Recent Advances in Multifunctional Wearable Sensors and Systems: Design, Fabrication, and Applications

Jia, Shigang; Gao, Hongwei; Xue, Zhaoguo; Meng, Xiangchen

doi:10.3390/bios12111057

Cited by 13 publications

(7 citation statements)

References 112 publications

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“…In addition to the widely used PTT applications of MXene, some emerging research areas are becoming topics of interest for researchers. Our keyword analysis indicated that some edgy applications are at the forefront of current research, namely, Frontiers in Bioengineering and Biotechnology frontiersin.org "wearable electronics," a class of physical sensors that can sense external physical and chemical signals and convert them into electrical signals (Jia et al, 2022). Compared with other materials, MXenes and their composites exhibit good mechanical flexibility and tensile properties, making them widely used in wearable sensors, energy storage and electromagnetic shielding (Xin et al, 2020).…”

Section: Keyword Analysismentioning

confidence: 99%

MXene nanomaterials in biomedicine: A bibliometric perspective

Guo

Liu

et al. 2023

Front. Bioeng. Biotechnol.

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Purpose: MXene is two-dimensional (2D) nanomaterials that comprise transition metal carbides, nitrides, and carbonitrides. Their unique nanostructure attributes it a special role in medical applications. However, bibliometric studies have not been conducted in this field. Therefore, the aim of the present study was to conduct a bibliometric analysis to evaluate the global scientific output of MXene in biomedical research, explore the current situation of this field in the past years and predicte its research hotpots.Methods: We utilized visual analysis softwares Citespace and Bibliometrix to analyze all relevant documents published in the period of 2011–2022. The bibliometric records were obtained from the Web of Science Core Collection.Results: A total of 1,489 publications were analyzed in this study. We observed that China is the country with the largest number of publications, with Sichuan University being the institution with the highest number of publications in this field. The most publications on MXene medicine research in the past year were found primarily in journals about Chemistry/Materials/Physics. Moreover, ACS Applied Materials and Interfaces was found to be the most productive journal in this field. Co-cited references and keyword cluster analysis revealed that #antibacterial# and #photothermal therapy# are the research focus keyword and burst detection suggested that driven wearable electronics were newly-emergent research hot spots.Conclusion: Our bibliometric analysis indicates that research on MXene medical application remains an active field of study. At present, the research focus is on the application of MXene in the field of antibacterial taking advantage of its photothermal properties. In the future, wearable electronics is the research direction of MXene medical application.

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Section: Keyword Analysismentioning

confidence: 99%

MXene nanomaterials in biomedicine: A bibliometric perspective

Guo

Liu

et al. 2023

Front. Bioeng. Biotechnol.

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“…Wearable sensors have the characteristics of light weight, flexibility, stability, and comfort. They are widely used for pulse and heartbeat monitoring purposes, gait analysis, and other health monitoring systems, disease diagnosis, and rehabilitation fields [ 45 ]. In the process of the diagnosis and rehabilitation of different diseases, different sensors are required to detect the physiological information required.…”

Section: Resultsmentioning

confidence: 99%

The Application of Wearable Sensors and Machine Learning Algorithms in Rehabilitation Training: A Systematic Review

Wei,

2023

Sensors

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The integration of wearable sensor technology and machine learning algorithms has significantly transformed the field of intelligent medical rehabilitation. These innovative technologies enable the collection of valuable movement, muscle, or nerve data during the rehabilitation process, empowering medical professionals to evaluate patient recovery and predict disease development more efficiently. This systematic review aims to study the application of wearable sensor technology and machine learning algorithms in different disease rehabilitation training programs, obtain the best sensors and algorithms that meet different disease rehabilitation conditions, and provide ideas for future research and development. A total of 1490 studies were retrieved from two databases, the Web of Science and IEEE Xplore, and finally 32 articles were selected. In this review, the selected papers employ different wearable sensors and machine learning algorithms to address different disease rehabilitation problems. Our analysis focuses on the types of wearable sensors employed, the application of machine learning algorithms, and the approach to rehabilitation training for different medical conditions. It summarizes the usage of different sensors and compares different machine learning algorithms. It can be observed that the combination of these two technologies can optimize the disease rehabilitation process and provide more possibilities for future home rehabilitation scenarios. Finally, the present limitations and suggestions for future developments are presented in the study.

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“…This requires integration of different types of materials with a wide spectrum of physical properties, which enables simultaneous response to various external signals. 6,7 In addition, manipulation with physicochemical material properties in the nanoscale and modification of nanomaterials for a certain purpose provide a wider range of possible new applications. [8][9][10] Controlling the size, shape, functionality, etc.…”

Section: Introductionmentioning

confidence: 99%