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Battery runtime optimization toolbox for wearable biomedical sensors

: Tobola, Andreas; Leutheuser, Heike; Schmitz, Björn; Hofmann, Christian; Struck, Matthias; Weigand, Christian; Eskofier, Bjoern M.; Fischer, Georg


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2016. Proceedings : 14-17 June 2016, San Francisco, California
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-3088-0 (Print)
ISBN: 978-1-5090-3087-3 (Online)
International Conference on Wearable and Implantable Body Sensor Networks (BSN) <13, 2016, San Francisco/Calif.>
Conference Paper
Fraunhofer IIS ()
Temperaturmessung; SpO2; medizinische Sensorik; Medizingeräte-Software; low power; low voltage design; EKG; Biosignalverarbeitung; Atmungsanstrengung

Battery runtime is a critical concern for practical usage of wearable biomedical sensor systems. A long runtime requires an interdisciplinary low-power knowledge and appropriate design tools. We addressed this issue designing a toolbox in three parts: (1) Modular evaluation kit for development of wearable ultra-low-power biomedical sensors; (2) Miniaturized, wearable, and code compatible sensor system with the same properties as the development kit; (3) Web-based battery runtime calculator for our sensor systems. The purpose of the development kit is optimization of the power consumption. Once optimization is finished, the same embedded software can be transferred to the miniaturized body worn sensor. The web-based application supports development quantifying the effects of use case and design decisions on battery runtime. A sensor developer can select sensor modules, configure sensor parameters, enter use case specific requirements, and select a battery to predict the battery runtime for a specific application. Our concept adds value to development of ultra-low-power biomedical wearable sensors. The concept is effective for professional work and educational purposes.