Highly Sensitive E-Textile Strain Sensors Enhanced by Geometrical Treatment for Human Monitoring

Abstract

Electronic textiles, also known as smart textiles or smart fabrics, are one of the best form factors that enable electronics to be embedded in them, presenting physical flexibility and sizes that cannot be achieved with other existing electronic manufacturing techniques. As part of smart textiles, e-sensors for human movement monitoring have attracted tremendous interest from researchers in recent years. Although there have been outstanding developments, smart e-textile sensors still present significant challenges in sensitivity, accuracy, durability, and manufacturing efficiency. This study proposes a two-step approach (from structure layers and shape) to actively enhance the performance of e-textile strain sensors and improve manufacturing ability for the industry. Indeed, the fabricated strain sensors based on the silver paste/single-walled carbon nanotube (SWCNT) layers and buffer cutting lines have fast response time, low hysteresis, and are six times more sensitive than SWCNT sensors alone. The e-textile sensors are integrated on a glove for monitoring the angle of finger motions. Interestingly, by attaching the sensor to the skin of the neck, the pharynx motions when speaking, coughing, and swallowing exhibited obvious and consistent signals. This research highlights the effect of the shapes and structures of e-textile strain sensors in the operation of a wearable e-textile system. This work also is intended as a starting point that will shape the standardization of strain fabric sensors in different applications.

Ultrasensitive Strain Sensor Based on Pre-Generated Crack Networks Using Ag Nanoparticles/Single-Walled Carbon Nanotube (SWCNT) Hybrid Fillers and a Polyester Woven Elastic Band

“…With the prebuilt cracks on the silver layer, relative resistance change increased by approximately 50 times. This was much greater than the effects reported by other studies that also leveraged shape deformations to enhance the sensitivity: the introduction of micro-sized pores and mechanical fragmentation increased the sensitivity by approximately five times [ 17 ] and 15 times [ 13 ], respectively. Pre-crack generation improved the relative resistance changes of both Ag/SWCNT and SWCNT sensors; however, the enhancement effect was only notably significant when the pre-cracks were formed on the surface of the silver pastes.…”

“…For example, Wang et al [ 30 ] proposed a printed crack-based strain sensor with PDMS and addressed that the adhesiveness to the printing device as well as hydrophobicity of PDMS make it inevitable to perform surface treatments beforehand. However, textile-based strain sensors can be fabricated utilizing the textiles as received and dipping or immersing them into solutions with active materials [ 17 , 25 , 27 ]. In addition, the woven PEB does not shrink in the direction perpendicular to the elongation stress, while TPU mat was reported to show such deformation [ 6 ].…”

“…Flexible polymers, such as Ecoflex [ 10 ], polydimethylsiloxane (PDMS) [ 2 ], thermoplastic polyurethane (TPU) [ 9 ], and textiles [ 17 ], are popular substrates for strain sensors. Here, the simplicity of the methodologies for embedding active nanomaterials into flexible substrates is a crucial determinant of the possibility for scaling-up production and practical applications.…”

Wearable Textile UHF-RFID Sensors: A Systematic Review

“…With regard to the scenario-based applications, textile UHF-RFID sensors have great development potential in many different fields of productions and life. Currently, the main application researches focus on the fundamental functions of textile UHF-RFID sensors such as the ID-sensing, strain sensing [84], humidity sensing, sweat sensing and others. However, advanced functions are not covered.…”

Effects of 3D Printing-Line Directions for Stretchable Sensor Performances

“…Some previous studies on the effects of geometry (shapes and structures) on the strain sensors [ 28 ] and 3D printing samples [ 29 , 30 , 31 ] are the motivation for the paper. We realize that the geometric approach is easy, fast, and low-cost to improve sensor performance in wearable systems.…”