High-performance resistive/capacitive pressure sensor applied on smart insoles detecting abnormal activity

초록

This paper presents an approach to pressure sensors with dual-function resistors and capacitors implemented with interdigitated capacitors fabricated on a flexible substrate for detecting abnormal actions during walking. In this study, we proposed a highly sensitive, broad-range pressure sensor achieved through a combination of porous Ecoflex, carbon nanotubes (CNTs), coating single-wall carbon nanotubes (SWCNTs), and interdigitated electrodes. First, characterizations of the capacitor and resistor sensor applied onto cotton fabric are completed by precision LCR meter across the frequency at 50 kHz. Subsequently, the presence of volume fraction CNTs enhances the bond strength of composites, and coating SWCNT improves sensor sensitivity. The robustness of our presented sensor is validated through testing under high pressure (50 kPa) for more than 1000 cycles. Furthermore, the combination of CNTs and porous dielectric, along with SWCNT coating, achieves a broad detection range (500 kPa) with a sensitivity range from 0.018 (at 500 kPa) to 0.15 KPa-1$\mathrm{KPa}{<}^{>}-1$ (at 5 kPa). Finally, our high-performance resistive/capacitive pressure sensor applied on smart insoles represents a significant advancement in wearable technology for health monitoring and safety applications. Leveraging an advanced autoencoder, our proposed sensor accurately detects abnormal activity patterns, such as sudden stops or irregular gait, thereby alerting users to potential safety concerns. Its ability to detect abnormal activity patterns enhances user safety and well-being, making it a tool for various healthcare and fitness applications. High-performance resistive/capacitive pressure sensor applied on smart insoles represents a significant advancement in wearable technology for health monitoring and safety applications. By using autoencoder, our proposed sensor accurately detects abnormal activity patterns, such as sudden stops or irregular gait, thereby alerting users to potential safety concerns, making them a valuable tool for next-generation personalized healthcare applications. image

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