Document Type
Article
Publication Date
2026
DOI
10.3390/ma19081647
Publication Title
Materials
Volume
19
Issue
8
Pages
1647
Abstract
Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, anatomical sites, calibration methods, and signal-processing approaches limit direct comparison of reported performance. In addition, challenges such as subject-specific calibration, motion artifacts, and limited clinical validation remain. Overall, this review highlights current progress and outlines key challenges for future development and translation of TENG-based cardiovascular monitoring systems.
Original Publication Citation
Sarode, A., Rajendran, J., & Slaughter, G. (2026). Recent advances in triboelectric nanogenerators for biomedical and cardiovascular monitoring. Materials, 19(8), Article 1647. https://doi.org/10.3390/ma19081647
Repository Citation
Sarode, A., Rajendran, J., & Slaughter, G. (2026). Recent advances in triboelectric nanogenerators for biomedical and cardiovascular monitoring. Materials, 19(8), Article 1647. https://doi.org/10.3390/ma19081647
ORCID
0009-0009-1752-6272 (Sarode), 0000-0002-4307-091X (Slaughter)
Included in
Artificial Intelligence and Robotics Commons, Biomedical Engineering and Bioengineering Commons, Diagnosis Commons
Comments
© 2026 by the authors.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Data Availability Statement: Article States: "No new data were created or analyzed in this study. Data sharing is not applicable to this article."