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A Flexible Strain Sensor Based on the Porous Structure of a Carbon Black/Carbon Nanotube Conducting Network for Human Motion Detection

High-performance flexible strain sensors are playing an increasingly important role in wearable electronics, such as human motion detection and health monitoring, with broad application prospects. This study developed a flexible resistance strain sensor with a porous structure composed of carbon bla...

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Detalles Bibliográficos
Autores principales: Zhang, Peng, Chen, Yucheng, Li, Yuxia, Zhang, Yao, Zhang, Jian, Huang, Liangsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071403/
https://www.ncbi.nlm.nih.gov/pubmed/32093154
http://dx.doi.org/10.3390/s20041154
Descripción
Sumario:High-performance flexible strain sensors are playing an increasingly important role in wearable electronics, such as human motion detection and health monitoring, with broad application prospects. This study developed a flexible resistance strain sensor with a porous structure composed of carbon black and multi-walled carbon nanotubes. A simple and low-cost spraying method for the surface of a porous polydimethylsiloxane substrate was used to form a layer of synergized conductive networks built by carbon black and multi-walled carbon nanotubes. By combining the advantages of the synergetic effects of mixed carbon black and carbon nanotubes and their porous polydimethylsiloxane structure, the performance of the sensor was improved. The results show that the sensor has a high sensitivity (GF) (up to 61.82), a wide strain range (0%–130%), a good linearity, and a high stability. Based on the excellent performance of the sensor, the flexible strain designed sensor was installed successfully on different joints of the human body, allowing for the monitoring of human movement and human respiratory changes. These results indicate that the sensor has promising potential for applications in human motion monitoring and physiological activity monitoring.