{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T12:48:07Z","timestamp":1765370887699,"version":"3.46.0"},"reference-count":16,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"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":["Iran J Comput Sci"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s42044-025-00313-0","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:21:47Z","timestamp":1753392107000},"page":"2255-2268","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Catch before they fall: a pose-guided attention framework for indoor safety"],"prefix":"10.1007","volume":"8","author":[{"given":"Ruchi","family":"Jayaswal","sequence":"first","affiliation":[]},{"given":"Mohd. Aquib","family":"Ansari","sequence":"additional","affiliation":[]},{"given":"Arvind","family":"Mewada","sequence":"additional","affiliation":[]},{"given":"Shahnawaz","family":"Ahmad","sequence":"additional","affiliation":[]},{"given":"Anchal","family":"Pathak","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"313_CR1","unstructured":"World Health Organization: Injuries and Violence. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/injuries-and-violence (2023). Accessed 20 May 2025"},{"key":"313_CR2","doi-asserted-by":"crossref","unstructured":"Singh, D.K., Ansari, M.A., Pallawi, S.: Computer vision based visual activity classification through deep learning approaches. In: 2022 IEEE Region 10 Symposium (TENSYMP), pp. 1\u20135. IEEE (2022)","DOI":"10.1109\/TENSYMP54529.2022.9864443"},{"key":"313_CR3","doi-asserted-by":"crossref","unstructured":"Ansari, M.A, Ahmad, S., Mewada, A., Maurya, S.K.: Posturalnet, an advanced architecture to detect shoplifting at megastores. In: 2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT), pp. 863\u2013867. IEEE (2025)","DOI":"10.1109\/CSNT64827.2025.10968916"},{"key":"313_CR4","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2021.692865","volume":"13","author":"X Yu","year":"2021","unstructured":"Yu, X., Jang, J., Xiong, S.: A large-scale open motion dataset (KFall) and benchmark algorithms for detecting pre-impact fall of the elderly using wearable inertial sensors. Front. Aging Neurosci. 13, 692865 (2021)","journal-title":"Front. Aging Neurosci."},{"key":"313_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.measen.2022.100614","volume":"25","author":"P Kulurkar","year":"2023","unstructured":"Kulurkar, P., Kumar, D.C., Bharathi, V.C., Monikavishnuvarthini, A., Dhakne, A., Preethi, P.: Ai based elderly fall prediction system using wearable sensors: a smart home-care technology with IOT. Meas. Sens. 25, 100614 (2023)","journal-title":"Meas. Sens."},{"issue":"22","key":"313_CR6","doi-asserted-by":"publisher","first-page":"15967","DOI":"10.1007\/s00521-021-06795-w","volume":"35","author":"P Wang","year":"2023","unstructured":"Wang, P., Li, Q., Yin, P., Zhonghao Wang, Yu., Ling, R.G., Li, Y.: A convolution neural network approach for fall detection based on adaptive channel selection of UWB radar signals. Neural Comput. Appl. 35(22), 15967\u201315980 (2023)","journal-title":"Neural Comput. Appl."},{"issue":"2","key":"313_CR7","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1109\/TCE.2019.2909698","volume":"65","author":"CN Phyo","year":"2019","unstructured":"Phyo, C.N., Zin, T.T., Tin, P.: Deep learning for recognizing human activities using motions of skeletal joints. IEEE Trans. Consum. Electron. 65(2), 243\u2013252 (2019). https:\/\/doi.org\/10.1109\/TCE.2019.2909698","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"6","key":"313_CR8","doi-asserted-by":"publisher","first-page":"2374","DOI":"10.3390\/app14062374","volume":"14","author":"A Elwaly","year":"2024","unstructured":"Elwaly, A., Abdellatif, A., El-Shaer, Y.: New eldercare robot with path-planning and fall-detection capabilities. Appl. Sci. 14(6), 2374 (2024)","journal-title":"Appl. Sci."},{"key":"313_CR9","unstructured":"Qu, Z., Huang, T., Ji, Y., Li, Y.: Physics sensor based deep learning fall detection system. Preprint. arXiv:2403.06994 (2024)"},{"issue":"6","key":"313_CR10","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.3390\/electronics13061066","volume":"13","author":"W Guo","year":"2024","unstructured":"Guo, W., Liu, X., Chenghong, L., Jing, L.: PIFall: a pressure insole-based fall detection system for the elderly using ResNet3D. Electronics 13(6), 1066 (2024)","journal-title":"Electronics"},{"key":"313_CR11","doi-asserted-by":"crossref","unstructured":"Mahmoud, M., Osama, M., Milad, A., Raafat, J., Elkafrawy, P., Fawzi, S.: Sudden fall detection and prediction using ai techniques. In: 2024 21st Learning and Technology Conference (L &T), pp. 308\u2013312. IEEE (2024)","DOI":"10.1109\/LT60077.2024.10469410"},{"key":"313_CR12","doi-asserted-by":"crossref","unstructured":"Kurchaniya, D., Kumar, S.: A framework for human activity recognition in multiview environment based on URILBP and ConvSTLSTM. In: 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN), pp. 1036\u20131041. IEEE (2024)","DOI":"10.1109\/CICN63059.2024.10847457"},{"key":"313_CR13","first-page":"141","volume":"23","author":"MA Ansari","year":"2023","unstructured":"Ansari, M.A., Singh, D.K.: Optimized parameter tuning in a recurrent learning process for shoplifting activity classification. Cybern. Inf. Technol. 23, 141\u2013160 (2023)","journal-title":"Cybern. Inf. Technol."},{"key":"313_CR14","doi-asserted-by":"crossref","unstructured":"Ahn, D., Kim, S., Hong, H., Ko, B.C.: Star-transformer: a spatio-temporal cross attention transformer for human action recognition. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 3330\u20133339 (2023)","DOI":"10.1109\/WACV56688.2023.00333"},{"key":"313_CR15","unstructured":"Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C-L., Yong, M., Lee, J., et al.: Mediapipe: A framework for perceiving and processing reality. In: Third Workshop on Computer Vision for AR\/VR at IEEE Computer Vision and Pattern Recognition (CVPR), vol. 2019 (2019)"},{"key":"313_CR16","doi-asserted-by":"crossref","unstructured":"Kushwaha, A., Khare, A: Human activity recognition in video sequences based on the integration of optical flow and appearance of human objects. In: Robotics, Control and Computer Vision: Select Proceedings of ICRCCV 2022, pp. 117\u2013125. Springer (2023)","DOI":"10.1007\/978-981-99-0236-1_9"}],"container-title":["Iran Journal of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42044-025-00313-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42044-025-00313-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42044-025-00313-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T09:10:24Z","timestamp":1765357824000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42044-025-00313-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"references-count":16,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["313"],"URL":"https:\/\/doi.org\/10.1007\/s42044-025-00313-0","relation":{},"ISSN":["2520-8438","2520-8446"],"issn-type":[{"type":"print","value":"2520-8438"},{"type":"electronic","value":"2520-8446"}],"subject":[],"published":{"date-parts":[[2025,7,24]]},"assertion":[{"value":"15 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 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 that there is no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}