A Novel Textile Stitch-Based Strain Sensor for Wearable End Users

Orathai Tangsirinaruenart, George K. Stylios

Research output: Contribution to journalArticle

Abstract

This research presents an investigation of novel textile-based strain sensors and evaluates their performance. The electrical resistance and mechanical properties of seven different textile sensors were measured. The sensors are made up of a conductive thread, composed of silver plated nylon 117/17 2-ply, 33 tex and 234/34 4-ply, 92 tex and formed in different stitch structures (304, 406, 506, 605), and sewn directly onto a knit fabric substrate (4.44 tex/2 ply, with 2.22, 4.44 and 7.78 tex spandex and 7.78 tex/2 ply, with 2.22 and 4.44 tex spandex). Analysis of the effects of elongation with respect to resistance indicated the ideal configuration for electrical properties, especially electrical sensitivity and repeatability. The optimum linear working range of the sensor with minimal hysteresis was found, and the sensor’s gauge factor indicated that the sensitivity of the sensor varied significantly with repeating cycles. The electrical resistance of the various stitch structures changed significantly, while the amount of drift remained negligible. Stitch 304 2-ply was found to be the most suitable for strain movement. This sensor has a wide working range, well past 50%, and linearity (R2 is 0.984), low hysteresis (6.25% ΔR), good gauge factor (1.61), and baseline resistance (125 Ω), as well as good repeatability (drift in R2 is −0.0073). The stitch-based sensor developed in this research is expected to find applications in garments as wearables for physiological wellbeing monitoring such as body movement, heart monitoring, and limb articulation measurement.
Original languageEnglish
Article number1469
Number of pages17
JournalMaterials
Volume12
Issue number9
DOIs
Publication statusPublished - 7 May 2019

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Textiles
Sensors
Acoustic impedance
Polyurethanes
Gages
Hysteresis
Knit fabrics
Monitoring
Nylons
Silver
Elongation
Electric properties
Mechanical properties
Substrates

Keywords

  • Conductive thread
  • Stitch structure
  • Textile-based stretch sensors
  • Wearable stretch sensor

ASJC Scopus subject areas

  • Materials Science(all)

Cite this

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title = "A Novel Textile Stitch-Based Strain Sensor for Wearable End Users",
abstract = "This research presents an investigation of novel textile-based strain sensors and evaluates their performance. The electrical resistance and mechanical properties of seven different textile sensors were measured. The sensors are made up of a conductive thread, composed of silver plated nylon 117/17 2-ply, 33 tex and 234/34 4-ply, 92 tex and formed in different stitch structures (304, 406, 506, 605), and sewn directly onto a knit fabric substrate (4.44 tex/2 ply, with 2.22, 4.44 and 7.78 tex spandex and 7.78 tex/2 ply, with 2.22 and 4.44 tex spandex). Analysis of the effects of elongation with respect to resistance indicated the ideal configuration for electrical properties, especially electrical sensitivity and repeatability. The optimum linear working range of the sensor with minimal hysteresis was found, and the sensor’s gauge factor indicated that the sensitivity of the sensor varied significantly with repeating cycles. The electrical resistance of the various stitch structures changed significantly, while the amount of drift remained negligible. Stitch 304 2-ply was found to be the most suitable for strain movement. This sensor has a wide working range, well past 50{\%}, and linearity (R2 is 0.984), low hysteresis (6.25{\%} ΔR), good gauge factor (1.61), and baseline resistance (125 Ω), as well as good repeatability (drift in R2 is −0.0073). The stitch-based sensor developed in this research is expected to find applications in garments as wearables for physiological wellbeing monitoring such as body movement, heart monitoring, and limb articulation measurement.",
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A Novel Textile Stitch-Based Strain Sensor for Wearable End Users. / Tangsirinaruenart, Orathai; Stylios, George K.

In: Materials, Vol. 12, No. 9, 1469, 07.05.2019.

Research output: Contribution to journalArticle

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