The Voltammetry-Based Sensing (VBS) methods are extremely interesting due to high specificity in several biochemical applications. Several considerations can be applied to use this method to measure different analytes, and implement efficient and optimized electronic measurement platform for point-of-care diagnostic, in wearable, portable, or IoT systems. The dataset contains the data presented in [1], which proves on real experimental data a method to define the optimized setup to develop efficient and electronic bio-sensing platforms. Namely, the dataset contains Scan Cyclic Voltammetry (SCV) and Differential Pulse Voltammetry (DPV) waveform, obtained from APAP (Paracetamol) samples, considering different sampling rate. [1] S. Aiassa, S. Carrara and D. Demarchi, "Optimized Sampling Rate for Voltammetry-Based Electrochemical Sensing in Wearable and IoT Applications," in IEEE Sensors Letters. doi: 10.1109/LSENS.2019.2918575.

Supplementary Material for Optimized Sampling Rate for Voltammetry-Based Electrochemical Sensing in Wearable and IoT Applications / Aiassa, Simone; Carrara, Sandro; Demarchi, Danilo. - ELETTRONICO. - (2019). [10.21227/g9bn-sn96]

Supplementary Material for Optimized Sampling Rate for Voltammetry-Based Electrochemical Sensing in Wearable and IoT Applications

Simone Aiassa;Sandro Carrara;Danilo Demarchi
2019

Abstract

The Voltammetry-Based Sensing (VBS) methods are extremely interesting due to high specificity in several biochemical applications. Several considerations can be applied to use this method to measure different analytes, and implement efficient and optimized electronic measurement platform for point-of-care diagnostic, in wearable, portable, or IoT systems. The dataset contains the data presented in [1], which proves on real experimental data a method to define the optimized setup to develop efficient and electronic bio-sensing platforms. Namely, the dataset contains Scan Cyclic Voltammetry (SCV) and Differential Pulse Voltammetry (DPV) waveform, obtained from APAP (Paracetamol) samples, considering different sampling rate. [1] S. Aiassa, S. Carrara and D. Demarchi, "Optimized Sampling Rate for Voltammetry-Based Electrochemical Sensing in Wearable and IoT Applications," in IEEE Sensors Letters. doi: 10.1109/LSENS.2019.2918575.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2734187
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