Capacitive sensor array (CSA) is vital in precise monitoring for lab-on-chip (LOC) systems. However, shrinking electrode sizes to increase spatial resolution bring challenges like noise interference and large data volumes. This paper presents an FPGA-based system that addresses these problems with multiple sampling (MS) and pixel-wise accumulation (PWA). MS reduces Gaussian noise by sampling multiple frames and retaining only representative data points, while PWA compresses data using Block RAM and minimal combinational logic, reducing size from 118 Mb to 0.46 Mb and boosting SNR to 25.30 dB. The system enables real-time monitoring every 5 seconds instead of 17 minutes, with pipeline sensing and transmission further optimizing sensing time. Experiments demonstrate its effectiveness in distinguish between droplets and monitor evaporation in real time. MS and PWA can be easily integrated into future chip designs, offering scalable solutions for fast and precise monitoring in LOC environments.

Dielectrophoresis (DEP) is a powerful tool for manipulating biological cells. However, single cell manipulation is usually time-consuming and skill-intensive. This paper presents a system that integrates AI for real-time image recognition with a programmable dielectrophoresis (DEP) array chip for automated particle manipulation. The system comprises a DEP chip, an FPGA, a computer, a microscope, and a server. The YOLO v8 model is used to detect particle positions within microscope images and generate DEP manipulation patterns. The system utilizes a Breadth-First Search (BFS) algorithm for path planning, ensuring collision-free movement of particles within a grid structure. Experimental results demonstrated the system’s effectiveness in manipulating 20 μm polystyrene particles with a success rate of over 90%. This system offers a significant advancement in automated DEP-based manipulation, providing precise control at micro scales with high computational efficiency.

Dielectrophoresis (DEP) is a powerful technique for manipulating biological cells. Yet, its widespread application has been limited by traditional glass-based chips with static electrode configurations that often require integrated microfluidic systems. This paper presents a novel DEP array chip fabricated in a standard CMOS process, featuring a 128 × 128 electrode matrix capable of generating dynamic, programmable electric field patterns that can be tailored to meet specific requirements for different use cases. Experiments have demonstrated the ability of the chip to manipulate fibroblast and THP-1 cells, with fibroblast movement observed at a velocity of 10µm/s with a DEP frequency of 800kHz and a peak-to-peak DEP voltage of 1.8V. The chip is designed for compatibility with standard petri dishes, obviating the requirement for microfluidics and facilitating its integration with traditional cell culture protocols. Our results indicate the chip’s potential as a versatile tool for cell biology research and applications.

Capacitive sensor array (CSA) has emerged as a prominent approach in the field of biomedical detection, particularly for the analysis of cell morphology and the construction of a Cell-on-CMOS platform. To enhance overall sensitivity, this paper presents a novel 2-D vernier digital-to-time converter (2D V-DTC) with a resolution of 31.25 ps and a dynamic range of 2.56 µs. The 2-D vernier structure attains sufficient resolution while reducing the number of delay elements required, and seamlessly integrates with a counter-based controller, extending the dynamic range to effectively cover a significantly larger sensing window. The CSA biochip, fabricated in 180-nm CMOS technology, achieves results with an overall sensitivity of 880 code/fF. This achievement translates into an sensing resolution of 1.13 aF, demonstrating its potential to further advance the development of CMOS-based cell-monitoring platform.