Good-Eye: A Combined Computer-Vision and Physiological-Sensor Based Device for Full-Proof Prediction and Detection of Fall of Adults - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

Good-Eye: A Combined Computer-Vision and Physiological-Sensor Based Device for Full-Proof Prediction and Detection of Fall of Adults

Laavanya Rachakonda
  • Fonction : Auteur
  • PersonId : 1112789
Akshay Sharma
  • Fonction : Auteur
  • PersonId : 1112790
Saraju P. Mohanty
  • Fonction : Auteur
  • PersonId : 1112791
Elias Kougianos
  • Fonction : Auteur
  • PersonId : 1112792

Résumé

It is imperative to find the most accurate way to detect falls in elders to help mitigate the disastrous effects of such unfortunate injuries. In order to mitigate fall related accidents, we propose the Good-Eye System, an Internet of Things (IoT) enabled Edge Level Device which works when there is an orientation change detected by a camera, and monitors physiological signal parameters. If the observed change is greater than the set threshold, the user is notified with information regarding a prediction of fall or a detection of fall, using LED lights. The Good-Eye System has a remote wall-attached camera to monitor continuously the subject as long as the person is in a room, along with a camera attached to a wearable to increase the accuracy of the model. The observed accuracy of the Good-Eye System as a whole is approximately 95%.
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hal-03371597 , version 1 (08-10-2021)

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Laavanya Rachakonda, Akshay Sharma, Saraju P. Mohanty, Elias Kougianos. Good-Eye: A Combined Computer-Vision and Physiological-Sensor Based Device for Full-Proof Prediction and Detection of Fall of Adults. 2nd IFIP International Internet of Things Conference (IFIPIoT), Oct 2019, Tampa, FL, United States. pp.273-288, ⟨10.1007/978-3-030-43605-6_16⟩. ⟨hal-03371597⟩
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