A design-space exploration shows flexible, low-power machine-learning circuits can classify stress with higher reported accuracy than prior rigid wearable systems, with some designs at 9 µW.
Detection of real- world driving-induced affective state using physiological signals and multi-view multi-task machine learning,
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Exploration of Low-Power Flexible Stress Monitoring Classifiers for Conformal Wearables
A design-space exploration shows flexible, low-power machine-learning circuits can classify stress with higher reported accuracy than prior rigid wearable systems, with some designs at 9 µW.