*3.3. Conductive Composite Yarns*

### 3.3.1. Wrapped Structure

The working strain range of the one-dimensional sensor may be limited if the resistance is changed only by the cracks on the surface of the fiber or yarn. To improve its working strain range and stability, the structural adjustment of the yarns has also been explored. Cai et al. prepared a cotton/CNT core-spun yarn sensor by coating CNTs and depositing PPy on the surface (Figure 8a,b) [95]. The yarn has a broad strain range, up to 350%, but its GF is small, only 5.11 and 3.41 at strains of 0–50% and 50–350%, respectively. Cheng et al. developed a simple and mass-produced graphene-based composite yarn with a compression spring structure by plasma treatment and dipping (Figure 8c,d) [96]. The minimum and maximum detection limits of this double-wrapped composite yarn are 0.2 and 100% strain, respectively. Additionally, the signal response speed is fast (<100 ms). After several stretching cycles under 30 and 50% strain, the performance is stable, but its sensitivity is very low. Zhu et al. introduced curcumin-assisted chemical deposition (ELD) to prepare a helical yarn with a metal coating, and established a model to analyze its sensing mechanism [46]. The relative resistance change of the yarn ∆*R* can be expressed as a function related to the tensile strain ε, including θ(ε), g(ε) and Rdetach(ε) (θ is the winding angle, g is the average gap of the separated winding, Rdetach is the resistance of an independent winding). As mentioned above, the yarn strain sensors based on geometric change sensing have excellent linearity, low hysteresis, high stability and a large sensing range, but their sensitivity is limited [15].

#### 3.3.2. Braided Structure

Another design is to use braided yarns to fabricate yarn-based strain sensors. Shi et al. reported a sensor (BWY-AgNWs) composed of stretchable yarns with a braided structure and silver nanowires by dip coating (Figure 9) [97]. The fiber sensor can not only detect various deformations such as stretching, torsion, and bending, but also has a high stable sensitivity (GF = 65) in a larger sensing range (strain can reach 100%). However, due to the insufficient recovery of the microstructure and the brittleness of the AgNWs film, the microcracks cannot be completely merged after release, resulting in the poor repeatability of the strain sensor during multiple cycles of stretching. Furthermore, the high hysteresis of the strain sensor makes its strain response slow, which limits its wearable application. Yang et al. proposed a PET/AgNW/PDMS yarn sensor with braid yarns as the substrate, AgNW as the active material and PDMS as the protective layer by dip coating [98]. The yarn sensor has high conductivity and a wide range of stretchable strain. However, the resistance change does not increase monotonously with the increase in strain, instead of a downward trend after 40% strain. In addition, the relative resistance changes in PET/AgNW/PDMS

yarns with an upward trend show relatively instability during multiple stretching and bending cycles. Pan et al. designed a yarn sensor with a core–sheath yarn structure, in which a braided composite yarn coated with CNTs is used as the core (BYs-CNT) and electrospun polyurethane nanofibers are used as the sheath [35]. This kind of combination of the yarn has extremely high sensing sensitivity (maximum GF up to 980) and long-term stability, but poor linearity. Additionally, the yarn preparation process is complicated and cannot be easily produced en masse. Similarly, the relative resistance change shows a downward trend after the strain exceeds 40%, due to the changes in the braid angle and contact area of braided yarns PET during the stretching process. After several stretching cycles under 30 and 50% strain, the performance is stable, but its sensitivity is very low. Zhu et al. introduced curcumin-assisted chemical deposition (ELD) to prepare a helical yarn with a metal coating, and established a model to analyze its sensing mechanism [46]. The relative resistance change of the yarn ∆ത can be expressed as a function related to the tensile strain ε, including θ(ε), g(ε) and Rୢୣ୲ୟୡ୦(ε) (θ is the winding angle, g is the average gap of the separated winding, Rୢୣ୲ୟୡ୦ is the resistance of an independent winding). As mentioned above, the yarn strain sensors based on geometric change sensing have excellent linearity, low hysteresis, high stability and a large sensing range, but their sensitivity is limited [15].

(**c**) (**d**)

**Figure 8.** (**a**) Schematic diagram of rubber thread and different core-spun yarns (**b**) Cross-sectional structure of the PCSCCY yarn [95] (**c**) SEM image of PDCY-RGO under 0% strain, 7° (**d**) SEM image of PDCY-RGO under 50% strain, with the winding angle marked as 29° [96]. **Figure 8.** (**a**) Schematic diagram of rubber thread and different core-spun yarns (**b**) Cross-sectional structure of the PCSCCY yarn [95] (**c**) SEM image of PDCY-RGO under 0% strain, 7◦ (**d**) SEM image of PDCY-RGO under 50% strain, with the winding angle marked as 29◦ [96].

#### 3.3.2. Braided Structure 3.3.3. Helical and Winding Structure

Another design is to use braided yarns to fabricate yarn-based strain sensors. Shi et al. reported a sensor (BWY-AgNWs) composed of stretchable yarns with a braided structure and silver nanowires by dip coating (Figure 9) [97]. The fiber sensor can not only detect various deformations such as stretching, torsion, and bending, but also has a high stable sensitivity (GF = 65) in a larger sensing range (strain can reach 100%). However, due to the insufficient recovery of the microstructure and the brittleness of the AgNWs film, the microcracks cannot be completely merged after release, resulting in the poor repeatability of the strain sensor during multiple cycles of stretching. Furthermore, the high hysteresis of the strain sensor makes its strain response slow, which limits its wearable application. Yang et al. proposed a PET/AgNW/PDMS yarn sensor with braid yarns as the substrate, AgNW as the active material and PDMS as the protective layer by dip coating In addition to fancy yarn, unconventional yarn sensors have been formed by twisting and winding conductive coated films, which remarkedly enhance the tensile strain range of one-dimensional sensors. Compared with the conventional planar wave structure, the coil structure has greater stretchability because the local stress is suppressed during the stretching process and the local maximum strain is reduced due to the non-planar motion of the coil [99]. Ultrahigh stretchable conductive helical yarn with CNT/PU nanocomposite fiber helical yarn was prepared by simple electrospinning, spraying and twisting processes (Figure 10a) [99]. With the help of the synergistic effect of the flexible polymer chain and the nanofiber spiral coil structure, the CNT/PU helical yarn will break the limitation of material stretchability due to its rigidity and excellent stretchability. Its recovery is within 900% strain, and the maximum of tensile elongation can reach 1700%, while its sensitivity

is very low. Xie et al. designed a SWCNT-RGO/TPU spiral layered composite yarn by spraying and winding technology (Figure 10b,c) [100]. Due to the special spiral layered structure of the composite yarn, the conductive layer is wrapped and protected by the elastic polymer layer, and there is no obvious interruption or crack on the surface of the yarn. Compared with the SWCNT-RGO/TPU thin-film sensor, the yarn sensor has a wider working strain range and has five linear regions. In the 50% tensile strain cycles, the relative resistance of the sensor continued to increase during the initial 100 cycles and then began to stabilize. tiple stretching and bending cycles. Pan et al. designed a yarn sensor with a core–sheath yarn structure, in which a braided composite yarn coated with CNTs is used as the core (BYs-CNT) and electrospun polyurethane nanofibers are used as the sheath [35]. This kind of combination of the yarn has extremely high sensing sensitivity (maximum GF up to 980) and long-term stability, but poor linearity. Additionally, the yarn preparation process is complicated and cannot be easily produced en masse. Similarly, the relative resistance change shows a downward trend after the strain exceeds 40%, due to the changes in the braid angle and contact area of braided yarns PET during the stretching process.

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[98]. The yarn sensor has high conductivity and a wide range of stretchable strain. However, the resistance change does not increase monotonously with the increase in strain, instead of a downward trend after 40% strain. In addition, the relative resistance changes in PET/AgNW/PDMS yarns with an upward trend show relatively instability during mul-

**Figure 9.** Schematic diagram of the manufacturing process of the BWY-Ag NW strain sensor [97]. **Figure 9.** Schematic diagram of the manufacturing process of the BWY-Ag NW strain sensor [97].

**Figure 10.** (**a**) Schematic diagram of the preparation of helical CNT/PU yarn [99] (**b**) Schematic diagram of the preparation of SWCNT-RGO/TPU strain sensor (**c**) SEM image of spiral layered SWCNT-RGO/TPU yarn [100]. **Figure 10.** (**a**) Schematic diagram of the preparation of helical CNT/PU yarn [99] (**b**) Schematic diagram of the preparation of SWCNT-RGO/TPU strain sensor (**c**) SEM image of spiral layered SWCNT-RGO/TPU yarn [100].

rized in Table 6. On the basis of the coating, improving the linearity and stability of the strain sensor by changing the yarn structure is an excellent method because the resistance The performance of yarn-based strain sensors with different structures are summarized in Table 6. On the basis of the coating, improving the linearity and stability of the strain

change mainly depends on the structure of the composite yarn. For example, in terms of

certain extent. Therefore, it is necessary to discuss the influence of structural changes on the sensing performance so that the yarn strain sensor has balanced performance indica-

**Range GF Repeata-**

5.11 (0– 50%); 3.41 (50–100%)

N/A

10,000 (30% and 50%)

(50%)

**bility Linearity Response** 

Linearity at 0–50% and 50– 350% strain, respectively

Good line-

**Time Ref.** 

N/A [95]

N/A <100 ms [96]

arity N/A [46]

**Strain** 

0.012 S/m 0.2–100% 3.7 (50%)

The performance of yarn-based strain sensors with different structures are summa-

**Table 6.** Characteristics of various yarn-based strain sensors.

**Conductivity** 

>300% 310 Ω/cm 350

PU Cu N/A 0.2 Ω/cm 50% N/A <sup>5000</sup>

**Breaking Stress and Strain** 

> 29.14 MPa; 676%

tors.

yarn PU/cotton CNT/PPy >7 N;

PU/PE Gr

**rials** 

**Method Structure Substrate Sensitive Mate-**

Core-spun

yarn

yarn

Dip coating and in situ polymerization

Dip coating Wrapped

ELD Wrapped

sensor by changing the yarn structure is an excellent method because the resistance change mainly depends on the structure of the composite yarn. For example, in terms of wrapped yarn-based sensors, the decrease in the contact of the spiral winding leads to an increase in resistance, but this also reduces the sensitivity and working strain range to a certain extent. Therefore, it is necessary to discuss the influence of structural changes on the sensing performance so that the yarn strain sensor has balanced performance indicators.


**Table 6.** Characteristics of various yarn-based strain sensors.

#### **4. Interconnection and Packaging**

For wearable electronic applications, strain-sensing fibers or yarns need to be interconnected with other structural circuit elements or data acquisition circuits to fully integrate electronic devices. In wearable electronic devices, it is required that the sensing element must be firmly, elastically and electrically connected to the conductive wire or the data connector, and the interconnection point can still maintain high conductivity under considerable mechanical stress. In addition, the interconnection needs to robustly transmit the signal to the transmission board or processing electronics with minimal loss. At present, the common bonding methods in interconnection are mechanical bonding, physical bonding and chemical bonding [101,102]. However, the chemical bonding is not suitable for the interconnection of heterogeneous devices. Mechanical bonding refers to the use of friction to clamp or connect electronic components to wires, which is suitable for electronic connections of various conductive textiles. For fiber or yarn strain sensors, the mechanical bonding can be thread-to-thread knotting, or embroidery [103,104], stitching [72], or interlacing. Physical bonding includes soldering [105], adhesive bonding [96] and so on. The advantages and disadvantages of different interconnection methods are summarized in Table 7. Soldering is a process that the metal is melted with the high temperature to tightly coat and wrap electronic components to form a connection. However, few common fibers and yarns with conductive materials can withstand high temperature welding, and the narrow interface between the components is too small and difficult to handle. It is a method widely used in laboratories to connect strain-sensing yarns and functional components with conductive adhesives such as conductive glue and copper tape. For example, He et al. stitched MWCNT/TPU fibers onto an elastic bandage with cotton yarns to detect the wrist bending (Figure 11a) [72]. Both ends of the fibers were connected with conductive wires using silver paste and fixed by conductive tapes and medical tapes. Cheng et al. used conductive copper tape and silver paste to interconnect the two ends of graphene-based fibers as external electrodes with copper wires (diameter: 2 µm) (Figure 11b) [96]. Although this method is simple to operate, the electrical connection quality of the conductive adhesive is affected by humidity and temperature, and the copper tape is easily oxidized and has poor mechanical fatigue resistance, which may cause safety problems. Therefore, this type of interconnection often requires further suitable packaging protection.

**Table 7.** Features of various interconnection methods.

**Figure 11.** (**a**) MWCNT/TPU fiber sensors on an elastic bandage [72]. (**b**) The use of copper tape and silver paste to form the interconnections [96]. (**c**) ΔR/R0 of the sensor with 50 wt% RGO as a function of ultrasonic time [106]. (**d**) Photograph showing a large textile tattoo of a wolf on skin [107]. (**e**,**f**) Resistance–time relationships of the GNS/Au/GNS/PU yarn strain sensor (**g**,**h**) Resistance–time relationships of the PDMS-wrapped GNS/Au/GNS/PU yarn strain sensor with an applied strain of 50% under water spray [42]. **Figure 11.** (**a**) MWCNT/TPU fiber sensors on an elastic bandage [72]. (**b**) The use of copper tape and silver paste to form the interconnections [96]. (**c**) ∆R/R<sup>0</sup> of the sensor with 50 wt% RGO as a function of ultrasonic time [106]. (**d**) Photograph showing a large textile tattoo of a wolf on skin [107]. (**e**,**f**) Resistance–time relationships of the GNS/Au/GNS/PU yarn strain sensor (**g**,**h**) Resistance–time relationships of the PDMS-wrapped GNS/Au/GNS/PU yarn strain sensor with an applied strain of 50% under water spray [42].

**Method Merits Demerits**

**5. Application**  Fiber- and yarn-based strain sensors exhibiting outstanding sensing performances have broad application prospects. In the healthcare industry, wearable strain sensors are installed or worn on different parts of a patient's body, such as hands, fingers, waist and feet, to analyze posture and gait. The traditional sensor for human motion analysis is the accelerometer, but its rigid structure is not easy to integrate into clothing, and would be uncomfortable for wearers over long periods [110]. In addition, the performance of the accelerometer is easily interfered by the environmental magnetic field and temperature. Textile sensors are more comfortable and flexible in measuring human posture and movement with low cost. In particular, fiber or yarn strain sensors can be woven into fabrics that can be worn directly on various body parts, such as knees, elbows and fingers, without any support structure or frame. By contrast, the nanofiber mats and fabric sensors are usually integrated into clothing by adhesive binding and stitching. Fiber and yarn strain sensor devices can be used for a variety of applications without platform constraints and accurately monitor strain in a single direction. However, their electrical performances are still unsatisfactory for practical applications of consumer-level sensor systems. Additionally, it is essential to develop supporting circuit and algorithm to achieve wearable applications. For instance, the problem of resistance drift with time and repeated use can be Considering the stability and reliability of electrical interconnection and the durability of the strain sensor, the strain sensor is packaged for use. If strain sensors are integrated into clothing by textile technology, insulating coatings are considered to protect the sensors. For example, Li et al. used hydrophobic PDMS to pack the yarn-based strain sensor to achieve a good waterproof performance [42]. The relative resistance change values of the sensor without the hydrophobic packing increased significantly when the sensor was sprayed with water during the tensile cycle test (Figure 11e,f). On the contrary, the relative resistance change values changed slightly before and after water (Figure 11g,h). Xu et al. reported the encapsulated TPU/SWCNT-RGO/PU core–sheath fiber [106]. The ∆R/R0 of the encapsulated composite fiber firstly increased by 10 and then remained stable, showing great washability compared with the SWCNT-RGO/PU sensor (Figure 11c). Kwon et al. used self-healing polymers (T-SHPs) as self-adhesive and durable interconnection materials to encapsulate conductive sensing fibers. This method easily achieved the patterned design (Figure 11d), but also effectively improved the conductivity of the sensing fiber over the 1000 stretch cycles [107]. Additionally, it is easy and convenient to fabricate, but not safe and reliable, only being suitable for laboratory tests. In addition, the strain sensor can be directly integrated into fabrics by the hot-melting process. The hot-melting package is made of elastic thermoplastic materials, such as TPU hot-melting adhesives. The materials

solved in algorithms with periodic calibration. The performance of different strain sensors used to monitor human movement and human–computer interaction is compared in Ta-

ble 8.

are heated to the melting temperature and cooled after molding. For instance, Bahadir et al. reported a waterproof textile transmission line with GoreTex® waterproof welding tape by hot air sealing [108]. From the perspective of structural mechanics, electronic packaging can be seen as a composite structure made of different materials (substrate-conductive coatingencapsulation layer), and the physical parameters between the layers will affect the average strain transfer rate and sensing performance. In addition, when the device is subjected to thermo-mechanical loads, the interface between these materials is the most prone to failure. This is due to the inherent stress concentration generated by the interface bonds between different materials and the free surface of the two materials. Under repeated external mechanical action, cracks are not limited to the interface, but also propagate and expand parallelly to the interface [109]. Therefore, the system integration of interconnected wires and strain sensors under high-level strain loads is still a huge challenge. Poor interfaces will not only cause serious errors, but also lead to low reliability of the entire sensor system. The mechanical and sensing properties of conductive yarns before and after encapsulation will change to a certain degree. However, there is currently a lack of comprehensive research on the effect of packaging process on the sensing performance of stretchable conductive fibers or yarns.

#### **5. Application**

Fiber- and yarn-based strain sensors exhibiting outstanding sensing performances have broad application prospects. In the healthcare industry, wearable strain sensors are installed or worn on different parts of a patient's body, such as hands, fingers, waist and feet, to analyze posture and gait. The traditional sensor for human motion analysis is the accelerometer, but its rigid structure is not easy to integrate into clothing, and would be uncomfortable for wearers over long periods [110]. In addition, the performance of the accelerometer is easily interfered by the environmental magnetic field and temperature. Textile sensors are more comfortable and flexible in measuring human posture and movement with low cost. In particular, fiber or yarn strain sensors can be woven into fabrics that can be worn directly on various body parts, such as knees, elbows and fingers, without any support structure or frame. By contrast, the nanofiber mats and fabric sensors are usually integrated into clothing by adhesive binding and stitching. Fiber and yarn strain sensor devices can be used for a variety of applications without platform constraints and accurately monitor strain in a single direction. However, their electrical performances are still unsatisfactory for practical applications of consumer-level sensor systems. Additionally, it is essential to develop supporting circuit and algorithm to achieve wearable applications. For instance, the problem of resistance drift with time and repeated use can be solved in algorithms with periodic calibration. The performance of different strain sensors used to monitor human movement and human–computer interaction is compared in Table 8.



#### *5.1. Human Motion Monitoring* the throat muscles. When people swallow something or say different words, different sig-

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Generally, human motion detection can be classified into exercises with large strain (for example, limb bending or stretching) [118,119] and subtle movements with small strain (such as swallowing or emotional expression) [120]. According to clinical data, the flexion ranges of fingers or wrists, elbows and knees of people with every age group are different, ranging from 0 to 90◦ , 0 to 160◦ , and 0 to 130◦ , respectively [121,122]. Therefore, the large deformation experienced by the human skin ranges from 0 to 100% strain, and thus the corresponding flexible strain sensors require a wider workable strain range. For example, Li et al. used epoxy adhesive to connect two coaxial fibers to the wristband in a perpendicular manner [38]. The sensor monitors the bending and relaxation of the wrist to show a repeatable switching signal (Figure 12a,b). By stitching fibers into the sleeves of the jacket, the stretching, pressing, folding and twisting motions of the sleeves create different signals. Liu et al. reported an elastic garment with a stretchable fiber-based strain sensor can sensitively detect the bending motion of the knee (Figure 12c,d) [88]. Fiber sensors can be snugly integrated into textiles, so the wearer can move comfortably and freely with accurate sensor monitoring. Jiang et al. used two thread-based sensors to monitor the head motion, and characterized the electrical signals by using a machine learning algorithm to realize head motion classification [115]. The accuracy of a set of nine head directions is about 92%. nals are recorded [95,106,123]. Strain sensors can detect complex epidermal/muscle movements by recording relative resistance changes, which have broad prospects in correcting standard pronunciation and expressing sounds of damaged vocal cords [124]. It is also possible to monitor facial expressions, such as crying, laughing, blinking and cheek bulging by installing flexible strain sensors on the cheeks, forehead or corners of the eyes (Figure 12e,f) [74]. Additionally, a high-performance strain sensor worn on the chest was used to track the breathing rate [96]. Flexible strain sensors were also implanted in the human bladder to monitor the size of the bladder to determine excretion [45,125]. In short, flexible fiber- and yarn-based strain sensors with excellent sensitivity have made significant progress in detecting human movement and activity information. They can be directly woven into clothes based on advanced textile machinery, which will facilitate low-cost and large-scale production. In addition, they can also be integrated with other one-dimensional flexible electronic devices, such as fiber-based batteries/supercapacitors, so as to realize miniaturized, portable wearable electronic products in the near future for potential medical care, rehabilitation and sports monitoring, etc.

For small motion detection, the strain sensors necessarily have extremely high sensitivity. Otherwise, the electrical signals are not easily characterized to distinguish between the strains. For instance, a strain sensor is attached to the neck to detect the movement of

**Figure 12.** *Cont*.

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**Figure 12.** (**a**) The movement of bending and relaxing the wrist (**b**) The relative resistance change when the wrist is bending and relaxing [38]. (**c**) The sensor was stuck on the joints of the lower limbs with tape to monitor the squatting posture (**d**) The typical raw data obtained by the fiber-based sensor when detecting the squat and the noise is caused by the natural vibration of the limbs [88]. (**e**) Optical images of open eyes (bottom) and closed eyes (top). (**f**) The relative resistance change of the sensor showing the movement of small muscles caused by blinking [74]. **Figure 12.** (**a**) The movement of bending and relaxing the wrist (**b**) The relative resistance change when the wrist is bending and relaxing [38]. (**c**) The sensor was stuck on the joints of the lower limbs with tape to monitor the squatting posture (**d**) The typical raw data obtained by the fiber-based sensor when detecting the squat and the noise is caused by the natural vibration of the limbs [88]. (**e**) Optical images of open eyes (bottom) and closed eyes (top). (**f**) The relative resistance change of the sensor showing the movement of small muscles caused by blinking [74].

*5.2. Human–Computer Interaction*  A data glove is a multimode virtual reality hardware that perform actions such as grabbing, moving and rotating objects in a virtual scene through software programming [125]. The emergence of the data glove provides a new interactive means for virtual reality systems. The product has been able to detect the bending of the finger and use the strain sensor to accurately locate the movement state of the hand. This kind of data glove combined with finger curvature test is called "real glove", which can provide users with a very real and natural three-dimensional interactive means. In addition, the data glove can also be used as an auxiliary device for human or robot movement recognition and deaf– mute people. Fiber- or yarn-based strain sensors can not only detect various finger move-For small motion detection, the strain sensors necessarily have extremely high sensitivity. Otherwise, the electrical signals are not easily characterized to distinguish between the strains. For instance, a strain sensor is attached to the neck to detect the movement of the throat muscles. When people swallow something or say different words, different signals are recorded [95,106,123]. Strain sensors can detect complex epidermal/muscle movements by recording relative resistance changes, which have broad prospects in correcting standard pronunciation and expressing sounds of damaged vocal cords [124]. It is also possible to monitor facial expressions, such as crying, laughing, blinking and cheek bulging by installing flexible strain sensors on the cheeks, forehead or corners of the eyes (Figure 12e,f) [74]. Additionally, a high-performance strain sensor worn on the chest was used to track the breathing rate [96]. Flexible strain sensors were also implanted in the human bladder to monitor the size of the bladder to determine excretion [45,125].

ments, but are also softs, light and knittable, and can be concealed in the glove without affecting its appearance. Choi et al. designed a conductive fiber sensor with a layered microsized hair-like structure, which exhibits excellent ductility (<200%) and sensitivity to various stimuli (pressure, stretching, and bending) [116]. They knit this kind of conductive fiber sensor into the glove and made a smart glove to detect the movement of the finger joints, so that the virtual interface was controlled by detecting the movement of the hand (Figure 13a). Lee et al. implanted AgNP-loaded spandex multifilament as a strain sensor In short, flexible fiber- and yarn-based strain sensors with excellent sensitivity have made significant progress in detecting human movement and activity information. They can be directly woven into clothes based on advanced textile machinery, which will facilitate low-cost and large-scale production. In addition, they can also be integrated with other one-dimensional flexible electronic devices, such as fiber-based batteries/supercapacitors, so as to realize miniaturized, portable wearable electronic products in the near future for potential medical care, rehabilitation and sports monitoring, etc.

#### on the nodes of the five fingers of the glove, which was used as a true wearable sensor *5.2. Human–Computer Interaction*

platform in the human–machine interface (Figure 13b,c) [45]. Due to the high sensitivity of the fiber strain sensor, smart gloves easily monitor the real-time movement of each finger. Through the signal processing of the drive circuit and the microcontroller, the response of the strain sensor integrated into the finger of the smart glove is used to control the bending motion of the corresponding finger of the hand-shaped robot. Chen et al. prepared a high-stretch conductive yarn composed of Poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) polymer nanofibers mat and AgNW coated on the surface of elastic woven yarn, and then integrated ten conductive yarns into a wearable data glove [117]. Human gestures were recognized by detecting the movement of human fingers (Figure 14). A data glove is a multimode virtual reality hardware that perform actions such as grabbing, moving and rotating objects in a virtual scene through software programming [125]. The emergence of the data glove provides a new interactive means for virtual reality systems. The product has been able to detect the bending of the finger and use the strain sensor to accurately locate the movement state of the hand. This kind of data glove combined with finger curvature test is called "real glove", which can provide users with a very real and natural three-dimensional interactive means. In addition, the data glove can also be used as an auxiliary device for human or robot movement recognition and deaf–mute people. Fiber- or yarn-based strain sensors can not only detect various finger movements, but are also softs, light and knittable, and can be concealed in the glove without affecting

its appearance. Choi et al. designed a conductive fiber sensor with a layered microsized hair-like structure, which exhibits excellent ductility (<200%) and sensitivity to various stimuli (pressure, stretching, and bending) [116]. They knit this kind of conductive fiber sensor into the glove and made a smart glove to detect the movement of the finger joints, so that the virtual interface was controlled by detecting the movement of the hand (Figure 13a). Lee et al. implanted AgNP-loaded spandex multifilament as a strain sensor on the nodes of the five fingers of the glove, which was used as a true wearable sensor platform in the human–machine interface (Figure 13b,c) [45]. Due to the high sensitivity of the fiber strain sensor, smart gloves easily monitor the real-time movement of each finger. Through the signal processing of the drive circuit and the microcontroller, the response of the strain sensor integrated into the finger of the smart glove is used to control the bending motion of the corresponding finger of the hand-shaped robot. Chen et al. prepared a high-stretch conductive yarn composed of Poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) polymer nanofibers mat and AgNW coated on the surface of elastic woven yarn, and then integrated ten conductive yarns into a wearable data glove [117]. Human gestures were recognized by detecting the movement of human fingers (Figure 14). *Textiles* **2022**, *2*, FOR PEER REVIEW 24

**Figure 13.** (**a**) Photos and virtual images of smart wearable gloves used for external stimulus control actions in the game interface [116]. (**b**) The resistance response of fiber strain sensor in the smart glove(**c**) Photograph of a remote hand robot controlled by the smart glove [45]. **Figure 13.** (**a**) Photos and virtual images of smart wearable gloves used for external stimulus control actions in the game interface [116]. (**b**) The resistance response of fiber strain sensor in the smart glove (**c**) Photograph of a remote hand robot controlled by the smart glove [45].

In summary, this review summarized the recent developments in fiber- and yarnbased strain sensors, from commonly used conductive materials to common preparation methods (spinning and coating). The structural designs of strain sensors are introduced in detail, including internal structures (uniform, coaxial, porous, and hollow structures), surface microstructures (microcrack and wrinkled structures) and macrostructures (wrapped, braided, and winding structures). The internal structure design lowers the percolation threshold of materials, and the surface microstructure design improves the performance of the sensor. Each macrostructure has its own characteristics. In addition, the

**Figure 14.** A data glove with ten fiber strain sensors fixed [117].

**6. Conclusions and Outlook** 

**Figure 14.** A data glove with ten fiber strain sensors fixed [117].

#### **6. Conclusions and Outlook**

In summary, this review summarized the recent developments in fiber- and yarn-based strain sensors, from commonly used conductive materials to common preparation methods (spinning and coating). The structural designs of strain sensors are introduced in detail, including internal structures (uniform, coaxial, porous, and hollow structures), surface microstructures (microcrack and wrinkled structures) and macrostructures (wrapped, braided, and winding structures). The internal structure design lowers the percolation threshold of materials, and the surface microstructure design improves the performance of the sensor. Each macrostructure has its own characteristics. In addition, the packaging and interconnection of strain sensors with other components are discussed. Finally, various potential practical applications of fiber- and yarn-based strain sensors are listed, such as health detection, biomedicine, data gloves, etc.

Although great progress has been made in the fabrication of strain sensors based on one-dimensional textile materials in recent years, there are still some problems that hinder their practical application. For example, strain sensors cannot have a high sensitivity, high stretchability, and high linearity at the same time. The crack mechanism or method of controlling conductive fillers near the percolation threshold can markedly improve the sensitivity of the materials, while they limit the working strain range of the sensor. The working strain range is not only related to the breaking strain of the elastic substrate, but also to the conductivity of the composite. The addition of conductive active materials by spinning or coating gives the textiles sufficient conductivity, but these treatments often reduce the breaking strain and elastic recovery rate of the composite. Furthermore, the hysteresis, repeatability, stability and durability of the sensor should be considered. At present, most of the current flexible strain sensors tend to use elastic polymers as the supporting substrate. However, the sensors inevitably present hysteresis, stress relaxation and creep phenomena due to the viscoelasticity of substrates. The interface between the conductive material and the supporting substrate will also affect the hysteresis and cycle stability of sensors. From a practical point of view, it is vital to study the interface between conductive materials and fiber ensembles.

The conductive sensing mechanisms of flexible fiber or yarn strain sensors are quite different from traditional semiconductor and metal sensors. For conductive composite fibers, the sensing mechanisms are mainly based on percolation theory [80,126] and tunnel theory [126,127]. Crack propagation is the main reason for the resistance variation of coating fiber sensors [118,128,129]. Geometric effects caused by changes in the structure or size of fibers or yarns will also affect the working effect of the sensor. The sensing mechanism is based on the contact resistances on different scales such as fibers and yarns [130]. These mechanisms allow us to understand the working mechanism of some flexible tensile strain sensors. However, for the "shoulder phenomenon" of existing strain sensors [64,81,131–133], there is still a lack of specific theoretical analyses to find the improvement methods for large hysteresis and unstable sensitivity. Therefore, it is meaningful to perfect the research on the controlling factors of the sensing performance of the fiber or yarn strain sensors. To fabricate the suitable working strain range and gauge factor of sensors, it is crucial to establish the relationship between yarn structure parameters and sensing performance.

At present, there are few reports of large-scale applications of flexible strain in the market, and the majority of reported fiber and yarn strain sensors are still in the laboratory study and development stage. It is also necessary to consider whether the sensor's performance and life will be interfered with by the external environment. For example, the washability of the wearable electronic textiles needs to be considered because they may be dirty during use. However, due to the lack of an insulating layer or protective layer, most current fiber or yarn strain sensors are not washable. The conductive coating on the yarn may crack or peel off during washing [134,135]. Moreover, there are few studies on the washability and instability mechanism of strain sensors at present. Another unsolved problem is the ability to reliably integrate these sensors with different components. The connection of strain sensors to other devices through soldering, mechanical clamping, or functional adhesives may cause safety issues. Therefore, it is worth studying the effect of packaging technology on the performance while meeting the security and stability requirements of the interconnection.

Finally, to achieve truly comfortable portable wearable applications, comprehensive advances in electronics, software, and textile manufacturing are required. For instance, these wearable power supplies and circuits should ideally be flexible and stretchable so as to withstand the large strains applied to the fabrics during their normal use. It is worth considering a method to highly integrate electronics with clothing comfortably and aesthetically. Artificial intelligence is a key step in realizing sensor applications. As well as applications in human movement monitoring and human–machine interactions, other applications are yet to be developed. In summary, although great progress has been made in fiber- and yarn-based strain sensors have achieved in terms of materials, preparation methods, and structural design, there are still many problems and challenges to be solved before their commercial use.

**Author Contributions:** The authors contributed to this paper as follows: material review, writing of the paper, methodology, draft preparation, revisions and final manuscript preparation, F.H.; supervisory, draft review and editing, J.H. and X.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Shanghai Natural Science Foundation (20ZR1400500) and the Fundamental Research Funds for the Central Universities (2232021G-01).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** Thank you to the supervisory team.

**Conflicts of Interest:** The authors declare no conflict of interest.
