{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T17:08:11Z","timestamp":1771520891435,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T00:00:00Z","timestamp":1695600000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T00:00:00Z","timestamp":1695600000000},"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":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17036-8","type":"journal-article","created":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T08:02:10Z","timestamp":1695628930000},"page":"33019-33030","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Real-time yoga pose classification with 3-D pose estimation model with LSTM"],"prefix":"10.1007","volume":"83","author":[{"given":"Ratnesh Prasad","family":"Srivastava","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6362-4476","authenticated-orcid":false,"given":"Lokendra Singh","family":"Umrao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramjeet Singh","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,25]]},"reference":[{"issue":"41","key":"17036_CR1","doi-asserted-by":"publisher","first-page":"30509","DOI":"10.1007\/s11042-020-09004-3","volume":"79","author":"DR Beddiar","year":"2020","unstructured":"Beddiar DR, Nini B, Sabokrou M, Hadid A (2020) Vision-based human activity recognition: a survey. Multimedia Tools and Applications 79(41):30509\u201330555","journal-title":"Multimedia Tools and Applications"},{"issue":"10","key":"17036_CR2","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2016","unstructured":"Greff K, Srivastava RK, Koutn\u00edk J, Steunebrink BR, Schmidhuber J (2016) LSTM: A search space odyssey. IEEE transactions on neural networks and learning systems 28(10):2222\u20132232","journal-title":"IEEE transactions on neural networks and learning systems"},{"key":"17036_CR3","first-page":"205","volume":"33","author":"M Lu\u0161trek","year":"2009","unstructured":"Lu\u0161trek M, Bo\u0161tjan K (2009) Fall detection and activity recognition with machine learning. Informatica 33:205\u2013212","journal-title":"Informatica"},{"key":"17036_CR4","first-page":"76","volume":"71","author":"CY Ma","year":"2019","unstructured":"Ma CY, Chen MH, Kira Z, AlRegib G (2019) TS-LSTM and temporal-inception: Exploiting spatiotemporal dynamics for activity recognition. Signal Processing: Image Communication 71:76\u201387","journal-title":"Signal Processing: Image Communication"},{"issue":"6","key":"17036_CR5","doi-asserted-by":"publisher","first-page":"1772","DOI":"10.17762\/turcomat.v12i6.4032","volume":"12","author":"VDPP Nagalakshmi","year":"2021","unstructured":"Nagalakshmi VDPP (2021) The Analysis of the Impact of Yoga on Healthcare and Conventional Strategies for Human Pose Recognition. Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12(6):1772\u20131783","journal-title":"Turkish Journal of Computer and Mathematics Education (TURCOMAT)"},{"key":"17036_CR6","unstructured":"Ramachandra S., Hoelzemann A., Van L. K. (2021) Transformer Networks for Data Augmentation of Human Physical Activity Recognition. arXiv preprint arXiv:2109.01081"},{"key":"17036_CR7","doi-asserted-by":"crossref","unstructured":"Ann O C, Theng L B (2014) Human activity recognition: a review. In 2014 IEEE international conference on control system, computing and engineering (ICCSCE 2014) 389-393","DOI":"10.1109\/ICCSCE.2014.7072750"},{"key":"17036_CR8","doi-asserted-by":"crossref","unstructured":"Jin X, Yao Y., Jiang Q, Huang X, Zhang J, Zhang X, & Zhang K (2015) Virtual personal trainer via the kinect sensor. In 2015 IEEE 16th international conference on communication technology (ICCT) 460-463","DOI":"10.1109\/ICCT.2015.7399879"},{"key":"17036_CR9","unstructured":"Quan J, Xu L, Xu R, Tong T, & Su J (2019) DaTscan SPECT Image Classification for Parkinson's Disease. arXiv preprint arXiv:1909.04142."},{"issue":"2021","key":"17036_CR10","first-page":"1","volume":"1110","author":"J Jose","year":"2021","unstructured":"Jose J, Shailesh S (2021) Yoga Asana Identification: A Deep Learning Approach. In IOP Conference Series: Materials Science and Engineering 1110(2021):1\u201310","journal-title":"In IOP Conference Series: Materials Science and Engineering"},{"key":"17036_CR11","doi-asserted-by":"crossref","unstructured":"Agrawal Y, Shah Y, Sharma A (2020) Implementation of machine learning technique for identification of yoga poses. In 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT) 40-43","DOI":"10.1109\/CSNT48778.2020.9115758"},{"issue":"12","key":"17036_CR12","doi-asserted-by":"publisher","first-page":"9349","DOI":"10.1007\/s00521-019-04232-7","volume":"31","author":"SK Yadav","year":"2019","unstructured":"Yadav SK, Singh A, Gupta A, Raheja JL (2019) Real-time Yoga recognition using deep learning. Neural Computing and Applications 31(12):9349\u20139361","journal-title":"Neural Computing and Applications"},{"issue":"12","key":"17036_CR13","doi-asserted-by":"publisher","first-page":"6427","DOI":"10.1007\/s00521-020-05405-5","volume":"33","author":"S Jain","year":"2021","unstructured":"Jain S, Rustagi A, Saurav S, Saini R, Singh S (2021) Three-dimensional CNN-inspired deep learning architecture for Yoga pose recognition in the real-world environment. Neural Computing and Applications 33(12):6427\u20136441","journal-title":"Neural Computing and Applications"},{"key":"17036_CR14","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1016\/j.neucom.2020.06.032","volume":"410","author":"Z Zhang","year":"2020","unstructured":"Zhang Z, Lv Z, Gan C, Zhu Q (2020) Human action recognition using convolutional LSTM and fully-connected LSTM with different attentions. Neurocomputing 410:304\u2013316","journal-title":"Neurocomputing"},{"key":"17036_CR15","doi-asserted-by":"crossref","unstructured":"Palanimeera J, Ponmozhi K (2021). Classification of yoga pose using machine learning techniques. Materials Today: Proceedings 37: 2930-8)(2933","DOI":"10.1016\/j.matpr.2020.08.700"},{"key":"17036_CR16","doi-asserted-by":"crossref","unstructured":"] Donahue J, Anne Hendricks L, Guadarrama S, Rohrbach M, Venugopalan S, Saenko K, Darrell T (2015) Long-term recurrent convolutional networks for visual recognition and description. In Proceedings of the IEEE conference on computer vision and pattern recognition 2625-2634","DOI":"10.1109\/CVPR.2015.7298878"},{"issue":"1","key":"17036_CR17","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TPAMI.2012.59","volume":"35","author":"S Ji","year":"2012","unstructured":"Ji S, Xu W, Yang M, Yu K (2012) 3D convolutional neural networks for human action recognition. IEEE transactions on pattern analysis and machine intelligence 35(1):221\u2013231","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"17036_CR18","unstructured":"Wang L, Xiong Y, Wang Z, Qiao Y (2015) Towards good practices for very deep two-stream convnets. arXiv preprint arXiv:1507.02159."},{"key":"17036_CR19","doi-asserted-by":"crossref","unstructured":"Peng X, Zou C, Qiao Y, Peng Q (2014) Action recognition with stacked fisher vectors. In European Conference on Computer Vision 581-595","DOI":"10.1007\/978-3-319-10602-1_38"},{"key":"17036_CR20","unstructured":"Simonyan K, Zisserman A (2014) Two-stream convolutional networks for action recognition in videos. arXiv preprint arXiv:1406.2199."},{"key":"17036_CR21","doi-asserted-by":"crossref","unstructured":"Taylor G W, Fergus R, LeCun Y, Bregler C (2010) Convolutional learning of spatio-temporal features. In European conference on computer vision and Springer, Berlin, Heidelberg 140-153","DOI":"10.1007\/978-3-642-15567-3_11"},{"key":"17036_CR22","unstructured":"Bazarevsky V, Grishchenko I, Raveendran K, Zhu T, Zhang F, Grundmann M (2020). BlazePose: On-device Real-time Body Pose tracking. arXiv preprint arXiv:2006.10204"},{"issue":"8","key":"17036_CR23","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural computation 9(8):1735\u20131780","journal-title":"Neural computation"},{"key":"17036_CR24","unstructured":"https:\/\/machinelearningmastery.com\/deep-learning-models-for-human-activity-recognition. Last accessed on 03-10-2021"},{"key":"17036_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-022-03910-0","author":"S Garg","year":"2022","unstructured":"Garg S, Saxena A, Gupta R (2022) Yoga pose classification: a CNN and MediaPipe inspired deep learning approach for real-world application. Journal of Ambient Intelligence and Humanized Computing. https:\/\/doi.org\/10.1007\/s12652-022-03910-0","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"17036_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-022-01618-8","volume":"4","author":"FB Ashraf","year":"2023","unstructured":"Ashraf FB, Islam MU, Kabir MR, Uddin J (2023) YoNet: A Neural Network for Yoga Pose Classification. SN Computer Science 4:1\u20139","journal-title":"SN Computer Science"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17036-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17036-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17036-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T07:08:25Z","timestamp":1709881705000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17036-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,25]]},"references-count":26,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["17036"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17036-8","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,25]]},"assertion":[{"value":"2 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 June 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 September 2023","order":4,"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 conflict of interest, financial or otherwise.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}