CN102164537B - 用于去除神经记录的刺激伪迹 - Google Patents

用于去除神经记录的刺激伪迹 Download PDF

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CN102164537B
CN102164537B CN200980136641.7A CN200980136641A CN102164537B CN 102164537 B CN102164537 B CN 102164537B CN 200980136641 A CN200980136641 A CN 200980136641A CN 102164537 B CN102164537 B CN 102164537B
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action potential
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stimulus artifact
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斯特凡·施特拉尔
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MED EL Elektromedizinische Geraete GmbH
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
    • A61B5/4041—Evaluating nerves condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2134—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on separation criteria, e.g. independent component analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/02—Details
    • A61N1/04—Electrodes
    • A61N1/05—Electrodes for implantation or insertion into the body, e.g. heart electrode
    • A61N1/0526—Head electrodes
    • A61N1/0541—Cochlear electrodes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/36036—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation of the outer, middle or inner ear
    • A61N1/36038—Cochlear stimulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08—Feature extraction

Abstract

本发明描述了如下一种方法，用于对含有刺激伪迹和一个或多个神经动作电位的波形信号进行处理。电刺激信号基于与多个已知神经动作电位波形满足成本函数比较而被获取。

Description

用于去除神经记录的刺激伪迹
本申请请求享受申请日为2008年9月17日的美国临时专利申请61/097,611的优先权，其通过引用结合于此。
技术领域
本发明涉及一种医学植入物，更具体地涉及的是在耳蜗植入系统中的诊断测量。
背景技术
对由在附近施加的电刺激所引起的神经动作电位(NAP)的记录提供了含有两种主分量的信号混合体：(1)想要得到的NAP，和(2)施加的电刺激。从该混合体中去除掉无意记录得到的刺激波形(也被称为刺激伪迹(stimulus artifact))已经被证明是一项困难的任务。
各种技术已经被用于从诸如耳蜗植入物的神经假体装置中引起的合成动作电位(ECAP)的记录中消除或减少刺激伪迹。在交替刺激法中，使用阴极-阳极和阳极-阴极双相刺激脉冲执行两种记录。参见通过引用而合并于此的Eisen MD，Franck KH所著的Electrically EvokedCompound Action Potential Amplitude Growth Functions andHiResolution Programming Levels in Pediatric CII Implant Subjects，Ear& Hearing 2004，25(6)：528-538。NAP假定与第一相的极性无关，因此刺激伪迹可通过平均抵消。但交替刺激使测量时间产生不期望的增加。另外，对NAP不随相位变化的假定并不完全成立。
在掩蔽探测法(masker probe method)中，第二探测脉冲在神经元的不应时间(refractory time)内发出，这允许对刺激伪迹的模板进行测量。参见通过引用而结合于此的Brown C，Abbas P，Gantz B所著的Electrically Evoked Whole-Nerve Action Potentials：Data From HumanCochlear Implant Users，Journal of the Acoustical Society of America1990，88(3)：1385-1391，和Miller CA，Abbas PJ，Brown CJ所著的AnImproved Method Of Reducing Stimulus Artifact In The ElectricallyEvoked Whole-Nerve Potential，Ear & Hearing 2000，21(4)：280-290。与利用交替刺激一样，掩蔽探测法也需要使测量时间产生不期望的增加。此外，有些神经典型地不处于不应状态。
可施加三相脉冲，并且选出的第三相的幅度能使得引入的总电荷等于零。参见通过引用而结合于此的Zimmerling M所著的Messung deselektrisch evozierten Summenaktionspotentials des  bei Patientenmit einem Cochlea-Implantat，PhD thesis  Innsbruck，Institutfür Angewandte Physik，1999，和Schoesser H，Zierhofer C，Hochmair ES所著的Measuring Electrically Evoked Compound Action Potentials UsingTriphasic Pulses For The Reduction Of The Residual Stimulation Artefact，In Conference On Implantable Auditory Prostheses，2001。但是使用三相脉冲导致了触发NAP的刺激部分和记录开始之间存在增大的延迟。
另一种方法记录了次临界水平下对刺激的响应，以测量刺激伪迹的模板，其随后被按比例缩放到超临界水平，并从记录的信号混合体中减去。参见通过引用而结合于此的Miller CA，Abbas PJ，Rubinstein JT，Robinson B，Matsuoka A，Woodworth G所著的Electrically EvokedCompound Action Potentials Of Guinea Pig And Cat：Responses ToMonopolar，Monophasic Stimulation，Hearing Research 1998，119(1-2)：142-154。该方法的一个缺点是伪迹不是随着幅度的增加而线性按比例缩放。
发明内容
本发明的实施方式针对的是一种处理波形信号的方法，所述波形信号含有刺激伪迹和一个或多个神经动作电位。电刺激信号基于与多个已知神经动作电位波形满足成本函数比较(cost function comparison)而被获取。
神经动作电位可以是电引发的合成动作电位，例如为耳蜗植入物确定的电位值。成本函数可以基于刺激伪迹和神经动作电位波形之间的距离计算，例如，基于对距离计算取最大值。满足成本比较可以基于梯度下降程序(gradient descent procedure)来进行。
该方法可进一步包括对靶神经组织施加电刺激信号，测量靶组织的波形信号，并使用源分离算法(source separation algorithm)将刺激伪迹从所述波形信号去除，所述源分离算法留下的是剩余的神经动作电位信号。
附图说明
图1显示了在根据现有技术的标准程序中与ECAP相关的波形信号。
图2显示了根据本发明实施方式与ECAP相关的波形信号。
具体实施方式
本发明的各种实施方式针对的是对诸如耳蜗植入物的神经假体装置中电引发的合成动作电位(ECAP)信号进行处理，所述合成动作电位含有刺激伪迹分量和神经动作电位(NAP)分量。电刺激信号基于与多个已知神经动作电位波形满足成本函数比较而被获取。这允许即使在信噪比低的情况下也能改进对刺激伪迹的去除，例如，通过使用使输出的信噪比取最大值的匹配滤波器。与现有技术的标准波形信号处理技术相比，本方法的测量时间不增加。NAP的自动测量是有可能实现的，这是因为使用者无需手动设定参数，因此使用者无需具备任何专业技术知识。
在信号处理的背景下，从ECAP波形信号混合体中去除刺激伪迹被称为源分离问题。将来自某源A(刺激伪迹)的波形分量与另一源B(NAP)所致的波形分量进行鲁棒分离(robust separation)是困难的，因为两种源都缺乏足够的脱离特征。即，它们太相似了，以致于不能在给定的信噪条件下获得良好的信号分离性能。为了克服这个问题，本发明的实施方式改变了电刺激波形，从而使得从刺激伪迹和触发的NAP所得到的波形更相异。
图1描绘了在根据现有技术的标准程序中与ECAP相关的波形信号。刺激伪迹形成了指数式衰减的直流偏移。与之相比，图2显示了刺激伪迹波形怎样不同于NAP，在该种情况下，通过添加具有诸如极小值和极大值(及进而的频率分量)的新特征的振动而改进了源分离的性能。
最初，有两种场合下可以实施对新型刺激伪迹波形的获取。在第一实施方式中，一般波形是通过使用已有NAP波形数据库获取的先验数据。源A(刺激伪迹)的取样波形被定义为xA，源B(NAP)的另一种取样波形被定义为xB，它们是长度为N的向量，其中N是测量到的采样数。由于源分离算法的性能直接与xA和xB的距离相关，因此最佳的新型刺激伪迹波形可以是取该距离的最大值。
测量这样的距离的一种简便方式应该是欧几里得度量(Euclideanmetric)，因此新型刺激伪迹波形可通过取成本函数的最大值得到：
C＝sqrt((xA(1)+xB1(1))2+(xA(2)+xB1(2))2+...+(xA(N)+xB1(N))2)
+sqrt((xA(1)+xB2(1))2+(xA(2)+xB2(2))2+...+(xA(N)+xB2(N))2)
+...
+sqrt((xA(1)+xBM(1))2+(xA(2)+xBM(2))2+...+(xA(N)+xBM(N))2)
其中，xB1，...，xBM是来自数据库的现有已知NAP波形，xA是可能的刺激伪迹波形的向量，其将被最优化。这是标准最优化问题，其中，可应用诸如梯度下降搜索(gradient descent search)的算法。
在第二实施方式中，与患者有关的波形被动态地取得。刺激伪迹的波形是已知的，因此实际测量所达到的分离性能可被得到。测量以如上所述从波形取得的先验数据开始。使用诸如梯度下降搜索的标准最优化算法，刺激伪迹波形可被改变，以对实际测量到的波形信号而言为最优，从而实现对分离性能的改进。
注意到对xA和xB的额外后处理，比如基于主分量分析的降维(dimension reduction)可以进一步地改进波形获取的性能。还有一种更具体的度量，比如加权度量(weighted metric)，也可显示出进一步的改进。
在记录的波形信号混合体中快速识别源A可以通过，例如，使用匹配滤波器的方法来实现，该方法可以实现可实时操作的源分离系统。除了使用在最优化处理过程中保持不变的特定刺激波形之外，备选实施方式可使用次佳但不一样的刺激波。
本发明的实施方式可用任何常规的计算机编程语言实现。例如，优选实施方式可以用程序化编程语言(如“C”)或面对对象的编程语言(如“C++”，Python)实现。本发明的备选实施方式可作为预先编程的硬件元件、其他相关零件，或作为硬件和软件零件的组合来实现。
实施方式可作为用于计算机系统的计算机程序产品实现。这种实现方式可包括一系列计算机指令，其固设于诸如计算机可读介质(如软盘、光盘驱动器、只读存储器、或硬盘)的有形介质，或者经由调制解调器或诸如经介质而连接到网络的通讯适配器的其他接口设备而传输到计算机系统。介质可以是有形介质(例如，光纤或模拟通信线路)，也可以是通过无线技术(如微波、红外线或其他传输技术)实现的介质。这一系列的计算机指令涵盖了此处关于所述系统先前介绍过的所有或部分功能性。本领域技术人员应理解，所述的计算机指令可以以多种编程语言编写，以使其用于多种计算机体系结构或操作系统。更进一步说，所述指令可被存储在任何存储设备中，比如半导体、磁性、光学或其他存储设备，并可利用任何传输技术进行传输，比如光学、红外、微波或其他传输技术。希望的是，所述的计算机程序产品是作为可移动介质(removable medium)而发布的，其可以是打印的或电子的文档(例如，紧凑套装软件(shrink wrapped software))、预置在计算机系统中(例如，在系统的只读存储器或硬盘上)、或在网上(例如互联网或万维网)从服务器或电子布告栏发布。当然，本发明的一些实施方式可作为软件(如计算机程序产品)和硬件两者的组合而实现。而本发明的其他实施方式可以作为完全的硬件、或完全的软件(如计算机程序产品)而实现。
尽管已经公开本发明的各种示例性实施方式，本领域技术人员应该清楚的是，在不脱离本发明真实范围的情况下，可以作出实现本发明一些优势的各种改变和修正。

Claims (4)

1.一种处理电刺激响应测量波形信号的方法，所述电刺激响应测量波形信号含有刺激伪迹分量和神经动作电位分量，所述方法包括：
改变电刺激信号；以及
基于满足所述刺激伪迹分量和来自已知神经动作电位波形数据库的多个已知神经动作电位波形之间的成本函数比较，来获取新的最优化的电刺激信号，以便去除所述刺激伪迹分量并留下所述神经动作电位波形。
2.根据权利要求1的方法，其中，所述神经动作电位波形是引发的合成动作电位波形。
3.根据权利要求2的方法，其中，所述引发的合成动作电位波形与耳蜗植入物关联。
4.根据权利要求1的方法，其中，满足成本函数比较是基于梯度下降程序进行的。
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