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Page 26 of 35 Nam et al. Soft Sci 2023;3:28 https://dx.doi.org/10.20517/ss.2023.19

applied by an H-shaped object in real time [Figure 8F, right].

Biochemical sensors
Point-of-care biochemical detection is vital for a complete assessment of the health status of an individual.
The ability to monitor metabolites and electrolytes in sweat, tears, and saliva provides valuable information
for diagnosing and monitoring various diseases. For instance, glucose monitoring is essential for diabetic
[191]
[190]
patients , while lactate monitoring is vital for athletes and critically ill patients . Electrolyte monitoring,
such as sodium and potassium, is also essential for patients with kidney and cardiovascular diseases . To
[192]
detect these biomarkers, antigen-antibody or enzymatic reactions are commonly used , which induce
[193]
electrical signal changes. Skin-interfaced biochemical sensors that use nanocomposites have been developed
to improve the selectivity and sensitivity of these sensors [194,195] . These sensors have a high potential for
clinical applications due to their non-invasive and convenient nature.

Garg et al. successfully detected the glucose concentration in sweat using a PANI-based double polymer
[196]
network nanocomposite . The nanocomposite comprised PVA as the primary matrix, conductive PANI,
and thermally-exfoliated GO (TEGO) as a conductive reinforcement. PANI not only served as a conductive
material but also enhanced thermal and electrochemical stabilities. The nanocomposite had a hierarchical
design where the nano-metric scale structure contributed to electrical conductance while the microscopic
level contributed considerably to the mechanical and electrochemical properties [Figure 9A, left]. The
nanocomposite exhibited superior mechanical strength of up to 7.7 MPa and toughness of 7.48 MJ·m but
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had a rather low electrical conductivity of 0.14 S·m . Glucose oxidase was stably immobilized on the
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nanocomposite due to its high porosity and large surface area, making it a prototype for a non-invasive
glucose sensor. Cyclic voltammetry revealed its pseudo-capacitive behavior with a redox peak potential
between -0.4 and -0.6 V. In a test with a glucose concentration ranging from 0.2 μM to 10 mM, the sensor
could detect glucose concentrations as low as 0.2 μM with a wide current gap of 2.1 μA [Figure 9A, right].

In another example, Shu et al. developed a glucose sensor using Ni-Co metal-organic framework (Ni-Co
MOF) nanosheets . The researchers coated the Ni-Co MOF nanosheets on a highly stretchable rGO/PU
[197]
fiber using Ag conductive glue [Figure 9B, left]. The fiber had a diameter of approximately 1 mm, and the
length of Ni-Co MOF nanosheets was hundreds of nanometers. This fiber electrode exhibited stable
electrochemical properties, with its oxidation peak reducing by only 19.9% under 100% strain and the redox
peak current remaining consistent even after 10,000 cycles of 20% strain. Specifically, this sensor could
detect glucose concentrations ranging from 10 μM to 0.66 mM with a high sensitivity of 425.9 μA·mM ·cm .
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By creating a three-electrode system with this fiber and absorbent fabric, it could function as a real-time
glucose monitor attached to human skin [Figure 9B, middle]. The sensor detected changes in glucose levels
in sweat throughout the day, which closely matched the data obtained from a commercial glucose meter
[Figure 9B, right].

In another example, the concentrations of various metabolites in sweat could be quantified using LM
particles coated with PSS and Pt-decorated CNTs (CMPs). Lee et al. developed CMP-based electrodes that
not only enhanced mechanical stability, conductivity, and processability over bare LM particle-based
[154]
electrodes but also enabled enzyme immobilization by the carboxyl group of CNTs . Biochemical sensors
were prepared by immobilizing the relevant redox enzyme (e.g., glucose oxidase, alcohol oxidase, and
lactate oxidase) on stencil-printed CMP-based electrodes [Figure 9C, left]. The sensors measured current
changes induced by enzymatic reactions and showed a linear response to the amount of change of target
metabolites with a high linearity of R > 0.98 [Figure 9C, right]. The chemical stability and selectivity of the
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sensors were examined, supporting the reliability of wearable biochemical sensors.