{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T21:55:29Z","timestamp":1757454929371,"version":"3.37.3"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100011665","name":"Deanship of Scientific Research, King Saud University, through the Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3091838","type":"journal-article","created":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T19:36:50Z","timestamp":1624477010000},"page":"94299-94308","source":"Crossref","is-referenced-by-count":13,"title":["FallDeF5: A Fall Detection Framework Using 5G-Based Deep Gated Recurrent Unit Networks"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5343-8370","authenticated-orcid":false,"given":"Mabrook S.","family":"Al-Rakhami","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8512-9687","authenticated-orcid":false,"given":"Abdu","family":"Gumaei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3256-3233","authenticated-orcid":false,"given":"Meteb","family":"Altaf","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3479-3606","authenticated-orcid":false,"given":"Mohammad Mehedi","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7479-7102","authenticated-orcid":false,"given":"Bader Fahad","family":"Alkhamees","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5302-1150","authenticated-orcid":false,"given":"Khan","family":"Muhammad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4039-891X","authenticated-orcid":false,"given":"Giancarlo","family":"Fortino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.05.004"},{"key":"ref38","article-title":"Fall detection algorithm based on accelerometer and gyroscope sensor data using recurrent neural networks","volume":"258","author":"wisesa","year":"2019","journal-title":"IOP Conf Ser Earth Environ Sci"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.maturitas.2017.03.317"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2009.2030171"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103520"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000204"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.3233\/BME-151452"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3347122.3347126"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/technologies8040072"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s00391-013-0559-8"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cobme.2019.08.015"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2019.2898891"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2019.2955141"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1519\/JPT.0b013e3182abe779"},{"key":"ref13","article-title":"AI-enabled wearable and flexible electronics for assessing full personal exposures","volume":"1","author":"shan","year":"2020","journal-title":"Innovation"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1177\/1847979017750669"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.12792\/icisip2017.077"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ISPA.2017.8073568"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-019-00692-y"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/DASC\/PiCom\/DataCom\/CyberSciTec.2018.00138"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2020.011740"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/s18103363"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3004779"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCP.2016.7737121"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ISPASS.2015.7095802"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.12.013"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-018-7407-3"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.113972"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2009.2031316"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2014.6780921"},{"volume":"3","journal-title":"The 2015 Ageing Report Economic and Budgetary Projections for the 28 EU Member States (2013&#x2013;2060)","year":"2015","key":"ref2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/GCCE.2016.7800404"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/2167160"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05328-1"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2920014"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6898-0"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0140929"},{"key":"ref24","first-page":"10536","article-title":"Complex gated recurrent neural networks","volume":"31","author":"wolter","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref41","article-title":"Online fall detection using recurrent neural networks","author":"musci","year":"2018","journal-title":"arXiv 1804 04976"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1504\/IJWMC.2020.104776"},{"key":"ref44","first-page":"133","article-title":"Experimentation and analysis of ensemble deep learning in IoT applications","volume":"5","author":"mauldin","year":"2019","journal-title":"Open Journal of the Internet of Things"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.02.026"},{"key":"ref43","first-page":"259","article-title":"A smartwatch-based assistance system for the elderly performing fall detection, unusual inactivity recognition and medication reminding","author":"deutsch","year":"2016","journal-title":"EHealthcom"},{"key":"ref25","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"2014","journal-title":"arXiv 1412 3555"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09462896.pdf?arnumber=9462896","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:56:44Z","timestamp":1639771004000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9462896\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3091838","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2021]]}}}