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Page 34 of 44 Jung et al. Soft Sci 2024;4:15 https://dx.doi.org/10.20517/ss.2024.02

brought on by different physiological parameters, remain as challenges to be resolved. Beyond single
biomarker analysis, multiplexed analysis for diabetes-related biomarkers can offer a more thorough
evaluation of patient health. However, a number of noteworthy obstacles are associated with deploying the
multi-analyte sensing platform, including optimizing sensitivity for analytes in biofluids due to their lower
concentration than blood, mitigating analytical interference or cross-talk among different analytes,
integrating various surface modifications and sensing modalities into a single wearable platform, and
requiring receptor regeneration in bioaffinity-based assay methods. AI can also be an effective solution for
enhancing the DM monitoring performance. In order to play a better role beyond the existing performance
such as forecasting glycemia, hypoglycemia, predictive monitoring for glucose levels, and insulin
recommendation, new AI models should be able to compare quantitatively the concentration differences
between individuals without diabetes and those with the disease, analyze correlations between multiple
biomarkers, and look at trends in concentrations based on dietary and lifestyle choices using multi-analytes
inputs. For clinical use of wearable electrochemical sensors, further efforts will be needed to address
challenges such as concentration accuracy and response time delay that may occur in sweat or tears
measurements, which include exploring clinical relevance compared to blood tests, multiplexed analysis,
and advanced AI models capable of matching non-invasive data with gold-standard levels.

In conclusion, the remarkable progression of wearable electrochemical biosensor technology underscores its
ability to furnish real-time quantitative and innovative information, particularly in the non-/minimally
invasive management of DM. Notably, advancements in nanotechnology, precise data acquisition facilitated
by nanotechnology, extensive data analysis through AI technology, and the incorporation of wireless
technologies for point-of-care applications have the potential to revolutionize the healthcare management
and diabetes prevention. In the realm of electrochemical sensors, developing wearable platforms has
garnered considerable attention for their distinctive features. This is attributed to their capability to produce
fully integrated devices in a compact, flexible, and robust manner, facilitating direct analysis of the human
body and seamless wireless data transmission to a portable device. Continued research efforts will extend
the range of sensing modalities, improving the accuracy and robustness of these systems for effective
management and prevention of DM and its complications.

DECLARATIONS
Authors’ contributions
Outlined the manuscript structure: Jung HH, Lee H, Yea J
Conducted the literature review and wrote the manuscript: Jung HH, Lee H, Yea J
Reviewed and revised the manuscript: Jang KI, Jung HH

Availability of data and materials
Not applicable.

Financial support and sponsorship
This work was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of
Science and ICT (2020R1C1C1013030, 00234581) and Ministry of Trade, Industry and Energy (20010667).
Further support was provided by the DGIST R&D Program of the Ministry of the Ministry of Science and
ICT (24-SENS-01).

Conflict of interest
All authors declared that there are no conflicts of interest.