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Scalable ECG hardware and algorithms for extended runtime of wearable sensors

: Tobola, A.; Espig, C.; Streit, F.J.; Korpok, O.; Schmitz, B.; Hofmann, C.; Struck, M.; Weigand, C.; Leutheuser, H.; Eskofier, B.M.; Fischer, G.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Instrumentation and Measurement Society:
IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015. Proceedings : Torino, Italy, 7 - 9 May 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4799-6478-9
ISBN: 978-1-4799-6476-5
ISBN: 978-1-4799-6477-2
International Symposium on Medical Measurements and Applications (MeMeA) <10, 2015, Torino>
Fraunhofer IIS ()

Everything in nature tries to reach the lowest possible energy level. Therefore any natural or artificial system must have the ability to adjust itself to the changing requirements of its surrounding environment. In this paper we address this issue by an ECG sensor designed to be adjustable during runtime, having the ability to reduce the power consumption at cost of the informational content. Accessible for everyone, standard ECG hardware and open source software has been used to realize an ECG processing system for wearable applications. The average power consumption has been measured for each mode of operation. Finally we take conclusion to conciser context-aware scaling as key feature to address the energy issue of wearable sensor systems.