# Fiber-Based Sensors and Energy Systems for Wearable Electronics
## 3 Fiber-Based Sensors
### Tactile Sensing Fibers  
Pressure and strain sensors have been a popular field of research for decades. They electrically mimic the function of mechanoreceptors inside human skin (hence the name e-skin) and show promising applicability in soft robotics and sensory prostheses [5]. Conventionally these e-skins were fabricated in a film using an elastic polymer substrate and conductive polymers or nanomaterials [6; 59]. These film e-skins usually adhere to the surface of robots and human skins for monitoring environmental and physiological stimuli, such as external pressure, heartbeat, or joint angle [60; 61]. Although these film e-skins showed great sensing capabilities, flexibility and stretchability, the longevity and breathability remain questionable, limiting their long-term usage, especially as wearable sensors [1; 12]. Therefore, many studies attempted to fabricate wearable e-skins using functional fiber-based textiles [19; 43; 62; 63]. These textile tactile sensors can be classified by the sensing mechanisms: (1) Resistive sensors [10; 40; 64; 65; 66; 67], (2) piezoelectric sensors [43], and (3) capacitive sensors [62; 68; 69]. To measure the sensitivity of resistive and capacitive tactile sensors, Gauge Factor (GF) is often used. GF can be calculated by \(\Delta\)R/R\({}_{0}\)/\(\epsilon\) or \(\Delta\)C/C\({}_{0}\)/\(\epsilon\) for resistive and capacitive sensors, respectively (\(\Delta\)R: change in resistance under the stain, R\({}_{0}\): baseline resistance, \(\epsilon\): strain). A number of factors can influence GF, such as the filler materials, percolation network, piezoresistive mechanism, and structure of the sensor. [69; 70]. Therefore, GF can be calibrated by tuning these factors. For example, woven or knitted structures of conductive fibers provide several electrical contacts and tend to increase GF [19]. However, it has been suggested that the higher GF is associated with lower stretchability [13; 71]. In the case of capacitive sensors, the parallel plate capacitor design leads to the changes in surface area and dielectric layer thickness at the same time in response to mechanical stimuli. This causes a linear sensitivity and a maximum GF of 1 [13; 72]. The resistive tactile sensors are the most popularly studied for their simplicity. These conductive sensors change their resistance in response to the mechanical stress, and this change in the resistance can be used to determine the amplitude of the stress. Pre-existing natural fibers can simply be made into resistive textile tactile sensors via the outside coating method. In one study, [PERSON] et al. reported that depositing nickel (Ni) onto cotton fabric via the electroless deposition (ELD) technique resulted in highly conductive fabrics (21.82 S/cm) that are capable of detecting strains via resistive changes [73]. This cotton fabric strain sensor suffered from limited stretchability of 14% and durability (50% decrease in sensitivity after ~300 stretch cycles), due to the mechanical characteristics of deposited Ni. Nonetheless, this fabric sensor showed promising applicability as a wearable strain sensor as it was able to be fixed onto the fingers and arm joints to detect bending. Dip-coating of various carbon-based materials and polymers is also a popular method of fabricating conductive natural fabrics because it is highly effective and cost-effective. One study fabricated conductive cotton and wool fabric by dip-coating them in a solution containing graphene nanoplate (GNP) and carbon black (CB) [12]. Both the conductive cotton and wool fabrics showed good stretchability and strain sensing ability up to 150%, with a maximum GF of 6 for cotton fabric and 0.5 for wool fabric. Furthermore, the sensitivity of the conductive fabrics decreased insignificantly after 1000 cycles of 75% stretching. These sensors were then taped onto a volunteer's finger and detected fast finger movements, further suggesting the usefulness of natural fabric-based sensors as wearable devices.