Design and development of graphene-based knitted textile strain sensors for human motion monitoring: optimisation and challenges for real world applications
File(s)
Author(s)
Zhou, Yi
Type
Thesis
Abstract
In recent years, flexible strain sensors based on textiles have been widely applied in human motion monitoring due to their lightweight, flexibility, and comfort. Textiles are characterised by their porous structure and tear resistance, making them optimal for serving as substrates for conductive materials like graphene, known for its excellent electromechanical properties and cost-effective production processes. Despite graphene's potential in textile strain sensors for human motion monitoring, challenges persist in maintaining high sensitivity over large sensing ranges and ensuring compatibility in real-world scenarios. This thesis presents a comprehensive study on developing graphene-based knitted textile strain sensors, focusing on optimising their performance for practical human motion monitoring applications.
To systematically design, analyse, and assess the application of graphene-based textile strain sensors in human motion monitoring, this thesis includes three key studies: 1) Identifying the textile design requirements for graphene-based strain sensors by analysing the characteristics of different textile materials suitable for preparing strain sensors; 2) Developing a flexible and durable graphene knitted strain sensor to cope with challenges encountered in real-world use such as washing, repetitive wearing, and sunlight exposure; 3) Investigating the integration methods of textile sensors into wearable devices, and developing a complete wearable sensing system as well as evaluating its performance in practical applications. Each study involves performance testing of the sensor, from material composition to the final integration into a complete wearable system. The findings indicate that the optimisation of textile design has potential to produce graphene-based strain sensors with high sensitivity and wide sensing ranges, capable of combining outstanding sensing performance with long-term monitoring stability and achieving comprehensive monitoring with fast, convenient integration processes. This research not only advances the state-of-the-art in strain sensing materials but also proposes a scalable manufacturing model for future industrial applications, promising widespread adoption in healthcare and athletic monitoring fields.
To systematically design, analyse, and assess the application of graphene-based textile strain sensors in human motion monitoring, this thesis includes three key studies: 1) Identifying the textile design requirements for graphene-based strain sensors by analysing the characteristics of different textile materials suitable for preparing strain sensors; 2) Developing a flexible and durable graphene knitted strain sensor to cope with challenges encountered in real-world use such as washing, repetitive wearing, and sunlight exposure; 3) Investigating the integration methods of textile sensors into wearable devices, and developing a complete wearable sensing system as well as evaluating its performance in practical applications. Each study involves performance testing of the sensor, from material composition to the final integration into a complete wearable system. The findings indicate that the optimisation of textile design has potential to produce graphene-based strain sensors with high sensitivity and wide sensing ranges, capable of combining outstanding sensing performance with long-term monitoring stability and achieving comprehensive monitoring with fast, convenient integration processes. This research not only advances the state-of-the-art in strain sensing materials but also proposes a scalable manufacturing model for future industrial applications, promising widespread adoption in healthcare and athletic monitoring fields.
Version
Open Access
Date Issued
2024-03
Date Awarded
2024-08
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Stewart, Rebecca
Myant, Connor
Publisher Department
Dyson School of Design Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)