NurseNet: Monitoring Elderly Levels of Activity with a Piezoelectric Floor.
activity monitoring
deep learning
floor sensor
piezoelectric sensor
pressure sensor
sparse dictionary learning
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
06 Sep 2019
06 Sep 2019
Historique:
received:
02
08
2019
revised:
30
08
2019
accepted:
02
09
2019
entrez:
7
9
2019
pubmed:
7
9
2019
medline:
7
9
2019
Statut:
epublish
Résumé
Monitoring the activity of elderly individuals in nursing homes is key, as it has been shown that physical activity leads to significant health improvement. In this work, we introduce NurseNet, a system that combines an unobtrusive, affordable, and robust piezoelectric floor sensor with a convolutional neural network algorithm, which aims at measuring elderly physical activity. Our algorithm is trained using signal embedding based on atoms of a pre-learned dictionary and focuses the network's attention on step-related signals. We show that NurseNet is able to avoid the main limitation of floor sensors by recognizing relevant signals (i.e., signals produced by patients) and ignoring events related to the medical staff, offering a new tool to monitor elderly activity in nursing homes efficiently.
Identifiants
pubmed: 31489924
pii: s19183851
doi: 10.3390/s19183851
pmc: PMC6767208
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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