Page 178 - Read Online
P. 178
Page 2 of 35 Nam et al. Soft Sci 2023;3:28 https://dx.doi.org/10.20517/ss.2023.19
INTRODUCTION
Recording biosignals and analyzing the recorded data are prevalent not only by medical experts in clinics [1-3]
[4-6]
but also by home users in their daily lives . Accordingly, wearable electronic devices that record various
physiological and electrophysiological signals, such as blood pressure (BP) , respiration rate ,
[7]
[8]
electrocardiogram (ECG) [9-11] , electromyogram (EMG) , and electroencephalogram (EEG) [13,14] , have been
[12]
widely used for personalized health monitoring and disease diagnosis and treatment [11,15] . Providing precise
and comprehensive information about the health condition of users is a key requirement for such devices.
However, conventional rigid devices have difficulties interfacing with soft skin, which leads to a low signal-
to-noise ratio (SNR) in biosensing and causes various side effects, including skin irritations , inflammatory
[16]
responses [17,18] , and user discomfort [19,20] . Additionally, accumulated mechanical stress can also degrade the
materials of the devices, particularly those on the device surface, which may release harmful chemicals and
trigger skin problems [21,22] . Therefore, breakthroughs in material and device design are necessary to enable
long-term and high-quality biosignal recordings.
To achieve performance improvements in wearable biosignal recording devices, a completely new approach
is necessary, such as adopting intrinsically soft materials instead of conventional rigid electronic materials.
Rigid materials, such as metals and silicon, have high Young’s moduli in the range of ~100 GPa , which are
[23]
significantly higher than that of human skin (~1 MPa) [24,25] by orders of magnitude. On the other hand, soft
materials, such as hydrogels (modulus range: 0.01 kPa-5 MPa) [26-30] and elastic polymers (modulus range:
50 kPa-50 MPa) [9,31,32] , can achieve low Young’s moduli for the fabricated devices, making their mechanical
properties analogous to the soft, dynamic, and curvilinear human body. This would result in highly effective
biosignal recordings with conformal integration with the skin and reduction of the aforementioned side
effects.
To fabricate soft conductive materials and their devices, conductive materials should be incorporated as
functional fillers into the soft elastomeric matrix. In particular, nanoscale conductive fillers are preferred, as
they can impart electrical conductivity to their nanocomposites without compromising their softness .
[33]
These nanofillers can be homogeneously dispersed in the soft media to form a highly percolated network
that maintains a seamless connection even when they are stretched. This property endows the
nanocomposites with electrical conductivity under mechanical deformations, allowing for the efficient
capture and noise-free transportation of biosignals [34-36] . By selecting appropriate nanofillers, the
[39]
nanocomposites can further achieve a low contact impedance [37,38] and high chemical stability . Therefore,
it is worth considering nanofillers of different dimensions (e.g., 0D, 1D, and 2D) and various material types
(e.g., carbon, polymer, and metal) to optimize the mechanical and electrical properties of the
nanocomposites, aiming for high-performance wearable electronic devices.
In this article, we explore the latest developments in soft conductive nanocomposites and their applications
in on-skin biosignal recording devices [Figure 1]. Firstly, we begin by categorizing the nanocomposites into
four groups depending on the material types of nanofillers employed: carbon-based nanomaterials,
conducting polymers (CPs), metal-based nanomaterials, and liquid metals (LMs). We then present detailed
strategies for maximizing the performance of each nanofiller and its corresponding nanocomposite.
Secondly, we categorize wearable biosignal recording devices into electrophysiological sensors, strain
sensors, pressure sensors, and biochemical sensors, depending on the target biosignals. We analyze how
each device category utilizes different types of nanocomposites to meet specific signal sensing requirements.
Finally, we describe the remaining challenges that need to be addressed to further develop nanocomposites
for practical applications in biosignal recording devices.

