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Recent advances in soft electronics and artificial intelligence are converging to revolutionize personalized health monitoring. In this talk, I will introduce our latest developments in AI-enabled wearable e-tattoo technology, focusing on ultrathin, skin-conformal electronic tattoos (e-tattoos) designed for continuous, noninvasive sensing of clinically and physiologically relevant signals. I will present two latest platforms developed by our group: the chest e-tattoo, which captures synchronized ECG, SCG, and PPG signals to infer clinically relevant cardiovascular metrics such as blood pressure (BP) and stroke volume (SV); and the brain e-tattoo, capable of detecting EEG signals related to mental workload and cognitive states. We leverage both laptop-based machine learning pipelines for model development and validation, as well as embedded edge AI architectures powered by Differential Weightless Neural Network (DWN) for real-time, on-tattoo inference. By integrating hardware innovations with intelligent signal interpretation, we aim for seamless, continuous monitoring of cardiovascular health and cognitive states in real-world environments.
