穿刺针尖光纤力传感信号的小波变换分析

杨唐文; 陈盼飞; 韩建达; 徐卫良

doi:10.3788/OPE.20152308.2149

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穿刺针尖光纤力传感信号的小波变换分析

现代应用光学 | 更新时间：2020-08-12

- 穿刺针尖光纤力传感信号的小波变换分析
- Wavelet transform analysis of optic fiber force sensing signals at puncture needle tip
- 光学精密工程 2015年23卷第8期页码：2149-2157
- 作者机构：
  
  1. 中国科学院沈阳自动化研究所机器人学国家重点实验室,辽宁沈阳,110016
  2. 北京交通大学信息科学研究所北京,100044
  3. 奥克兰大学机械工程系,新西兰
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.61375109,No.61273356)();机器人学国家重点实验室科研基金资助项目(No.2013-012)()
- DOI：10.3788/OPE.20152308.2149
  中图分类号： TN253
- 收稿日期：2014-12-20，
  
  修回日期：2015-01-15，
  
  纸质出版日期：2015-08-25
- 稿件说明：
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杨唐文, 陈盼飞, 韩建达等. 穿刺针尖光纤力传感信号的小波变换分析[J]. 光学精密工程, 2015,23(8): 2149-2157

YANG Tang-wen, CHEN Pan-fei, HAN Jian-da etc. Wavelet transform analysis of optic fiber force sensing signals at puncture needle tip[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2149-2157
杨唐文, 陈盼飞, 韩建达等. 穿刺针尖光纤力传感信号的小波变换分析[J]. 光学精密工程, 2015,23(8): 2149-2157 DOI： 10.3788/OPE.20152308.2149.

YANG Tang-wen, CHEN Pan-fei, HAN Jian-da etc. Wavelet transform analysis of optic fiber force sensing signals at puncture needle tip[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2149-2157 DOI： 10.3788/OPE.20152308.2149.

摘要

经皮软组织穿刺过程中

穿刺针尖会历经不同材料特性的器官组织

受到复杂变化的作用力。为了测量针尖处的作用力并鉴定穿刺路径上不同层次的软组织

研制了一种光纤力传感器

并进行了力信号分析。首先

基于法-珀干涉介绍了光纤力传感器的测量原理、光链路设计、及其与针的集成和标定方法。在穿刺力信号分析的基础上

提出利用Mallat算法对力信号进行小波变换

提取信号的特征模式

界定软组织的各层边界。最后

在猪的肝脏和肋条组织样本上进行了针穿刺实验验证。结果显示:光纤力传感器的可测力为0至3.20N

测量精度可达0.01N。得到的穿刺试验结果表明Mallat算法能够有效地区分软组织的类型。研制的光纤传感器满足穿刺力的测量范围、精度和可靠性等要求

所提出的小波变换算法可用于软组织边界的界定

有望用于机器人穿刺控制。

Abstract

During a percutaneous soft tissue puncture

a puncture needle is inserted into the layered tissues with various material properties

and the interactive force at the needle tip occurs discriminately. To measure the force and identify the boundaries of the layered tissues in the puncture path

a fiber optic force sensor was fabricated

and the force data acquired with the sensor were analyzed. In terms of a Fabry-Perot interferometer

the measuring principle of the fiber optic sensor was presented

and its optical link

its integration into the needle and calibration approach were introduced. Then

based on the insertion force signal analysis

the force signals were decomposed via the Mallat algorithm into wavelets

and their patterns were recognized and used to identify the layered tissue boundaries. Finally

needle insertion tests were performed with the swine liver and belly tissue phantoms. The experimental results show that the working range of the force sensor is 0-3.20 N and the measuring resolution is under 0.01 N. Moreover

the insertion test results indicate that the Mallat algorithm is effective to the discrimination of layered tissues. It concludes that the fabricated fiber optic sensor meets the requirements of working range

accuracy and reliability to measure an insertion force. The proposed wavelet transform algorithm is able to identify the boundaries of the layered tissues and is expected to used in the percutaneous control by a robot.

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Keywords

references

赵新刚,杨唐文,韩建达,等. 机器人辅助针穿刺技术[J]. 科学通报,2013,58:20-27. ZHAO X G, YANG T W, HAN J D, et al.. A review on the robot-assisted needle puncture technology [J]. Chin. Sci. Bull., 2013, 58:20-27. (in Chinese)

OKAMURA A, MATARIC M J, CHRISTENSEN H I. Medical and health-care robotics: achievements and opportunities [J]. IEEE Robotics & Automation Magazine, 2010, 17(3): 26-37.

UDD E, SPILLMAN W. Fiber Optic Sensors: An Introduction for Engineers and Scientists [M]. 2nd ed..New Jersey: John Wiley & Sons Inc., 2011.

龙亮,钟少龙,徐静,等. 微型光纤磁传感器设计与制作[J]. 光学精密工程,2013, 21(9): 2294-2302. LONG L, ZHONG SH L, XU J, et al.. Design and fabrication of micro fiber-optic magnetic sensor [J]. Opt. Precision Eng., 2013, 21(9): 2294-2302. (in Chinese)

HIROSE S,YONEDA K. Development of optical 6-axial force sensor and its signal calibration considering non-linear interference [C]. Proceedings of International Conference on Advanced Robotics, Tokyo, Japan, 1990: 46-53.

TADA M, KANADE T. Design of an MR-compatible three-axis force sensor[C]. Proceedings of IEEE International Conference on Intelligent Robots and Systems, Edmonton, Alberta, Canada, 2005: 2618-2623.

SU H, FISCHER G S. A 3-axis optical force/torque sensor for prostate needle placement in magnetic resonance imaging environments[C]. Proceedings of the 2nd Annual IEEE International Conference on Technologies for Practical Robot Applications, Woburn, Massachusetts, USA, 2009: 5-9.

KESNER S B, HOWE R D. Design principles for rapid prototyping forces sensors using 3-D printing[J]. IEEE/ASME Transactions on Mechatronics, 2011, 16(5): 866-870.

POLYGERINOS P, SENEVIRATNE L D, ALTHOEFER K, et al.. Triaxial catheter-tip force sensor for MRI-guided cardiac procedures[J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(1): 386-396.

PINET E. Fabry-Perot fiber-optic sensors for physical parameters measurement in challenging conditions[J]. Journal of Sensors, 2009: 1-9.

LIU X, IORDACHITA I, HE X, et al.. Miniature fiber-optic force sensor based on low-coherence Fabry-Perot interferometry for vitreoretinal microsurgery[J]. Biomedical Optics Express, 2012, 3(5): 1062-1076.

梁艺军,刘俊锋,张巧萍,等. 环形腔全光纤F-P干涉仪的声发射检测实验研究[J]. 光学精密工程,2009,17(8): 1825- 1831. LIANG Y J, LIU J F, ZHANG Q P, et al.. Ring cavity all fiber F-P interferometer used in detection of acoustic emission [J]. Opt. Precision Eng., 2009, 17(8): 1825-1831. (in Chinese)

BRACEWELL R N. The Fourier Transform and its Applications [M]. 3rd Edition. McGraw Hill, 2000.

GRIFFIN D W, LIM J S. Signal estimation from modified short-time Fourier transform [J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1984, 32(2): 236-243.

RIOUL O, VETTERLI M. Wavelets and signal processing [J]. IEEE Signal Processing Magazine, 1991, 8(4): 14-38.

MALLAT S. A Wavelet Tour of Signal Processing[M]. 2nd Edition. Academic Press, 1999.

YANG T W, ZHU H F, HAN J D, et al.. Identification of tissue types and boundaries with a fiber optic force sensor [J]. Science China(Information Sciences), 2014, 57(12):120206(7).

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