About this Webinar

Wearable electronics for non-invasive personal health monitoring require advanced multimodal sensing and seamless energy system integration. However, current platforms are hindered by insufficient energy budget, limited sensing performance, user discomfort, complex circuit architectures, and bulky device form factors. In this webinar, we present a wireless, energy-autonomous, sweat sensing system based on a wearable microgrid framework. This system integrates high-efficiency, self-voltage-regulated microgrids—comprising wearable energy harvesters (similar to electrochemical biofuel cells) and flexible rechargeable batteries—to harvest and manage energy from the body.

Critical system-level design strategies, including precise energy budgeting, electrochemical circuit compatibility, and adaptive hybrid energy harvesting, enable reliable integration of low-power signal acquisition electronics and wireless data transmission modules. The fluidic interface facilitates continuous sweat sampling, delivering analytes to an electrochemical sensor array for real-time, on-demand detection of multiple biomarkers, such as glucose, lactate, vitamin C, and levodopa. Utilizing enzyme-based and redox-active sensing strategies, the platform achieves selective and stable electrochemical measurements over extended durations. This self-powered wearable system offers a compact, user-friendly, and robust solution for continuous, non-invasive metabolic health monitoring.

Attendee learning outcomes:

• Understand the concept and system architecture of wearable microgrids for integrating energy harvesting, storage, and biosensing on the body.
• Learn how autonomous energy management strategies enable continuous, self-sustained operation of wearable biosensors without external power supplies.
• Gain insights into the co-design of energy modules and biosensing units, and how their interactions affect stability, efficiency, and sensing performance.
• Explore emerging applications and challenges of distributed, self-powered wearable systems for long-term health monitoring and personalized medicine.

Who Should Attend:

• Material scientists
• Electrical engineers
• Chemists
• Biomedical and biophysical researchers