Scalable ECG Hardware and Algorithms for Extended Runtime of Wearable Sensors

Beitrag bei einer Tagung
(Konferenzbeitrag)


Details zur Publikation

Autor(en): Tobola A, Streit FJ, Espig C, Streit FJ, Korpok O, Leutheuser H, Schmitz B, Hofmann C, Struck M, Weigand C, Eskofier B, Fischer G
Verlag: IEEE
Jahr der Veröffentlichung: 2015
Tagungsband: 2015 IEEE International Symposium on Medical Measurements and Applications
Seitenbereich: 255-260
ISBN: 978-1-4799-6476-5


Abstract


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.



FAU-Autoren / FAU-Herausgeber

Eskofier, Björn Prof. Dr.
Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports)
Fischer, Georg Prof. Dr.-Ing.
Professur für Technische Elektronik
Leutheuser, Heike
Lehrstuhl für Informatik 5 (Mustererkennung)
Streit, Franz-Josef
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)


Zusätzliche Organisationseinheit(en)
Zentralinstitut für Medizintechnik


Autor(en) der externen Einrichtung(en)
Fraunhofer-Institut für Integrierte Schaltungen (IIS)


Zitierweisen

APA:
Tobola, A., Streit, F.-J., Espig, C., Streit, F.J., Korpok, O., Leutheuser, H.,... Fischer, G. (2015). Scalable ECG Hardware and Algorithms for Extended Runtime of Wearable Sensors. In 2015 IEEE International Symposium on Medical Measurements and Applications (pp. 255-260). Torino, IT: IEEE.

MLA:
Tobola, Andreas, et al. "Scalable ECG Hardware and Algorithms for Extended Runtime of Wearable Sensors." Proceedings of the IEEE International Symposium on Medical Measurements and Applications (MeMeA), Torino IEEE, 2015. 255-260.

BibTeX: 

Zuletzt aktualisiert 2018-12-11 um 12:38