Chuanqing WANG received the B.S. degree in material science and engineering from Harbin Engineering University, Harbin, China. He participated in summer program of Neuroscience and Cognitive Science in Tsinghua-Peking University. He joined the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech) and became a PhD Candidate of Westlake University in September 2019.
Retinal prostheses are intended to enhance vision in individuals suffering from retinal impairments such as Age-related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP). Intelligent and low-power retinal prostheses are highly demanded in this era, where wearable and implantable devices are used for numerous healthcare applications. To stay current and address this challenge, we propose a bio-inspired power-efficient optogenetics-based retinal prostheses. This approach utilizes a spike-based processing framework that mimics the behavior of the human retina and replaces the function of degenerative cell layers. This algorithm is being implemented on a custom neuromorphic processor to meet the criteria for real-time processing and low-power consumption. This optogenetic-based retinal prosthesis with bio-inspired processing framework as well as power efficient characteristics will provide a promising solution for improving vision restoration in both AMD and RP.
 Wang C, Fang C, M. Sawan, et al. “Artificial intelligence techniques for retinal prostheses: A comprehensive review and future direction”. Journal of Neural Engineering, 2023, doi: 10.1088/1741-2552/acb295.
 C. Wang, J. Yang and M. Sawan, "NeuroSEE: A Neuromorphic Energy-Efficient Processing Framework for Visual Prostheses," in IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 8, pp. 4132-4141, Aug. 2022, doi: 10.1109/JBHI.2022.3172306. (Journal cover)
 Wang C, Fang C, M. Sawan, et al. SpikeSEE: An Energy-Efficient Dynamic Scenes Processing Framework for Retinal Prostheses. arXiv preprint arXiv:2209.07898, 2022.