Acceleration sensors capable of human physiological information and unmanned equipment operating state evaluating have significant applications in advanced sensing and intelligent control. Especially, achieving self-powered sensing of various vibration information in irregular space is still a challenge. Herein, a multi-source fusion self-powered acceleration sensor integrated two triboelectric sensing modules and two electromagnetic sensing modules is successfully proposed via heterogeneous integration strategy and micro-capacitor model, which realizes the high-accuracy and high-reliability vibration acceleration monitoring. In addition, the flexible symmetric structure imparts the device with conformal property, broadening its application scenarios. Combined with customed four-channel acquisition storage circuit and linear fitting algorithm of multi-source sensory data, the developed acceleration sensor has excellent practicality to accurately sense and predict various acceleration states with accuracy of 96%. This capability of the sensing system underscores the practical utility of human sole and unmanned aerial vehicle wing to evaluate physiological and operating state, which addresses the critical acceleration sensory challenges in irregular space by providing a sensitive, reliable and conformal sensing strategy.

Designing stretchable and skin-conformal self-powered sensors for intelligent sensing and posture recognition is challenging. Here, based on a multi-force mixing and vulcanization process, as well as synergistically piezoelectricity of BaTiO₃ and polyacrylonitrile, an all-in-one, stretchable, and self-powered elastomer-based piezo-pressure sensor (ASPS) with high sensitivity is reported. The ASPS presents excellent sensitivity (0.93 V/10⁴ Pa of voltage and 4.92 nA/10⁴ Pa of current at a pressure of 10–200 kPa) and high durability (over 10,000 cycles). Moreover, the ASPS exhibits a wide measurement range, good linearity, rapid response time, and stable frequency response. All components were fabricated using silicone, affording satisfactory skin-conformality for sensing postures. Through cooperation with a homemade circuit and artificial intelligence algorithm, an information processing strategy was proposed to realize intelligent sensing and recognition. The home-made circuit achieves the acquisition and wireless transmission of ASPS signals (transmission distance up to 50 m), and the algorithm realizes the classification and identification of ASPS signals (accuracy up to 99.5%). This study proposes not only a novel fabrication method for developing self-powered sensors, but also a new information processing strategy for intelligent sensing and recognition, which offers significant application potential in human–machine interaction, physiological analysis, and medical research.

Stretchable, skin-conformal, and self-powered wearable pressure sensors have garnered significant attention for use in human joint bending motion monitoring. Here, a piezo-triboelectric pressure sensor (P-TPS) based on triboelectric nanogenerator and piezoelectric nanogenerator is demonstrated. The P-TPS can generate an enhanced electrical output by coupling the dual-mode triboelectrification and piezoelectric effect. The P-TPS shows high sensitivity (voltage = 0.3 V/kPa; current = 4.3 nA/kPa; pressure range = 0–200 kPa), high linearity, and good stability. Furthermore, it demonstrates a wide measurement range (0–800 kPa), table frequency response, and fast response time. Additionally, all components of the P-TPS are fabricated using flexible and stretchable materials, affording satisfactory stretchability and excellent skin conformality. Owing to their ability to self-power, they can be attached to the outside of joints to monitor human joint bending movements in real time. Hence, this study provides a novel method of using a stretchable and skin-conformal piezo-triboelectric nanogenerator with high electrical performance as a self-powered pressure sensor, which offers significant potential in personalized recognition, medical research, and human machine interface.