Design Considerations for Self-Powered Wearable Wireless Multimodal Vigilant Sensing Systems

Body Sensor Networks (BSNs) are cyber-physical sensor systems that address the weaknesses of traditional remote patient monitoring methods in healthcare and provide the opportunity for the continuous collection of high-quality data. However, they must overcome the obstacles of user acceptance and battery life in order for widespread adoption to occur. User acceptance can be addressed by designing BSNs to be wearable and wireless while battery life can be addressed by designing them to have self-powered operation. BSNs must also have multimodal vigilant sensing so that they do not miss any critical events for their given application. One application is cardiac and activity monitoring and it can potentially reduce the number of hospitalizations in patients with a cardiovascular disease (CVD) by tracking CVD symptoms and alerting healthcare professionals when one is detected. One such BSN that performs this kind of monitoring is the testbed for the Self-Powered and Adaptive Low Power Sensing Platform (SAP).

This thesis presents the design of the SAP testbed, which is a self-powered wearable sensor system designed to perform vigilant long-term cardiac and activity monitoring by continuously sensing and wirelessly streaming ECG and motion data to a smartphone. It consumes only 370 μW on average and is powered solely by indoor solar allowing it to maintain its monitoring at a vigilant sampling rate so that it does not miss any critical cardiac and activity events. The testbed was deployed on several subjects in the laboratory to validate this behavior. Designing BSNs with similar characteristics to the SAP testbed presents a number of design challenges that must be addressed. These challenges include power management, energy harvesting optimization, system wearability optimization, and system flexibility and modularity optimization. Therefore, in addition to the presentation of the SAP testbed, this thesis discusses the design considerations that must be made in order to make intelligent design decisions when addressing these challenges.