Smartphone-based integrated voltammetry system for simultaneous detection of ascorbic acid, dopamine, and uric acid
Daizong Ji1, Zixiang Liu2, Lei Liu1
1Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, PR China; Collaborative Innovation Center of TCM Health Management, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, PR China.
Abstract:
Ascorbic acid, dopamine, and uric acid are important electroactive biomolecules for health monitoring and they coexist in serum or urine. Their quantitative determination by electrochemistry could provide the accurate reference for diseases diagnosis and treatment. However, the traditional electrochemical workstations are too large for on-field inspection. Hence, the design of handheld electrochemical system for the detection of biomolecules is significant for point-of-care testing (POCT). In this paper, a smartphone-based integrated voltammetry system using modified electrode was developed for simultaneous detection of biomolecules. The system contained a disposable sensor, a coin-size detector, and a smartphone equipped with application program. Screen-printed electrodes were used as sensors for the detection, on which reduced graphene oxide and gold nanoparticles were electrochemically deposited by the system. The detector was used with voltammetric methods, in which excitation voltage was applied on the sensors and subsequent current responses were detected. The smartphone is the core component to communicate with the detector, calculate data, and plot voltammograms in real-time. Then, the system was applied to detect standard solutions of the biomolecules and their mixtures as examples. The results showed that the peak currents of each substance increased with higher concentration and the method allowed the discrimination of the different potentials of the studied species. Finally, the practical applications of the system were tested through detections of the biomolecules in artificial urine. The results exhibited that the system could be used to detect electrochemical activity of biomolecules with linear, high sensitivity, and specific responses in point-of-care testing.
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