WO2011072507A1 - 定位心腔导管的方法和装置 - Google Patents

定位心腔导管的方法和装置 Download PDF

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Publication number
WO2011072507A1
WO2011072507A1 PCT/CN2010/072266 CN2010072266W WO2011072507A1 WO 2011072507 A1 WO2011072507 A1 WO 2011072507A1 CN 2010072266 W CN2010072266 W CN 2010072266W WO 2011072507 A1 WO2011072507 A1 WO 2011072507A1
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Prior art keywords
catheter
positioning
respiratory
reference signal
weight coefficient
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PCT/CN2010/072266
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English (en)
French (fr)
Inventor
李楚文
李斌
薛奋
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四川锦江电子科技有限公司
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Priority to EP10836945.5A priority Critical patent/EP2514379A4/en
Publication of WO2011072507A1 publication Critical patent/WO2011072507A1/zh

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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
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/06—Devices, other than using radiation, for detecting or locating foreign bodies ; determining position of probes within or on the body of the patient
    • A61B5/061—Determining position of a probe within the body employing means separate from the probe, e.g. sensing internal probe position employing impedance electrodes on the surface of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7207—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
    • A61B18/12—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating by passing a current through the tissue to be heated, e.g. high-frequency current
    • A61B18/14—Probes or electrodes therefor
    • A61B18/1492—Probes or electrodes therefor having a flexible, catheter-like structure, e.g. for heart ablation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B17/00—Surgical instruments, devices or methods, e.g. tourniquets
    • A61B2017/00681—Aspects not otherwise provided for
    • A61B2017/00694—Aspects not otherwise provided for with means correcting for movement of or for synchronisation with the body
    • A61B2017/00699—Aspects not otherwise provided for with means correcting for movement of or for synchronisation with the body correcting for movement caused by respiration, e.g. by triggering
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20—Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A61B2034/2046—Tracking techniques
    • A61B2034/2063—Acoustic tracking systems, e.g. using ultrasound
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20—Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0833—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures
    • A61B8/0841—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures for locating instruments

Definitions

  • the present invention relates to a method and apparatus for positioning a cardiac lumen catheter, and more particularly to a method and apparatus for positioning a cardiac lumen catheter using respiratory compensation techniques. Background technique
  • a three-dimensional mapping system for cardiac catheter positioning mainly used in radiofrequency ablation (RFCA) arrhythmia surgery, recording the three-dimensional spatial position of the intracardiac catheter, using the acquired information to establish an anatomical geometry of the three-dimensional heart chamber, and performing Excited time mapping, stimulating propagation mapping.
  • RFCA radiofrequency ablation
  • the intracardiac catheter will fluctuate with the effects of breathing and heartbeat.
  • the heartbeat frequency is faster than the catheter movement, and can be eliminated by filtering or specific heartbeat period, and the respiratory effect will become the main factor causing the catheter electrode positioning error.
  • breathing in addition to changing the position of the catheter in the heart chamber, breathing also changes the path of the excitation current due to the breathing air in the lungs, and the blood impedance that has returned from the lungs back to the heart chamber, thereby causing greater Impact.
  • the respiratory band is generally 0. 1 - 2HZ, which overlaps with the catheter motion frequency. Filtering with a lower cutoff frequency filters out the movement of the catheter and affects the real-time motion of the catheter. With higher cutoff frequency filtering, respiratory interference cannot be completely filtered out, for example, low-pass filtering with a cutoff frequency of 0. 25HZ, the respiratory effect will cause the catheter position to fluctuate by 1 - 2cm.
  • a method of positioning a cardiac lumen catheter comprising the steps of:
  • A acquiring a collection position signal of the cardiac catheter and a reference signal containing respiratory information
  • the adaptive noise cancellation method is used to process the respiratory information signal in step A, and the respiratory fluctuation in the catheter acquisition position signal is eliminated.
  • a device for positioning a cardiac catheter comprising a cardiac catheter acquisition position signal input and a data processing unit, characterized by: further comprising: a reference signal input including respiratory information, a position signal and a reference signal input data processing unit, and data processing The unit applies an adaptive denoising method to process the breathing information in the reference signal, eliminating the breathing fluctuations in the catheter acquisition position signal.
  • the introduced reference signal contains respiratory information
  • the reference signal is obtained by one or more of an electric field, a magnetic field, and an ultrasound method somewhere on the body surface or within the heart.
  • the DC offset signal including the fixed position information of the reference signal is filtered out to obtain a signal containing only the respiratory related information.
  • the respiratory motion of the positioning catheter is tracked by the weight coefficient W1
  • the displacement of the positioning catheter is tracked by the weight coefficient W2
  • the adjustment method of the weight coefficient ⁇ or W2 uses a variable-step LMS (Minimum Mean Square Algorithm) Adaptive Algorithm.
  • the respiratory motion of the positioning catheter is tracked by using the weight coefficient W1
  • the displacement of the positioning catheter is tracked by the weight coefficient W2
  • the adjustment method of the weight coefficient W1 or W2 adopts the LMS adaptive noise canceling algorithm.
  • the beneficial effects of the present invention are: because the same breathing affects the catheter at different positions in the heart Off, using the principle of adaptive denoising, a reference signal containing respiratory information is introduced, which is used to locate the respiratory displacement of the catheter in the cavity, without distortion to other signals. It can avoid the use of low-pass filtering, reduce the real-time performance of the catheter movement, and the effect is not good. Because it is real-time tracking and filtering, there is no problem of different parts and different effects, and systems using electric field, magnetic field and ultrasonic positioning are applicable.
  • FIG. 1 is a schematic block diagram of an embodiment of the present invention.
  • Figure 2 is a schematic illustration of the catheter positioned within the heart chamber.
  • Figure 3 is the actual effect map of respiratory compensation.
  • Figure 4 is a flow chart of an adaptive compensation algorithm. detailed description
  • the present invention illustrates a method for positioning a cardiac catheter, comprising the steps of: acquiring a position signal of a cardiac catheter and a reference signal containing respiratory information;
  • the position signal is collected in the heart 6 by the catheter 7, which is currently at the left ventricle 8.
  • the position signal can be obtained by any means such as an electric field, a magnetic field, an ultrasound, or the like.
  • the collected position signals generally include positioning information in three directions of x, y, and z.
  • the compensation operations shown in Figure 1 should be performed in the three directions.
  • the signal D (n) in the Y direction is used as the positioning signal 1 as an example. Other directions are similar.
  • a catheter 9 is placed in the coronary sinus of the heart to collect a reference signal because the catheter is typically not moved during surgery and only fluctuates with breathing and heartbeat.
  • the heartbeat information contained in the reference signal does not affect the effect of respiratory compensation.
  • Body surface electrode collection For the reference signal, just attach it to the chest.
  • the reference input signal 2 can also be obtained by any means such as electric field, magnetic field, ultrasonic, etc., and generally includes information in three directions of x, y, and z. However, it needs to be implemented in the same way as the positioning input signal 1.
  • the direction can be selected as one.
  • the signal X (n) in the Y direction is used as the positioning input signal 1 as an example, and the other directions are similar.
  • the DC offset signal including the fixed position information of the reference signal may be filtered out to obtain a signal containing only the relevant information of the breath.
  • the function of filtering DC offset 3 is to filter out the DC component of signal X ( n ), so that the reference signal contains only respiratory information, and the method of subtracting the moving average by high-pass filtering or subtraction can be used.
  • the method of subtracting the moving mean is used to realize a small amount of calculation, which is easy to implement, and the selection of the moving time window should include at least one breathing interval. 0. 1HZ frequency of breathing, should select at least 10S data as the moving time window, when the sampling period is 16mS, it needs 625 points, then
  • XI (n) X (n) - ( X (n) + X (n-1) + X (n-2) ... +X (n-624) ) /625
  • the purpose of introducing DC input 4 in this example is to introduce a low frequency reference associated with the catheter displacement signal, which is used to track the displacement of the positioning catheter.
  • a fixed DC input B l can be selected.
  • the above signal is adaptively denoised, and the virtual frame part of the figure is an adaptive denoising part.
  • the adaptive filter is essentially a special Wiener filter capable of automatically adjusting its own parameters, and it is not necessary to know in advance about the design. Knowledge of the statistical properties of the input signal and noise, which can gradually "understand” or estimate the required statistical characteristics in the course of their work, and automatically adjust their parameters based on this to achieve the best filtering effect. Once the statistical characteristics of the input signal change, it is able to track this change and automatically adjust the parameters to optimize filter performance.
  • the following examples illustrate two adaptive algorithms:
  • the first using a variable-step LMS algorithm
  • the weight coefficient Wl is used to track the respiratory motion of the positioning catheter; and the weight coefficient W2 is used to track the displacement of the catheter.
  • ⁇ 1 ( n + 1) a 1 ⁇ 1 ( n) + y 1P1 ( n)
  • ⁇ 1 ( n + 1) ⁇ lmax
  • ⁇ 1 ( n + 1) ⁇ lmin
  • Equation (4) 0 ⁇ al ⁇ 1 , Y 1> 0.
  • equation (5) the upper and lower boundaries ⁇ lmax and ⁇ lmin are set for the step size, ⁇ lmax defines the maximum possible convergence speed, ⁇ lmin guarantees Small steady state error.
  • the step size of the algorithm is actually controlled by ⁇ 1, ⁇ .
  • ⁇ is the genetic factor of the step size, which mainly determines the step value when the algorithm is converged.
  • ⁇ 1P1 ( ⁇ ) ⁇ 0 the step size is basically reduced by the exponent a In until ⁇ ( ⁇ ) ⁇ ⁇ 1 ⁇ .
  • ⁇ 1 determines the influence of the step size on the energy PI ( ⁇ ), which mainly controls the start-up and tracking speed of the algorithm.
  • Figure 4 is the software flow chart of the algorithm, which is not only the specific implementation of the above formula, but also realized by the iterative and recursive methods.
  • the algorithm has small calculation amount, good real-time performance and less resource occupation. It can be implemented by the upper computer or the underlying DSP, MCU, programmable chip and other devices.
  • Fig. 3 is a diagram showing the actual compensation effect after the algorithm is used, wherein Sigl is a y-direction moving trajectory of a positioning catheter containing respiratory motion. Sig2 is the y-direction trajectory of the reference catheter containing respiratory motion. Sig3 is the trajectory of the positioning catheter in the y direction after the respiratory compensation. T is a breathing cycle.
  • the visible signal Si g 3 not only filters out the effects of breathing, but also does not affect the tracking of the real-time motion of the catheter.
  • the weight coefficient W1 is used to track the respiratory motion of the positioning catheter; the weight coefficient W2 is used to track the displacement of the positioning catheter.
  • the adjustment of Wl is specifically the M-order filter, and the weighting coefficient is Wli.
  • the specific iteration formula is as follows:
  • W2 (n+1) W2 (n) + 2 ⁇ 2E (n) B (4)
  • ⁇ ⁇ is the step size to track the breath.
  • the step factor ⁇ ⁇ is related to the power of the filter order ⁇ and the input signal XI.
  • the value of ⁇ ⁇ should be inversely proportional to the order of the filter when the same signal is input, and different steps should be taken according to different filter orders, so as to ensure the best signal. Processing result;
  • ⁇ ⁇ is the only parameter that affects the convergence speed of the LMS algorithm, and ⁇ ⁇ varies with the input signal power.
  • the value of ⁇ ⁇ should not be too large. When the value of ⁇ ⁇ is too large, a large gradient noise will be introduced in the adaptive process, and the transition will oscillate and cannot converge. If the ⁇ ⁇ value is too small, although the gradient noise is reduced, the convergence speed is slower. Therefore, the value of ⁇ ⁇ should be compromised.
  • the order of the filter ⁇ is determined: ⁇ hour prediction parameters are small, the error is large, especially when the breathing changes are irregular, and if the phase between the reference signal and the positioning signal is greatly different, the convergence time is long.
  • ⁇ 2 is the step size for tracking the displacement of the catheter.
  • the transition process will oscillate and will not converge. If the ⁇ 2 value is chosen too small, it affects the tracking speed of the positioning catheter. So the value of ⁇ 2 should be compromised. If necessary, different ⁇ 2 values can be selected according to different ⁇ ( ⁇ ).
  • variable step size LMS algorithm has the advantages of fast convergence and small error.
  • An apparatus for operating the method of the above embodiment in accordance with a conventional cardiac catheter positioning system, comprising a position acquisition catheter and a reference signal acquisition catheter or body surface electrode, and a probe mounted on the catheter, the collected data entering through the data collection device.
  • the computer processing the data or the underlying DSP, the single chip microcomputer, the programmable chip and the like can be processed in the data processing device according to the above steps.
  • the invention is not limited to the specific embodiments described above.
  • the invention extends to any new feature or any new combination disclosed in this specification, as well as any novel method or process steps or any new combination disclosed.

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Description

定位心腔导管的方法和装置 技术领域
本发明涉及心腔导管的定位方法和装置， 尤其是一种应用了呼吸补偿技术 的定位心腔导管的方法及其装置。 背景技术
心腔导管定位的三维标测系统， 主要用于射频消融 （RFCA ) 心律失常的手 术中， 记录心腔内导管的三维空间位置， 利用所获取的信息建立三维心腔的解 剖几何图， 以及进行激动时间标测、 激动传播标测。 其中导管电极位置的精度 将直接影响模型的形状及指导消融的效果。
无论采用磁场还是电场定位的系统， 心腔内导管会随呼吸和心跳的影响波 动。 心跳频率相对导管运动较快， 釆用滤波或特定心跳期釆样即可消除， 则呼 吸影响将成为造成导管电极定位误差的主要因素。 尤其在电场定位的系统中， 呼吸除了改变了心腔内导管的本身位置外， 还会由于肺中呼吸空气， 改变激励 电流的路径， 已及从肺返回心腔的血液阻抗， 从而造成更大的影响。 现有技术的呼吸补偿主要有两种。
其一， 低通滤波。 呼吸频带一般为 0. 1 - 2HZ , 与导管运动频率交叠。 采用 较低的截止频率滤波， 会滤除导管的移动信息， 影响导管的实时运动。 采用较 高的截止频率滤波， 无法完全滤除呼吸干扰， 例如采用 0. 25HZ截止频率低通 滤波， 呼吸影响会造成导管位置波动 1 - 2cm。
其二， Un i ted S ta te s Pa tent 7, 26 3, 397 所述呼吸补偿方式。 该方法不适 用于磁场原理定位的系统， 而且极为复杂。 其不仅将三轴电场激励方式， 改为 多极电场切换方式， 而且每次计算呼吸补偿系数， 需要保证导管稳定 10秒钟， 采集数据。 由于心腔内不同部位呼吸影响相位、 幅值不同， 为保证效果， 需要 在不同部位釆集 1 0秒数据计算。 当处于不同部位补偿效果不佳时， 需重新计 算系数。 发明内容
本发明的目的是提供一种基于自适应滤波的呼吸补偿技术， 可以准确的定 位心腔导管。
本发明的技术方案如下：
一种定位心腔导管的方法， 包括如下步骤：
A、 获取心腔导管的采集位置信号和包含呼吸信息的参考信号；
B、 利用自适应消噪方法处理 A步骤中的呼吸信息信号，消除导管采集位 置信号中的呼吸波动。
一种定位心腔导管的装置， 包括心腔导管采集位置信号输入和数据处理单 元， 其特征在于： 还包括包含呼吸信息的参考信号输入， 采集位置信号和参考 信号输入数据处理单元后，数据处理单元应用自适应消噪方法处理参考信号中 的呼吸信息， 消除导管采集位置信号中的呼吸波动。
本发明的附加技术方案如下：
优选地， 引入的参考信号包含呼吸信息， 参考信号釆用电场、 磁场、 超声 方式中的一种或几种在体表或心内的某处获取。
优选地， 在对参考信号进行自适应消噪前， 先滤除参考信号中包含本身固 定位置信息的直流偏移信号， 得到仅包含呼吸相关信息的信号。
优选地， 在自适应消噪处理中， 利用权系数 W1追踪定位导管的呼吸运动， 利用权系数 W2追踪定位导管的位移， 其中， 权系数 Ή或 W2的调整方法， 采 用可变步长的 LMS (最小均方算法） 自适应算法。
优选的， 在自适应消噪处理中， 利用权系数 W1追踪定位导管的呼吸运动， 利用权系数 W2追踪定位导管的位移， 其中， 权系数 W1或 W2的调整方法， 采 用 LMS 自适应消噪算法。
本发明的有益效果是： 由于同一呼吸对在心脏中不同位置导管的影响是相 关的， 利用自适应消噪原理， 引入包含呼吸信息的参考信号， 用于 ·ί氏消心腔内 定位导管的呼吸位移， 而对其它信号不产生畸变。 可避免利用低通滤波， 降低 导管运动的实时性， 且效果不佳影响， 由于是实时跟踪滤波， 不会存在不同部 位， 效果不同的问题， 并且采用电场、 磁场、 超声定位的系统均适用。 附图说明
本发明将通过例子并参照附图的方式说明， 其中：
图 1是本发明实施例的原理框图。
图 2是导管位于心腔内的示意图。
图 3是呼吸补偿的实际效杲图。
图 4是自适应补偿算法的流程图。 具体实施方式
本发明如图 1、 图 2所示， 一种定位心腔导管的方法， 包括以下步骤： Α、 获取心腔导管的釆集位置信号和包含呼吸信息的参考信号；
Β、 利用自适应消噪方法处理 Α步骤中的呼吸信息信号，消除导管采集位 置信号中的呼吸波动。 上述位置信号和包含呼吸信息的参考信号获取方法如下：
如图 2所示， 用导管 7在心脏 6中采集位置信号， 目前其处于左心室 8处。 位置信号的获得， 可以采用如电场、磁场、超声等任何方式。 采集的位置信号， 一般包含 x、 y、 z三个方向的定位信息， 三个方向应分别进行图 1所示的补偿 运算， 现以 Y方向的信号 D (n)作为定位信号 1举例说明， 其他方向类似。
当选用心内导管采集参考信号时，采用一根放置在心脏的冠状窦内的导管 9 采集参考信号，因为该导管在手术中通常不会被移动，仅会随呼吸和心跳波动。 参考信号中包含的心跳信息， 不影响呼吸补偿的效果。 也可选用体表电极采集 参考信号， 只需将其贴于胸部即可。
参考输入信号 2 的获得， 同样可以采用如电场、 磁场、 超声等任何方式， 一般也包含 x、 y、 z三个方向的信息。但需与定位输入信号 1的实现方式相同， 方向可任选其一， 现以 Y方向的信号 X (n)作为定位输入信号 1举例说明， 其 他方向类似。
为了进一步优化参考信号的评价效果， 可以在对参考信号进行自适应消噪 前， 先滤除参考信号中包含本身固定位置信息的直流偏移信号， 得到仅包含呼 吸相关信息的信号。 如图 1所示， 滤除直流偏移 3的作用是滤除信号 X ( n ) 中的直流成分， 使参考信号中仅包含呼吸信息， 通过高通滤波或釆用减去移动 均值的方式均可实现。
在滤除直流偏移信号过程中， 由于参考信号中包含较少的移动， 因此采用 减去移动均值的方式实现运算量小， 易于实现， 移动时间窗的选取应至少包含 一个呼吸间期，考虑 0. 1HZ频率的呼吸，应至少选取 10S的数据为移动时间窗， 当采样周期为 16mS时， 需 625点， 则
XI (n) = X (n) - ( X (n) + X (n-1) + X (n-2) ... +X (n-624) ) /625
本例中引入直流输入 4 的作用是引入与导管位移信号相关的低频参考， 利 用其追踪定位导管的位移。 可选取固定的直流输入 B=l。
对上述信号进行自适应消噪， 图中虚框部分为自适应消噪部分， 自适应滤 波器实质上是一种能够自动调整本身参数的特殊维纳滤波器，在设计时不需要 事先知道关于输入信号和噪声的统计特性的知识，它能在自己工作过程中逐渐 "了解" 或估计出所需的统计特性， 并以此为依据自动调整自己的参数， 以达 到最佳滤波效果。 一旦输入信号的统计特性发生变化， 它又能够够跟踪这种变 化， 自动调整参数使滤波器性能重新达到最佳。 以下举例说明两种自适应算法：
第一种， 采用可变步长 LMS 算法
本发明中利用权系数 Wl， 追踪定位导管的呼吸运动； 利用权系数 W2， 追 定位导管的位移。
具体釆用的迭代公式如下
Y (n) =X1 (n) Wl (n) +BW2 (n)
E (n) =D (n) -Y (n)
Wl (n+1) =Ψ1 (n)+ μ 1 ( n) E (n) XI (n)
μ 1 ( n + 1) = a 1 μ 1 ( n) + y 1P1 ( n)
并且
If μ 1 ( n + 1) > μ lmax
μ 1 ( n + 1) = μ lmax
if μ 1 ( n + 1) < μ lmin
μ 1 ( n + 1) = μ lmin
else μ 1 ( n + 1) =μ 1 ( n + 1) (5)
式（4) 中， 0 <al< 1 , Y 1> 0. 式（5) 中为步长设定了上下边界 μ lmax和 μ lmin, μ lmax限定了最大可能的收敛速度， μ lmin保证了较小的稳态误差。 算法的步长实际上由 α1、 γΐ控制。 αΐ 为步长的遗传因子，主要决定算法收 敛时的步长值。 算法深度收敛时， γ 1P1 ( η) →0 ,步长基本上按指数 a In 减 小，直到 μΐ( η) → μ1ηΰη。 γ 1 决定步长受能量 PI ( η) 的影响程度，主要控 制了算法的启动、 跟踪速度。
P1 ( η) = β 1P1 ( η - 1) + (1 - β 1) Ε( η) Ε ( η - 1) (6)
(6) 式中， 0 < (31< 1。 ¥2 (n+1) =Ψ2 (n) + μ 2 ( n) E (n) B (7)
μ2( n + 1) = a 2 2 ( n) + y 2P2 ( n)
Figure imgf000008_0001
并且
If μ 2 ( n + 1) > μ 2max
μ 2 ( n + 1) = μ 2max
if μ 2 ( n + 1) < μ 2min
μ 2 ( n + 1) = μ 2min
else 2( n + 1)
Figure imgf000008_0002
P2( n) = β 2P2( n - 1) + (1 β 2) E( n) E( n - 1) (10) OUT (n) = BW2 (n) (11)
式（8)、 （ 9 )、 （ 10 ) 中 α2、 γ2、 μ 2max, μ 2min、 β2含义与上述 c l、 γ 1、 μ lmax、 μ lmin、 β 1类似。
图 4是本算法的软件流程图， 既是对上述公式的具体实现， 由于釆用迭代、 递推方式实现， 算法计算量小， 实时性好， 占用资源少。 可采用上层计算机或 底层 DSP、 单片机、 可编程芯片等器件实现。
图 3为采用本算法后的实际补偿效果图， 其中， Sigl为含呼吸运动的定位 导管 y方向移动轨迹。 Sig2为包含呼吸运动的参考导管 y方向轨迹。 Sig3为 呼吸补偿后的定位导管 y方向移动轨迹。 T为一个呼吸周期。 可见信号 Sig3 不仅滤除了呼吸的影响， 而且未影响对导管实时运动的跟踪。
第二种， LMS 自适应消噪算法
利用权系数 W1, 追踪定位导管的呼吸运动； 利用权系数 W2, 追踪定位导管 的位移。 这里 Wl的调整， 具体为 M阶滤波器， 其权重系数为 Wli 具体采用的迭代公式如下：
M-1
Y(n)=T Wli(n)Xl(n-i)+BW2(n)
w) 0≤i≤M-l (1)
E (n) =D (n) - Y (n) (2) Wli (n+1) = Wli (n) + 2 μ IE (n) XI (n-i) 0≤i≤M-l (3)
W2 (n+1) =W2 (n) + 2 μ 2E (n) B (4)
μ ΐ为追踪呼吸的步长。
步长因子 μ ΐ 与滤波器阶数 Μ 和输入信号 XI的功率都有关系。为使系统收 敛， 在输入同一信号的情况下， μ ΐ 的取值应该和滤波器阶数成反比， 且应根 据不同的滤波器阶数取不同的步长， 这样才能保证有最佳的信号处理结果； 当 Μ —定时， μ ΐ 是唯一影响 LMS 算法收敛速度的参数， 并且 μ ΐ 随输入信号 功率的变化而变化。 μ ΐ 值的选取不能过大， μ ΐ 值过大时， 在自适应的过程 中会引入较大的梯度噪声，过渡过程将出现振荡， 不能收敛。如果 μ ΐ 值太小， 虽然梯度噪声降低了， 但是收敛速度较慢。 所以对 μ ΐ 值要折中考虑。
滤波器阶数 Μ的确定： Μ小时预测参数少， 误差较大， 尤其是呼吸变化不规 律时， 同时如果参考信号和定位信号的呼吸信息之间的相位有较大差异则收敛 时间长。
Μ大时， 则输出不能及时反映输入的快速变化， 同时可能引入相当的误差。 μ 2 为追踪定位导管位移的步长。 μ 2 值选择过大时， 过渡过程将出现振 荡， 不能收敛。 如果 μ 2 值选择太小， 影响对定位导管的跟踪速度。 所以对 μ 2 值要折中考虑。 必要时， 可根据不同的 Ε (η) , 分段选不同的 μ 2 值。
上述两种算法中， 可变步长 LMS 算法具有收敛快、 误差小的优点。 一种运行上述实施例方法的设备， 与传统心脏导管定位系统相一致， 包括 位置采集导管和参考信号采集导管或体表电极， 以及安装在导管上的探头， 采 集的数据经过数据釆集装置进入处理数据的计算机或底层 DSP、 单片机、 可编 程芯片等器件， 在数据处理器件中按上述步骤进行处理即可。
本说明书中公开的所有特征， 或公开的所有方法或过程中的步骤， 除了互 相排斥的特征和 /或步骤以外， 均可以以任何方式组合。
本说明书 （包括任何附加权利要求、 摘要和附图） 中公开的任一特征， 除 非特别叙述， 均可被其他等效或具有类似目的的替代特征加以替换。 即， 除非 特别叙述， 每个特征只是一系列等效或类似特征中的一个例子而已。
本发明并不局限于前述的具体实施方式。 本发明扩展到任何在本说明书中 披露的新特征或任何新的组合，以及披露的任一新的方法或过程的步骤或任何 新的组合。

Claims

1、 一种定位心腔导管的方法， 包括如下步骤：
A、 获取心腔导管的釆集位置信号和包含呼吸信息的参考信号；
B、 利用自适应消噪方法处理 A步骤中的呼吸信息信号，消除导管采集位 置信号中的呼吸波动。
2、 根据权利要求 1 所述的定位心腔导管的方法， 其特征在于： 引入的参考信 号包含呼吸信息， 参考信号采用电场、 磁场、 超声方式中的一种或几种在体表 或心内的某处获取。
3、 根据权利要求 1或 2所述的定位心腔导管的方法， 其特征在于： 在对参考 信号进行自适应消噪前，先滤除参考信号中包含本身固定位置信息的直流偏移 信号， 得到仅包含呼吸相关信息的信号。
4、 根据权利要求 1或 2所述的定位心腔导管的方法， 其特征在于： 在自适应 消噪处理中， 利用权系数 W1追踪定位导管的呼吸运动， 利用权系数 W2追踪定 位导管的位移， 其中， 权系数 W1或 的调整方法， 采用可变步长的 LMS 自适 应算法。
5、 根据权利要求 3所述的定位心腔导管的方法， 其特征在于： 在自适应消噪 处理中， 利用权系数 W1追踪定位导管的呼吸运动， 利用权系数 W2追踪定位导 管的位移， 其中， 权系数 W1或 的调整方法， 采用可变步长的 LMS 自适应算 法。
6、 根据权利要求 3所述的定位心腔导管的方法， 其特征在于： 在自适应消噪 处理中， 利用权系数 W1追踪定位导管的呼吸运动， 利用权系数 W2追踪定位导 管的位移， 其中， 权系数 或 W2的调整方法， 采用 LMS 自适应消噪算法。
7、 一种定位心腔导管的装置， 包括心腔导管釆集位置信号输入和数据处理单 元， 其特征在于： 还包括包含呼吸信息的参考信号输入， 采集位置信号和参考 信号输入数据处理单元后，数据处理单元应用自适应消噪方法处理参考信号中 的呼吸信息， 消除导管釆集位置信号中的呼吸波动。
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