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作者(中文):許哲維
作者(外文):Hsu, Che-Wei
論文名稱(中文):視網膜晶片輸出分析與周邊電路
論文名稱(外文):Retinal Prosthesis Chip Output Analysis and Peripheral circuits
指導教授(中文):張彌彰
指導教授(外文):Chang, Mi-Chang
口試委員(中文):徐永珍
馬席彬
口試委員(外文):Hsu, Yung-Jane
Ma, Hsi-Pin
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學號:103061580
出版年(民國):108
畢業學年度:107
語文別:英文
論文頁數:109
中文關鍵詞:人工視網膜晶片
外文關鍵詞:retinal prosthesis chip
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世界上得到視網膜相關疾病的病人,像是老年性黃斑部病變以及視網膜色素病變的人逐年增加,因此近年來有不少研究開發新的治療方法,其中一種方式就是用人工視網膜取代受損的細胞。
本篇完成了視網膜晶片裡的內建時脈控制電路,此控制電路管理了晶片裡所有控制訊號,此架構具有靈活的設計彈性,設計時,若要更改控制訊號的波寬、升起或落下時機是很容易做到的。為了測試晶片,本篇設計了連續近似類比數轉換器,它的取樣頻率是51.2 kS/s,解析度是9碼,ENOB為7.8。
此晶片將植入病人體內,因此其完整測試非常重要,但測試所有的可能性非常花時間,可以說是近乎不可能,所以減少測試數量是很重要的,而且過長的測試時間對於商業考量來說是一大成本,本篇認為在人眼無法分辨的基礎下,測試影像可以被簡化成16個亮度層級以減少測試時間且提升測試效率。此外,還研究分析了晶片系統性變異及局部性變異對輸出影像的影響,希望結果在未來可以用以幫助減少不必要的測試圖案;最後提出了PSNR於非線性誤差模擬及局部性變異模擬的快速算法,以減少大量的模擬時間。
The number of patients suffering from retinal diseases such as Age-related macular degeneration (AMD) and retinitis pigmentosa (RP) are increasing every year in the world. Treatments by retina prosthesis for AMD and RP are fruitful in recent years. Retinal prosthesis is one of treatment and used to replace the function of the damaged cells.
A controller with a built-in clock is developed for the retinal prosthesis chip. All control signals in the chip are well maneged by the controller. The architecture of the controller is a flexible design. It is easy to modify the pulse width or any rising and falling timing whenever the specification is changed in design phase. A SAR ADC is designed for chip testing. The sample rate is 51.2 kS/s, the resolution is 9 bits and ENOB is 7.8 bits.
This chip will be implanted in human body so the complete testing is very crucial. However, testing all patterns takes very long time and is almost impossible. To reduce test patterns is important since long test time is a lot of cost for commercial consideration. The test images could be simplified to 16 light intensity levels which could reduce test pattern number and increase testing efficiency. Also, the influence of the output images from the retinal prosthesis chip with systematic variation and local variation is studied and analyzed. The results could help us reduce the unnecessary test patterns. The PSNR calculation in non-linearity error and local variation are proposed, which could save a lot of simulation time.
摘要………………………………………………………………………….……….………….…. ii
Abstract……………………………………………………………………………………………...iii
Table of Contents…………………………………………………………………………………... iv
List of Figures………………………………………………………………………………………vii
List of Tables………………………………………………………………………………………...xi
Chapter 1 Introduction……………………………………………………………..…………………1
1.1 Background…………………………….……….…………….…………………………….1
1.2 Motivation…………………………………………………………………………………..2
1.3 Retinal Prosthesis Chip……………………………………………………………………..3
1.4 Organization……………………………………….…….………………….………………6
Chapter 2 Controller…………………………….……………….…….….…………….……………7
2.1 Objective……………………………….…….…….……………………………………….7
2.2 Approach……………………………………………………………………………………9
2.3 Block Diagram……………………………………………………………………………..11
2.4 Circuits Implementation……………………………………………………………...……12
2.4.1 Clock Generator………………………………………………………….…………..12
2.4.2 Frequency Divider…………………………………………………………………...12
2.4.3 Pulse Generator…………………………………………………………..………….14
2.4.4 Window Generator…………………………………………………………………..16
2.4.5 Cluster Signal Generator…………………………………………………………….17
2.5 Layout and Measurement Results…………………………………………………………19
2.6 Summary………………………………………....………….....………....………......……23
Chapter 3 Successive Approximation Register Analog-to-Digital Converter ……………………...24
3.1 Principle and Architecture…………………………………..….………………………….24
3.2 Circuit Implementation…………………………………………………………………….26
3.2.1 Track and Hold Circuit with Bootstrapped Analog Switch………………….….….26
3.2.2 Comparator…………………………………………………………………………28
3.2.3 SAR Control Logic………………………………………………………………....28
3.3 Experimental Results………………………....….……....……......……..…......…….……29
Chapter 4 Image Comparison……………………………………….............……………...…….…32
4.1 Two Image Quality Indexes……………………………………………………………….32
4.2 Ten Sample Pictures……………………………………………………………………….34
4.3 SSIM Using Boundary Condition…………………………………………………....……36
4.3.1 Three Boundary Conditions………………………………………………….….…37
4.3.2 Non-linearity Systematic Variation Simulation.…….………….………….………39
4.3.3 Simulation Results………………………………………….………………………40
4.4 Reducing Number of Light Intensity Levels………………………………………………52
4.4.1 Number of Light Intensity Levels……………………………………….…………52
4.4.2 Results…………………………………….………….……………….……………53
4.5 Summary…………………………………………………………………………………...55
Chapter 5 Systematic Variation and Local Variation……………………………………..…...……56
5.1 Systematic Variation………………………………………………………………………56
5.1.1 Three Systematic Variation…………………………………………………...……56
5.1.2 Systematic Variation Simulation…………………………………………………...59
5.1.3 Results and Analysis………………………………………………………………..60
5.1.4 Summary……………………………………………………………………………86
5.2 Local Variation……………………………………………………………………….……86
5.2.1 Local Variation………………………………………………………………..……86
5.2.2 Local Variation Simulation……………………………………………….……..…87
5.2.3 Results and Analysis………………………………………………………..………88
5.2.4 Summary……………………………………………………………………………93
5.3 PSNR calculation…………………………………………………………………………..94
5.3.1 Non-linearity Error…………………………………………………………………94
5.3.2 Local Variation……………………………………………………………………..99
5.4 Summary………………………………………………………………………………….102
Chapter 6 Conclusions and Future Works…………………………………………………………103
6.1 Conclusions………………………………………………………………………………103
6.2 Future Works……………………………………………………………………………..104
References…………………………………………………………………………………………106
[1] Stone JL, Barlow WE, Humayun MS, de Juan EJ, and A. H. Milam, “Morphometric analysis of macular photoreceptors and ganglion cells in retinas with retinitis pigmentosa,” Arch. Ophthalmol, vol. 110, no. 11, pp. 1634–1639, 1992.
[2] A. Santos, M. S. Humayun, de Juan EJ, R. J. Greenburg, M. J. Marsh, I. B. Klock, and A. H. Milam, “Preservation of the inner retina in retinitis pigmentosa A morphometric analysis,” Arch. Ophthalmol, vol. 115, no. 4, pp. 511–515, 1997.
[3] M. S. Humayun, M. Prince, de Juan EJ, Y. Barron, M. Moskowitz, I. B. Klock, and A. H. Milam, “Morphometric analysis of the extramacular retina from postmortem eyes with retinitis pigmentosa,” Investigative Ophthalmology & Visual Science, vol. 40. no. 1, pp. 143-148, January 1999.
[4] E. L. Berson, “Retinitis pigmentosa. The Friedenwald Lecture,” Investigative Ophthalmology & Visual Science, Vol. 34, No. 5, pp.1659-1676, 1993.
[5] S. Y. Kim, S. Sadda, J. Pearlman, M. S. Humayun, E. Jr. de Juan, B. M. Melia, W. R. Green, “Morphometric Analysis of The Macula In Eyes With Disciform Age-Related Macular Degeneration,” Retina, vol. 22, issue 4, pp. 4171-477, 2002.
[6] J.D. Weiland, and W.T. Liu, and M. S. Humayun. "Retinal prosthesis," Annual Review of Biomedical Engineering, vol. 7, pp.361-401, 2005.
[7] J. D. Weiland, and M. S. Humayun, "Retinal Prosthesis," IEEE Transactions on Biomedical Engineering, vol. 61, no. 5, pp. 1412-1424, May 2014.
[8] M. S. Humayun, J. D. Dorn, L. da Cruz, G. Dagnelie, J.-A. Sahel, P. E. Stenga, A. V. Cideciyan, J. L. Duncan, D. Eliott, E. Filley, A. C. Ho, A. Santos, A. B. Safran, A. Arditi, L. V. D. Priore, and R. J. Greenberg, "Interim results from the international trial of Second Sight's visual prosthesis", Ophthalmology, vol. 119, pp. 779-788, 2012.
[9] K. Stingl, K.-U. Bartz-Schmidt, F. Gekeler, A. Kusnyerik, H. Sachs and E. Zrenner, "Functional outcome in subretinal electronic implants depends on foveal eccentricity", Invest. Ophthalmol. Vis. Sci., vol. 54, pp. 7658-7665, 2013.
[10] L. S. Theogarajan, “A Low-Power Fully Implantable 15-Channel Retinal Stimulator Chip,” IEEE Journal of Solid-State Circuits, Vol. 43, No. 10, Oct., pp. 2322-2337, 2008.
[11] T. Tokuda, K. Hiyama, S. Sawamura, K. Sasagawa, Y. Terasawa, K. Nishida, Y.i Kitaguchi, T. Fujikado, Y. Tano, and J. Ohta, “CMOS-Based Multichip Networked Flexible Retinal Stimulator Designed for Image-Based Retinal Prosthesis,” IEEE Transactions on Electron Devices, Vol. 56, No. 11, Nov., pp. 2577-2585, 2009.
[12] B. K. Thurgood, D. J. Warren, N. M. Ledbetter, G. A. Clark, and R. R. Harrison, “A Wireless Integrated Circuit for 100-Channel Charge-Balanced Neural Stimulation”, IEEE Transactions On Biomedical Circuits And Systems, Vol. 3, No. 6, Dec., pp. 405-414, 2009.
[13] A. Rothermel, L. Liu, N. P. Aryan, Michael Fischer, J. Wuenschmann, S. Kibbel, and A. Harscher, “A CMOS Chip With Active Pixel Array and Specific Test Features for Subretinal Implantation,” IEEE Journal Of Solid-State Circuits, Vol. 44, No. 1, Jan., pp. 290-330, 2009.
[14] K. Chen, Y.-K. Lo, Z. Yang, J. D. Weiland, M. S. Humayun, and W. Liu, “A System Verification Platform for High-Density Epiretinal Prostheses,” IEEE Transactions On Biomedical Circuits And Systems, Vol. 7, No. 3, June, pp. 326-337, 2013.
[15] N. Sharmili, V. Bhujanga Rao, P. Seetharamaiah, and N. Swapna, “A Prototype 1024 Electrode Embedded Eomputer based Epiretinal Prosthesis System,” International Conference on Signal Processing and Integrated Networks, 2016, pp. 337-341.
[16] C. L. Lee, and Chih-Cheng Hsieh, “A 0.8-V 4096-Pixel CMOS Sense-and-Stimulus Imager for Retinal Prosthesis,” IEEE Transactions On Electron Devices, Vol. 60, No. 3, Mar., pp. 1162-1168, 2013.
[17] K. Shimokawa, Z. Qian, Y. Takezawa, H. Kino,T. Fukushima, K. Kiyoyama, and T. Tanaka, “Experimental Evaluation of Stimulus Current Generator with Laplacian Edge-Enhancement for 3-D Stacked Retinal Rrosthesis Chip,” 2017 IEEE Biomedical Circuits and Systems Conference, Turin, 2017, pp. 1-4.
[18] Z. Ye, “Retinal prosthesis signal processing using pulse logic approach,” M. S. thesis, National Tsing Hua University, R. O. C., 2016
[19] T. Yao, “Neurotic biphasic stimulation driver,” M. S. thesis, National Tsing Hua University, R. O. C., 2016
[20] D. Zhang, A. Bhide, and A. Alvandpour, “A 53-nW 9.1-ENOB 1-kS/s SAR ADC in 0.13- μm CMOS for Medical Implant Devices,” IEEE journal of solid-state circuits, vol. 47, no. 7, Jul., pp. 1585-1593, 2012.
[21] L. Chi-Chang and L. Tsung-Sum, "A 10-bit 60-MS/s Low-Power CMOS Pipelined Analog-to-Digital Converter," IEEE Transactions on Circuits and Systems II: Express Briefs , vol. 54, pp. 658-662, 2007.
[22] G. Van der Plas and B. Verbruggen, “A 150 MS/s 133 W 7 b ADC in 90 nm digital CMOS using a comparator-based asynchronous binarysearch sub-ADC,” in IEEE ISSCC Dig. Tech. Papers, pp. 242–243, Feb. 2008.
[23] A. Rossi and G. Fucili, "Nonredundant successive approximation register for A/D converters," Electronics Letters, Vol.32, pp. 1055-1057, 1996.
[24] Y. A. Y. Al-Najjar, and Der C. Soong, “Comparison of Image Quality Assessment: PSNR, HVS, SSIM, UIQI,” International Journal of Scientific & Engineering Research, vol. 3, no. 8, pp. 1-5, August-2012.
[25] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image Quality Assessment: From Error Visibility to Structural Similarity,” IEEE Transactions On Image Processing, vol. 13, no. 4, Apr., pp. 600-612, 2004.
 
 
 
 
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