A wearable yarn-based piezo-resistive sensor

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Abstract

Smart textiles using fabric-based sensors to monitor gesture, posture or respiration have been exploited in many applications. Most of fabric-based sensors were fabricated by either coating piezo-resistive materials on a fabric or directly knitting conductive fibers into fabrics. Obviously, structures of textiles, including yarn structure and fabric structure, will affect the performances of sensors. However, researches on the effects of the structures have not been explored yet. In this paper, yarn-based sensors were fabricated by using piezo-resistive fibers, elastic, and regular polyester fibers. Single and double wrapping methods were employed to fabricate the yarn-based sensors. Performances of the designed yarn-based sensors were evaluated by measuring their resistance changes under variable loading. It is shown that slippage occurs between the piezo-resistive fibers and the core fibers. The relationship of the resistance versus the strain cannot be described as a linear function and should be modeled as a second order equation. Due to the symmetric structure, the double wrapping yarn could resist the slippage and higher linearity in the resistance curve can be provided. Thus it can be served as a better sensing element. The study also investigates the issue of the twist per meter (TPM) and finds that there are no significant effects for using different TPM. Finally, experiments were conducted on a respiration monitoring system to prove the feasibility of the yarn-based sensors and the results demonstrate that the yarn-based sensor can track the respiratory signals precisely.

Introduction

Smart textiles are becoming very popular in the past decade [1]. One advanced study was to develop a wearable-computing technique which integrated smart textures with semiconductors. An intelligent textile was proposed to fabricate silicon flexible skins with regular textiles [2]. Another application in semiconductors was to form flexible transistors on textile fibers [3], [4]. Although inspiring results have been reported in the past, problems such as complicated process, mass production, washability, and wearing comforts are still under investigation.

The other study was to develop textiles which can detect environmental conditions, and then react and adapt to environmental changes. These smart textiles can measure and monitor the physiological conditions of the wearer. Thus they could be applied in healthcare systems. One type of the smart sensing textures was developed by using fabrics having piezo-resistive properties. The approach for fabricating the fabrics was to coat a thin layer of piezo-resistive materials, such as polypyrrole (PPy, a ∏-electron conjugated conducting polymer) or a mixture of rubbers and carbons, on conventional fabrics to form fabric-based sensors [5], [6], [7], [9], [12]. The function of the developed sensors is similar to that of flexible strain gauges which can measure strains when they are subjected to a tensile stress. Many applications based on this kind of sensing fabrics were developed. One typical application was to capture posture or motion [6], [11], [13], [14]. The others were related to measuring biomechanical signals for healthcare, especially for respiration detections [15], [16], [17], [18], [19]. The coated fabrics were highly dependent upon knitting or weaving topology. Performances can be quite limited if structures of fabrics and yarns were not properly designed or optimized. Therefore, the piezo-resistive sensing fabrics might have some shortcomings such as low dynamic range, poor repeatability, performance deterioration after washing or repeated folding, and complicated manufacturing process.

Besides the development of the piezo-resistive sensing fabrics, another approach was to knit conductive fibers with non-conductive base fibers [8]. The knitted fabrics sensors can be regarded as equivalent circuits with a network of resistances, capacitances, and inductances. As the deformation of the fabrics sensor occurs, the electrical properties of the elements will be changed. The changes were measured to calculate the deformation [8], [9], [10]. Although the integration of conductive fibers improve the sensing performance even after washing, the sensor can only be made by using knitting process and a large knitting cloth is needed in order to obtain satisfactory results. This requirement might limit the freedom in design of modern clothes. Furthermore, the fabric-based sensor is considered only as two-dimensions because it is made by plane knitting. Space resolution is not high and the obtained information from the average area change could be quite limited. Moreover, the research issues such as yarn topology and structural deformation of fabrics-based sensors have not been investigated yet.

In this paper, yarn-based sensors were developed to improve sensing characteristics [20]. Instead of using fabrics as base elements, we first fabricated the yarns by using piezo-resistive fibers, elastic, and regular polyester fibers. Then the yarn was used as raw materials to make cloth, dress and sensing textiles. As compared to fabric-based sensors, the yarn itself is a sensing element and thus it is easier to be used in smart textiles by conventional knitting or weaving processes. Dependent upon different applications, several sensing segments can be embedded into textiles such that distributed strains can be measured with the sensors. This approach has the advantages such as higher space resolutions, more comforts, better functionality and easier in style design. For fabrication process, single and double wrapping methods were employed. Experiments were performed to measure the resistance changes of the yarn under variable loading. The linearity of the single and double wrapping yarn sensors was evaluated. It is found that the double wrapping method can achieve higher linearity than the single wrapping approach. Physical interpretations are given to illustrate this phenomenon. Furthermore, different twists per meter (TPM) of carbon coated fibers (CCF) wrapping on the core yarn was also investigated. No significant effects on different TPM were found in the experiments. Finally, a respiration monitoring system was used as a test bed to prove the feasibility of the yarn-based sensors and the results demonstrate that the yarn-based sensor can track the respiratory signals precisely.

Section snippets

Materials and methods of the yarn-based sensors

Yarns are normally considered as the basic elements of forming fabrics and textiles. But fibers are truly the raw elements of yarns. Yarns are made by combining different types of fibers into a skein. Fiber materials and forming process can have dramatically effects on the characteristics of the yarn. The process of forming a yarn can be categorized into three main methods. One simplest method is the doubling which the fibers are put in parallel to form the yarn. The fibers are bonded together

Experimental results of the yarn-based sensors

To evaluate the sensing behaviors of the yarn, experiments on resistance changes under different loadings were conducted in this section. The Mini44 INSTRON was utilized for measuring tensile forces and Fluke189 multi-meter was used to measure the resistances. The samples were selected to be 6 cm long with the preload equal to 20 g. The force and the resistance were measured as the length of the sample was stretched per mm. The total stretched length was 14 mm and 15 points were taken. To evaluate

Experimental test on a respiration monitoring system

In order to verify the feasibility of the yarn-based sensor, an experimental system for monitoring respiration signal was developed in this section. For simplicity, a Crochet knitting machine was used to make elastic bands, which were combined with several commercial polyester yarns (333 dtex), rubber yarns (Φ 0.5 mm) and two sensing yarns. The function of the rubber yarns is to provide the flexibility. The length of the elastic band is about 5 cm. Two elastic bands were sewed on a garment to form

Conclusions

In this paper, an innovative yarn-based sensor was developed and its functionality was verified by using a respiration monitoring system. Yarn-based sensors were fabricated by using piezo-resistive fibers, elastic, and regular polyester fibers. Single and double wrapping methods were utilized to fabricate the yarn-based sensor. It is shown that the relationship between the resistance and the strain of the single CCF fiber can be described as a linear function. However, the resistance curve for

Ching-Tang Huang, graduated from National Taiwan University in 1988, and received the M.S. degrees in Mechanical Engineering from National Taiwan University in 1993. Now, he is a Ph.D. student in Mechanical Engineering, National Taiwan University. Simultaneously, he is also the chief of system and information section, Taiwan Textile Research Institute. The major research topic is about the smart textile, focusing on how to develop sensors and actuators, which are tiny and could be embedded in

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Ching-Tang Huang, graduated from National Taiwan University in 1988, and received the M.S. degrees in Mechanical Engineering from National Taiwan University in 1993. Now, he is a Ph.D. student in Mechanical Engineering, National Taiwan University. Simultaneously, he is also the chief of system and information section, Taiwan Textile Research Institute. The major research topic is about the smart textile, focusing on how to develop sensors and actuators, which are tiny and could be embedded in the textile, or the textiles are sensors or actuators themselves, and how to implement the smart clothing with miscellaneous sensors and actuators on the basis of maintaining the traditional comfort.

Chien-Lung Shen, was born in Tainan, Taiwan in 1976. He received his M.S. degree in Department of Automatic Control Engineering at Feng Chia University, Taiwan in 2000. From 2001, he has been joining Department of Product Development, Taiwan Textile Research Institute as a researcher. From 2005, he has been joining Institute of Biomedical Engineering System Engineering at National Yang-Ming University as a candidate for doctor's degree. His main research interests are electronic and electric circuits design, computer programming, biomedical and sensor applications.

Chien-Fa Tang, received the M.Sc. degree in textiles from the UMIST (University of Manchester Institute of Science and Technology), UK, in 1997. He has worked on the TTRI since 1990. His research interests include electrical interface, biomedical signal processing, digital/analog circuit design, and system control.

Shuo-Hung Chang, received the B.S. degree in 1974 from National Chen Kung University, Taiwan and the M.S. and Ph.D. degrees in 1981 and 1985 from the University of Cincinnati. From 1984 to 1990 he worked with the IBM T.J. Watson Research Center in Yorktown Heights, NY, involved in advanced computer peripheral devices, such as printer, data storage and information display. Since 1990, he has been at the National Taiwan University, where he is a professor in Mechanical Engineering Department. He is the Director of the Nano-Electro-Mechanical Systems (NEMS) Research Center and the Deputy Director of the Center for Nano-Science and Technology. He was a visiting scholar with National Institute of Standards and Technology (NIST) and the Stanford University in 2000 and 2003, respectively. His research interests involve electro-elasticity theory and modeling, ultrasonics, sensors and actuators, nanometer positioning and carbon nanotubes.

Dr. Chang is a member of the IEEE, American Society of Mechanical Engineers (ASME), Chinese Society of Mechanical Engineers (CSME), Chinese society of Mechanism and Machine Theory, and a member of the executive committee of the Nanotechnology and Micro-System Association.

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