Next Article in Journal
Er3+/Ho3+-Codoped Fluorotellurite Glasses for 2.7 µm Fiber Laser Materials
Previous Article in Journal
Welcome to Fibers—A New Open Access Journal for Fibrous Material Science

Fibers 2013, 1(1), 2-10; doi:10.3390/fib1010002

Article
Preliminary Investigations into the Development of Textile Based Temperature Sensor for Healthcare Applications
Muhammad Dawood Husain 1,* and Richard Kennon 2
1
Department of Textile Engineering, NED University of Engineering and Technology, University Road 75270, Karachi, Pakistan
2
School of Materials, University of Manchester, Manchester, M60 1QD, UK; E-Mail: richard.kennon@manchester.ac.uk
*
Author to whom correspondence should be addressed; E-Mail: dawood@neduet.edu.pk; Tel.: +92-21-9926-1261 (ext. 2295); Fax: +92-21-9926-1255.
Received: 28 January 2013; in revised form: 18 March 2013 / Accepted: 17 April 2013 /
Published: 25 April 2013

Abstract

: Human body temperature is an important sign of physical condition in terms of comfort, heat or cold stresses, and of performance. This paper presents the preliminary investigation into the design, manufacturing and testing of the textile based temperature sensor. This sensing fabric may be employed to measure the temperature of the human body on a continuous basis over extensive periods of time, outside the clinical environment. The sensing fabric was manufactured on an industrial scale flat-bed knitting machine by laying-in the sensing element (in the form of fine metal wire) into the double layer knitted structure. The operational principle of the sensing fabric is based on the inherent tendency of metal wire to change in its electrical resistance because of the change in its temperature. An experimental resistance-temperature relationship showed promising validation in comparison with their modeled counterparts.
Keywords:
temperature sensor; conductive textiles; industrial knitting machine; temperature-resistance; resistance thermometers; human body temperature

1. Introduction

In last few years, within the domain of electronic textiles, rigorous research has been carried out, predominantly in respect of the inclusion of sensing functions into the textile products. Textiles are comfortable to wear and offer a flexible platform for imparting sensing functions. The direct outcome of applying this technology is the advancement of Wearable Health Monitoring Systems (WHMS) intended for round the clock monitoring of the vital signs of the human body over extended periods of time. One of the important components of WHMS is the sensor which receives vital signs information from the wearer and relays it for further processing. This information may be utilized to help generate a general health picture for the diagnosis of various diseases and its management [1].

Within the domain of WHMS, the focal point of most of the research has been the development of textile integrated Electrocardiography (ECG) and respiration sensors. For the measurement of human body temperature, most researchers have relied on commercially available thermistor and temperature ICs, which are generally attached outwardly to the garment [2,3,4,5]. The literature also demonstrates that the fabrication of sensing fabric for temperature measurement has only been little explored in a few individual studies [6,7]. These studies were preliminary in nature and their products were manufactured by cumbersome manual processes.

Human body temperature is one of the four vital signs which are standard in medical settings in addition to heart rate, blood pressure and respiratory rate. Vital signs information is used for the medical assessment of the state of the health. Human body temperature is an important indicator of the physical condition of human body. It relates to the comfort and performance of human body in heat and cold stresses. The deviation of few degrees, from the normal body temperature, i.e., 37 °C can cause impairment and fatality to the human body [8].

This paper presents preliminary research into the design, manufacturing and testing of Temperature Sensing Fabric (TSF), developed by embedding fine metallic wire into the structure of textile material. The operational principle of the TSF is based on the inherent tendency of metal wire to change in its electrical resistance because of the change in its temperature. Samples created on a commercial textile manufacturing machine have been tested in various thermal environments, under laboratory conditions, to study the relationship between the resistance and temperature of the sensing fabric. The temperature-resistance relationship demonstrated a linear trend with a goodness of fit (r2-value) of over 99%.

2. Materials and Methods

The Temperature Sensing Fabric (TSF) was constructed by laying-in a defined length of a fine metallic wire within the courses of a double layer knitted structure as shown in Figure 1. The structure of the TSF fabric was designed in the Shima Seiki Knit Paint environment before being manufactured on a 10 gauge Shima Seiki flat bed knitting machine. Samples were developed with an 8 cm × 8 cm sensing area as shown in Figure 2.. Each sample comprised of 39 wales; 33 for the inlay area and 6 for the protective edging. In order to achieve high sensitivity from a small-sized TSF, it was desirable to pack a high density of wire inlay into the designated sensing area. Therefore, extra spacer courses were introduced, along with knit courses to prevent the surface of individual lengths of wire from touching adjacent wires. TSF samples were developed with two different wire inlay densities, i.e., 4.7 and 6.4 inlays/cm. Low inlay Density (LD) samples required more spacer yarn than High inlay Density (HD) to achieve the same compactness as HD samples.

For a base fabric of TSF, knitted structures were preferred over woven structures because of their comfort and ability to conform according to body shape. The metal filament is embedded exactly in the middle of a double layer structure; hence it is barely visible and does not affect the aesthetic properties of the fabric. The double layer structure of the TSF also provides protection of the metal wire from wear and tear.

Fibers 01 00002 g001 1024
Figure 1. Concept of Temperature Sensing Fabric (TSF); sensing wire inlaid in a double layer knitted structure.

Click here to enlarge figure

Figure 1. Concept of Temperature Sensing Fabric (TSF); sensing wire inlaid in a double layer knitted structure.
Fibers 01 00002 g001 1024
Fibers 01 00002 g002 1024
Figure 2. A TSF sample of sensing area of 8 cm × 8 cm along with its magnified view.

Click here to enlarge figure

Figure 2. A TSF sample of sensing area of 8 cm × 8 cm along with its magnified view.
Fibers 01 00002 g002 1024

The classic equation representing the relationship of the resistance of metal wire Rref to its diameter (d), length (1) and resistivity (ρ) is expressed in equation (1) [9]:

Fibers 01 00002 i001

Resistance (Rref) is expressed at a reference temperature. Resistivity (ρ) is a function of the metal, while diameter (d) & length (1) are the functions of the wire. The length of metal wire can be mathematically related to the dimensions of the TSF as:

Fibers 01 00002 i002

Where L and W represents the length and width of the TSF and (D) denotes the packing density of the metal wire. From Equation (2), it can be noticed that a metal wire of one meter (with packing density of 6 cm−1) can easily be contained in a 4 cm × 4 cm patch of TSF. A modified relationship between resistance of TSF to its dimensional parameters may be obtained by combining Equations (1) and (2):

Fibers 01 00002 i003

Once the diameter and resistivity of the wire are known, dimensions of a TSF patch can be optimized in order to meet required reference resistance by making use of Equation (3). By employing sensing element of high resistivity and fine diameter, the target reference resistance may be achieved on a small sensing area. Therefore it is important to lay-in the sensing wire as compactly as possible to accomplish the maximum ratio of the TSF reference resistance to the TSF sensing area. In order to realize highly sensitive TSF, high value of reference resistance is desirable; while small sensing area is desirable for producing highly responsive (thermally) TSF. The relationship between the temperature (T) of the metal wire to its resistance can be expressed as [10].

Fibers 01 00002 i004

Where α is the temperature coefficient of resistance. After merging Equation (3) and Equation (4), the resistance–temperature relationship of the TSF can be expressed in the following form:

Fibers 01 00002 i005

Various types of metal wire could be employed as the sensing element of a TSF. Nickel, tungsten and copper wires were selected as experimental sensing elements for TSF samples, because of their high resistivity and temperature coefficient of resistivity, and to take advantage of their linear temperature-resistance relationship between 0 °C and 100 °C. Besides that, they are easily available in the market and relatively inexpensive. Table 1 presents the classification of developed samples according to inlay density and type of metal wire.

Table Table 1. Categories of TSF samples along with parameters for modelling.

Click here to display table

Table 1. Categories of TSF samples along with parameters for modelling.
Sample TagSensing WireDia. (µm)Inlay Density (cm−1)Sensing Area (Length × Width) cm2Resistivity (Ωm) at 20 °CTemp. Resist. Coeff. (/°C)
N100HDNickel1006.4–High8 × 89.5e-080.0048
N100LD4.7–Low
W50HDTungsten506.4–High8 × 86.4e-080.0035
W50LD4.7–Low
NC125HDCopper (Nickel Coated)1256.4–High8 × 82.2e-080.0040
NC125LD4.7–Low

TSF samples were calibrated at steady thermal points of 20, 30, 40, 50 and 60 °C in a laboratory oven. An Agilent multimeter 34401 was used to measure resistance at steady temperature points.

3. Results and Discussion

The reference resistance (R20) of the TSF samples was measured at a reference temperature of 20 °C. Table 2 presents the comparison between average experimental and modelled reference resistance for each sample category. It can be observed that modelled resistance is slightly higher than the experimental resistance in all instances. This could be due to the non-conformance of the sensing fabric to its designed dimension of 8 cm × 8 cm. Unlike in electronics, where the boundaries of a circuit may be defined with high precision, textile materials exhibit a much higher degree of manufacturing tolerance. It has been observed that experimental resistance of all the samples and their replicates were within 2 percent of their modelled counterparts. This gave a 98% confidence level in respect of Equation (3) prior to the design of sensing fabrics with the required reference resistance.

Table Table 2. Comparison of experimental and modelled reference resistance (at 20 °C).

Click here to display table

Table 2. Comparison of experimental and modelled reference resistance (at 20 °C).
Sample TypeExperimental Resistance (Ω)Modelled Resistance (Ω)Difference (Ω)% change
N100HD46.3347.130.801.72
N100LD35.1035.350.250.70
W50HD121.81124.162.351.93
W50LD92.1992.950.760.82
NC125HD6.646.740.101.56
NC125LD5.045.060.020.46

Irrespective of the type of sensing element and the wire diameter, the experimental resistance of samples with Low inlay Density (LD) are closer to their modelling counterparts, as compared to samples with High inlay Density (HD). One of the possible reasons could be the sensing wire making unplanned contact with itself at the fabric edges. Since HD samples have high wire density and fewer spacer courses, so the chances of reduced resistance, by wire to wire shorting at the edges of the sample, are higher.

Experimental Resistance-Temperature data shows a linear correlation and follows the same behavior as their modeled counterparts. Figure 3 presents the one such correlation belongs to the TSF sample N100HD1. Resistance-Temperature data from all the TSF samples has been fitted with straight line polynomials. Variance between RT data points and the fitted polynomial has been calculated and presented in the form of r2-value (coefficient of determination).

Fibers 01 00002 g003 1024
Figure 3. Comparison of experimental and modelled temperature-resistance relationship of sample N100HD-S1.

Click here to enlarge figure

Figure 3. Comparison of experimental and modelled temperature-resistance relationship of sample N100HD-S1.
Fibers 01 00002 g003 1024

Table 3 presents the average r2-value and the reference equation of each sample category. It can be seen from Table 3 that all samples exhibit a high value of r2 i.e., over 99%. The r2-values of HD samples is slightly less than for the LD samples. A possible reason could be wire-to-wire contact at the edges of the samples caused by small changes in the length of the wire by thermal expansion at elevated temperatures.

Table Table 3. Coefficient of determination and reference equation of each sample category.

Click here to display table

Table 3. Coefficient of determination and reference equation of each sample category.
Sample Typer2-valueReference Equation
N100HD0.992R = 0.23*T + 42.05
N100LD0.996R = 0.17*T + 31.86
W50HD0.989R = 0.43*T + 113.78
W50LD0.999R = 0.32*T + 85.76
NC125HD0.990R = 0.027*T + 6.14
NC125LD0.995R = 0.020*T + 4.61

The Resistance-Temperature curves of the TSF samples can also be defined in terms of Resistance Ratio (RR), which was calculated by taking the ratio of “fitted resistanc (Rfitted) at temperature (T)” to “reference resistance (R20) at a reference temperature of 20 °C.

Fibers 01 00002 i006

Defining the TSF resistance-temperature data by normalizing their resistance data with respect to their reference resistance has several advantages [11]. TSF samples comprised of different inlay density and dimensions but with the same type of sensing element could be readily compared in this way.

The resistance-ratio curves of all the TSF samples are shown in Figure 4. All TSF samples with the same type of sensing wire exhibited the same trend irrespective of their inlay density. In the same figure, experimental values for the temperature coefficient of resistivity (α) are also shown; these have been calculated using the reference equations presented in Table 3. As expected, nickel shows the highest alpha values. Usually the copper alpha value is expected to be close to 0.0042; hence the increased value for nickel-coated copper wire almost certainly derives from the nickel coating. As expected, tungsten possesses the lowest alpha values.

Fibers 01 00002 g004 1024
Figure 4. Fitted resistance ratios along with their corresponding alpha values (Temperature coefficient of resistivity).

Click here to enlarge figure

Figure 4. Fitted resistance ratios along with their corresponding alpha values (Temperature coefficient of resistivity).
Fibers 01 00002 g004 1024

It should, however, be borne in mind that the alpha values cannot on their own be used to judge the sensitivity of the sensing fabric, as the reference resistance of the TSF is equally important. Due to the high reference resistance of the TSF fabric samples made with nickel and tungsten elements, they possess high sensitivities. Figure 5 shows the average sensitivity of each sample type calculated by considering the change in resistance resulting from a 1 °C change in temperature. Due to the low sensitivity of nickel-coated copper wire, it would be difficult to develop an electronic circuit with a resolution of 0.1 °C.

Fibers 01 00002 g005 1024
Figure 5. Sensitivity analysis; change of resistance (mΩ) for 1 °C change in temperature.

Click here to enlarge figure

Figure 5. Sensitivity analysis; change of resistance (mΩ) for 1 °C change in temperature.
Fibers 01 00002 g005 1024

It has also been observed that inlaid wire showed constant values of experimental sensitivity over the tested temperature range. These observations suggest that each sample has to be calibrated individually at one temperature point, which would be enough to generate a calibration equation.

It has been previously mentioned that researchers have developed smart garments with integrated textile-based ECG, respiration and activity sensors. This new design of temperature sensing fabric can be used either as a standalone sensing device to measure human body temperature or, in conjunction with other integrated textile-based sensors, as part of a smart shirt to provide a complete health picture. It may also be used to measure the temperature of the environment by embedding it into the outer layer of jackets. A combination of two sensing patches integrated into the inner and outer strata of the garment can also help us to measure the heat flux or loss of heat from the body to the environment [12].

4. Conclusions

This paper reports preliminary investigation into the design and development of commercially knitted smart fabric for temperature measurement that can be integrated into garments, for the measurement of skin temperatures of the human body. Nickel and tungsten wires proved to be good candidates for the sensing element of the temperature sensitive fabric because of their high reference resistance, sensitivity and availability. A modified mathematical relationship can be used, to design the sensing fabric with optimised dimensions, in order to achieve a targeted reference resistance. It has been observed that experimental reference resistance of all samples were within two percent of their modelled values. Experimental temperature-resistance curves show a linear relationship and follow the same trend as their modelled counterparts. The packing density of the wire within the knitted samples has a small effect on the reference resistance and on the smoothness of the RT curves, as low inlay densities demonstrated better agreement of results with their modelled values. Future work includes the development of a smart shirt with integrated temperature sensing patches and its testing in a realistic environment to specify the baseline characteristics i.e., accuracy, response time, thermal conduction errors, self heating, insulation resistance, etc.

Acknowledgments

The authors would like to acknowledge the funding provided by the NED University of Engineering & Technology, Pakistan through the Higher Education Commission of Pakistan, to carry out this study.

Conflict of Interest

The authors declare no conflict of interest.

References and Notes

  1. Funnell, R.; Koutoukidis, G.; Lawrence, K. Chapter 21–Vital Signs. In Tabbner’s Nursing Care: Theory and Practice; Churchill Livingstone, Australia, 2008; pp. 251–274. [Google Scholar]
  2. Curone, D.; Dudnik, G.; Loriga, G.; Magenes, G.; Secco, E.L.; Tognetti, A.; Bonfiglio, A. Smart Garments for Emergency Operators: Results of Laboratory and Field Tests. In Proceedings of the 30th Annual International IEEE Engineering in Medicine and Biology Society (EMBS) Conference, Vancouver, British Columbia, Canada, 20−24 August 2008.
  3. Derchak, P.A.; Ostertag, K.L.; Coyle, M.A. LifeShirt® System as a Monitor of Heat Stress and Dehydration. In VivoMetrics, Inc: Ventura, CA, USA, 2004. [Google Scholar]
  4. Noury, N.; Dittmar, A.; Corroy, C.; Baghai, R.; Weber, J.L.; Blanc, D.; Klefstat, F.; Blinovska, A.; Vaysse, S.; Comet, B. VTAMN–A Smart Clothe for Ambulatory Remote Monitoring of Physiological Parameters and Activity. In Proceedings of the 26th Annual International IEEE Engineering in Medicine and Biology Society (EMBS) Conference, San Francisco, California, USA, 1−4 September 2004.
  5. Pandian, P.S.; Mohanavelu, K.; Safeer, K.P.; Kotresh, T.M.; Shakunthala, D.T.; Gopal, P.; Padaki, V.C. Smart Vest: Wearable multi-parameter remote physiological monitoring system. Med. Eng. Phys. 2008, 30, 466–477. [Google Scholar] [CrossRef]
  6. De Rossi, D.; Della Santa, A.; Mazzoldi, A. Dressware: Wearable hardware. Mater. Sci. Eng. C 1999, 7, 31–35. [Google Scholar] [CrossRef]
  7. Locher, I.; Kirstein, T.; Troester, G. Temperature Profile Estimation with Smart Textiles. In Proceedings of the International Conference on Intelligent textiles, Smart clothing, Well-being, and Design, Tampere, Finland, 19−20 September 2005.
  8. Ring, E.F.J. Progress in the measurement of human body temperature. Eng. Med. Biol. Mag. IEEE 1998, 17, 19–24. [Google Scholar] [CrossRef]
  9. Burns, J. 32.2 Resistive Thermometers. In The Measurement, Instrumentation, and Sensors: Handbook; Webster, J.-G., Ed.; CRC Press LLC: Boca Raton, FL, USA, 1999; pp. 3213–3224. [Google Scholar]
  10. Dogan, I. Chapter 4–RTD Temperature Sensors. In Microcontroller Based Temperature Monitoring and Control; Newnes: Oxford, UK, 2002; pp. 87–106. [Google Scholar]
  11. McGee, T.D. Electrical Resistance Temperature Measurement using Metallic Sensors. In Principle and Method of Temperature Measurement; Wiley-Intercience: Hoboken, NJ, 1988; pp. 141–168. [Google Scholar]
  12. Oliveira, A.; Gehin, C.; Massot, B.; Ramon, C.; Dittmar, A.; McAdams, E. Thermal Parameters Measurement on Fire Fighter: Improvement of the Monitoring System. In Proceedings of the Engineering in Medicine and Biology Society (EMBC), Annual International Conference of the IEEE, Buenos Aires, Argentina, 31 August−4 September 2010; pp. 6453–6456.
Fibers EISSN 2079-6439 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert