Research Motivations:

• Addressing Existing Neural Interface Limitations: Neuromorphic neural interface SoCs aim to solve issues related to signal delay, high power use, and limited processing capacity in current systems.

• neuron-like Efficiency: By mimicking the neural circuits, these SoCs seek to process information more efficiently with lower energy consumption.

Research Outlook:

• Improved Rehabilitation and Assistive Tech: These SoCs promise enhanced support for individuals with sensory impairments or neural damage, improving their quality of life.

• Energy Efficiency: Neuromorphic designs are geared towards using much less energy than traditional systems, ideal for devices where power conservation is key.

• Ongoing Innovation: The field is rapidly advancing, with interdisciplinary research paving the way for new breakthroughs that could significantly impact human life.

Our research focuses on the integration of neuromorphic processors with neural interface SoCs (e.g., artificial retinas, cochlear implants) to achieve ultra-low power consumption and precise communication with sensory neural networks. This work aims to significantly improve the quality of life for patients.  

Reference

• Jeong Hoan Park, Joanne Si Ying Tan, Han Wu, Yilong Dong, and Jerald Yoo, “1225-Channel Neuromorphic Retinal-Prosthesis SoC with Localized Temperature-Regulation”, IEEE Transactions on Biomedical Circuits and Systems, vol. 14, no .6, pp.1230-1240, 2020.

• Jeong Hoan Park, Joanne Si Ying Tan, Han Wu, Jerald Yoo,  “1225-Channel Localized Temperature-Regulated Neuromorphic Retinal-Prosthesis SoC with 56.3nW/Channel Image Processor,” IEEE International Solid- State Circuits Conference - (ISSCC) Dig. Tech. Papers, Feb. 2020.