Invited Paper: Feature-to-Classifier Co-Design for Mixed-Signal Smart Flexible Wearables for Healthcare at the Extreme Edge
This work addresses the problem of enabling efficient ML-based healthcare monitoring on flexible wearable devices for edge applications, representing a novel system-wide approach rather than an incremental improvement.
The paper tackles the challenge of implementing machine learning-based healthcare systems on flexible electronics by addressing area and power constraints, proposing a holistic mixed-signal feature-to-classifier co-design framework that includes the first analog feature extractors in flexible electronics and a hardware-aware feature selection strategy, resulting in highly accurate and ultra-area-efficient systems suitable for disposable wearable monitoring.
Flexible Electronics (FE) offer a promising alternative to rigid silicon-based hardware for wearable healthcare devices, enabling lightweight, conformable, and low-cost systems. However, their limited integration density and large feature sizes impose strict area and power constraints, making ML-based healthcare systems-integrating analog frontend, feature extraction and classifier-particularly challenging. Existing FE solutions often neglect potential system-wide solutions and focus on the classifier, overlooking the substantial hardware cost of feature extraction and Analog-to-Digital Converters (ADCs)-both major contributors to area and power consumption. In this work, we present a holistic mixed-signal feature-to-classifier co-design framework for flexible smart wearable systems. To the best of our knowledge, we design the first analog feature extractors in FE, significantly reducing feature extraction cost. We further propose an hardware-aware NAS-inspired feature selection strategy within ML training, enabling efficient, application-specific designs. Our evaluation on healthcare benchmarks shows our approach delivers highly accurate, ultra-area-efficient flexible systems-ideal for disposable, low-power wearable monitoring.