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Anomaly detection with smartwatches as an opportunity for implicit interaction

 
: Haescher, Marian; Matthies, Denys J.C.; Urban, Bodo

:
Volltext urn:nbn:de:0011-n-3672411 (1.5 MByte PDF)
MD5 Fingerprint: 7ec9aa32f473be98ef0d87f52e3b2300


Association for Computing Machinery -ACM-:
MobileHCI 2015, 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. Proceedings : August 24th - 27th, 2015, Copenhagen, Denmark
New York: ACM, 2015
ISBN: 978-1-4503-3652-9
ISBN: 978-1-4503-3653-6
pp.955-958
International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) <17, 2015, Copenhagen>
English
Conference Paper, Electronic Publication
Fraunhofer IGD ()
activity recognition; E-health; Human-computer interaction (HCI); pattern recognition; smart watches; activity recognition

Abstract
In this paper we introduce application scenarios for implicit interaction with Smartwatches for the purpose of user assistance, to create awareness, and to enhance as well as simplify the interaction with Wearables. We envision three scenarios (1) the detection of sleep apnea, (2) the detection of epileptic seizures, and (3) a detection of accidents such as falling, car crashes etc., which are presented and discussed. Therefore, the recognition of all incidents described will be discussed under the meta-topic of anomaly detection.

: http://publica.fraunhofer.de/documents/N-367241.html