Recent Advances in Electrochemical Biosensors: Applications, Challenges, and Future Scope

被引:343
作者
Singh, Anoop [1 ]
Sharma, Asha [1 ]
Ahmed, Aamir [1 ]
Sundramoorthy, Ashok K. [2 ]
Furukawa, Hidemitsu [3 ]
Arya, Sandeep [1 ]
Khosla, Ajit [3 ]
机构
[1] Univ Jammu, Dept Phys, Jammu 180006, India
[2] SRM Inst Sci & Technol, Dept Chem, Kattankulathur 603203, India
[3] Yamagata Univ, Grad Sch Sci & Engn, Dept Mech Syst Engn, Yamagata 9928510, Japan
来源
BIOSENSORS-BASEL | 2021年 / 11卷 / 09期
关键词
biosensor; electrochemical; sensitivity; amperometric; voltammetric; food quality monitoring; machine learning; PRINTED CARBON ELECTRODE; SUPPORT VECTOR MACHINES; LABEL-FREE; IMPEDIMETRIC BIOSENSOR; AMPEROMETRIC BIOSENSOR; GOLD NANOPARTICLES; OPTICAL BIOSENSOR; CELIAC-DISEASE; SENSOR; IMMUNOSENSOR;
D O I
10.3390/bios11090336
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The electrochemical biosensors are a class of biosensors which convert biological information such as analyte concentration that is a biological recognition element (biochemical receptor) into current or voltage. Electrochemical biosensors depict propitious diagnostic technology which can detect biomarkers in body fluids such as sweat, blood, feces, or urine. Combinations of suitable immobilization techniques with effective transducers give rise to an efficient biosensor. They have been employed in the food industry, medical sciences, defense, studying plant biology, etc. While sensing complex structures and entities, a large data is obtained, and it becomes difficult to manually interpret all the data. Machine learning helps in interpreting large sensing data. In the case of biosensors, the presence of impurity affects the performance of the sensor and machine learning helps in removing signals obtained from the contaminants to obtain a high sensitivity. In this review, we discuss different types of biosensors along with their applications and the benefits of machine learning. This is followed by a discussion on the challenges, missing gaps in the knowledge, and solutions in the field of electrochemical biosensors. This review aims to serve as a valuable resource for scientists and engineers entering the interdisciplinary field of electrochemical biosensors. Furthermore, this review provides insight into the type of electrochemical biosensors, their applications, the importance of machine learning (ML) in biosensing, and challenges and future outlook.
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页数:31
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