CMOS based capacitive sensor matrix for characterizing and tracking of biological cells

Area of Science:

• Biotechnology
• Bioengineering
• Cell Biology

Background:

• Biosensors are crucial for cell characterization and monitoring in cell culture.
• Capacitive sensors can extract detailed cell features like position, shape, and capacitance.

Purpose of the Study:

• To design and simulate a CMOS-based biochip with a capacitive sensor matrix (CSM) and pixel readout circuit (PRC).
• To track and characterize single biological cells, specifically Hepatocellular carcinoma cells (HCC) and normal liver cells (NLC), using their distinct features.

Main Methods:

• Designed and simulated a CMOS biochip integrating a CSM and PRC.
• Utilized COMSOL Multiphysics for capacitance extraction and sensor performance testing.
• Employed Virtuoso Analog Design Environment to evaluate the PRC's detection capabilities.
• Developed a MATLAB algorithm for cell location and shape prediction based on capacitance data.

Main Results:

• The biochip successfully characterized and distinguished between HCC and NLC.
• Capacitance measurements from the CSM correlated with frequency readings from the PRC.
• The system demonstrated the ability to predict cell location and shape.

Conclusions:

• The proposed CMOS biochip effectively characterizes and differentiates between normal and cancerous liver cells.
• The integration of CSM and PRC enables precise cell tracking and feature extraction.
• This technology holds potential for advanced cell culture monitoring and diagnostics.