Soft Microelectronics Power Wearable AI in Health Tech

Schematic of the wearable in-sensor computing platform.

Schematic of the wearable in-sensor computing platform.

Leveraging rapid technological advances for human health is a global trend, driving the rise of biomedical engineering research. A fast-rising field is wearable biosensors, which have the potential to realise digital healthcare and AI medicine.

Developing edge-computing and AI capabilities from wearable sensors enhances their intelligence, critical for the AI of Things, and reduces power consumption by minimising data exchange between sensory terminals and computing units. This enables wearable devices to process data locally, offering real-time processing, faster feedback, and decreased reliance on network connectivity and external devices, thereby enhancing efficiency, privacy, and responsiveness in applications like health monitoring, activity tracking, and smart wearable technology.

However, current sensors lack computing capabilities and their mechanical mismatch with soft tissues leads to motion artifacts, restricting their practical wearable applications.

In response, a research team led by Professor Shiming Zhang of the Department of Electrical and Electronic Engineering at the University of Hong Kong (HKU) has introduced a groundbreaking wearable in-sensor computing platform. This platform is built on an emerging microelectronic device, an organic electrochemical transistor (OECT), invented explicitly for bioelectronics applications. The team established a standardised materials and fabrication protocol to endow OECTs with stretchability. Through those efforts, the built microelectronics platform integrates sensing, computing, and stretchability into one hardware entity, endowing it with an exclusively capability for wearable in-sensor computing applications.

The research team further developed an accessible, multi-channel printing platform to ease the fabrication of the sensors at scale. Through integration with circuits, they demonstrated the platform's ability to measure human electrophysiological signals in real time. Results showed stable, low-power in-situ computing even during motion.

The work has recently been published in Nature Electronics in an article titled "A wearable in-sensor computing platform based on stretchable organic electrochemical transistors".

"We built a wearable in-sensor computing platform using unconventional soft microelectronics technology, providing hardware solutions long sought by emerging fields such as human-machine interfacing, digital health, and AI medicine," said Professor Zhang.

The research team believes their work will push the boundaries of wearables and edge-AI for health. Their next steps include refining the platform and exploring its potential applications in various healthcare settings.

"This groundbreaking work not only showcases the innovative capabilities of the HKU team but also opens new opportunities for wearable technology. The team's dedication to improving the quality of life through advanced health technology is evident in this remarkable achievement." Professor Zhang added.

For the article published in Nature Electronics: https://www.nature.com/articles/s41928-024-01250-9

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