本論文中採用台積電0.18 微米CMOS 製程設計了一個自動增益放大
器，以應用於神經訊號擷取與刺激研究平台的無限植入式深層腦部刺激
(Deep Brain Stimulation, DBS) 微系統。
植入式神經訊號擷取系統有兩個主要訊號，一者是速度較快但震幅較小
的神經突波(Neural spike)，另一者則是速度較慢但震幅較大的局部場電
位(local filed potential, LFP)，且於最近幾年退化性神經疾病的研究指出，
在帕金森斯症(Parkinson Disease, PD) 患者中，於發症前會偵測到High
Voltage Spindle(HVS)，是一種較快且振幅較大的訊號，HVS 屬於LFP 的
一種。
為了避免HVS 發生時因放大器的倍率無法及時調變而導致飽和，本論
文提出一種二位元式的自動倍率控制放大器架構，除了自動倍率調變外，
透過二位元切換的方式能讓後端ASIC 數位電路能快速的將倍率資訊與輸
出訊號反解回原始訊號。
放大器有新舊兩版的設計，新版的設計是為了解決舊版設計上的問題及
缺點，在新版設計的TT-corner post-simulation 中，於供給電壓為1V 的
情況下，可以提供53.7dB、59.7dB、65.7dB 三種類型的倍率，低通頻率
為1.57KHz 且高通頻率可從0.05Hz 調至5Hz，全系統一共6.9uW 並呈現
5.4uV 的輸入對應雜訊。
本論文在第一章簡介研究背景；在第二章對系統面的考量和設計進行說
明，並且回顧過去相關文獻；第三章介紹自動倍率放大器的電路設計、呈
現模擬與量測結果、進行討論，並且說明新舊兩版電路的設計差異；第四
章則以結論和未來工作為全文作結。
關鍵字–植入式系統，深層腦部刺激（DBS），自動倍率調控，神經訊
號放大器。

In this thesis, an automatic gain cotnrol amplifier for implantable microsystem
of deep brain stimulation (DBS) is proposed. DBS is a prodecure
that using neurostimulator to send electrical pulse to specific targets
in brains. Pakinson disease is one of the indications of DBS. In order to
measure the response from brain, an analog front-end is needed to capture
the local field potential. High voltage spindle is one type signal of local field
potential which founded in parkinson disease induced rat’s basal ganglia.
In order to avoid the saturation caused by high voltage spindle, the binary
switch control method is proposed. With the method, neural signal would
be amplified to specific range until the front-end is set to the largest gain
set.
The system provides three gain sets, 53.7dB, 59.7dB and 65.7dB. The
low pass corner is 1.57KHz, and the high pass corner ranges from 0.05Hz
to 5Hz. The gain is control by a digital circuit which can operate from
5KHz to 50KHz. The total power consumption is 6.9uW with 5.4uV input
referred noise.
The thesis has four chapters. In chapter1, we would review the backgroud
of the implant device. The consideration and design of the system
would be introduced in chapter2. The chapter3 shows the implementation
of the automatic gain control ampilifer, simulation and measurement result.
The conculsion and future work would be shown in chapter4
Keywords –Closed-loop system, Low-noise amplifiers, Implantable micro
system, Neural amplifier.

[1] R. R. Harrison and C. Charles, “A low-power low-noise cmos amplifier for neural recording applications,” IEEE Journal of Solid-State Circuits, vol. 38, no. 6, pp. 958–965, June 2003.

[2] Y. Chen, A. Basu, L. Liu, X. Zou, R. Rajkumar, G. S. Dawe, and M. Je, “A digitally assisted, signal folding neural recording amplifier,” IEEE Transactions on Biomedical Circuits and Systems, vol. 8, no. 4, pp. 528–542, Aug 2014.

[3] R. S. Sanders and M. T. Lee, “Implantable pacemakers,” Proceedings of the IEEE, vol. 84, no. 3, pp. 480–486, Mar 1996.

[4] F. A. Spelman, “The past, present, and future of cochlear prostheses,” IEEE Eng. Med. Biol. Mag., vol. 18, no. 3, pp. 27–33, May 1999.

[5] W. Liu, K. Vichienchom, M. Clements, S. C. DeMarco, C. Hughes,
E. McGucken, M. S. Humayun, E. D. Juan, J. D. Weiland, and R. Greenberg, “A neuro-stimulus chip with telemetry unit for retinal prosthetic device,” IEEE J. Solid-State Circuits, vol. 35, no. 10, pp. 1487–1497, Oct 2000.

[6] M. L. Kringelbach, N. Jenkinson, S. L. Owen, and T. Z. Aziz, “Translational principles of deep brain stimulation,” Nature Reviews Neuroscience, vol. 8, no. 8, pp. 623–635, Aug 2007.

[7] S. Kim, R. A. Normann, R. Harrison, and F. Solzbacher, “Preliminary study of the thermal impact of a microelectrode array implanted in the brain,” in Int. Conf. IEEE Engineering in Medicine and Biology Soc., Aug 2006, pp.2986–2989.

[8] M. S. J. Steyaert and W. M. C. Sansen, “A micropower low-noise monolithic instrumentation amplifier for medical purposes,” IEEE Journal of Solid-State Circuits, vol. 22, no. 6, pp. 1163–1168, Dec 1987.

[9] R. R. Harrison, “The design of integrated circuits to observe brain activity,”Proceedings of the IEEE, vol. 96, no. 7, pp. 1203–1216, July 2008.

[10] M. S. Chae, Z. Yang, M. R. Yuce, L. Hoang, and W. Liu, “A 128-channel 6 mw wireless neural recording ic with spike feature extraction and uwb transmitter,”IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 17, no. 4, pp. 312–321, Aug 2009.

[11] M. van Elzakker, E. van Tuijl, P. Geraedts, D. Schinkel, E. Klumperink, and B. Nauta, “A 1.9 μw 4.4fj/conversion-step 10b 1ms/s chargeredistribution adc,” in 2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers, Feb 2008, pp. 244–610.

[12] Y. P. Lin, C. Y. Yeh, P. Y. Huang, Z. Y. Wang, H. H. Cheng, Y. T. Li, C. F. Chuang, P. C. Huang, K. T. Tang, H. P. Ma, Y. C. Chang, S. R. Yeh, and H. Chen, “A battery-less, implantable neuro-electronic interface for studying the mechanisms of deep brain stimulation in rat models,” IEEE Transactions on Biomedical Circuits and Systems, vol. 10, no. 1, pp. 98–112, Feb 2016.

[13] M. Azin, D. J. Guggenmos, S. Barbay, R. J. Nudo, and P. Mohseni, “A battery-powered activity-dependent intracortical microstimulation ic for brain-machine-brain interface,” IEEE Journal of Solid-State Circuits, vol. 46, no. 4, pp. 731–745, April 2011.

[14] J. Wu, M. K. Law, P. I. Mak, and R. P. Martins, “A 2- W 45-nv/ √. hz readout front end with multiple-chopping active-high-pass ripple reduction

[15] C. Enz, M. A. Chalkiadaki, and A. Mangla, “Low-power analog/rf circuit design based on the inversion coefficient,” in ESSCIRC Conference 2015 - 41st European Solid-State Circuits Conference (ESSCIRC), Sept 2015, pp.202–208.