IEEE J Biomed Health Inform. 2018 Jan;22(1):33-39. doi: 10.1109/JBHI.2017.2733549. Epub 2017 Jul 31.
Energy harvesting is a promising solution to the limited battery lifetimes of body sensor nodes. Self-powered sensor systems capable of quasi-perpetual operation enable the possibility of truly continuous monitoring of patients beyond the clinic. However, the discontinuous and dynamic characteristics of harvesting in real-world scenarios-and their implications for the design and operation of self-powered systems-are not yet well understood. This paper presents a mobile energy harvesting and data collection (EHDC) platform designed to provide a deeper understanding of energy harvesting dynamics. The EHDC platform monitors and records the instantaneous usable power generated by body-worn harvesters, while also collecting human activity and environmental data to provide a comprehensive real-world evaluation of two energy harvesting modalities common to body sensor networks: solar and thermoelectric. The platform was initially validated with benchtop tests and later with real-world deployments on two subjects. 7-h-long multimodal energy harvesting profiles were generated, and the environmental and behavioral data were used to expand upon previously developed Kalman filter based mathematical models for energy harvesting prediction. Results confirm the validity of the EHDC platform and harvesting models, establishing the potential for longer term monitoring of energy harvesting characteristics; thus, informing the design and operation of self-powered body sensor networks.
能量收集是解决体传感器节点电池寿命有限问题的一种很有前途的解决方案。能够实现近乎永久运行的自供电传感器系统使对患者进行真正持续监测成为可能,而不仅仅局限于临床环境。然而,在实际场景中,收集的不连续性和动态性特征及其对自供电系统的设计和运行的影响,还尚未被很好地理解。本文提出了一种移动能量收集和数据收集(EHDC)平台,旨在提供对能量收集动态性的更深入理解。EHDC 平台监测和记录佩戴式收集器产生的瞬时可用功率,同时收集人体活动和环境数据,对两种常见于体传感器网络的能量收集方式:太阳能和热电进行全面的实际评估。该平台最初通过台式测试进行了验证,随后在两名受试者身上进行了实际部署。生成了长达 7 小时的多模态能量收集曲线,并使用环境和行为数据对基于卡尔曼滤波的能量收集预测数学模型进行了扩展。结果证实了 EHDC 平台和收集模型的有效性,为更长期的能量收集特性监测奠定了基础,从而为自供电体传感器网络的设计和运行提供了信息。