Abstract
Flexible resistive sensors currently face challenges such as low sensitivity and poor stability. In this work, inspired by the skin structure of earthworm, a double strain layer with annular cracks aiming to achieve precise construction of conductive pathways in strain materials is proposed. This design strategy enhances the sensitivity, detection range, stability, and consistency of flexible resistive sensor. The sensing materials utilized primarily consist of mechanically and electrically modified PEDOT:PSS. The sensor showcases high sensitivity (with a gauge factor up to 1973.83), a wide detection range (0 ∼ 10 %), rapid response time (60–70 ms), and exceptional repeatability (1000 cycles). The sensor is integrated into finger clips for measurement of pulse wave. By analyzing features extracted from pulse wave, neural networks are employed for the prediction of encompassing coronary heart disease (CHD), atrial septal defect (ASD), atrial fibrillation (AF) and blood pressure levels. The classification accuracy of CHD, ASD and AF surpasses 96 %. The average prediction errors for systolic blood pressure, diastolic blood pressure and mean arterial pressure are found to be −0.3455, −0.2025 and −0.0319, respectively, meeting the standards set by the Association for the Advancement of Medical Instrumentation and the British Hypertension Society Class A criteria.
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