Deep Recurrent Neural Networks for Edge Monitoring of Personal Risk and Warning Situations
Joint Authors
Torti, Emanuele
Musci, Mirto
Guareschi, Federico
Leporati, Francesco
Piastra, Marco
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-13
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Accidental falls are the main cause of fatal and nonfatal injuries, which typically lead to hospital admissions among elderly people.
A wearable system capable of detecting unintentional falls and sending remote notifications will clearly improve the quality of the life of such subjects and also helps to reduce public health costs.
In this paper, we describe an edge computing wearable system based on deep learning techniques.
In particular, we give special attention to the description of the classification and communication modules, which have been developed by keeping in mind the limits in terms of computational power, memory occupancy, and power consumption of the designed wearable device.
The system thus developed is capable of classifying 3D-accelerometer signals in real-time and to issue remote alerts while keeping power consumption low and improving on the present state-of-the-art solutions in the literature.
American Psychological Association (APA)
Torti, Emanuele& Musci, Mirto& Guareschi, Federico& Leporati, Francesco& Piastra, Marco. 2019. Deep Recurrent Neural Networks for Edge Monitoring of Personal Risk and Warning Situations. Scientific Programming،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1210769
Modern Language Association (MLA)
Torti, Emanuele…[et al.]. Deep Recurrent Neural Networks for Edge Monitoring of Personal Risk and Warning Situations. Scientific Programming No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1210769
American Medical Association (AMA)
Torti, Emanuele& Musci, Mirto& Guareschi, Federico& Leporati, Francesco& Piastra, Marco. Deep Recurrent Neural Networks for Edge Monitoring of Personal Risk and Warning Situations. Scientific Programming. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1210769
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210769