{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T17:21:46Z","timestamp":1793035306002,"version":"4.5.0"},"reference-count":46,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T00:00:00Z","timestamp":1786320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universit\u00e9 Marie et Louis Pasteur","award":["4718 ANR-23-CPJ1-0010-01"],"award-info":[{"award-number":["4718 ANR-23-CPJ1-0010-01"]}]},{"award":["4718 ANR-23-CPJ1-0010-01"],"award-info":[{"award-number":["4718 ANR-23-CPJ1-0010-01"]}],"id":[{"id":"https:\/\/ror.org\/04asdee31","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Falls represent a threat to older adults, overload healthcare systems, and reduce quality of life. Vision-based fall detection has advanced recently through deep learning, yet most proposed models lack validation on physical hardware and do not report inference-time metrics. This systematic review, following PRISMA and Kitchenham guidelines, targets this gap. We focus exclusively on vision-based systems that report inference speed on a specified device. We define real-time performance using a threshold of 10 fps, based on the reported duration of the critical fall phase in real-life falls. From 588 records across IEEE Xplore, ACM Digital Library, Web of Science Core Collection, and PubMed (2019\u20132024), only 11 met all inclusion criteria, highlighting how few studies validate real-time performance on physical hardware. The findings show that CNN-based architectures dominate algorithm choice, edge devices dominate deployment platforms, and optimization remains central to real-time inference on constrained hardware. Across these studies, we identify two persistent limitations: no real-world testing with older adults and reliance on small, controlled datasets with simulated falls.<\/jats:p>","DOI":"10.3390\/s26165069","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T15:10:24Z","timestamp":1786374624000},"page":"5069","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Real-Time Vision-Based Fall Detection Systems for the Elderly: A Systematic Review"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0553-3315","authenticated-orcid":false,"given":"Mahammad","family":"Nabizade","sequence":"first","affiliation":[{"name":"SINERGIES (UR 4662), Universit\u00e9 Marie et Louis Pasteur, 25030 Besan\u00e7on, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4178-0432","authenticated-orcid":false,"given":"R\u00e9da","family":"Yahiaoui","sequence":"additional","affiliation":[{"name":"SINERGIES (UR 4662), Universit\u00e9 Marie et Louis Pasteur, 25030 Besan\u00e7on, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabelle","family":"Lajoie","sequence":"additional","affiliation":[{"name":"SINERGIES (UR 4662), Universit\u00e9 Marie et Louis Pasteur, 25030 Besan\u00e7on, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nassima","family":"Nacer","sequence":"additional","affiliation":[{"name":"LyRIDS, ECE, 75015 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7798-2060","authenticated-orcid":false,"given":"Fr\u00e9d\u00e9ric","family":"Auber","sequence":"additional","affiliation":[{"name":"Department of Pediatric Surgery, SINERGIES (UR 4662), Universit\u00e9 Marie et Louis Pasteur, CHU Besan\u00e7on, 25030 Besan\u00e7on, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9509-4681","authenticated-orcid":false,"given":"Moustafa","family":"Fayad","sequence":"additional","affiliation":[{"name":"SINERGIES (UR 4662), Universit\u00e9 Marie et Louis Pasteur, 25030 Besan\u00e7on, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"ref_1","unstructured":"United Nations Population Fund (2025, December 04). 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