Abstract
The field of in-vivo electrochemical sensors is envisioned to greatly transform point-of-care diagnostic devices and bio-chip sensing technology. However, these sensors' sensitivity and selectivity suffer from fundamental challenges that deteriorate the output electrochemical signal and the underlying diagnostic information. In analytical chemistry, the term ‘chemometrics’ involves utilizing advanced multivariate models to transform the output analytical signals; this shifts the complexity of the analysis from the physical domain to the digital processing domain. These digital processing methods can help to alleviate matrix and interference effects and help to address problems of drift or nonlinearity; therefore, it can potentially provide reliable in-vivo analysis. In this review, we will discuss the main challenges that implantable electrochemical sensors encounter, the currently utilized chemometric approaches for in-vivo electrochemical analysis, as well as opportunities and pitfalls for integrating chemometrics with implantable electrochemical sensors.
Original language | English |
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Article number | 117089 |
Journal | TrAC - Trends in Analytical Chemistry |
Volume | 164 |
DOIs | |
State | Published - 1 Jul 2023 |
Keywords
- Artificial intelligence models
- Chemometrics
- Electroanalysis
- Electroanalytical chemistry
- Electrochemical sensors
- Implantable sensors
- In-vivo bioanalysis
- Machine learning models
- Multivariate analysis
- Pattern recognition models
All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Spectroscopy