## 4 Conclusions  
This paper proposed a low-noise potentiostat readout circuit with a chopper fully differential difference amplifier for glucose monitoring. The potentiostat electrochemical current mode sensors convert potential differences into current signals according to the concentration of the solution, and the readout circuit converts current signals into voltage signals.  
The proposed potentiostat ROIC consists of a potentiostat biasing circuit with a chopper FDDA, bias circuit, SPI, and timing logic. The implementation of the chopper FDDA scheme for the potentiostat readout circuit can decrease the number of amplifiers in the control part, with reduced power consumption and a wide dynamic output range. In addition, the maximum signal swing can be realized using the rail-to-rail input stage, and a high open-loop gain is obtained through the cascode stage, allowing \(V_{\textit{c}\textit{c}\textit{f}}\) to track close to \(V_{\textit{src}}\). Moreover, the implemented Monticelli-style class-AB output stage can increase the power efficiency. The chopping technique can reduce low-frequency noises, such as 1/f noise, thereby achieving the requisite low-noise characteristic for highly accurate glucose monitoring.  
The proposed potentiostat readout circuit was designed in the standard 0.18 \(\upmu\)m CMOS process, and the current consumption was 48.54 \(\upmu\)A with a 1.8 V power supply. The measured input-referred noise at 1 Hz was 802.2 fA/\(\upmu\)Hz by the chopper operation with a 200 k\(\Omega\) feedback resistor. The input-referred RMS noise from 0.5 Hz to 50 Hz was 11.2 pARMS.  
Conceptualization and supervision, H.K.; investigation and writing--original draft preparation, G.C.; writing--review and editing, K.N., M.Y., S.K., B.J., K.K. and H.S. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & **This Work** & **IEEE MIEL** & **IEEE iSES** & **IEEE Access** & **Sensors** & **ISCAS** \\  & **2021**[19] & **2021**[20] & **2020**[17] & **2020**[13] & **2017**[13] & **2015**[18] \\ \hline Process (\(\upmu\)m) & 0.18 & 0.18 & 0.18 & 0.065 & 0.18 & 0.18 \\ \hline Architecture & FDDA & Current & Current & \begin{tabular}{c} 1 st-order \\ delta-sigma \\ converter \\ \end{tabular} & FDDA & \begin{tabular}{c} 1 st-order \\ delta-sigma \\ converter \\ \end{tabular} \\ \hline Chopper & Y (8 kHz) & N & N & N & N \\ \hline Output format & Voltage & Current & Voltage & Digital codes & Voltage & Voltage \\ \hline Supply voltage (V) & 1.8 & 1.8 & 1.5 & 1.2 & 1.8 & 1.8 \\ \hline Power consumption (\(\upmu\)W) & 86.4 & 2300 & 124 & \begin{tabular}{c} 15–25 \\ (0.1–1.5 \(\upmu\)A) \\ \end{tabular} & 53 & 72.36 \\ \hline \multirow{2}{*}{Input-referred noise (pARMS)} & \begin{tabular}{c} 11.2 \\ (50 Hz BW) \\ (measured) \\ \end{tabular} & \
\begin{tabular}{c} 153 \\ (0.01–1 kHz) \\ \end{tabular} & N/A &
\begin{tabular}{c} 168.3 [FOOTNOTE:] Output digital code is limited to 10 bits.[ENDFOOTNOTE] \\ (1 Hz BW) \\ (measured) \\ \end{tabular} & N/A & N/A \\ \hline \end{tabular}
\end{table}
Table 4: Comparison of performance with previous studies.  
Figure 12: Input-referred current noise.  
**Funding:** This work was supported by the Practical Technology development medical microrobot Program (R&D Center for Practical Medical Microrobot Platform, HI9C0642) funded by the Ministry of Health and Welfare (MOHW, Korea) and the Korea Health Industry Development Institute (KHIDI, Korea). This work was supported (funded) by the Nanomedical Devices Development Project of NNFC (CP22021M). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2022R1A2C100517011).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The EDA tool was supported by the IC Design Education Center (IDEC), Korea.  
**Conflicts of Interest:** The authors declare no conflict of interest.