A CMOS Cellular Interface Array for Digital Physiology Featuring High-Density Multi-Modal Pixels and Reconfigurable Sampling Rate

Adam Y. Wang, Yuguo Sheng, Wanlu Li, Doohwan Jung, Gregory V. Junek, Jongseok Park, Dongwon Lee, Mian Wang, Sushila Maharjan, Sagar R. Kumashi, Jin Hao, Yu Shrike Zhang, Kevin Eggan, Hua Wang

Abstract: With the recent pandemic, the necessity of digital physiology/pathology, a set of high-resolution cellular/tissue-level images uploaded to the cloud for remote analytics and diagnostics, has skyrocketed as in-person lab services are limited by processing throughputs and increased exposure risks to patients/medical professionals [1]–[2]. Presently, cellular physiology diagnoses rely on high-resolution medical imaging and when translated to a cellular/tissue-level, these images, albeit with different biomarkers, may not holistically characterize a pathogen's effect due to the cell's complex multi-physiological responses [3]. In particular, new pathogen/virus variants often exhibit unknown pathological effects on cellular physiological functions. Hence, desired digital physiology cellular platforms should support sensing a wide variety of cells under different conditions, including those with rapid physiological features, e.g., neuron/cardiac cells.