Real-Time Stress Monitoring With Flexible Electronics: A Co-Design Approach From ADCs to Feature Extractors and Classifiers

Prolonged stress has significant consequences for mental and physical health, making its continuous monitoring a necessity. Wearable devices can offer real-time physiological tracking but primarily rely on rigid silicon-based hardware, which does not adapt well to the body surface, leading to discomfort during extended use and is frequently too expensive for broad accessibility. Flexible electronics (FEs) provide an attractive alternative, offering lightweight and bendable systems at ultralow costs, making them ideal for affordable and comfortable healthcare devices. Current FE approaches primarily focus on identifying stress levels via machine learning (ML) classifiers or propose standalone hardware (e.g., biosensors) but overlook the impact and potential co-design benefits of end-to-end system design, such as sensor interfacing and feature extraction costs, which may dominate the system’s requirements. In our work, we propose an automated hardware-aware framework to co-design all major system components: analog-to-digital converters (ADCs), feature extractors, and an ML classifier. Our co-optimization framework tailors the flexible hardware implementation to the application requirements, thus complying with demanding area and power constraints associated with FE. ... mehrOur experiments demonstrate that the proposed framework reduces ADC interfacing and feature-extraction costs by 86.76%, improves energy efficiency by 50.6× compared to a programmable flexible RISC-V baseline, and enables approximately 60 days of battery-powered operation with a typical flexible battery, with silicon-level accuracy along with the unique advantages of flexible, conformal hardware.