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Human activity recognition from sensor-based large-scale co..:

, In: Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies,

Cheng, Wei-Yi ; Scotland, Alf ; Lipsmeier, Florian... - p. 249-250 , 2017

Link: https://dl.acm.org/doi/10.1109/CHASE.2017.87

RT 
T1 <cTitle>Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies</cTitle>: T1 <Title>Human activity recognition from sensor-based large-scale continuous monitoring of Parkinson's disease patients</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3204131&Exemplar=1&LAN=DE
				
A1 Cheng, Wei-Yi
A1 Scotland, Alf
A1 Lipsmeier, Florian
A1 Kilchenmann, Timothy
A1 Jin, Liping
A1 Schjodt-Eriksen, Jens
A1 Wolf, Detlef
A1 Zhang-Schaerer, Yan-Ping
A1 Garcia, Ignacio Fernandez
A1 Siebourg-Polster, Juliane
A1 Verselis, Lynne
A1 Facklam, Meret Martin
A1 Boess, Frank
A1 Ghosh, Anirvan
A1 Kremer, Thomas
A1 Taylor, Kirsten I.
A1 Czech, Christian
A1 Gossens, Christian
A1 Monsch, Andreas U.
A1 Soto, Jay
A1 Koller, Martin
A1 Postuma, Ron
A1 Grundman, Michael
A1 Lindemann, Michael
PB IEEE Press
YR 2017
K1 Parkinson's disease
K1 accelerometer
K1 activity recognition
K1 cell phone
K1 clinical trial
K1 deep learning
K1 sensors
K1 wearable
SP 249
OP 250
LK http://dx.doi.org/https://dl.acm.org/doi/10.1109/CHASE.2017.87
DO https://dl.acm.org/doi/10.1109/CHASE.2017.87
SF ELIB - SuUB Bremen

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