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Nam et al. Soft Sci 2023;3:28 https://dx.doi.org/10.20517/ss.2023.19 Page 3 of 35

Figure 1. Schematics depicting various biosignals recorded by wearable devices and commonly used nanofillers for soft conductive
nanocomposites. ECG: Electrocardiogram; EEG: electroencephalogram; EGaIn: eutectic gallium-indium; EMG: electromyogram;
MWCNT: multi-walled carbon nanotube; PEDOT:PSS: poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate); SWCNT: single-
walled carbon nanotube.

NANOSCALE FILLERS FOR SOFT CONDUCTIVE NANOCOMPOSITES
As the way nanofillers assemble and form a percolated network inside elastic matrices decides the electrical
properties of nanocomposites, it is important to determine the effect of their distribution and geometry on
the performance of the nanocomposites, especially for high-quality biological signal sensing [16,33] . The
percolation threshold, which is defined as the minimum volume fraction of nanoscale fillers required to
form a long-range connectivity inside the nanocomposites, serves as a reference point for the
nanocomposites to exhibit electrical conductivity. A small volume change of the filler near the percolation
threshold can lead to a sudden transition of the electrical property between an insulator and a conductor ,
[40]
and a rapid enhancement of the conductivity can be achieved by embedding more conductive fillers beyond
the percolation threshold.

However, excessive filler amounts lead to their aggregation, increase mechanical stiffness, and result in high
costs. Therefore, modifying the characteristics and maximizing the performance of the nanocomposites by
changing the volume fraction of the filler alone has limitations. Instead, controlling the types of filler
materials and their morphologies can be a more effective way to tune the electrical properties of the
nanocomposites. For instance, metal-based nanomaterials have higher intrinsic electrical conductivities
compared to other types of nanomaterials [41,42] . Additionally, the morphologies, including sizes, aspect ratios,