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Cell models are one of the most widely used basic models in biological research, and a variety of in vitro cell culture techniques and models have been developed recently to simulate the physiological microenvironment in vivo. However, regardless of the technique or model, cell culture is the most fundamental but crucial component. As a result, we have developed a cell culture monitoring system to assess the functional status of cells within a biochip. This article focuses on a mini-microscope made from a readily available camera for in situ continuous observation of cell growth within a biochip and a pH sensor based on optoelectronic sensing for measuring pH. With the aid of this monitoring system, scientists can keep an eye on cell growth in real time and learn how the pH of the culture medium affects it. This study offers a new approach for tracking cells on biochips and serves as a valuable resource for enhancing cell culture conditions.

Affinity biosensors of interdigitated electrodes have been widely used in cell detection. This research presents a mass-producible and disposable three-dimensional (3D) structure capacitive sensor based on the integrated circuit package lead frames for cell concentration detection. The fully symmetric 3D interdigital electrode structure makes the sensor more homogeneous and sensitive. (3-Aminopropyl) triethoxysilane (APTES) and glutaraldehyde are immobilized onto gold-plated electrodes. By overlaying the microfluidic channels on top, the volume of the solution is kept constant to obtain repeatable measured capacitance values. Moreover, using the upgraded reading and writing functions and circular measurement of the E4980A Data Transfer Program, an automatic multigroup test system is developed. It is shown that the cell concentration and capacitance are inversely correlated, and the cell concentration range of 103–106 CFU∙mL−1 is achieved. In addition, the rate of capacitance change matches that of state-of-the-art biosensors reported. A program is developed to find the optimal voltage and frequency for linear fitting between the capacitance change and cell concentration. Future work will employ machine learning-based data analysis to drug resistance sensitivity test of cell lines and cell survival status.