Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence

For leveraging wearable technologies to advance precision medicine, personalized and learning-based analysis of continuously acquired health data is indispensable, for which neuromorphic computing provides the most efficient implementation of artificial intelligence (AI) data processing. For realizing on-body neuromorphic computing, skin-like stretchability is required but has yet to be combined with the desired neuromorphic metrics, including linear symmetric weight update and sufficient state retention, for achieving high computing efficiency. Here, we report an intrinsically stretchable electrochemical transistor-based neuromorphic device, which provides a large number (>800) of states, linear/symmetric weight update, excellent switching endurance (>100 million), and good state retention (>104 s) together with the high stretchability of 100% strain. We further demonstrate a prototype neuromorphic array that can perform vector-matrix multiplication even at 100% strain and also the feasibility of implementing AI-based classification of health signals with a high accuracy that is minimally influenced by the stretched state of the neuromorphic hardware.

Automated summary

This study reports an intrinsically stretchable electrochemical transistor-based neuromorphic device that provides a large number of states, excellent switching endurance, and good state retention. It also demonstrates the feasibility of performing vector-matrix multiplication even under high strain and achieving high accuracy in AI-based classification of health signals, minimally affected by the stretched state of the neuromorphic hardware.