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Kim et al. Soft Sci 2024;4:24 https://dx.doi.org/10.20517/ss.2024.09 Page 7 of 27

sensor was stably integrated with clothing such as gloves and stockings, detecting various human motions
[Figure 3E]. The CSF-based device monitored and specified knee joint motions such as extending/flexing,
marching, jogging, jumping, and combinations of squatting/jumping [Figure 3F]. The results from the
carbonated silk-based strain sensors suggest that textile devices can be easily and simply produced using
other fabrics including wool, cotton, and other artificial fiber fabrics.

With the increased demand for mass production of strain sensors, several research teams have explored
cost-effective and scalable production methods using the fluidic properties of organic materials, such as
[38]
spraying, ink-jet printing, and 3D printing techniques . Among these methods, printing-on-substrate
techniques, including 3D printing and ink-jet printing, promise advances in high resolution, sophisticated
structure manufacturing, and mass production. Figure 3G displays a schematic illustration of a flexible
strain gauge utilizing a 2D material-percolated thin film, realized by spraying a graphene flake-distributed
1-methylpyrrolidone (NMP) solution and instantly annealing it . The applied strain degree was evaluated
[39]
by measuring the resistance change caused by the conduction pathway breakdown of graphene flakes in the
thin film. The sensitivity of the graphene flake network-based device was reliable under various strain values
and easily modulated by tuning the 2D material ratio in the sprayed solution. The solution spraying-on-
substrate method has the potential for commercializing wearable strain sensors using other 2D materials
with low-cost production and easy scalability.

Figure 3H is a process image of an embedded 3D printing (e-3DP) method on elastomeric matrices using
ink-form sensing materials, enhancing the stretchability and tunability of the active material by controlling
the printing path. Muth et al. printed carbon conductive ink at the interface between Ecoflex and silicone
thinner to demonstrate highly conformal and extensible elastomeric electronics . The printing parameters,
[40]
including nozzle size, pressure, and printing speed, were sophisticatedly optimized to realize the specific
shape “hairpin”. The resistance of the printed ink increased from 11 to 60 kΩ by decreasing the cross-
2
sectional areas of the features (0.71 to 0.066 mm ) with the printing speed increase. Furthermore, the
structure and electrical properties of the conductive ink were stably maintained on the cured elastomer
under stretching/bending conditions.

Wang et al. reported an ultrathin, mechanically stable, and durable nanomesh-based strain gauge enabled
[41]
by an electrospinning and dipping process of polyurethane (PU) nanomesh conductors . Figure 3I
indicates the fabricated nanomesh structures with different polydimethylsiloxane (PDMS)/hexane weight
ratios (1/40 and 1/80) to verify the optimized condition for the nanomesh-based strain sensor. The 1/40
ratio strain sensor had the highest GF of 46.3, enabling it to map facial movements during speech onto the
cheek skin surface [Figure 3J]. Figure 3K presents strain distribution mapping images of the nanomesh
devices compared to a PDMS thin-film device during the speech of “a”. The nanomesh-based strain sensor
in this work exhibited advantages of being lightweight, having a large detectable strain range, and being gas-
permeable.

Transistor-based mechanical sensors
Organic material-based wearable mechanical sensors, despite their advantages of being ultrathin,
lightweight, and having a simple fabrication process, still suffer from low electronic mobility, heat/humidity
stability, and robustness in the air . To address these challenges, a promising approach involves applying
[42]
inorganic material to transistor-based sensors through microfabrication processes. In particular, inorganic
thin-film transistors (TFTs) have received much attention due to their cost-effectiveness, simplicity, and
[43]
rapid response times .