Three custom TENG sensors integrated into eyeglasses capture arterial pulse, jaw kinematics, and facial activity at 4.1 µW total front-end power, achieving 93.8% activity accuracy and 1.82 BPM heart rate error in a 20-participant study.
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An end-to-end hardware-aware optimization pipeline produces DNNs for PPG-based blood pressure estimation with up to 7.99% lower error and 83x fewer parameters that fit on ultra-low-power SoCs like GAP8.
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End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables
An end-to-end hardware-aware optimization pipeline produces DNNs for PPG-based blood pressure estimation with up to 7.99% lower error and 83x fewer parameters that fit on ultra-low-power SoCs like GAP8.