Battery runtime optimization toolbox for wearable biomedical sensors

A. Tobola, Heike Leutheuser, Björn Schmitz, Christian Hofmann, M. Struck, C. Weigand, B. Eskofier, Georg Fischer
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引用次数: 1

Abstract

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.
可穿戴生物医学传感器电池运行时间优化工具箱
电池运行时间是可穿戴生物医学传感器系统实际使用的关键问题。长时间的运行需要跨学科的低功耗知识和适当的设计工具。针对这一问题,我们设计了一个工具箱,分为三个部分:(1)开发可穿戴超低功耗生物医学传感器的模块化评估工具包;(2)小型化、可穿戴、兼容代码的传感器系统,与开发套件具有相同的性能;(3)基于web的传感器系统电池运行时间计算器。开发套件的目的是优化功耗。一旦优化完成,同样的嵌入式软件可以转移到小型化的穿戴式传感器上。基于web的应用程序支持量化用例和设计决策对电池运行时的影响的开发。传感器开发人员可以选择传感器模块,配置传感器参数,输入特定用例需求,并选择电池来预测特定应用程序的电池运行时间。我们的概念为超低功耗生物医学可穿戴传感器的发展增加了价值。这个概念对专业工作和教育目的是有效的。
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