{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T16:06:19Z","timestamp":1771862779334,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"28","license":[{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s00521-023-08829-x","type":"journal-article","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T06:01:37Z","timestamp":1691128897000},"page":"21229-21245","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Activity recognition in rehabilitation training based on ensemble stochastic configuration networks"],"prefix":"10.1007","volume":"35","author":[{"given":"Wenhua","family":"Jiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruilin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianguo","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5356-7268","authenticated-orcid":false,"given":"Dianhui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,4]]},"reference":[{"issue":"5","key":"8829_CR1","first-page":"7385","volume":"19","author":"MK O\u2019Brien","year":"2017","unstructured":"O\u2019Brien MK, Shawen N, Mummidisetty CK, Kaur S, Bo X, Poellabauer C, Kording K, Jayaraman A (2017) Activity recognition for persons with stroke using mobile phone technology: toward improved performance in a home setting. J Med Internet Res 19(5):7385","journal-title":"J Med Internet Res"},{"issue":"2","key":"8829_CR2","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1016\/j.apmr.2003.05.002","volume":"85","author":"SE Lord","year":"2004","unstructured":"Lord SE, McPherson K, McNaughton HK, Rochester L, Weatherall M (2004) Community ambulation after stroke: how important and obtainable is it and what measures appear predictive? Arch Phys Med Rehabil 85(2):234\u2013239","journal-title":"Arch Phys Med Rehabil"},{"issue":"8","key":"8829_CR3","doi-asserted-by":"publisher","first-page":"2060","DOI":"10.1161\/01.STR.0000020711.38824.E3","volume":"33","author":"JS Grant","year":"2002","unstructured":"Grant JS, Elliott TR, Weaver M, Bartolucci AA, Giger JN (2002) Telephone intervention with family caregivers of stroke survivors after rehabilitation. Stroke 33(8):2060\u20132065","journal-title":"Stroke"},{"key":"8829_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12984-020-00789-w","volume":"17","author":"Q Qiu","year":"2020","unstructured":"Qiu Q, Cronce A, Patel J, Fluet GG, Mont AJ, Merians AS, Adamovich SV (2020) Development of the home based virtual rehabilitation system (HoVRS) to remotely deliver an intense and customized upper extremity training. J Neuroeng Rehabil 17:1\u201310","journal-title":"J Neuroeng Rehabil"},{"issue":"6","key":"8829_CR5","doi-asserted-by":"publisher","first-page":"4755","DOI":"10.1007\/s10462-021-10116-x","volume":"55","author":"N Gupta","year":"2022","unstructured":"Gupta N, Gupta SK, Pathak RK, Jain V, Rashidi P, Suri JS (2022) Human activity recognition in artificial intelligence framework: a narrative review. Artif Intell Rev 55(6):4755\u20134808","journal-title":"Artif Intell Rev"},{"issue":"9","key":"8829_CR6","doi-asserted-by":"publisher","first-page":"4509","DOI":"10.1007\/s00500-021-06534-2","volume":"26","author":"P Sruthi","year":"2022","unstructured":"Sruthi P, Udgata SK (2022) An improved wi-fi sensing-based human activity recognition using multi-stage deep learning model. Soft Comput 26(9):4509\u20134518","journal-title":"Soft Comput"},{"key":"8829_CR7","doi-asserted-by":"publisher","first-page":"8585","DOI":"10.1007\/s00521-019-04365-9","volume":"32","author":"MF Aslan","year":"2020","unstructured":"Aslan MF, Durdu A, Sabanci K (2020) Human action recognition with bag of visual words using different machine learning methods and hyperparameter optimization. Neural Comput Appl 32:8585\u20138597","journal-title":"Neural Comput Appl"},{"key":"8829_CR8","doi-asserted-by":"publisher","first-page":"75490","DOI":"10.1109\/ACCESS.2019.2922104","volume":"7","author":"R Zhu","year":"2019","unstructured":"Zhu R, Xiao Z, Li Y, Yang M, Tan Y, Zhou L, Lin S, Wen H (2019) Efficient human activity recognition solving the confusing activities via deep ensemble learning. IEEE Access 7:75490\u201375499","journal-title":"IEEE Access"},{"issue":"3","key":"8829_CR9","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1109\/SURV.2012.110112.00192","volume":"15","author":"OD Lara","year":"2013","unstructured":"Lara OD, Labrador MA (2013) A survey on human activity recognition using wearable sensors. IEEE Commun Surv Tutor 15(3):1192\u20131209. https:\/\/doi.org\/10.1109\/SURV.2012.110112.00192","journal-title":"IEEE Commun Surv Tutor"},{"issue":"23","key":"8829_CR10","doi-asserted-by":"publisher","first-page":"6990","DOI":"10.3390\/s20236990","volume":"20","author":"R Ahmed Bhuiyan","year":"2020","unstructured":"Ahmed Bhuiyan R, Ahmed N, Amiruzzaman M, Islam MR (2020) A robust feature extraction model for human activity characterization using 3-axis accelerometer and gyroscope data. Sensors 20(23):6990","journal-title":"Sensors"},{"issue":"6","key":"8829_CR11","doi-asserted-by":"publisher","first-page":"6164","DOI":"10.1109\/JSEN.2022.3148431","volume":"22","author":"L Tong","year":"2022","unstructured":"Tong L, Ma H, Lin Q, He J, Peng L (2022) A novel deep learning Bi-GRU-I model for real-time human activity recognition using inertial sensors. IEEE Sens J 22(6):6164\u20136174","journal-title":"IEEE Sens J"},{"key":"8829_CR12","doi-asserted-by":"publisher","first-page":"56855","DOI":"10.1109\/ACCESS.2020.2982225","volume":"8","author":"K Xia","year":"2020","unstructured":"Xia K, Huang J, Wang H (2020) LSTM-CNN architecture for human activity recognition. IEEE Access 8:56855\u201356866","journal-title":"IEEE Access"},{"issue":"9","key":"8829_CR13","first-page":"1295","volume":"19","author":"D Anguita","year":"2013","unstructured":"Anguita D, Ghio A, Oneto L, Llanas Parra FX, Reyes Ortiz JL (2013) Energy efficient smartphone-based activity recognition using fixed-point arithmetic. J Univ Comput Sci 19(9):1295\u20131314","journal-title":"J Univ Comput Sci"},{"issue":"1","key":"8829_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-09521-1","volume":"12","author":"G Csizmadia","year":"2022","unstructured":"Csizmadia G, Liszkai-Peres K, Ferdinandy B, Mikl\u00f3si \u00c1, Konok V (2022) Human activity recognition of children with wearable devices using lightGBM machine learning. Sci Rep 12(1):1\u201310","journal-title":"Sci Rep"},{"issue":"6","key":"8829_CR15","doi-asserted-by":"publisher","first-page":"5889","DOI":"10.1109\/JSEN.2022.3149337","volume":"22","author":"X Cheng","year":"2022","unstructured":"Cheng X, Zhang L, Tang Y, Liu Y, Wu H, He J (2022) Real-time human activity recognition using conditionally parametrized convolutions on mobile and wearable devices. IEEE Sens J 22(6):5889\u20135901. https:\/\/doi.org\/10.1109\/JSEN.2022.3149337","journal-title":"IEEE Sens J"},{"issue":"3","key":"8829_CR16","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1109\/JBHI.2021.3085602","volume":"26","author":"X Zhang","year":"2022","unstructured":"Zhang X, Yu H, Yang Y, Gu J, Li Y, Zhuang F, Yu D, Ren Z (2022) Harmi: human activity recognition via multi-modality incremental learning. IEEE J Biomed Health Inform 26(3):939\u2013951. https:\/\/doi.org\/10.1109\/JBHI.2021.3085602","journal-title":"IEEE J Biomed Health Inform"},{"issue":"18","key":"8829_CR17","doi-asserted-by":"publisher","first-page":"5114","DOI":"10.3390\/s20185114","volume":"20","author":"Q Ni","year":"2020","unstructured":"Ni Q, Fan Z, Zhang L, Nugent CD, Cleland I, Zhang Y, Zhou N (2020) Leveraging wearable sensors for human daily activity recognition with stacked denoising autoencoders. Sensors 20(18):5114","journal-title":"Sensors"},{"key":"8829_CR18","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1016\/j.ins.2022.06.028","volume":"607","author":"MJ Felicetti","year":"2022","unstructured":"Felicetti MJ, Wang D (2022) Deep stochastic configuration networks with different random sampling strategies. Inf Sci 607:819\u2013830","journal-title":"Inf Sci"},{"issue":"10","key":"8829_CR23","doi-asserted-by":"publisher","first-page":"3466","DOI":"10.1109\/TCYB.2017.2734043","volume":"47","author":"D Wang","year":"2017","unstructured":"Wang D, Li M (2017)\u00a0Stochastic configuration networks: Fundamentals and algorithms.\u00a0IEEE Trans On Cybernetics 47(10): pp. 3466-3479","journal-title":"IEEE Trans On Cybernetics"},{"key":"8829_CR19","unstructured":"Wang Q, Hong Q, Wu S, Dai W (2022) Multi-target stochastic configuration network and applications. IEEE Transactions on Artificial Intelligence"},{"issue":"12","key":"8829_CR20","doi-asserted-by":"publisher","first-page":"5426","DOI":"10.1109\/TNNLS.2020.2967816","volume":"31","author":"J Lu","year":"2020","unstructured":"Lu J, Ding JL, Dai X, Chai T (2020) Ensemble stochastic configuration networks for estimating prediction intervals: a simultaneous robust training algorithm and its application. IEEE Trans Neural Netw Learn Syst 31(12):5426\u20135440","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8829_CR21","doi-asserted-by":"crossref","unstructured":"Kushwaha A, Khare A, Prakash O (2023) Micro-network-based deep convolutional neural network for human activity recognition from realistic and multi-view visual data. Neural Comput Appl 1\u201321","DOI":"10.1007\/s00521-023-08440-0"},{"key":"8829_CR22","doi-asserted-by":"crossref","unstructured":"Dai W, Ning C, Nan J, Wang D (2022) Stochastic configuration networks for imbalanced data classification. Int J Mach Learn Cybern 1\u201313","DOI":"10.1007\/s13042-022-01565-z"},{"issue":"3","key":"8829_CR24","doi-asserted-by":"publisher","first-page":"349","DOI":"10.4310\/SII.2009.v2.n3.a8","volume":"2","author":"T Hastie","year":"2009","unstructured":"Hastie T, Rosset S, Zhu J, Zou H (2009) Multi-class adaboost. Stat Its Interface 2(3):349\u2013360","journal-title":"Stat Its Interface"},{"issue":"5","key":"8829_CR25","doi-asserted-by":"publisher","first-page":"4145","DOI":"10.1007\/s00521-022-07937-4","volume":"35","author":"G Saleem","year":"2023","unstructured":"Saleem G, Bajwa UI, Raza RH (2023) Toward human activity recognition: a survey. Neural Comput Appl 35(5):4145\u20134182","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08829-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08829-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08829-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T00:31:39Z","timestamp":1693355499000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08829-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,4]]},"references-count":25,"journal-issue":{"issue":"28","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["8829"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08829-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,4]]},"assertion":[{"value":"17 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2023","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 declared no potential conflicts of interest with respect to the research, authorship and publication of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}