{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T04:08:06Z","timestamp":1751602086334,"version":"3.41.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"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":["SIViP"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s11760-025-04366-3","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T07:41:37Z","timestamp":1750405297000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A novel spatio-temporal attention-based graph model for patient rehabilitation behavior recognition"],"prefix":"10.1007","volume":"19","author":[{"given":"Hang","family":"Cao","sequence":"first","affiliation":[]},{"given":"Qiang","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Song","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"issue":"5","key":"4366_CR1","first-page":"61443","volume":"16","author":"M Ekong","year":"2024","unstructured":"Ekong, M., Monga, T.S., Daher, J.C., Sashank, M., Soltani, S.R., Nwangene, N.L., Mohammed, C., Halfeld, F.F., AlShelh, L., Fukuya, F.A.: From the intensive care unit to recovery: managing post-intensive care syndrome in critically ill patients. Cureus 16(5), 61443 (2024)","journal-title":"Cureus"},{"issue":"4","key":"4366_CR2","doi-asserted-by":"publisher","first-page":"323","DOI":"10.3390\/muscles3040028","volume":"3","author":"RA Bernardes","year":"2024","unstructured":"Bernardes, R.A., Parola, V., Cruz, A., Correia, N., Neves, H.: Functional rehabilitation for medial gastrocnemius silent contractures to prevent foot and ankle disorders: a review. Muscles 3(4), 323\u2013338 (2024)","journal-title":"Muscles"},{"issue":"1","key":"4366_CR3","doi-asserted-by":"publisher","first-page":"8548","DOI":"10.2196\/rehab.8548","volume":"5","author":"JM Cogollor","year":"2018","unstructured":"Cogollor, J.M., Rojo-Lacal, J., Hermsd\u00f6rfer, J., Ferre, M., Waldmeyer, M.T.A., Giachritsis, C., Armstrong, A., Martinez, J.M.B., Loza, D.A.B., Sebasti\u00e1n, J.M.: Evolution of cognitive rehabilitation after stroke from traditional techniques to smart and personalized home-based information and communication technology systems: literature review. JMIR rehabilitation and assistive technologies 5(1), 8548 (2018)","journal-title":"JMIR rehabilitation and assistive technologies"},{"issue":"4","key":"4366_CR4","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1007\/s10055-024-01065-1","volume":"28","author":"V Mani Bharathi","year":"2024","unstructured":"Mani Bharathi, V., Manimegalai, P., George, S.T., Pamela, D., Mohammed, M.A., Abdulkareem, K.H., Jaber, M.M., Dama\u0161evi\u010dius, R.: A systematic review of techniques and clinical evidence to adopt virtual reality in post-stroke upper limb rehabilitation. Virtual Real. 28(4), 172 (2024)","journal-title":"Virtual Real."},{"issue":"3","key":"4366_CR5","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1161\/CIRCULATIONAHA.122.061046","volume":"147","author":"AL Beatty","year":"2023","unstructured":"Beatty, A.L., Beckie, T.M., Dodson, J., Goldstein, C.M., Hughes, J.W., Kraus, W.E., Martin, S.S., Olson, T.P., Pack, Q.R., Stolp, H.: A new era in cardiac rehabilitation delivery: research gaps, questions, strategies, and priorities. Circulation 147(3), 254\u2013266 (2023)","journal-title":"Circulation"},{"issue":"4","key":"4366_CR6","doi-asserted-by":"publisher","first-page":"124","DOI":"10.4103\/mtsp.mtsp_24_23","volume":"7","author":"O Ayo-Farai","year":"2023","unstructured":"Ayo-Farai, O., Ogundairo, O., Maduka, C.P., Okongwu, C.C., Babarinde, A.O., Sodamade, O.T.: Telemedicine in health care: a review of progress and challenges in africa. Matrix Sci. Pharma 7(4), 124\u2013132 (2023)","journal-title":"Matrix Sci. Pharma"},{"issue":"1","key":"4366_CR7","volume":"3","author":"X Wang","year":"2023","unstructured":"Wang, X., Yu, H., Kold, S., Rahbek, O., Bai, S.: Wearable sensors for activity monitoring and motion control: a review. Biomim. Intell. Robot. 3(1), 100089 (2023)","journal-title":"Biomim. Intell. Robot."},{"key":"4366_CR8","doi-asserted-by":"publisher","first-page":"943","DOI":"10.2147\/IJGM.S453903","volume":"17","author":"UB Khalid","year":"2024","unstructured":"Khalid, U.B., Naeem, M., Stasolla, F., Syed, M.H., Abbas, M., Coronato, A.: Impact of ai-powered solutions in rehabilitation process: recent improvements and future trends. Int. J. Gen. Med. 17, 943\u2013969 (2024)","journal-title":"Int. J. Gen. Med."},{"issue":"1","key":"4366_CR9","doi-asserted-by":"publisher","first-page":"20230060","DOI":"10.57197\/JDR-2023-0060","volume":"3","author":"MF Almufareh","year":"2024","unstructured":"Almufareh, M.F., Kausar, S., Humayun, M., Tehsin, S.: A conceptual model for inclusive technology: advancing disability inclusion through artificial intelligence. J. Disability Res. 3(1), 20230060 (2024)","journal-title":"J. Disability Res."},{"issue":"24","key":"4366_CR10","doi-asserted-by":"publisher","first-page":"7973","DOI":"10.3390\/s24247973","volume":"24","author":"P Lobo","year":"2024","unstructured":"Lobo, P., Morais, P., Murray, P., Vila\u00e7a, J.L.: Trends and innovations in wearable technology for motor rehabilitation, prediction, and monitoring: a comprehensive review. Sensors 24(24), 7973 (2024)","journal-title":"Sensors"},{"issue":"5","key":"4366_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3655620","volume":"23","author":"R Sarwar","year":"2024","unstructured":"Sarwar, R., Perera, M., Teh, P.S., Nawaz, R., Hassan, M.U.: Crossing linguistic barriers: authorship attribution in sinhala texts. ACM Trans. Asian Low-Resour. Lang. Inf. Process. 23(5), 1\u201314 (2024)","journal-title":"ACM Trans. Asian Low-Resour. Lang. Inf. Process."},{"key":"4366_CR12","doi-asserted-by":"publisher","first-page":"33532","DOI":"10.1109\/ACCESS.2021.3061626","volume":"9","author":"H Ramirez","year":"2021","unstructured":"Ramirez, H., Velastin, S.A., Meza, I., Fabregas, E., Makris, D., Farias, G.: Fall detection and activity recognition using human skeleton features. Ieee Access 9, 33532\u201333542 (2021)","journal-title":"Ieee Access"},{"key":"4366_CR13","doi-asserted-by":"crossref","unstructured":"Mathe, E., Maniatis, A., Spyrou, E., Mylonas, P.: A deep learning approach for human action recognition using skeletal information. In: GeNeDis 2018: Computational Biology and Bioinformatics, pp. 105\u2013114 (2020). Springer","DOI":"10.1007\/978-3-030-32622-7_9"},{"key":"4366_CR14","doi-asserted-by":"publisher","first-page":"15911","DOI":"10.1109\/ACCESS.2022.3148132","volume":"10","author":"SB Abdullahi","year":"2022","unstructured":"Abdullahi, S.B., Chamnongthai, K.: American sign language words recognition using spatio-temporal prosodic and angle features: a sequential learning approach. IEEE Access 10, 15911\u201315923 (2022)","journal-title":"IEEE Access"},{"key":"4366_CR15","doi-asserted-by":"publisher","first-page":"88511","DOI":"10.1109\/ACCESS.2023.3305255","volume":"11","author":"SB Abdullahi","year":"2023","unstructured":"Abdullahi, S.B., Chamnongthai, K.: Idf-sign: addressing inconsistent depth features for dynamic sign word recognition. IEEE Access 11, 88511\u201388526 (2023)","journal-title":"IEEE Access"},{"key":"4366_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123258","volume":"248","author":"SB Abdullahi","year":"2024","unstructured":"Abdullahi, S.B., Chamnongthai, K., Bolon-Canedo, V., Cancela, B.: Spatial-temporal feature-based end-to-end fourier network for 3d sign language recognition. Expert Syst. Appl. 248, 123258 (2024)","journal-title":"Expert Syst. Appl."},{"issue":"10","key":"4366_CR17","doi-asserted-by":"publisher","first-page":"12852","DOI":"10.3390\/s131012852","volume":"13","author":"R Khusainov","year":"2013","unstructured":"Khusainov, R., Azzi, D., Achumba, I.E., Bersch, S.D.: Real-time human ambulation, activity, and physiological monitoring: taxonomy of issues, techniques, applications, challenges and limitations. Sensors 13(10), 12852\u201312902 (2013)","journal-title":"Sensors"},{"key":"4366_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103687","volume":"119","author":"Y Liao","year":"2020","unstructured":"Liao, Y., Vakanski, A., Xian, M., Paul, D., Baker, R.: A review of computational approaches for evaluation of rehabilitation exercises. Comput. Biol. Med. 119, 103687 (2020)","journal-title":"Comput. Biol. Med."},{"issue":"11","key":"4366_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13042-024-02254-9","volume":"15","author":"H Ren","year":"2024","unstructured":"Ren, H., Zhang, X., Shi, Y., Liang, K.: Enhanced spatial-temporal dynamics in pose forecasting through multi-graph convolution networks. Int. J. Mach. Learn. Cybern. 15(11), 1\u201315 (2024)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"4366_CR20","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.patrec.2014.04.011","volume":"48","author":"JK Aggarwal","year":"2014","unstructured":"Aggarwal, J.K., Xia, L.: Human activity recognition from 3d data: a review. Pattern Recogn. Lett. 48, 70\u201380 (2014)","journal-title":"Pattern Recogn. Lett."},{"key":"4366_CR21","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.engappai.2018.08.014","volume":"77","author":"C Dhiman","year":"2019","unstructured":"Dhiman, C., Vishwakarma, D.K.: A review of state-of-the-art techniques for abnormal human activity recognition. Eng. Appl. Artif. Intell. 77, 21\u201345 (2019)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"4366_CR22","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/j.neucom.2022.09.071","volume":"512","author":"R Yue","year":"2022","unstructured":"Yue, R., Tian, Z., Du, S.: Action recognition based on rgb and skeleton data sets: a survey. Neurocomputing 512, 287\u2013306 (2022)","journal-title":"Neurocomputing"},{"key":"4366_CR23","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.patcog.2017.10.033","volume":"76","author":"JC Nunez","year":"2018","unstructured":"Nunez, J.C., Cabido, R., Pantrigo, J.J., Montemayor, A.S., Velez, J.F.: Convolutional neural networks and long short-term memory for skeleton-based human activity and hand gesture recognition. Pattern Recogn. 76, 80\u201394 (2018)","journal-title":"Pattern Recogn."},{"issue":"11","key":"4366_CR24","doi-asserted-by":"publisher","first-page":"1332","DOI":"10.3390\/bioengineering10111332","volume":"10","author":"S Umirzakova","year":"2023","unstructured":"Umirzakova, S., Mardieva, S., Muksimova, S., Ahmad, S., Whangbo, T.: Enhancing the super-resolution of medical images: introducing the deep residual feature distillation channel attention network for optimized performance and efficiency. Bioengineering 10(11), 1332 (2023)","journal-title":"Bioengineering"},{"issue":"2","key":"4366_CR25","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1109\/TAI.2021.3076974","volume":"2","author":"T Ahmad","year":"2021","unstructured":"Ahmad, T., Jin, L., Zhang, X., Lai, S., Tang, G., Lin, L.: Graph convolutional neural network for human action recognition: a comprehensive survey. IEEE Trans. Artif. Intell. 2(2), 128\u2013145 (2021)","journal-title":"IEEE Trans. Artif. Intell."},{"key":"4366_CR26","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3509500","author":"N Naz","year":"2024","unstructured":"Naz, N., Sajid, H., Ali, S., Hasan, O., Ehsan, M.K.: Mse-gcn: a multiscale spatiotemporal feature aggregation enhanced efficient graph convolutional network for dynamic sign language recognition. IEEE Trans. Emerg. Top. Comput. Intell. (2024). https:\/\/doi.org\/10.1109\/TETCI.2024.3509500","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"issue":"6","key":"4366_CR27","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.3390\/s22062091","volume":"22","author":"M Feng","year":"2022","unstructured":"Feng, M., Meunier, J.: Skeleton graph-neural-network-based human action recognition: a survey. Sensors 22(6), 2091 (2022)","journal-title":"Sensors"},{"key":"4366_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2024.109633","volume":"120","author":"A Roy","year":"2024","unstructured":"Roy, A., Tiwari, A., Saurav, S., Singh, S.: Enhancing skeleton-based action recognition using a knowledge-driven shift graph convolutional network. Comput. Electr. Eng. 120, 109633 (2024)","journal-title":"Comput. Electr. Eng."},{"key":"4366_CR29","doi-asserted-by":"publisher","first-page":"112470","DOI":"10.1109\/ACCESS.2024.3423765","volume":"12","author":"X Zhao","year":"2024","unstructured":"Zhao, X., Zhang, H., Ban, Q., Qu, H.: Accuracy and adaptability improvement in aerobic training: integration of self-attention mechanisms in 3d pose estimation and kinematic modeling. IEEE Access 12, 112470\u2013112481 (2024)","journal-title":"IEEE Access"},{"key":"4366_CR30","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/j.aej.2024.10.099","volume":"112","author":"S Yuan","year":"2025","unstructured":"Yuan, S., Zhou, L.: Gta-net: an iot-integrated 3d human pose estimation system for real-time adolescent sports posture correction. Alex. Eng. J. 112, 585\u2013597 (2025)","journal-title":"Alex. Eng. J."},{"key":"4366_CR31","doi-asserted-by":"publisher","first-page":"16526","DOI":"10.1109\/ACCESS.2023.3246127","volume":"11","author":"Z Xie","year":"2023","unstructured":"Xie, Z., Zheng, G., Miao, L., Huang, W.: Stgl-gcn: spatial-temporal mixing of global and local self-attention graph convolutional networks for human action recognition. IEEE Access 11, 16526\u201316532 (2023)","journal-title":"IEEE Access"},{"key":"4366_CR32","doi-asserted-by":"crossref","unstructured":"Kryeem, A., Raz, S., Eluz, D., Itah, D., Hel-Or, H., Shimshoni, I.: Personalized monitoring in home healthcare: An assistive system for post hip replacement rehabilitation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1868\u20131877 (2023)","DOI":"10.1109\/ICCVW60793.2023.00201"},{"key":"4366_CR33","doi-asserted-by":"crossref","unstructured":"Edriss, S., Romagnoli, C., Caprioli, L., Zanela, A., Panichi, E., Campoli, F., Padua, E., Annino, G., Bonaiuto, V.: The role of emergent technologies in the dynamic and kinematic assessment of human movement in sport and clinical applications. Appl. Sci. 14(3), 1012 (2024)","DOI":"10.3390\/app14031012"},{"issue":"21","key":"4366_CR34","doi-asserted-by":"publisher","first-page":"8950","DOI":"10.3390\/s23218950","volume":"23","author":"DA Szabo","year":"2023","unstructured":"Szabo, D.A., Neagu, N., Teodorescu, S., Apostu, M., Predescu, C., P\u00e2rvu, C., Veres, C.: The role and importance of using sensor-based devices in medical rehabilitation: a literature review on the new therapeutic approaches. Sensors 23(21), 8950 (2023)","journal-title":"Sensors"},{"issue":"19","key":"4366_CR35","doi-asserted-by":"publisher","first-page":"8982","DOI":"10.1007\/s10489-024-05645-1","volume":"54","author":"FX Gaya-Morey","year":"2024","unstructured":"Gaya-Morey, F.X., Manresa-Yee, C., Buades-Rubio, J.M.: Deep learning for computer vision based activity recognition and fall detection of the elderly: a systematic review. Appl. Intell. 54(19), 8982\u20139007 (2024)","journal-title":"Appl. Intell."},{"issue":"9","key":"4366_CR36","doi-asserted-by":"publisher","first-page":"1988","DOI":"10.3390\/s19091988","volume":"19","author":"L Mart\u00ednez-Villase\u00f1or","year":"2019","unstructured":"Mart\u00ednez-Villase\u00f1or, L., Ponce, H., Brieva, J., Moya-Albor, E., N\u00fa\u00f1ez-Mart\u00ednez, J., Pe\u00f1afort-Asturiano, C.: Up-fall detection dataset: a multimodal approach. Sensors 19(9), 1988 (2019)","journal-title":"Sensors"},{"issue":"7","key":"4366_CR37","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2013","unstructured":"Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3. 6m: large scale datasets and predictive methods for 3d human sensing in natural environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1325\u20131339 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"4366_CR38","doi-asserted-by":"publisher","first-page":"2575","DOI":"10.1109\/TVCG.2023.3247075","volume":"29","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Zhang, H., Li, Y., He, K., Xu, D.: Skeleton-based human action recognition via large-kernel attention graph convolutional network. IEEE Trans. Visual Comput. Graphics 29(5), 2575\u20132585 (2023)","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"key":"4366_CR39","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"4366_CR40","unstructured":"Li, Y., Tarlow, D., Brockschmidt, M., Zemel, R.: Gated graph sequence neural networks. arXiv preprint arXiv:1511.05493 (2015)"},{"key":"4366_CR41","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural inf. process. syst. 30 (2017)"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04366-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04366-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04366-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T14:44:20Z","timestamp":1751553860000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04366-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,20]]},"references-count":41,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["4366"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04366-3","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2025,6,20]]},"assertion":[{"value":"20 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 May 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"764"}}