Enhanced sensitivity and broadband response in porous triple periodic minimal surface piezoresistive sensors for telemedicine applications

Abstract

Wearable pressure sensors with outstanding performance have garnered significant attention in fields such as telemedicine. However, the development of sensors that achieve both adjustable high sensitivity and a wide response range remains a formidable challenge. To address these issues, we propose the development of a flexible piezoresistive sensor featuring simultaneous macro- and microstructures. This is achieved by constructing a complex macro-topological skeleton using Fused Deposition Molding (FDM) technology and integrating supercritical carbon dioxide (ScCO2) foaming technology for microscopic pore creation. The unique conductive network structure, coupled with the Triple Periodic Minimal Surface (TPMS) metamaterial framework and microscopic pore architecture, endows the piezoresistive sensors with exceptional sensing performance, including high sensitivity (12.13 MPa−1), a broad response range (exceeding 30 MPa), and long-term fatigue resistance (over 26,000 s cycles). In addition, the sensors are shielded from electromagnetic interference, with a maximum EMI shielding effectiveness of 53.2 dB for the TMFM with a thickness of 2.3 mm. The effects of varying porosities and foaming pressures on sensitivity were analyzed using finite element simulations. Owing to these remarkable features, multiple foot movement recognition was successfully demonstrated with volunteer participants by assembling sensing unit array modules. Based on this, an intelligent fall warning recognition system is developed using machine learning. This system accurately distinguishes four types of activity behaviors—standing, walking, spraining foot, and falling—with accuracy rates of 98.9 %, 97.1 %, 98.9 %, and 95.1 %, respectively. The system automatically generates an alarm pattern for detected fall behaviors. These findings suggest that the combination of TPMS skeleton and micropores structure offers a promising strategy for developing sensors with adjustable sensitivity and wide detection range for wearable devices. This technology holds significant potential for applications in telemedicine assistance, particularly for the elderly and other vulnerable populations.