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Communication dans un congrès

Integrated monitoring system for fall detection in elderly

Abstract :

Falling and its resulting injuries are an important public health problem for older adults. The National Safety Council estimates that persons over the age of 65 have the highest mortality rate (death rate) from injuries. The risk of falling increases with age; one of three adults 65 or older falls every year. Demographic predictions of population aged 65 and over suggest the need for telemedicine applications in the eldercare domain. This paper presents an integrated monitoring system for the detection of people falls in home environment. The system consist of combining low level features extracted from a video and heart rate tracking in order to classify the fall event. The extracted data will be processed by a neural network for classifying the events in two classes: fall and not fall. Reliable recognition rate of experimental results underlines satisfactory performance of our system.

Type de document :
Communication dans un congrès
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Contributeur : Okina Univ Angers Connectez-vous pour contacter le contributeur
Soumis le : mardi 16 novembre 2021 - 12:24:34
Dernière modification le : vendredi 17 décembre 2021 - 10:30:33
Archivage à long terme le : : jeudi 17 février 2022 - 19:27:52


Fichiers produits par l'(les) auteur(s)




Shadi Khawandi, Bassam Daya, Pierre Chauvet. Integrated monitoring system for fall detection in elderly. International Conference on Audio, Language and Image Processing (ICALIP 2012), 2012, Shanghai, China, Chine. pp.62-67, ⟨10.1109/ICALIP.2012.6376585⟩. ⟨hal-03430621⟩



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