- This computer patch performs instant, on-skin AI analysis for health data
- Minimal latency is critical for conditions such as ventricular fibrillation
- It could also overhaul robotics and improve AI for disaster relief
Researchers at the University of Chicago Pritzker School of Molecular Engineering have developed a computer patch that can run AI models directly on the body instead of sending data to a connected smartphone, cloud server or other external processor.
Published in the journal Nature Electronics, researcher Sihong Wang likened the development to having a “personal, instant doctor integrated into [users’] units.”
Although far from commercially available, the technology tackles the fact that most wearables today serve largely only as data collectors. While smartwatches have long measured heart rate, movement, oxygen levels, EKG signals and more, this data is typically transferred to a smartphone for analysis or even cloud servers in the case of the recently launched Google Health with AI capabilities.
Skin-based AI inference could revolutionize healthcare
Developed by researchers, the new patch performs both sensing and AI inference directly on the skin, with analysis occurring in milliseconds without relying on wireless communications, cloud computing or other external factors.
Ultra-low latency is especially important for some medical conditions like ventricular fibrillation, where even a few seconds of latency can make a difference.
However, there are other benefits to this technology as well, with the paper highlighting a reduction in power consumption and privacy risks thanks to on-device processing.
Stretchable transistors that bend and conform to the skin are credited with making the patch possible, while conventional chips and rigid silicon in older hardware would have previously made this impossible. However, a gel electrolyte layer presented its own challenges, threatening to move like a liquid and short out electrical components.
“What we had to ask was whether we could use or change the properties of these polymers to make them compatible with photolithography—the main patterning method used in the microelectronics industry,” Wang added.”
Ventricular fibrillation was clearly a major focus of the study, and thanks to a donated human heart, the team was able to confirm the patch’s ability to locate wavefront positions with 99.6% accuracy.
The research claims to enable the “various edge processing functions applicable to various types of health data, including multilayer perceptron (MLP) for heart attack prediction and convolution operations for precise tracking of arrhythmia fibrillation wavefronts on the heart surface.”
While this specific study relates to spots on the skin, it also hints at a future of “implantable on-body edge” computing for true smart health. “High-resolution signal measurements” are targeted for next-generation implantable devices for highly accurate real-time data from actual living organs.
The future of this technology extends far beyond human healthcare
In addition to human data, patches and implantables with integrated computing can also overhaul robotics, giving humanoids human-like senses with real-time accuracy, making them perfect for disaster recovery where wireless communications can be unreliable.
This form of reinforcement learning was put to the test in an ant-like robot study, where the miniature robot was able to navigate environments with comparable success to conventional computer simulations.
Looking ahead, commercial versions of this technology will mark a major shift in artificial intelligence, with the technology being deployed at the edge rather than in latency-prone data centers.
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