tool for assessing sarcopenia. J Ultrasound Med. 2023;42:891\u2013900. https:\/\/doi.org\/10.1002\/jum.16082.","journal-title":"J Ultrasound Med"},{"key":"1841_CR52","doi-asserted-by":"publisher","first-page":"104446","DOI":"10.1016\/j.bspc.2022.104446","volume":"81","author":"B Krishnan","year":"2023","unstructured":"Krishnan B, Zanelli S, Boudaoud S, Scapucciati L, McPhee J, Jiang N. Age-sensitive high density surface electromyogram indices for detecting muscle fatigue using core shape modelling. Biomed Signal Process Control. 2023;81:104446. https:\/\/doi.org\/10.1016\/j.bspc.2022.104446.","journal-title":"Biomed Signal Process Control"},{"key":"1841_CR53","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.archger.2018.07.014","volume":"79","author":"AB Gadelha","year":"2018","unstructured":"Gadelha AB, Vainshelboim B, Ferreira AP, Neri SGR, Bottaro M, Lima RM. Stages of sarcopenia and the incidence of falls in older women: a prospective study. Arch Gerontol Geriatr. 2018;79:151\u20137. https:\/\/doi.org\/10.1016\/j.archger.2018.07.014.","journal-title":"Arch Gerontol Geriatr"},{"key":"1841_CR54","doi-asserted-by":"publisher","first-page":"M112","DOI":"10.1093\/gerona\/55.3.M112","volume":"55","author":"JK Rankin","year":"2000","unstructured":"Rankin JK, Woollacott MH, Shumway-Cook A, Brown LA. Cognitive influence on postural stability: a neuromuscular analysis in young and older adults. J Gerontol A Biol Sci Med Sci. 2000;55:M112\u20139. https:\/\/doi.org\/10.1093\/gerona\/55.3.M112.","journal-title":"J Gerontol A Biol Sci Med Sci"},{"key":"1841_CR55","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1080\/00222890209601929","volume":"34","author":"S-I Lin","year":"2002","unstructured":"Lin S-I, Woollacott MH. Postural muscle responses following changing balance threats in young, stable older, and unstable older adults. J Mot Behav. 2002;34:37\u201344. https:\/\/doi.org\/10.1080\/00222890209601929.","journal-title":"J Mot Behav"},{"key":"1841_CR56","doi-asserted-by":"publisher","first-page":"1204","DOI":"10.3390\/healthcare13101204","volume":"13","author":"Y Liao","year":"2025","unstructured":"Liao Y, Tan G, Zhang H. Surface electromyography combined with artificial intelligence in predicting neuromuscular falls in the elderly: a narrative review of present applications and future perspectives. Healthcare. 2025;13:1204. https:\/\/doi.org\/10.3390\/healthcare13101204.","journal-title":"Healthcare"},{"key":"1841_CR57","doi-asserted-by":"publisher","first-page":"6679","DOI":"10.1109\/JSEN.2020.3043285","volume":"21","author":"A Mehmood","year":"2021","unstructured":"Mehmood A, Nadeem A, Ashraf M, Siddiqui MS, Rizwan K, Ahsan K. A fall risk assessment mechanism for elderly people through muscle fatigue analysis on data from body area sensor network. IEEE Sens J. 2021;21:6679\u201390. https:\/\/doi.org\/10.1109\/JSEN.2020.3043285.","journal-title":"IEEE Sens J"},{"key":"1841_CR58","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.3390\/s17061229","volume":"17","author":"X Xi","year":"2017","unstructured":"Xi X, Tang M, Miran SM, Luo Z. Evaluation of feature extraction and recognition for activity monitoring and fall detection based on wearable sEMG sensors. Sensors. 2017;17:1229. https:\/\/doi.org\/10.3390\/s17061229.","journal-title":"Sensors"},{"key":"1841_CR59","doi-asserted-by":"publisher","first-page":"31","DOI":"10.2298\/JAC0201031A","volume":"12","author":"A Aruin","year":"2002","unstructured":"Aruin A. The organization of anticipatory postural adjustments. Journal of Automatic Control. 2002;12:31\u20137. https:\/\/doi.org\/10.2298\/JAC0201031A.","journal-title":"Journal of Automatic Control"},{"key":"1841_CR60","doi-asserted-by":"publisher","first-page":"e0232135","DOI":"10.1371\/journal.pone.0232135","volume":"15","author":"AY Kim","year":"2020","unstructured":"Kim AY, Lee JK, Kim SH, Choi J, Song JJ, Chae SW. Is postural dysfunction related to sarcopenia? A population-based study PLoS One. 2020;15:e0232135. https:\/\/doi.org\/10.1371\/journal.pone.0232135.","journal-title":"A population-based study PLoS One"},{"issue":"4","key":"1841_CR61","first-page":"425","volume":"14","author":"C Beaudart","year":"2014","unstructured":"Beaudart C, Reginster JY, Slomian J, et al. Prevalence of sarcopenia: the impact of different diagnostic cut-off limits. Journal of Musculoskeletal Neuronal Interactions. 2014;14(4):425\u201331.","journal-title":"Journal of Musculoskeletal Neuronal Interactions"},{"key":"1841_CR62","doi-asserted-by":"publisher","first-page":"e13678","DOI":"10.7717\/peerj.13678","volume":"10","author":"Y Yang","year":"2022","unstructured":"Yang Y, Zhang Q, He C, Chen J, Deng D, Lu W, et al. Prevalence of sarcopenia was higher in women than in men: a cross-sectional study from a rural area in eastern China. PeerJ. 2022;10:e13678. https:\/\/doi.org\/10.7717\/peerj.13678.","journal-title":"PeerJ"}],"container-title":["GeroScience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11357-025-01841-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11357-025-01841-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11357-025-01841-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T09:39:07Z","timestamp":1773049147000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11357-025-01841-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,28]]},"references-count":62,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["1841"],"URL":"https:\/\/doi.org\/10.1007\/s11357-025-01841-0","relation":{},"ISSN":["2509-2723"],"issn-type":[{"value":"2509-2723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,28]]},"assertion":[{"value":"11 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}