Recent Advances in Self-Powered Biomechanical Sensors: Transduction Mechanisms, Functional Materials, and Emerging Applications

Abstract

Self-powered biomechanical sensors convert motion, pressure, vibration, and physiological deformation directly into electrical signals, thereby reducing or eliminating the external bias required at the sensing interface. Their practical value is determined not only by peak voltage or power, but also by signal fidelity, source impedance, mechanical compliance, environmental stability, and compatibility with signal-conditioning and wireless modules. This review summarizes recent advances in three representative transduction platforms: Triboelectric nanogenerators (TENGs), Piezoelectric nanogenerators (PENGs), and soft Magnetoelastic generators (MEGs). The voltage-charge-displacement relationship of TENGs, the constitutive equations of PENGs, and the stress-dependent magnetic-flux variation and Faraday induction of MEGs are discussed in relation to device architecture and functional materials. Recent examples are organized according to biomechanical inputs and intended functions, including ocular and eyelid motion, respiration, cardiovascular pulse and cardiac motion, speech assistance, fatigue assessment, self-powered electrical stimulation for cellular programming and regenerative bioelectronics, and sweat induction, collection, and monitoring. The review further compares material and interface strategies, humidity tolerance, biocompatibility, source-load matching, machine-learning-assisted interpretation, and the distinction between self-powered sensing and fully energy-autonomous operation. Finally, key challenges are outlined for standardized benchmarking, scalable manufacturing, long-term wearability, and integrated closed-loop bioelectronic systems.