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Xi et al. Soft Sci 2023;3:26                                              Soft Science
               DOI: 10.20517/ss.2023.13



               Review Article                                                                Open Access



               Self-powered wearable IoT sensors as human-

               machine interfaces


                      1,2
                                   2
               Yuan Xi , Puchuan Tan , Zhou Li 2,3,4,5,*  , Yubo Fan 1,*
               1
                Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of
               Ministry of Education, School of Biological Science and Medical Engineering, School of Engineering Medicine, Beihang University,
               Beijing 100191, China.
               2
                Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences, Beijing 101400, China.
               3
                School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
               4
                Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning 530004, Guangxi,
               China.
               5
                Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.
               * Correspondence to: Prof. Zhou Li, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and
               Nanosystems, Chinese Academy of Sciences, Yangyan East 1st Road, Yanqi Economic Development Zone, Huairou District,
               Beijing 101400, China. E-mail: zli@binn.cas.cn; Prof. Yubo Fan, Beijing Advanced Innovation Centre for Biomedical Engineering,
               Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical
               Engineering, School of Engineering Medicine, Beihang University, XueYuan Road No.37, HaiDian District, Beijing, 100191, China.
               E-mail: yubofan@buaa.edu.cn
               How to cite this article: Xi Y, Tan P, Li Z, Fan Y. Self-powered wearable IoT sensors as human-machine interfaces. Soft Sci
               2023;3:26. https://dx.doi.org/10.20517/ss.2023.13

               Received: 28 Feb 2023  First Decision: 10 Apr 2023  Revised: 1 May 2023  Accepted: 12 Jun 2023  Published: 1 Aug 2023
               Academic Editors: Chengkuo Lee, Tianyiyi He, Chuanfei Guo  Copy Editor: Pei-Yun Wang  Production Editor: Pei-Yun Wang

               Abstract
               Self-powered wearable Internet of Things (IoT) sensors have made a significant impact on human life and health in
               recent years. These sensors are known for their convenience, durability, affordability, and longevity, leading to
               substantial improvements in people’s lives. This review summarizes the development of self-powered wearable IoT
               sensors in recent years. Materials for self-powered wearable sensors are summarized and evaluated, including
               nanomaterials, flexible materials, and degradable materials. The working mode of self-powered wearable IoT
               sensors is analyzed, and the different principles of its physical sensing and chemical sensing are explained. Several
               common technologies for self-powered wearable IoT sensors are presented, such as triboelectric technology,
               piezoelectric technology, and machine learning. The applications of self-powered IoT wearable sensors in human-
               machine interfaces are reviewed. Its current shortcomings and prospects for its future development are also
               discussed. To conduct this review, a comprehensive literature search was performed using several electronic
               databases, resulting in the inclusion of 225 articles. The gathered data was extracted, synthesized, and analyzed
               using a thematic analysis approach. This review provides a comprehensive analysis and summary of its working
               mode, technologies, and applications and provides references and inspiration for related research in this field.



                           © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
                           adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
               long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
               indicate if changes were made.

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