无线无源DBS的关键技术与强噪声下脑电诱发电位的检测
|
摘要
脑深部刺激技术能够绿色有效治疗帕金森病（PD）。但由于国外的技术垄断，使得设备费用很高；而且，目前临床应用脑深部刺激器（DBS）因电池容量有限，使用数年后需再次手术更换电池或刺激器，增加了患者的痛苦和经济负担。因此，对DBS整体设计方案的研究、开发终身使用、低成本的DBS势在必行。
相比DBS的在临床上的迅速应用，其治疗机理并不十分明确。因此，强刺激信号作用下的微弱诱发脑电信号的检测与分析对于DBS的作用机理研究显得尤为重要，这不仅能进一步改进DBS，而且对研究和治疗各种神经类疾病具有重要意义。
本文研究了终身使用的DBS，有两种设计方案--无线无源DBS和可充电式DBS，设计了强噪声下神经电信号采集系统，并运用不同的方法提取诱发信号。主要的工作及结果包括以下几个方面：
1）创新性地提出了无线无源参数可调脉冲发生器的设计方案，实现了刺激脉冲各项参数的可调；体内刺激器部分不需任何电池，有望实现DBS的一次植入、终身使用，设计并制作了无线无源的DBS样机。
2）首次将超级电容作为体内刺激器的储能单元，设计了其无线充电方案以及输出稳压电路；设计了基于MOS管的脉冲发生方案，使得刺激脉冲的各项参数易于调节且系统稳定性高，设计并制作可充电式DBS样机。
3）针对强电刺激和微弱脑电信号相差6个数量级难于检测的难题，设计了高精度的信号采集系统，采用过采样技术和高分辨率与高速ADC器件实现超大动态范围信号采集，完成同步刺激等强噪声背景下大鼠脑深部电位的采集。
4）刺激中诱发脑电信号淹没在强噪声与自发脑电信号中，信噪比很低。本文研究了基于线性与非线性理论的大鼠脑深部诱发电位的提取方法。提出了以提升小波处理后的信号作为自适应信号增强器的参考输入的方法提取诱发电位。得到的诱发电位精度较高，而算法运算速度快，耗时短，在实时处理上效果突出。就单导脑深部诱发电位的检测提出了采用经验模态分解与盲源分离相结合的方法。该方法不仅能处理非平稳信号的分离，而且可适用于源信号数多于观测信号数的分离等。
Deep Brain Stimulating could cure Parkinson’s disease without causing damageto the brain tissues. But the monopolization of foreign DBS’s technology drives up theprice of this device. Moreover, due to the limit of battery, the Deep Brain Stimulator(DBS) include its battery will have to be replaced via surgery in clinical application.And all of this will increase patient's suffering and economic burden. So research ofthe DBS overall design and development of lifetime use and low cost DBS isimperative.
Compared to the DBS technology development, its therapeutic mechanism is notclear, the detection and research of weak evoked potentials signal under strongstimulation are particularly important for its mechanism study, as the result in thatthese could not only further improve the DBS, but also be of great significance for theresearch and treatment of neurological diseases.
This paper proposed two designs for lifelong DBS: wireless passive DBS andrechargeable DBS, the design of the nerve signal acquisition system in strong noise ispresented too. Then rat EEG under stimulating is detected and the evoked potentialsare extracted from them.
The main parts and achievements are as following:
1) A design of wireless passive pulse generator was innovatively proposed, and itcould adjust parameters of the stimulation pulses. This design didn’t need battery invivo stimulation parts, so the DBS could be lifetime use after the first implant. Thewireless passive DBS prototype was developed.
2) Super-capacitor was used as the energy storage unit in vivo, the wirelesscharging scheme and output voltage regulation circuit was designed. A pulsegenerator based on MOSFET was presented which made it easier to adjust theparameters of the DBS, and the system has a high stability. The rechargeable DBSprototype was produced.
3) The high-precision signal acquisition system was developed for the detectionof weak EEG which differed six orders in magnitude from stimulation signal.Combining the oversampling technology and high-resolution, high-speed ADCdevices to achieve large dynamic range signal acquisition, thus the acquisition of the rat deep brain potential was completed under the strong noise which includessynchronization stimulation.
4) The signal-to-noise ratio of stimulation evoked EEG is very low because itwas buried in strong noise and Spontaneous EEG. This paper studied the extractionmethods of deep evoked potential in rat brain under different requirements based onlinear and nonlinear theory. The algorithm utilized the signal de-noised by liftingwavelet transform as the input of adaptive signal enhancer to extract evoked potential.This method could take very short time to achieve a high precise, and it hadprominent effect on the real-time processing. What’s more, the method of combiningempirical mode decomposition method with blind source separation was raised toextract single channel deep brain evoked potentials. This method can not only be usedin the separation of non-stationary signal, but also be applied to the situation wherethere were more source signals than observed signals.
相比DBS的在临床上的迅速应用，其治疗机理并不十分明确。因此，强刺激信号作用下的微弱诱发脑电信号的检测与分析对于DBS的作用机理研究显得尤为重要，这不仅能进一步改进DBS，而且对研究和治疗各种神经类疾病具有重要意义。
本文研究了终身使用的DBS，有两种设计方案--无线无源DBS和可充电式DBS，设计了强噪声下神经电信号采集系统，并运用不同的方法提取诱发信号。主要的工作及结果包括以下几个方面：
1）创新性地提出了无线无源参数可调脉冲发生器的设计方案，实现了刺激脉冲各项参数的可调；体内刺激器部分不需任何电池，有望实现DBS的一次植入、终身使用，设计并制作了无线无源的DBS样机。
2）首次将超级电容作为体内刺激器的储能单元，设计了其无线充电方案以及输出稳压电路；设计了基于MOS管的脉冲发生方案，使得刺激脉冲的各项参数易于调节且系统稳定性高，设计并制作可充电式DBS样机。
3）针对强电刺激和微弱脑电信号相差6个数量级难于检测的难题，设计了高精度的信号采集系统，采用过采样技术和高分辨率与高速ADC器件实现超大动态范围信号采集，完成同步刺激等强噪声背景下大鼠脑深部电位的采集。
4）刺激中诱发脑电信号淹没在强噪声与自发脑电信号中，信噪比很低。本文研究了基于线性与非线性理论的大鼠脑深部诱发电位的提取方法。提出了以提升小波处理后的信号作为自适应信号增强器的参考输入的方法提取诱发电位。得到的诱发电位精度较高，而算法运算速度快，耗时短，在实时处理上效果突出。就单导脑深部诱发电位的检测提出了采用经验模态分解与盲源分离相结合的方法。该方法不仅能处理非平稳信号的分离，而且可适用于源信号数多于观测信号数的分离等。
Deep Brain Stimulating could cure Parkinson’s disease without causing damageto the brain tissues. But the monopolization of foreign DBS’s technology drives up theprice of this device. Moreover, due to the limit of battery, the Deep Brain Stimulator(DBS) include its battery will have to be replaced via surgery in clinical application.And all of this will increase patient's suffering and economic burden. So research ofthe DBS overall design and development of lifetime use and low cost DBS isimperative.
Compared to the DBS technology development, its therapeutic mechanism is notclear, the detection and research of weak evoked potentials signal under strongstimulation are particularly important for its mechanism study, as the result in thatthese could not only further improve the DBS, but also be of great significance for theresearch and treatment of neurological diseases.
This paper proposed two designs for lifelong DBS: wireless passive DBS andrechargeable DBS, the design of the nerve signal acquisition system in strong noise ispresented too. Then rat EEG under stimulating is detected and the evoked potentialsare extracted from them.
The main parts and achievements are as following:
1) A design of wireless passive pulse generator was innovatively proposed, and itcould adjust parameters of the stimulation pulses. This design didn’t need battery invivo stimulation parts, so the DBS could be lifetime use after the first implant. Thewireless passive DBS prototype was developed.
2) Super-capacitor was used as the energy storage unit in vivo, the wirelesscharging scheme and output voltage regulation circuit was designed. A pulsegenerator based on MOSFET was presented which made it easier to adjust theparameters of the DBS, and the system has a high stability. The rechargeable DBSprototype was produced.
3) The high-precision signal acquisition system was developed for the detectionof weak EEG which differed six orders in magnitude from stimulation signal.Combining the oversampling technology and high-resolution, high-speed ADCdevices to achieve large dynamic range signal acquisition, thus the acquisition of the rat deep brain potential was completed under the strong noise which includessynchronization stimulation.
4) The signal-to-noise ratio of stimulation evoked EEG is very low because itwas buried in strong noise and Spontaneous EEG. This paper studied the extractionmethods of deep evoked potential in rat brain under different requirements based onlinear and nonlinear theory. The algorithm utilized the signal de-noised by liftingwavelet transform as the input of adaptive signal enhancer to extract evoked potential.This method could take very short time to achieve a high precise, and it hadprominent effect on the real-time processing. What’s more, the method of combiningempirical mode decomposition method with blind source separation was raised toextract single channel deep brain evoked potentials. This method can not only be usedin the separation of non-stationary signal, but also be applied to the situation wherethere were more source signals than observed signals.
引文
[1]陈茹．帕金森研究进展[J]．中国康复理论与实践，2007，13(7)：637-639.
[2]Dauer W, Predborski S. Parkinson’s disease:mechanisms and models[J]. Ncuron,2003,39:889-909.
[3]Andersen JK. Does neuronal loss in Parkinson’s disease involve programmed cell death[J].Bioessays,2001,23(7):640~646.
[4]陈慧梅．代谢组学及其研究方法和应用[J]．肾脏病与透析肾移植杂，2005，14(1)：59-64.
[5]卢芳，刘树民，杨婷婷．帕金森病的最新国内外研究进展[J]．中国老年学杂志，2009，29(9)：1171-1174.
[6]Allan L E, Petit G H, Brundin P. Cell transplantation in Parkinson's disease: problems andperspectives[J]. Current opinion in neurology,2010,23(4):426-432.
[7]Singleton A B, Farrer M J, Vincenzo B. The genetics of Parkinson's disease: Progress andtherapeutic implications[J]. Movement Disorders: Official Journal of the Movem,2013,28(1):14-23.
[8]Wakeman D R, Dodiya H B. Cell Transplantation and Gene Therapy in Parkinson's Disease[J].Mount Sinai Journal of Medicine,2011,78(1):126-158.
[9]Wang J, Xu Z, Fang H, et al. Gene expression profiling of MPP(+) treated MN9D ceHs:Amechanism of toxicity study[J]. Neurotoxicology,2007,28:979-987.
[10]Ascherio A, Chen H, Schwarzschild MA, et al. Caffeine postmenopausal estrogen and risk ofPD[J]. Neurology,2003,60:790.
[11]Benmoyal-Segal L, Soreq H. Gene-environment interactions in sporadic Parkinson’sdisease[J]. J Neurochem,2006,97:1740-1755.
[12]Lesage S, Brice A. Parkinson's disease: from monogenic forms to genetic susceptibilityfactors[J]. Human molecular genetics,2009,18(R1): R48-R59.
[13]许继平，李玉莲，蔺薪英，等．帕金森病患者血液抗氧化功能的变化及多巴制剂与VitE对其影响的研究[J]．中风与神经疾病杂志，2000，17(1)：46-48.
[14]Kickler N, Lacombe E, Chassain C, et al. Assessment of metabolic changes in the striatum ofa rat model of parkinsonism: An in vivo1H MRS study[J]. NMR in Biomedicine,2009,22:207-212.
[15]Kanaan NM, Kordower JH, Collier TJ. Age and region-specific responses of microglia, butnot astrocytes, suggest a role in selective vulnerability of dopamine neurons after1-methyl-4-phenyl-1,2,3,6-tetrahy-dropyridine exposure in monkeys[J]. Glia,2008,56:1199-1214.
[16]吴浩翔，刘玉玲．帕金森病治疗药物研究进展[J]．中国药学杂志，2004，39（6）：409-412.
[17]卢明，雒晓东，张华．帕金森病治疗现状及中成药研制的机遇与挑战[J]．中国中医药信息杂志，2008，15(4)：4-5.
[18]Oliver Fiehn, Metabolomics-the link between genotypes and phenotypes[J]. Plant MolecularBiology,2002,48:155-171.
[19] German J B, Bauman D E, Burrin D G, et al. Metabolomics in the opening decade of the21stcentury: building the roads to individualized health[J]. The Journal of nutrition,2004,134(10):2729-2732.
[20]Sorbera LA, Martin L. Etilevodopa. Atiparkinsonian dopamine precursor [J]. Drugs Future,2001,26(3):219.
[21]Buey PC, CaseTJ, Tremor. Physiologic mechanism and abolition by surgical means[J]. ArehNeurol Psyehiatry,1939,41:721-746.
[22]Meyers R. Surgical experiments in the therapy of certain extrapyramidal diseases: a currentevaluation[J]. Acta Neurol,1951,67:7-42.
[23]Laitinen LV, Bergenheim AT, Hariz Ml, Leksell’s posteroventral pallidotomy in the treatmentof Parkinson disease[J]. J.Neurosurg,1992,76:53-61.
[24]Benebid AL, Caparros-Lefebvre D, Pollak P, History of surgery for movementdisorders[M].1998,PP:19-36.
[25]Speelman JD, Bosch DA, Resurgence of functional neurosurgery for Parkinson’s disease: ahistorical perspective[J]. Mov.Disord,1998,13:582-588.
[26]Kelly PJ, Ahlskog JE, Goerss SJ, et al. Computer-assisted stereotactic ventralis lateralisthalamotomy with microelectrode recording control in patients with Parkinson’s disease[J].Mayo Clin Proc,1987,62:655-664.
[27]Narabayashi H, Surgical Approach to tremor. In: Marsden CD, ed. Neurology2: movementdisorders[J]. ondon: Butterworth,1982.
[28]Narabayashi H, Yokochi F, Nakajima Y. Levodopainduced dyskinesia and thalamotomy[J]. JNeurol Neurosurg Psyehiatry,1984,47:831-839.
[29]Selby G. Stereotactic surgery for the relief of Parkinson’s disease, A critical review[J]. JNeurol Sci,1967,5:315-342.
[30]Vitek JL, Bakay RA, Freeman A, et al. Randomized trial of pallidotomy versus Medical thetherapy for Parkinson’s disease[J].Ann Neurol,2003,53:558-569.
[31]De Bie RM, Schuurman PR, Esselink RA, et al. Bilateral pallidotomy in Parkinson’s disease:a retrospective study[J]. Mov Disord,2002,17:533-538.
[32]Su PC, Tseng HM, Liu HM, et al. Treatment of advanced Parkinson’s disease bysubthalamotomy: one-year results[J]. Mov Disord,2003,18:531-538.
[33]Hengqing Tong, Jing Tang, Hui Peng, et al. Heart Pacemaker Wear Life Model forPsychological Health Based on Frequent Properties[C]//2008The2nd InternationalConference on Volume, Issue: Bioinformatics and Biomedical Engineering,2008:596~599.
[34]SPeelman JD. Parkinson’s disease and stereotaxic surgery[M]. Amsterdam: Elsevier SciencePublishers,1991.
[35]Matsumoto K, Asano T, Baba T, et al. Long-term follow-up results of bilateral Thalamotomyfor Parinsonism[J]. Appl Neurophysiol,1976,39:257-260.
[36]De Bie RM, De Haan RJ, Nijssen PC, et al. Unilateral pallidotomy in Parkinson’s disease: arandomised, single-blind, multicentre trial[J]. Lancet,1999,354:1665-1669.
[37]Favre J, Burchiel KJ, Taha JM, et al. Outcome of unilateral and bilateral pallidotomy forParkinson’s disease: patient assessment[J]. Neurosurgery,2000,46:344-353.
[38]Alvarez L, Maeias R, Guriidi J, et al. Dorsal subthalamotomy for Parkinson’s disease[J].MovDisord,2001,16:72-78.
[39]VIDAL J, GHOVANLOO M. Towards a Switched-Capacitor based Stimulator for efficientdeep-brain stimulation[C]//Conference proceedings: Annual International,2010,2010:2927-2930
[40]Valente V, Demosthenous A, Bayford R. Design of a current-steering implantable stimulatorwith electric field shifting for deep brain stimulation[C]//Biomedical Circuits and SystemsConference (BioCAS),2010IEEE. IEEE,2010:162-165.
[41]WM G, WEI X-f. High efficiency electrodes for deep brain stimulation[C]//Conferenceproceedings: Annual International,2009,2009:3298-3301
[42]曹玉珍，刘洪涛，陈敏．可充电的植入式脑深部刺激器及其低功耗设计[J]．电子技术应用，2005，31（2）：37-39.
[43]郝红伟，李路明，马伯志，等．一种可编程植入式神经刺激系统[J]．航天医学与医学工程，2008，21（2）：147-151.
[44]Yazicioglu R F, Merken P, Puers R, et al. A200μW eight-channel acquisition ASIC forambulatory EEG systems[J]. IEEE JSSC,2008,43(12):3025-3038.
[45]Yazicioglu R F, Merken P, Puers R, et al. Low-power low-noise8-channel EEG front-endASIC for ambulatory acquisition systems[C]//Solid-State Circuits Conference,2006.ESSCIRC2006. Proceedings of the32nd European. IEEE,2006:247-250.
[46]Yates D, Lopez-Morillo E, Carvajal R G, et al. A low-voltage low-power front-end forwearable EEG systems[C]//Engineering in Medicine and Biology Society,2007. EMBS2007.29th Annual International Conference of the IEEE. IEEE,2007:5282-5285.
[47]Engin M, Dalbast T, Güldüren M, et al. A prototype portable system for EEGmeasurements[J]. Measurement,2007,40(9):936-942.
[48]Warlar R. Integer Coefficient Bandpass Filter for the Simultaneous Removal of baselinewander50Hz and100Hz interference from the ECG[J]. Med.&Biol., Eng.&Comp.,1991,29(3):333-336.
[49]孙京霞，白延强，杨玉星．一种抑制心电信号50Hz工频干扰的改进Levkov方法[J]．航天医学与医学工程，2000，13(3)：196-199.
[50]Li Gang, et al. A new adaptive coherent model algorithm for removal of power lineinterference[J]. Clin.Engin.,1995,20(5):147-150.
[51]纪跃波，秦树人，唐宝平．零相位数字滤波器[J]．重庆大学学报，2000，23(6)：4-7.
[52]Kaur M, Arora A S. Combination Method for Powerline Interference Reduction in ECG[J].International Journal of Computer Applications,2010,1(14):10-16.
[53]罗小刚，彭承琳．基于小波变换与形态学运算的ECG综合检测算法的研究[J]．生物医学工程学杂志，2004，21(5)：788-790.
[54]杜晓燕，李颖洁，朱贻盛，等．脑电信号伪迹去除的研究进展[J]．生物医学工程学杂志，2008，25（2）：464-467.
[55]Romero S, Ma anas M A, Barbanoj M J. Ocular reduction in EEG signals based on adaptivefiltering, regression and blind source separation[J]. Annals of biomedical engineering,2009,37(1):176-191.
[56]Sadasivan P K, Dutt D N. SVD based technique for noise reduction inelectroencephalographic signals[J]. Signal Processing,1996,55(2):179-189.
[57]Vigário R N. Extraction of ocular artefacts from EEG using independent componentanalysis[J]. Electroencephalography and clinical neurophysiology,1997,103(3):395-404.
[58]Joyce C A, Gorodnitsky I F, Kutas M. Automatic removal of eye movement and blink artifactsfrom EEG data using blind component separation[J]. Psychophysiology,2004,41(2):313-325.
[59]Berg P, Scherg M. A multiple source approach to the correction of eye artifacts[J].Electroencephalography and clinical neurophysiology,1994,90(3):229-241.
[60]Davila C E, Mobin M S. Weighted averaging of evoked potentials[J]. Biomedical Engineering,IEEE Transactions on,1992,39(4):338-345.
[61]Bezerianos A, Laskaris N, Fotopoulos S, et al. Data dependent weighted averages forrecording of evoked potential signals[J]. Electroencephalography and ClinicalNeurophysiology/Evoked Potentials Section,1995,96(5):468-471.
[62]王永轩，邱天爽，刘蓉．基于虚拟通道ICA方法的诱发电位单导少次提取[J]．中国生物医学工程学报，2012.
[63]Hyv rinen A, Oja E. Independent component analysis: algorithms and applications[J]. Neuralnetworks,2000,13(4):411-430.
[64]Zou L, Zhang Y, Yang L T, et al. Single-trial evoked potentials study by combining waveletdenoising and principal component analysis methods[J]. Journal of Clinical Neurophysiology,2010,27(1):17-24.
[65]Hu L, Zhang Z G, Hung Y S, et al. Single-trial detection of somatosensory evoked potentialsby probabilistic independent component analysis and wavelet filtering[J]. ClinicalNeurophysiology,2011,122(7):1429-1439.
[66]Casta eda-Villa N, James C J. Independent component analysis for auditory evoked potentialsand cochlear implant artifact estimation[J]. Biomedical Engineering, IEEE Transactions on,2011,58(2):348-354.
[67]师黎，钟丽辉，王端．基于虚拟通道ICA-WT大鼠视觉诱发电位少次提取［J］．中国生物医学工程学报，2010，29(3):379-383.
[68]李洪，孙云莲．基于EMD虚拟通道的ICA算法在信号消噪中的应用［J］．中国生物医学工程学报，2007，30(5)：33-36.
[69]季忠，金涛，杨炯明，等．虚拟噪声通道在基于ICA消噪过程中的应用［J］．中国机械工程，2005，16(4)：350-364.
[70]刘钦团，邱飞岳，李浩君．基于虚拟通道的ICA的P-VEP提取方法的研究［J］．计算机工程与科学，2010，32(7)：137-139.
[71]段新昱，林家瑞，司海芹．ECG监视过程中的消噪问题[J]．国外医学生物学工程分册，1992，15（3）：131-138.
[72]克雷奇，克拉菲尔德等著，周先庚等译．心理学纲要[M]．北京：文化教育出版社，1980.
[73]Jimei Ma, et al.Transcutaneous Energy and Information Transmission System With OptimizedTransformer Parameters for the Artificial Heart[J]. IEEE Trans. Applied Superconductivity2010,20(3):798-801.
[74]Ada S. Y. Poon, et al.Optimal Frequency for Wireless Power Transmission Into DispersiveTissue[J]. IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION,2010,58(5):1739-1750.
[75]Kenji Shiba, Akira Morimasa and Harutoyo Hirano.Design and Development of Low-LossTransformer for Powering Small Implantable Medical Devices[J]. IEEE TRANSACTIONSON BIOMEDICAL CIRCUITS AND SYSTEMS,2010,4(2):77-85.
[76]李刚，于超，林凌．微功耗深部脑刺激器刺激输出模块的设计及实现[J]．仪器仪表学报，2008，29（7）：1418-1421
[77]Hidekazu Miura, et al. Improvement of the Transcutaneous Energy Transmission SystemUtilizing Ferrite Cored Coils for Artificial Hearts [J]. IEEE Transactions on MAGNETICS,2006，42(10):3578-3580.
[78]Pernia AM, Orille IC, Martinez JA, et al.Transcutaneous microvalve activation system using acoreless transformer[J].Sensors and Actuators A-Physical,2007,136(1):313-320.
[79]陈海燕，高晓琳，杨庆新，等．用于人心脏的经皮传能系统耦合特性及补偿的研究[J]．电工电能新技术，2008，27(2)．
[80]ROSELL J,COLOMINAS J,PERERI U, et al. Skinimpedance from1Hz to1MHz[J].IEEETransactionson Biomedical Engineering,1998,35(8):649-652
[81]Xun Liu, S Y Hui. Simulation Study and Experimental Verification of a Universal ContactlessBattery Charging Platform With Localized Charging Features[J]. IEEE TRANSACTIONS ONPOWER ELECTRONICS2007,22(6):2202-2207.
[82]洪玮．ECG波形分类算法研究[D]．浙江大学，2001.
[83]曹细武，邓亲恺．心电图各波的频率分析[J]．中国医学物理学杂志，2001，18（1）：46-48.
[84]行鸿彦，黄敏松．心电信号特征点提取的算法研究[J]．仪器仪表学报，2008(11)：2362-2366.
[85]Madias J E. A comparison of2-lead,6-lead, and12-lead ECGs in patients with changingedematous states-Implications for the employment of quantitative electrocardiography inresearch and clinical applications[J]. Chest,2003,124(6):2057-2063.
[86]Roberto A, Chiara R, Abbatecola A M, et al. Validation of the3-lead tele-ECG versus the12-lead tele-ECG and the conventional12-lead ECG method in older people[J]. Journal ofTelemedicine and Telecare,2012,18(2):104-108.
[87]王保华．生物医学测量与仪器[M]．上海：复旦大学出版社，2009.
[88]姜健康．医学电信号的提取和处理[J]，信息与电脑，2012，5：160-161.
[89]Sobakin M A, Smirnov I P, Mishin L N. Electrogastrography[J]. Bio-Medical Electronics, IRETransactions on,1962,9(2),129-132.
[90]D Komorowski, S Pietraszek. The Noise Influence on Determination Dominant Frequenciesof EGG Signal[C]//31st Annual International Conference of the IEEE EMBS Minneapolis,Minnesota, USA,2009.
[91]龚严冰，高上凯．胃电研究的进展和前景[J]．北京生物医学工程，2001，20(3)：221-224.
[92]李刚，张旭．生物医学电子学[M]．北京：电子工业出版社，2008.
[93]陈真诚，钟靖.脑电信号采集预处理电路设计[J].中国医学物理学杂志，2009，26(4)：1299-1301，1305.
[94]戴立军．基于DSP和FPGA的数控系统研究与开发[D]．南京航空航天大学，2008.
[95]高晋占．微弱信号检测[M]．北京：清华大学出版社，2011.
[96]朱欣华，邹丽欣，朱桂荣．智能仪器与设计[M]．北京：高等教育出版社，2011.
[97]何峰．胃电检测方法的研究及相关数据分析[D]．天津：天津大学，2008.
[98]AD7760的技术资料.
[99]Saeid Sanei, J A Chambers. EEG signal processing[M]. England: John Wiley&Sons Ltd,2007.
[100]张新刚，王泽忠．基于过采样技术提高数据采集精度的新方法[J]．电力系统自动化，2004，28(14)：58-62.
[101]党淑雯．光纤陀螺的信号分析及滤波技术研究[D]．上海交通大学，2010.
[102]张俊华，张伟，蒲中奇．过采样系统中数据抽取的设计及实现[J]．国外电子测量技术，2005，24(4)：34-37.
[103]Hamilton J L, Micheli-Tzanakou E, Lehman R. Analysis of electrophysiological data insurgical treatment for Parkinson's disease [C]//Bioengineering Conference, Proceedings ofthe IEEE24th Annual Northeast,1998.
[104]吴晓爽．基于FPGA的数字锁相检测系统[D]．天津大学，2010.
[105]Mcintyre C C, Savasta M M, Walter B B, et al. How does deep brain stimulation work?Present understanding and future questions[J]. Journal of Clinical Neurophysiology,2004,21(1):40-50.
[106]Katja A, Makela J P, Samu T, et al. effects of DBS on auditory and somatosensory processingin parkinson's disease[J]. human brain mapping,2011,32(7):1091-1099.
[107]Okun M S, Foote K D. parkinson's disease DBS: what, when, who and why? the time hascome to tailor DBS targets[J]. expert review of neurotherapeutics,2010,10(12):1847-1857.
[108]Joseph F, Anthony D. impact of STN-DBS on life and health satisfaction in patients withparkinson's disease[J]. journal of neurology neurosurgery and psychiatry,2010,81(3):315-319.
[109]Baiamonte, Valentina. deep brain stimulation of pedunculopontine tegmental nucleus: role insleep modulation in advanced parkinson disease patients-one-year follow-up[J]. sleep,2012,35(12):1637-1642.
[110]Paxinos G, Watson C. The Rat Brain in Stereotactic Coordinates[Z]. Second Edition ed. USA:San Diego, Academic Press,1998,36.
[111]Hamilton J L, Micheli-Tzanakou E, Lehman R. Analysis of electrophysiological data insurgical treatment for Parkinson's disease [J]. Bioengineering Conference, Proceedings of theIEEE24th Annual Northeast,1998:5-6.
[112]李刚，刘巍，虞启琏，等．抑止工频干扰的及基线漂移的快速算法[J]．中国生物医学工程学报，2000，19(1)：99-103.
[113]堪雅琴，李刚，叶文宇，等．自适应相干模板法在心电图机中应用的一种改进算法[J]．信号处理，2002，18(3)：244-248.
[114]Shi Li-hong, Luo Fei, Woodward D J, et al. Basal ganglia neural responses duringbehaviorally effective deep brain stimulation of the subthalamic nucleus in rats performing atreadmill locomotion test[J]. Synapse,2006,59(7):445-457.
[115]Chang Jing-yu, Shi Li-hong, Luo Fei, et al. Studies of the neural mechanisms of deep brainstimulation in rodent models of Parkinson’s disease[J]. neuroscience and biobehavioralreviews,2007,31(5):643-657.
[116]Kent AR, Grill WM. recording evoked potentials during deep brain stimulation: developmentand validation of instrumentation to suppress the stimulus artifact[J]. Journal of neuralengineering,2012,9(3):036004.
[117]Rossi L, Bracchi F. an electronic device for artefact suppression in human local fieldpotential recordings during deep brain stimulation[J]. journal of neural engineering,2007,4(2):96-106
[118]AL-ANI T, CAZETTES F, PALFI S. Automatic removal of high-amplitude stimulus artefactfrom neuronal signal recorded in the subthalamic nucleus[J]. Journal of NeuroscienceMethods,2011,198(1):135-146.
[119]Hashimoto T, Elder CM, Vitek JL. a template subtraction method for stimulus artifactremoval in high-frequency deep brain stimulation[J]. journal of neuroscience methods,2002,113(2):181-186.
[120]Jung Tzyy-ping, Makeig Scott, Humphries Colin, et al. Removing electroencephalographicartifacts by blindsource separation [J]. Psychophysiology,2000,37(2):163-178.
[121]NAM Yunjun, ZHAO Qibin, CICHOCKI Andrzej, et al. A tongue-machine interface:Detection of tongue positions by glossokinetic potentials[C]//Sydney:17th InternationalConference on Neural Information Processing,2010:34-41.
[122]刘铁军．脑电信号中眼电伪迹去除方法研究[D]．电子科技大学，2008.
[123]Romero S, Mananas M A, Barbanoj M J. Ocular reduction in EEG signals based on adaptivefiltering，regression and blind source separation[J]. Annals of Biomedical Engineering,2009,37(1):176-191.
[124]韦明，杨辉，孙晓，等．两种去除脑电信号中眼动伪迹的方法比较及其在脑力疲劳测量中的应用[J]．航天医学与医学工程，2012（1）:50-53.
[125]吴小培，冯焕清，周荷琴，等．基于小波变换的脑电信号噪声消除方法[J]．电路与系统学报，2000，5（3）：96-98.
[126]计瑜，沈继忠，施锦河．一种基于盲源分离的眼电伪迹自动去除方法[J]．浙江大学学报(工学版)，2013，47：1-8.
[127]Whitham E M, Pope K J, Fitzgibbon S P, et al. Scalp electrical recording during paralysis:quantitative evidence that EEG frequencies above20Hz are contaminated by EMG[J].Clinical Neurophysiology,2007,118(8):1877-1888.
[128]黄磊，刘郁林，罗羽慧，等．基于高阶累积量算法的脑电信号中心电伪迹的消除[J]．中国医学物理学杂志，2006，23(4)：302-304.
[129]高莉，黄力宇，丁翠玲．结合PCA和ICA的脑磁信号消噪研究[J]．西安电子科技大学学报，2007，34(6)：939-943.
[130]万柏坤，朱欣，杨春梅，等．ICA去除EEG中眼动伪差和工频干扰方法研究[J]．电子学报，2003，31（10）：1571-1574.
[131]Emre Cek M, Ozgoren Murat, Acar Savaci F. Continuous time wavelet entropy of auditoryevoked potentials [J]. Computers in Biology and Medicine,2010,40(1):90-96.
[132]Harris Arief R, Schwerdtfeger Karsten, Strauss Daniel J. Adapted filter banks for featureextraction in transcranial magnetic stimulation evoked responses[J]. Medical and BiologicalEngineering and Computing,2011,49(2):221-231.
[133]Merzagora, Anna C, Bracchi, et al. Evaluation and application of a RBF neural network foronline single-sweep extraction of SEPs during scoliosis surgery[J]. IEEE Transactions onBiomedical Engineering,2007,54(7):1300-1308.
[134]Lin Bor-Shyh, Lin Bor-Shing, Chong Fok-Ching, et al. Higher order statistics-based RadialBasis Function Network for evoked potentials [J]. IEEE Transactions on BiomedicalEngineering,2009,56(1):93-100.
[135]Qiu W, Chang C, Liu W, et al. Real-time data-reusing adaptive learning of a radial basisfunction network for tracking evoked potentials[J]. Biomedical Engineering, IEEETransactions on,2006,53(2):226-237.
[136]C A Vaz, N V Thakor. Adaptive Fourier estimation of time-varying evoked potentials[J],IEEE Trans. Biomed. Eng.,1989,36:448-455.
[137]W Qiu, F H Y Chan, F K Lam,et al. Brainstem auditory evoked potential measurement usingadaptive signal enhancement [J], Australasian Phys. Eng. Sci. in Med.,1994,17(3):131-135.
[138]P Laguna, R Jane, O Meste,et al. Adaptive filter for event-related bioelectric signals using animpulse correlated reference input: Comparison with signal averaging techniques [J]. IEEETrans. Biomed. Eng.,1992,39:1032-1044.
[139]W Qiu, K S M. Fung, F H Y Chan,et al. Adaptive filtering of evoked potentials withradial-basis function neural network prefilter [J], IEEE Trans. Biomed. Eng.,2002,49(3):225-232.
[140]耿新玲．诱发电位非线性动态提取的研究[D]．天津医科大学，2002.
[141]孟彬．低频地波传播时延修正的季节效应研究[D]．西安理工大学，2009.
[142]田心等．婴儿痉挛症脑干信息传导障碍的混沌学研究[J]．生物物理学报，2001，17(1)：91-97.
[143]Sayers BM, Beagley HA, Henshall WR. The mechanism of auditory evoked EEGresponses[J]. Nature,1974,247:481-483.
[144]Makeig S, Westerfield M, Jung TP, et al. Dynamic brain sources of visual evokedresponses[J]. Seience,2002,29:690-694.
[145]Shigeto Nishida, Masatoshi Nakamura, Akio Ikeda, Hiroshi Shibasaki. Signal separation ofbackground EEG and spike by using morphological filter [J]. Medical Engineering&Physics.1999,21(9):601-608.
[146]赵春晖,孙圣和．一种形态开、闭自适应加权组合滤波器[J]．电子学报，1997，25(6)：109-111.
[147]Unser M, Aldroubi A. A review of wavelets in biomedical applications[J]. Proceedings of theIEEE,1996,84(4):626-638.
[148]W Sweldens. The Lifting Scheme: A new Philosophy in Biorthogonal Wavelet Construction[J]. Wavelet Applied Signal and Image Processing,1995, Proc. SPIE2569:68-79.
[149]孙轶．基于自适应提升小波的信号去噪技术研究[D]．中国科学技术大学，2008
[150]党淑雯．光纤陀螺的信号分析及滤波技术研究[D]．上海交通大学，2010
[151]高广春，熊凯，赵胜颖，等．自适应小波变换更新滤波器的优化研究[J]．电路与系统学报，2011，16(3)：81-86.
[152]刘海龙，唐奇伶．人工神经网络预滤波的自适应运动心电信号增强器[J]．生物医学工程学杂志，2006，23(5)：1118-1122.
[153]Cyril Dejean, Brian Hyland, Gordon Arbuthnott. Cortical Effects of Subthalamic StimulationCorrelate with Behavioral Recovery from Dopamine Antagonist Induced Akinesia[J].Cerebral Cortex,2009,19:1055-1063.
[154]Zouridakis G, Jansen BH, Boutros NN. A fuzzy clustering approach to EP Estimation[J].IEEE Trans Biomed Eng,1997,44(8):673-680.
[155]Makeig S, Bell AJ, Jung TP, et al. Independent component analysis ofelectroencephalographic data[J]. Adv Neural Inform Proc Syst,1996,8:145-151.
[156]万柏坤，朱欣，杨春梅，高扬．ICA去除EEG中眼动伪差和工频干扰方法研究[J]．电子学报，2003，31(10)：1571-1574
[157]Moghavvemi M, Mehrkanoon S. Detection of the onset of epileptic seizure signal from scalpEEG using blind signal separation[J]. Biomedical Engineering,2009,21(4):287-290.
[158]邹凌，王新光，马正华．基于独立分量分析提取仿真脑电诱发电位信号[J]．中国组织工程研究与临床康复，2009，13(17)：3265-3267.
[159]罗志增，曹铭．基于最大信噪比盲源分离的脑电信号伪迹滤波算法[J]．电子学报，2011，32(12)：2926-2931.
[160]Lewicki M S, Sejnowski TJ.Learning overcomplete representations[J]. Neural Computation,2000,12(2):337-365.
[161]Theis F J, Lang E W, Westenhuber T, et al. Overcomplete ICA with a geometric algorithm[J].Artificial Neural Networks,2002,2415:1049-1054.
[162]Li Y, Cichocki A, Amari S. Sparse component analysis for blind source separation with lesssensors than source[C]. Proceeding of ICA,2003:89-94.
[163]李志农，吕亚平，范涛，等．基于经验模态分解的机械故障欠定盲源分离方法[J]．航空动力学报，2009，24(8)：1886-1892.
[164]刘佳，杨士莪，朴胜春．基于EEMD的地声信号单通道盲源分离算法[J]．哈尔滨工程大学学报，2011，32(2)：194-199.
[165]Heraut J, Jutten C. Space or time adaptive signal processing by neural network model[J].Neural networks for computing: AIP conf. Processing151, New York: American Institutefor physics,1986:13-16.
[166]Jutten C, Herault J.Blind separation of source, Part I: An adaptive algorithm based onneuromimatic architecture [J]. Signal Processing,1991,24(1):1-10.
[167]Sorouchyari E. Blind separation of source, Part III: Stability Analysis [J]. Signal Processing,1991,24(1):21-29.
[168]Comom P. Blind separation of source, Part II: Problem statement[J]. Signal Processing,1991,24(1):11~20.
[169]Tong L, Liu R, Soon VC, et al. Indeterminacy and identifiability of blind identification[J].IEEE Trans Signal Processing,1991,38(5):499~509.
[170]P. Comon, et al. Independent Component Analysis. A new concept[J]. Signal Processing,1994,36(3):287~314.
[171]Matsuoka K, Kawamoto M, Ohya M, et al. A neural net for blind separation of nonstationarysignals[J]. Neural Network,1995,8(3):411-419.
[172]Zhang Wei-tao, Liu Ning, Lou Shun-tian. Joint Approximate Diagonalization Using BilateralRank-Reducing Householder Transform with Application in Blind Source Separation[J].Chinese Journa1of Electronics,2009,18(3):471-476.
[173]陈晓军，成昊，唐斌．基于ICA的雷达信号欠定盲分离算法[J]．电子与信息学报，2010，32(4)：919-924.
[174]刘霖雯，刘超，江成顺.EMD新算法及其应用[J]．系统仿真学报，2007，19(2)：446-447，464.
[175]白石岩，苟正品，张榆锋，等．基于经验模态分解自适应滤波的胎儿心电信号提取[J]．生物医学工程与临床，2010，14（1）：5-9.
[176]姚志湘，刘焕彬，粟晖．盲信号分离输出与源信号的一致性判断[J]．华南理工大学学报，2007，35(5)：50-53..
[2]Dauer W, Predborski S. Parkinson’s disease:mechanisms and models[J]. Ncuron,2003,39:889-909.
[3]Andersen JK. Does neuronal loss in Parkinson’s disease involve programmed cell death[J].Bioessays,2001,23(7):640~646.
[4]陈慧梅．代谢组学及其研究方法和应用[J]．肾脏病与透析肾移植杂，2005，14(1)：59-64.
[5]卢芳，刘树民，杨婷婷．帕金森病的最新国内外研究进展[J]．中国老年学杂志，2009，29(9)：1171-1174.
[6]Allan L E, Petit G H, Brundin P. Cell transplantation in Parkinson's disease: problems andperspectives[J]. Current opinion in neurology,2010,23(4):426-432.
[7]Singleton A B, Farrer M J, Vincenzo B. The genetics of Parkinson's disease: Progress andtherapeutic implications[J]. Movement Disorders: Official Journal of the Movem,2013,28(1):14-23.
[8]Wakeman D R, Dodiya H B. Cell Transplantation and Gene Therapy in Parkinson's Disease[J].Mount Sinai Journal of Medicine,2011,78(1):126-158.
[9]Wang J, Xu Z, Fang H, et al. Gene expression profiling of MPP(+) treated MN9D ceHs:Amechanism of toxicity study[J]. Neurotoxicology,2007,28:979-987.
[10]Ascherio A, Chen H, Schwarzschild MA, et al. Caffeine postmenopausal estrogen and risk ofPD[J]. Neurology,2003,60:790.
[11]Benmoyal-Segal L, Soreq H. Gene-environment interactions in sporadic Parkinson’sdisease[J]. J Neurochem,2006,97:1740-1755.
[12]Lesage S, Brice A. Parkinson's disease: from monogenic forms to genetic susceptibilityfactors[J]. Human molecular genetics,2009,18(R1): R48-R59.
[13]许继平，李玉莲，蔺薪英，等．帕金森病患者血液抗氧化功能的变化及多巴制剂与VitE对其影响的研究[J]．中风与神经疾病杂志，2000，17(1)：46-48.
[14]Kickler N, Lacombe E, Chassain C, et al. Assessment of metabolic changes in the striatum ofa rat model of parkinsonism: An in vivo1H MRS study[J]. NMR in Biomedicine,2009,22:207-212.
[15]Kanaan NM, Kordower JH, Collier TJ. Age and region-specific responses of microglia, butnot astrocytes, suggest a role in selective vulnerability of dopamine neurons after1-methyl-4-phenyl-1,2,3,6-tetrahy-dropyridine exposure in monkeys[J]. Glia,2008,56:1199-1214.
[16]吴浩翔，刘玉玲．帕金森病治疗药物研究进展[J]．中国药学杂志，2004，39（6）：409-412.
[17]卢明，雒晓东，张华．帕金森病治疗现状及中成药研制的机遇与挑战[J]．中国中医药信息杂志，2008，15(4)：4-5.
[18]Oliver Fiehn, Metabolomics-the link between genotypes and phenotypes[J]. Plant MolecularBiology,2002,48:155-171.
[19] German J B, Bauman D E, Burrin D G, et al. Metabolomics in the opening decade of the21stcentury: building the roads to individualized health[J]. The Journal of nutrition,2004,134(10):2729-2732.
[20]Sorbera LA, Martin L. Etilevodopa. Atiparkinsonian dopamine precursor [J]. Drugs Future,2001,26(3):219.
[21]Buey PC, CaseTJ, Tremor. Physiologic mechanism and abolition by surgical means[J]. ArehNeurol Psyehiatry,1939,41:721-746.
[22]Meyers R. Surgical experiments in the therapy of certain extrapyramidal diseases: a currentevaluation[J]. Acta Neurol,1951,67:7-42.
[23]Laitinen LV, Bergenheim AT, Hariz Ml, Leksell’s posteroventral pallidotomy in the treatmentof Parkinson disease[J]. J.Neurosurg,1992,76:53-61.
[24]Benebid AL, Caparros-Lefebvre D, Pollak P, History of surgery for movementdisorders[M].1998,PP:19-36.
[25]Speelman JD, Bosch DA, Resurgence of functional neurosurgery for Parkinson’s disease: ahistorical perspective[J]. Mov.Disord,1998,13:582-588.
[26]Kelly PJ, Ahlskog JE, Goerss SJ, et al. Computer-assisted stereotactic ventralis lateralisthalamotomy with microelectrode recording control in patients with Parkinson’s disease[J].Mayo Clin Proc,1987,62:655-664.
[27]Narabayashi H, Surgical Approach to tremor. In: Marsden CD, ed. Neurology2: movementdisorders[J]. ondon: Butterworth,1982.
[28]Narabayashi H, Yokochi F, Nakajima Y. Levodopainduced dyskinesia and thalamotomy[J]. JNeurol Neurosurg Psyehiatry,1984,47:831-839.
[29]Selby G. Stereotactic surgery for the relief of Parkinson’s disease, A critical review[J]. JNeurol Sci,1967,5:315-342.
[30]Vitek JL, Bakay RA, Freeman A, et al. Randomized trial of pallidotomy versus Medical thetherapy for Parkinson’s disease[J].Ann Neurol,2003,53:558-569.
[31]De Bie RM, Schuurman PR, Esselink RA, et al. Bilateral pallidotomy in Parkinson’s disease:a retrospective study[J]. Mov Disord,2002,17:533-538.
[32]Su PC, Tseng HM, Liu HM, et al. Treatment of advanced Parkinson’s disease bysubthalamotomy: one-year results[J]. Mov Disord,2003,18:531-538.
[33]Hengqing Tong, Jing Tang, Hui Peng, et al. Heart Pacemaker Wear Life Model forPsychological Health Based on Frequent Properties[C]//2008The2nd InternationalConference on Volume, Issue: Bioinformatics and Biomedical Engineering,2008:596~599.
[34]SPeelman JD. Parkinson’s disease and stereotaxic surgery[M]. Amsterdam: Elsevier SciencePublishers,1991.
[35]Matsumoto K, Asano T, Baba T, et al. Long-term follow-up results of bilateral Thalamotomyfor Parinsonism[J]. Appl Neurophysiol,1976,39:257-260.
[36]De Bie RM, De Haan RJ, Nijssen PC, et al. Unilateral pallidotomy in Parkinson’s disease: arandomised, single-blind, multicentre trial[J]. Lancet,1999,354:1665-1669.
[37]Favre J, Burchiel KJ, Taha JM, et al. Outcome of unilateral and bilateral pallidotomy forParkinson’s disease: patient assessment[J]. Neurosurgery,2000,46:344-353.
[38]Alvarez L, Maeias R, Guriidi J, et al. Dorsal subthalamotomy for Parkinson’s disease[J].MovDisord,2001,16:72-78.
[39]VIDAL J, GHOVANLOO M. Towards a Switched-Capacitor based Stimulator for efficientdeep-brain stimulation[C]//Conference proceedings: Annual International,2010,2010:2927-2930
[40]Valente V, Demosthenous A, Bayford R. Design of a current-steering implantable stimulatorwith electric field shifting for deep brain stimulation[C]//Biomedical Circuits and SystemsConference (BioCAS),2010IEEE. IEEE,2010:162-165.
[41]WM G, WEI X-f. High efficiency electrodes for deep brain stimulation[C]//Conferenceproceedings: Annual International,2009,2009:3298-3301
[42]曹玉珍，刘洪涛，陈敏．可充电的植入式脑深部刺激器及其低功耗设计[J]．电子技术应用，2005，31（2）：37-39.
[43]郝红伟，李路明，马伯志，等．一种可编程植入式神经刺激系统[J]．航天医学与医学工程，2008，21（2）：147-151.
[44]Yazicioglu R F, Merken P, Puers R, et al. A200μW eight-channel acquisition ASIC forambulatory EEG systems[J]. IEEE JSSC,2008,43(12):3025-3038.
[45]Yazicioglu R F, Merken P, Puers R, et al. Low-power low-noise8-channel EEG front-endASIC for ambulatory acquisition systems[C]//Solid-State Circuits Conference,2006.ESSCIRC2006. Proceedings of the32nd European. IEEE,2006:247-250.
[46]Yates D, Lopez-Morillo E, Carvajal R G, et al. A low-voltage low-power front-end forwearable EEG systems[C]//Engineering in Medicine and Biology Society,2007. EMBS2007.29th Annual International Conference of the IEEE. IEEE,2007:5282-5285.
[47]Engin M, Dalbast T, Güldüren M, et al. A prototype portable system for EEGmeasurements[J]. Measurement,2007,40(9):936-942.
[48]Warlar R. Integer Coefficient Bandpass Filter for the Simultaneous Removal of baselinewander50Hz and100Hz interference from the ECG[J]. Med.&Biol., Eng.&Comp.,1991,29(3):333-336.
[49]孙京霞，白延强，杨玉星．一种抑制心电信号50Hz工频干扰的改进Levkov方法[J]．航天医学与医学工程，2000，13(3)：196-199.
[50]Li Gang, et al. A new adaptive coherent model algorithm for removal of power lineinterference[J]. Clin.Engin.,1995,20(5):147-150.
[51]纪跃波，秦树人，唐宝平．零相位数字滤波器[J]．重庆大学学报，2000，23(6)：4-7.
[52]Kaur M, Arora A S. Combination Method for Powerline Interference Reduction in ECG[J].International Journal of Computer Applications,2010,1(14):10-16.
[53]罗小刚，彭承琳．基于小波变换与形态学运算的ECG综合检测算法的研究[J]．生物医学工程学杂志，2004，21(5)：788-790.
[54]杜晓燕，李颖洁，朱贻盛，等．脑电信号伪迹去除的研究进展[J]．生物医学工程学杂志，2008，25（2）：464-467.
[55]Romero S, Ma anas M A, Barbanoj M J. Ocular reduction in EEG signals based on adaptivefiltering, regression and blind source separation[J]. Annals of biomedical engineering,2009,37(1):176-191.
[56]Sadasivan P K, Dutt D N. SVD based technique for noise reduction inelectroencephalographic signals[J]. Signal Processing,1996,55(2):179-189.
[57]Vigário R N. Extraction of ocular artefacts from EEG using independent componentanalysis[J]. Electroencephalography and clinical neurophysiology,1997,103(3):395-404.
[58]Joyce C A, Gorodnitsky I F, Kutas M. Automatic removal of eye movement and blink artifactsfrom EEG data using blind component separation[J]. Psychophysiology,2004,41(2):313-325.
[59]Berg P, Scherg M. A multiple source approach to the correction of eye artifacts[J].Electroencephalography and clinical neurophysiology,1994,90(3):229-241.
[60]Davila C E, Mobin M S. Weighted averaging of evoked potentials[J]. Biomedical Engineering,IEEE Transactions on,1992,39(4):338-345.
[61]Bezerianos A, Laskaris N, Fotopoulos S, et al. Data dependent weighted averages forrecording of evoked potential signals[J]. Electroencephalography and ClinicalNeurophysiology/Evoked Potentials Section,1995,96(5):468-471.
[62]王永轩，邱天爽，刘蓉．基于虚拟通道ICA方法的诱发电位单导少次提取[J]．中国生物医学工程学报，2012.
[63]Hyv rinen A, Oja E. Independent component analysis: algorithms and applications[J]. Neuralnetworks,2000,13(4):411-430.
[64]Zou L, Zhang Y, Yang L T, et al. Single-trial evoked potentials study by combining waveletdenoising and principal component analysis methods[J]. Journal of Clinical Neurophysiology,2010,27(1):17-24.
[65]Hu L, Zhang Z G, Hung Y S, et al. Single-trial detection of somatosensory evoked potentialsby probabilistic independent component analysis and wavelet filtering[J]. ClinicalNeurophysiology,2011,122(7):1429-1439.
[66]Casta eda-Villa N, James C J. Independent component analysis for auditory evoked potentialsand cochlear implant artifact estimation[J]. Biomedical Engineering, IEEE Transactions on,2011,58(2):348-354.
[67]师黎，钟丽辉，王端．基于虚拟通道ICA-WT大鼠视觉诱发电位少次提取［J］．中国生物医学工程学报，2010，29(3):379-383.
[68]李洪，孙云莲．基于EMD虚拟通道的ICA算法在信号消噪中的应用［J］．中国生物医学工程学报，2007，30(5)：33-36.
[69]季忠，金涛，杨炯明，等．虚拟噪声通道在基于ICA消噪过程中的应用［J］．中国机械工程，2005，16(4)：350-364.
[70]刘钦团，邱飞岳，李浩君．基于虚拟通道的ICA的P-VEP提取方法的研究［J］．计算机工程与科学，2010，32(7)：137-139.
[71]段新昱，林家瑞，司海芹．ECG监视过程中的消噪问题[J]．国外医学生物学工程分册，1992，15（3）：131-138.
[72]克雷奇，克拉菲尔德等著，周先庚等译．心理学纲要[M]．北京：文化教育出版社，1980.
[73]Jimei Ma, et al.Transcutaneous Energy and Information Transmission System With OptimizedTransformer Parameters for the Artificial Heart[J]. IEEE Trans. Applied Superconductivity2010,20(3):798-801.
[74]Ada S. Y. Poon, et al.Optimal Frequency for Wireless Power Transmission Into DispersiveTissue[J]. IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION,2010,58(5):1739-1750.
[75]Kenji Shiba, Akira Morimasa and Harutoyo Hirano.Design and Development of Low-LossTransformer for Powering Small Implantable Medical Devices[J]. IEEE TRANSACTIONSON BIOMEDICAL CIRCUITS AND SYSTEMS,2010,4(2):77-85.
[76]李刚，于超，林凌．微功耗深部脑刺激器刺激输出模块的设计及实现[J]．仪器仪表学报，2008，29（7）：1418-1421
[77]Hidekazu Miura, et al. Improvement of the Transcutaneous Energy Transmission SystemUtilizing Ferrite Cored Coils for Artificial Hearts [J]. IEEE Transactions on MAGNETICS,2006，42(10):3578-3580.
[78]Pernia AM, Orille IC, Martinez JA, et al.Transcutaneous microvalve activation system using acoreless transformer[J].Sensors and Actuators A-Physical,2007,136(1):313-320.
[79]陈海燕，高晓琳，杨庆新，等．用于人心脏的经皮传能系统耦合特性及补偿的研究[J]．电工电能新技术，2008，27(2)．
[80]ROSELL J,COLOMINAS J,PERERI U, et al. Skinimpedance from1Hz to1MHz[J].IEEETransactionson Biomedical Engineering,1998,35(8):649-652
[81]Xun Liu, S Y Hui. Simulation Study and Experimental Verification of a Universal ContactlessBattery Charging Platform With Localized Charging Features[J]. IEEE TRANSACTIONS ONPOWER ELECTRONICS2007,22(6):2202-2207.
[82]洪玮．ECG波形分类算法研究[D]．浙江大学，2001.
[83]曹细武，邓亲恺．心电图各波的频率分析[J]．中国医学物理学杂志，2001，18（1）：46-48.
[84]行鸿彦，黄敏松．心电信号特征点提取的算法研究[J]．仪器仪表学报，2008(11)：2362-2366.
[85]Madias J E. A comparison of2-lead,6-lead, and12-lead ECGs in patients with changingedematous states-Implications for the employment of quantitative electrocardiography inresearch and clinical applications[J]. Chest,2003,124(6):2057-2063.
[86]Roberto A, Chiara R, Abbatecola A M, et al. Validation of the3-lead tele-ECG versus the12-lead tele-ECG and the conventional12-lead ECG method in older people[J]. Journal ofTelemedicine and Telecare,2012,18(2):104-108.
[87]王保华．生物医学测量与仪器[M]．上海：复旦大学出版社，2009.
[88]姜健康．医学电信号的提取和处理[J]，信息与电脑，2012，5：160-161.
[89]Sobakin M A, Smirnov I P, Mishin L N. Electrogastrography[J]. Bio-Medical Electronics, IRETransactions on,1962,9(2),129-132.
[90]D Komorowski, S Pietraszek. The Noise Influence on Determination Dominant Frequenciesof EGG Signal[C]//31st Annual International Conference of the IEEE EMBS Minneapolis,Minnesota, USA,2009.
[91]龚严冰，高上凯．胃电研究的进展和前景[J]．北京生物医学工程，2001，20(3)：221-224.
[92]李刚，张旭．生物医学电子学[M]．北京：电子工业出版社，2008.
[93]陈真诚，钟靖.脑电信号采集预处理电路设计[J].中国医学物理学杂志，2009，26(4)：1299-1301，1305.
[94]戴立军．基于DSP和FPGA的数控系统研究与开发[D]．南京航空航天大学，2008.
[95]高晋占．微弱信号检测[M]．北京：清华大学出版社，2011.
[96]朱欣华，邹丽欣，朱桂荣．智能仪器与设计[M]．北京：高等教育出版社，2011.
[97]何峰．胃电检测方法的研究及相关数据分析[D]．天津：天津大学，2008.
[98]AD7760的技术资料.
[99]Saeid Sanei, J A Chambers. EEG signal processing[M]. England: John Wiley&Sons Ltd,2007.
[100]张新刚，王泽忠．基于过采样技术提高数据采集精度的新方法[J]．电力系统自动化，2004，28(14)：58-62.
[101]党淑雯．光纤陀螺的信号分析及滤波技术研究[D]．上海交通大学，2010.
[102]张俊华，张伟，蒲中奇．过采样系统中数据抽取的设计及实现[J]．国外电子测量技术，2005，24(4)：34-37.
[103]Hamilton J L, Micheli-Tzanakou E, Lehman R. Analysis of electrophysiological data insurgical treatment for Parkinson's disease [C]//Bioengineering Conference, Proceedings ofthe IEEE24th Annual Northeast,1998.
[104]吴晓爽．基于FPGA的数字锁相检测系统[D]．天津大学，2010.
[105]Mcintyre C C, Savasta M M, Walter B B, et al. How does deep brain stimulation work?Present understanding and future questions[J]. Journal of Clinical Neurophysiology,2004,21(1):40-50.
[106]Katja A, Makela J P, Samu T, et al. effects of DBS on auditory and somatosensory processingin parkinson's disease[J]. human brain mapping,2011,32(7):1091-1099.
[107]Okun M S, Foote K D. parkinson's disease DBS: what, when, who and why? the time hascome to tailor DBS targets[J]. expert review of neurotherapeutics,2010,10(12):1847-1857.
[108]Joseph F, Anthony D. impact of STN-DBS on life and health satisfaction in patients withparkinson's disease[J]. journal of neurology neurosurgery and psychiatry,2010,81(3):315-319.
[109]Baiamonte, Valentina. deep brain stimulation of pedunculopontine tegmental nucleus: role insleep modulation in advanced parkinson disease patients-one-year follow-up[J]. sleep,2012,35(12):1637-1642.
[110]Paxinos G, Watson C. The Rat Brain in Stereotactic Coordinates[Z]. Second Edition ed. USA:San Diego, Academic Press,1998,36.
[111]Hamilton J L, Micheli-Tzanakou E, Lehman R. Analysis of electrophysiological data insurgical treatment for Parkinson's disease [J]. Bioengineering Conference, Proceedings of theIEEE24th Annual Northeast,1998:5-6.
[112]李刚，刘巍，虞启琏，等．抑止工频干扰的及基线漂移的快速算法[J]．中国生物医学工程学报，2000，19(1)：99-103.
[113]堪雅琴，李刚，叶文宇，等．自适应相干模板法在心电图机中应用的一种改进算法[J]．信号处理，2002，18(3)：244-248.
[114]Shi Li-hong, Luo Fei, Woodward D J, et al. Basal ganglia neural responses duringbehaviorally effective deep brain stimulation of the subthalamic nucleus in rats performing atreadmill locomotion test[J]. Synapse,2006,59(7):445-457.
[115]Chang Jing-yu, Shi Li-hong, Luo Fei, et al. Studies of the neural mechanisms of deep brainstimulation in rodent models of Parkinson’s disease[J]. neuroscience and biobehavioralreviews,2007,31(5):643-657.
[116]Kent AR, Grill WM. recording evoked potentials during deep brain stimulation: developmentand validation of instrumentation to suppress the stimulus artifact[J]. Journal of neuralengineering,2012,9(3):036004.
[117]Rossi L, Bracchi F. an electronic device for artefact suppression in human local fieldpotential recordings during deep brain stimulation[J]. journal of neural engineering,2007,4(2):96-106
[118]AL-ANI T, CAZETTES F, PALFI S. Automatic removal of high-amplitude stimulus artefactfrom neuronal signal recorded in the subthalamic nucleus[J]. Journal of NeuroscienceMethods,2011,198(1):135-146.
[119]Hashimoto T, Elder CM, Vitek JL. a template subtraction method for stimulus artifactremoval in high-frequency deep brain stimulation[J]. journal of neuroscience methods,2002,113(2):181-186.
[120]Jung Tzyy-ping, Makeig Scott, Humphries Colin, et al. Removing electroencephalographicartifacts by blindsource separation [J]. Psychophysiology,2000,37(2):163-178.
[121]NAM Yunjun, ZHAO Qibin, CICHOCKI Andrzej, et al. A tongue-machine interface:Detection of tongue positions by glossokinetic potentials[C]//Sydney:17th InternationalConference on Neural Information Processing,2010:34-41.
[122]刘铁军．脑电信号中眼电伪迹去除方法研究[D]．电子科技大学，2008.
[123]Romero S, Mananas M A, Barbanoj M J. Ocular reduction in EEG signals based on adaptivefiltering，regression and blind source separation[J]. Annals of Biomedical Engineering,2009,37(1):176-191.
[124]韦明，杨辉，孙晓，等．两种去除脑电信号中眼动伪迹的方法比较及其在脑力疲劳测量中的应用[J]．航天医学与医学工程，2012（1）:50-53.
[125]吴小培，冯焕清，周荷琴，等．基于小波变换的脑电信号噪声消除方法[J]．电路与系统学报，2000，5（3）：96-98.
[126]计瑜，沈继忠，施锦河．一种基于盲源分离的眼电伪迹自动去除方法[J]．浙江大学学报(工学版)，2013，47：1-8.
[127]Whitham E M, Pope K J, Fitzgibbon S P, et al. Scalp electrical recording during paralysis:quantitative evidence that EEG frequencies above20Hz are contaminated by EMG[J].Clinical Neurophysiology,2007,118(8):1877-1888.
[128]黄磊，刘郁林，罗羽慧，等．基于高阶累积量算法的脑电信号中心电伪迹的消除[J]．中国医学物理学杂志，2006，23(4)：302-304.
[129]高莉，黄力宇，丁翠玲．结合PCA和ICA的脑磁信号消噪研究[J]．西安电子科技大学学报，2007，34(6)：939-943.
[130]万柏坤，朱欣，杨春梅，等．ICA去除EEG中眼动伪差和工频干扰方法研究[J]．电子学报，2003，31（10）：1571-1574.
[131]Emre Cek M, Ozgoren Murat, Acar Savaci F. Continuous time wavelet entropy of auditoryevoked potentials [J]. Computers in Biology and Medicine,2010,40(1):90-96.
[132]Harris Arief R, Schwerdtfeger Karsten, Strauss Daniel J. Adapted filter banks for featureextraction in transcranial magnetic stimulation evoked responses[J]. Medical and BiologicalEngineering and Computing,2011,49(2):221-231.
[133]Merzagora, Anna C, Bracchi, et al. Evaluation and application of a RBF neural network foronline single-sweep extraction of SEPs during scoliosis surgery[J]. IEEE Transactions onBiomedical Engineering,2007,54(7):1300-1308.
[134]Lin Bor-Shyh, Lin Bor-Shing, Chong Fok-Ching, et al. Higher order statistics-based RadialBasis Function Network for evoked potentials [J]. IEEE Transactions on BiomedicalEngineering,2009,56(1):93-100.
[135]Qiu W, Chang C, Liu W, et al. Real-time data-reusing adaptive learning of a radial basisfunction network for tracking evoked potentials[J]. Biomedical Engineering, IEEETransactions on,2006,53(2):226-237.
[136]C A Vaz, N V Thakor. Adaptive Fourier estimation of time-varying evoked potentials[J],IEEE Trans. Biomed. Eng.,1989,36:448-455.
[137]W Qiu, F H Y Chan, F K Lam,et al. Brainstem auditory evoked potential measurement usingadaptive signal enhancement [J], Australasian Phys. Eng. Sci. in Med.,1994,17(3):131-135.
[138]P Laguna, R Jane, O Meste,et al. Adaptive filter for event-related bioelectric signals using animpulse correlated reference input: Comparison with signal averaging techniques [J]. IEEETrans. Biomed. Eng.,1992,39:1032-1044.
[139]W Qiu, K S M. Fung, F H Y Chan,et al. Adaptive filtering of evoked potentials withradial-basis function neural network prefilter [J], IEEE Trans. Biomed. Eng.,2002,49(3):225-232.
[140]耿新玲．诱发电位非线性动态提取的研究[D]．天津医科大学，2002.
[141]孟彬．低频地波传播时延修正的季节效应研究[D]．西安理工大学，2009.
[142]田心等．婴儿痉挛症脑干信息传导障碍的混沌学研究[J]．生物物理学报，2001，17(1)：91-97.
[143]Sayers BM, Beagley HA, Henshall WR. The mechanism of auditory evoked EEGresponses[J]. Nature,1974,247:481-483.
[144]Makeig S, Westerfield M, Jung TP, et al. Dynamic brain sources of visual evokedresponses[J]. Seience,2002,29:690-694.
[145]Shigeto Nishida, Masatoshi Nakamura, Akio Ikeda, Hiroshi Shibasaki. Signal separation ofbackground EEG and spike by using morphological filter [J]. Medical Engineering&Physics.1999,21(9):601-608.
[146]赵春晖,孙圣和．一种形态开、闭自适应加权组合滤波器[J]．电子学报，1997，25(6)：109-111.
[147]Unser M, Aldroubi A. A review of wavelets in biomedical applications[J]. Proceedings of theIEEE,1996,84(4):626-638.
[148]W Sweldens. The Lifting Scheme: A new Philosophy in Biorthogonal Wavelet Construction[J]. Wavelet Applied Signal and Image Processing,1995, Proc. SPIE2569:68-79.
[149]孙轶．基于自适应提升小波的信号去噪技术研究[D]．中国科学技术大学，2008
[150]党淑雯．光纤陀螺的信号分析及滤波技术研究[D]．上海交通大学，2010
[151]高广春，熊凯，赵胜颖，等．自适应小波变换更新滤波器的优化研究[J]．电路与系统学报，2011，16(3)：81-86.
[152]刘海龙，唐奇伶．人工神经网络预滤波的自适应运动心电信号增强器[J]．生物医学工程学杂志，2006，23(5)：1118-1122.
[153]Cyril Dejean, Brian Hyland, Gordon Arbuthnott. Cortical Effects of Subthalamic StimulationCorrelate with Behavioral Recovery from Dopamine Antagonist Induced Akinesia[J].Cerebral Cortex,2009,19:1055-1063.
[154]Zouridakis G, Jansen BH, Boutros NN. A fuzzy clustering approach to EP Estimation[J].IEEE Trans Biomed Eng,1997,44(8):673-680.
[155]Makeig S, Bell AJ, Jung TP, et al. Independent component analysis ofelectroencephalographic data[J]. Adv Neural Inform Proc Syst,1996,8:145-151.
[156]万柏坤，朱欣，杨春梅，高扬．ICA去除EEG中眼动伪差和工频干扰方法研究[J]．电子学报，2003，31(10)：1571-1574
[157]Moghavvemi M, Mehrkanoon S. Detection of the onset of epileptic seizure signal from scalpEEG using blind signal separation[J]. Biomedical Engineering,2009,21(4):287-290.
[158]邹凌，王新光，马正华．基于独立分量分析提取仿真脑电诱发电位信号[J]．中国组织工程研究与临床康复，2009，13(17)：3265-3267.
[159]罗志增，曹铭．基于最大信噪比盲源分离的脑电信号伪迹滤波算法[J]．电子学报，2011，32(12)：2926-2931.
[160]Lewicki M S, Sejnowski TJ.Learning overcomplete representations[J]. Neural Computation,2000,12(2):337-365.
[161]Theis F J, Lang E W, Westenhuber T, et al. Overcomplete ICA with a geometric algorithm[J].Artificial Neural Networks,2002,2415:1049-1054.
[162]Li Y, Cichocki A, Amari S. Sparse component analysis for blind source separation with lesssensors than source[C]. Proceeding of ICA,2003:89-94.
[163]李志农，吕亚平，范涛，等．基于经验模态分解的机械故障欠定盲源分离方法[J]．航空动力学报，2009，24(8)：1886-1892.
[164]刘佳，杨士莪，朴胜春．基于EEMD的地声信号单通道盲源分离算法[J]．哈尔滨工程大学学报，2011，32(2)：194-199.
[165]Heraut J, Jutten C. Space or time adaptive signal processing by neural network model[J].Neural networks for computing: AIP conf. Processing151, New York: American Institutefor physics,1986:13-16.
[166]Jutten C, Herault J.Blind separation of source, Part I: An adaptive algorithm based onneuromimatic architecture [J]. Signal Processing,1991,24(1):1-10.
[167]Sorouchyari E. Blind separation of source, Part III: Stability Analysis [J]. Signal Processing,1991,24(1):21-29.
[168]Comom P. Blind separation of source, Part II: Problem statement[J]. Signal Processing,1991,24(1):11~20.
[169]Tong L, Liu R, Soon VC, et al. Indeterminacy and identifiability of blind identification[J].IEEE Trans Signal Processing,1991,38(5):499~509.
[170]P. Comon, et al. Independent Component Analysis. A new concept[J]. Signal Processing,1994,36(3):287~314.
[171]Matsuoka K, Kawamoto M, Ohya M, et al. A neural net for blind separation of nonstationarysignals[J]. Neural Network,1995,8(3):411-419.
[172]Zhang Wei-tao, Liu Ning, Lou Shun-tian. Joint Approximate Diagonalization Using BilateralRank-Reducing Householder Transform with Application in Blind Source Separation[J].Chinese Journa1of Electronics,2009,18(3):471-476.
[173]陈晓军，成昊，唐斌．基于ICA的雷达信号欠定盲分离算法[J]．电子与信息学报，2010，32(4)：919-924.
[174]刘霖雯，刘超，江成顺.EMD新算法及其应用[J]．系统仿真学报，2007，19(2)：446-447，464.
[175]白石岩，苟正品，张榆锋，等．基于经验模态分解自适应滤波的胎儿心电信号提取[J]．生物医学工程与临床，2010，14（1）：5-9.
[176]姚志湘，刘焕彬，粟晖．盲信号分离输出与源信号的一致性判断[J]．华南理工大学学报，2007，35(5)：50-53..