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Wearable Electronics and Self-Powered Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Nanosensors".

Deadline for manuscript submissions: closed (25 April 2026) | Viewed by 3033

Special Issue Editors

Dr. Yang Jiang

E-Mail Website1 Website2
Guest Editor
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, China
Interests: energy harvesting; self-powered systems and active sensors; nanogenerators
Dr. Jianjun Luo

E-Mail Website
Guest Editor
1. Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
2. School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Interests: triboelectric nanogenerators; energy harvesting; self-powered sensing; intelligent sports
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advancement of the Internet of Things (IoT), big data, and artificial intelligence depends on a broadly distributed sensing network, driven by energy storage units that have finite lifespans and environmental impacts. The wide distribution and high mobility of these sensors necessitate renewable, distributed energy sources to ensure the success of the IoT and sustainable human development. Mechanical energy has emerged as the most abundant renewable resource in various environments and is unaffected by weather conditions. This Special Issue, “Wearable Electronics and Self-Powered Sensors”, explores harvesting ambient mechanical energy (e.g., body motion) to create battery-free, autonomous systems. Core technologies, such as Triboelectric Generators (TENGs) and Piezoelectric Generators (PENGs), enable intrinsically self-powered sensing for physiological, biochemical, and environmental parameters. Innovations in flexible materials and fabrication facilitate wearable integrated technologies (patches, e-textiles). Key challenges include system integration (harvesters, power management, sensors, ultra-low-power electronics, and wireless communications like BLE/NFC) into robust, autonomous packages. Addressing stability, biocompatibility, and scalable manufacturing is crucial for deployment. The Special Issue highlights self-powered technology's potential to enable pervasive, sustainable wearable and IoT sensing networks, which are essential for future digitalization and societal progress.

Yours faithfully,

Dr. Yang Jiang
Dr. Jianjun Luo
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wearable sensors
  • wearable electronics
  • self-powered systems
  • self-powered sensing
  • triboelectric generators
  • piezoelectric generators
  • blue energy
  • high-voltage applications
  • nanomaterials

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Published Papers (2 papers)

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17 pages, 3803 KB  
Article
Three Key Aspects of Electron Transfer Behavior in Single-Electrode Triboelectric Nanogenerators for Sensing Optimization
by Dazheng Shi, Jingkai Xi, Yu Hou, Siyu Qu and Ding Li
Sensors 2026, 26(1), 56; https://doi.org/10.3390/s26010056 - 21 Dec 2025
Viewed by 686
Abstract
With the rapid development of the Internet of Things, self-powered sensing technology has become a crucial solution for scenarios where an external power supply is inconvenient or unavailable, such as wild monitoring and flexible wearables. The triboelectric nanogenerator (TENG)—an excellent self-powered sensor, particularly [...] Read more.
With the rapid development of the Internet of Things, self-powered sensing technology has become a crucial solution for scenarios where an external power supply is inconvenient or unavailable, such as wild monitoring and flexible wearables. The triboelectric nanogenerator (TENG)—an excellent self-powered sensor, particularly in the single-electrode mode—demonstrates broad application prospects due to its simple structure and ease of integration. However, a comprehensive understanding of the electron transfer behavior of TENGs for performance optimization remains insufficient. Here, we investigate such behaviors from three key aspects—the polymer functional groups, the configurations of TENGs, and corona polarization. It is found that polymer functional groups critically determine electron transfer ability, with fluorinated polymers exhibiting superior performance across all configurations. Moreover, the configuration significantly influences electron transfer efficiency, where the sliding configuration vastly outperforms contact–separation configurations. Furthermore, the effect of corona polarization is highly configuration-dependent, improving performance in contact–separation configurations while generally reducing it in sliding configuration. These findings provide valuable theoretical guidance and practical strategies for optimizing the design and selecting appropriate materials and configurations of TENG-based self-powered sensors. They also pave the way for a new generation of highly efficient, miniaturized, and adaptive self-powered systems. Full article
(This article belongs to the Special Issue Wearable Electronics and Self-Powered Sensors)
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14 pages, 2463 KB  
Article
Gesture-Based Secure Authentication System Using Triboelectric Nanogenerator Sensors
by Doohyun Han, Kun Kim, Jaehee Shin and Jinhyoung Park
Sensors 2025, 25(16), 5170; https://doi.org/10.3390/s25165170 - 20 Aug 2025
Cited by 2 | Viewed by 1583
Abstract
This study presents a gesture-based authentication system utilizing triboelectric nanogenerator (TENG) sensors. As self-powered devices capable of generating high-voltage outputs without external power, TENG sensors are well-suited for low-power IoT sensors and smart device applications. The proposed system recognizes single tap, double tap, [...] Read more.
This study presents a gesture-based authentication system utilizing triboelectric nanogenerator (TENG) sensors. As self-powered devices capable of generating high-voltage outputs without external power, TENG sensors are well-suited for low-power IoT sensors and smart device applications. The proposed system recognizes single tap, double tap, and holding gestures. The electrical characteristics of the sensor were evaluated under varying pressure conditions, confirming a linear relationship between applied force and output voltage. These results demonstrate the sensor’s high sensitivity and precision. A threshold-based classification algorithm was developed by analyzing signal features enabling accurate gesture recognition in real time. To enhance the practicality and scalability of the system, the algorithm was further configured to automatically segment raw sensor signals into gesture intervals and assign corresponding labels. From these segments, time-domain statistical features were extracted to construct a training dataset. A random forest classifier trained on this dataset achieved a high classification accuracy of 98.15% using five-fold cross-validation. The system reduces security risks commonly associated with traditional keypad input, offering a user-friendly and reliable authentication interface. This work confirms the feasibility of TENG-based gesture recognition for smart locks, IoT authentication devices, and wearable electronics, with future improvements expected through AI-based signal processing and multi-sensor integration. Full article
(This article belongs to the Special Issue Wearable Electronics and Self-Powered Sensors)
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