In this work, we have developed a portable electrochemical sensing device controlled by a smartphone through Bluetooth, which was applied for regular uric acid (UA) monitoring in prevention and healthcare management. On the core lies a nonlinear fitting model (I = k·(N − exp(−K·cbulk + b))) which is proposed for the first time and given from the differential equation based on the theoretical analysis. We believe this model can reflect the intrinsic relationship between the obtained current and the bulk analyte concentration, therefore leading to an expanding UA detection range (10-fold) compared to the widely used linear standard curve model and reducing the requirements for the modification of the electrode materials. Besides, the integration of the microfluidic chip promoted the removal of UA oxidation products at the electrode surface, yielding excellent sensing stability with a relative standard deviation (RSD) lower than 1 % during 10 consecutive runs. Consequently, we acquired the relationship between Square Wave Voltammetry (SWV) current and UA concentration (I = 15.27*(2.05 − exp(−0.00108*(cbulk − 663.5))), R2 = 0.9999) in the range of 5 to 1000 μM with a limit of detection (LoD) of 2.4 μM using a completely unmodified screen-printed carbon electrode (SPCE). Proof of concept experiments using 25× diluted human urine spiked with UA yielded a recovery rate of 87.5–101.4 % and a satisfactory selectivity result, which is within the value expected for clinical use, indicating the potential of the developed instrument and nonlinear fitting model for urinary UA detection.