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MEMS-based system and image processing strategy for epiretinal prosthesis

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 4th International Conference on Biomedical Engineering and Biotechnology, 18–21 August 2015, Shanghai, China

Guest editors: Feng Liu, Dong-Hoon Lee, Ricardo Lagoa and Sandeep Kumar

Article type: Research Article

Authors: Xia, Peng | Hu, Jie; * | Qi, Jin | Gu, Chaochen | Peng, Yinghong

Affiliations: State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan RD. Minhang District, Shanghai, 200240, China

Correspondence: [*] Address for correspondence: Jie Hu, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan RD. Minhang District, Shanghai, 200240, China. Tel.: 021-34206552; Fax: 021-34206313; E-mail: hujie@sjtu.edu.cn.

Keywords: Retinal prosthesis, MEMS, image processing, simulated prosthetic vision

DOI: 10.3233/BME-151423

Journal: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1257-S1263, 2015

Published: 2015
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Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.

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