一种基于LabVIEW图像处理技术的膝关节表观应变测量方法的研究
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摘要
膝关节因其特殊性、复杂性和重要性一直是人们研究的热点和难点,其中涉及到的膝关节生物力学特性研究具有极其重要的意义。在膝关节生物力学特性研究方法中,膝关节体表软组织力学特性的实验测量尤为重要,但目前常用的测量方法大都存在这样或那样的缺点。因此,提出一种基于机器视觉技术采用LabVIEW开发环境的快速表观应变测量方法。该方法在保持膝关节较完整的情况下实现对膝关节表观应变的非接触式动态快速测量,并具有可靠性高、操作简便、易于普及与数据挖掘等特点,可细分为三个方面的内容:有效屈膝加载、动态屈曲度测量、特征点提取。主要研究内容和结果如下。
①构建了膝关节屈曲运动加载控制系统,即通过机械臂推动膝关节进行屈曲运动,并由此设计了各类夹具,然后设计了基于LabVIEW的上位机人机交互界面,下位机通过精确控制步进电机而实现对机械臂运动方向、速度和运动时间的控制,从而达到对膝关节屈曲运动中屈膝速度、屈膝强度和运动时间的精确加载。
②设计了基于图像技术的非接触式屈曲角度测量方法及系统,即在膝关节上引入屈曲指针,在图像中通过测量屈曲指针的指向来判定屈曲角度,同时该参数作为加载系统的反馈,间接控制膝关节的屈曲范围,从而使加载系统更真实的模拟各种生理条件下对膝关节进行屈膝加载。
③设计了基于图像技术的特征点提取方法及系统,即通过适当角度方位的摄像系统记录膝关节运动视频信息和反映体表组织力学特性的标记点阵运动轨迹的图像信息,通过图像处理技术从图像中提取标记点轨迹,并计算出组织应变量,实现了在动态条件下快速提取膝关节体表特征点的目的。
④将上述各部分集成整合成完整的膝关节屈曲运动加载与测量系统,并应用该系统研究了猪后蹄髌骨(模拟人膝关节,共12例)切口区的软组织力学特性。首先将猪后蹄髌骨切口区体表引入有序的标记点阵,然后通过特征点提取系统对有序标记点的运动轨迹进行提取,进而计算关节体表在屈曲运动过程中随时间变化的表观应变。另外,采用本方法对微磁珠的图像进行了识别,从而验证了特征点提取方法的有效性。
综上可知,基于LabVIEW的膝关节屈曲运动表观应变非接触式动态快速测量方法是一种可靠性高、操作性强、易于普及与数据挖掘的膝关节生物力学试验方法,为研究膝关节生物力学特性提供了有效途径。
Knee is a major joint in the body, and its biomechanical behavior is extremely important for body stability and motion. However, the current methods to study knee biomechanics are mostly complicated and costly. Thus, it is necessary to develop new experimental methods that are easy to build and less expensive. Here, described is a new method that measures the apparent tissue strain of knee during flexion based on imaging analysis technique using LabVIEW. This method consists of three components: knee flexion loading, flexion measurement, and strain measurement via surface marker identification. With this method non-contact measurement of apparent tissue strain of knew can be done dynamically during flexion, and it is easy to operate, highly reliable, The design and building of the measurement system are described as follows.
①A loading system of knee flexion was designed. Knee was held with a variety of clamps, and driven in flexion movement by a mechanical arm and a stepper motor. The stepper motor was controlled electronically with an embedded micro-control unit (MCU) via an interactive interface on PC based on LabVIEW, thus to achieve accurate control of the direction, speed and the duration of the flexion.
②A system to measure flexion angle without contacting the knee was designed. A straight rigid dial was attached onto the moving section of the knee as a marking of its position. By analyzing the image of this marking line, the angle of flexion was obtained. In the meanwhile, the measured angle was be used as the feedback to control the loading system to drive knee flexion at the preset magnitude.
③A tissue strain measurement system was designed based on the technique of extracting image feature. A video camera system in the proper orientation was used to record images of knee surface that was marked by an array of points in an ordered list. Using image processing technology, coordinates of the marker points were identified from the recorded images, and the corresponding displacements of the marker points over time were measured. From the displacement data, the apparent tissue strain, or knee surface deformation, was calculated. In addition, the marker identification technique was tested to extract coordinates of magnetic microbeads from recorded images, and the results confirmed the effectiveness of the system.
④The flexion-loading and measuring system, tissue strain measurement system were integrated and used to study the biomechanical properties of knee tissue (swine hoof, n=12) over the area of patellar incision. The apparent tissue strain of the swine hoof during flexion was measured at different flexion magnitudes, with different methods of patellar incision and suture. By comparing the strain fields in different cases, different surgical procedures of knee incision could be quantitatively evaluated.
In summary, a new method and system of non-contact dynamic fast measurement is realized for measuring apparent strain on the surface of knee during flexion. This method is easy to operate and highly reliable, economical for popularization and data-mining, and thus provides an effective way to study biomechanical properties of knee, which is useful for clinical guidance of knee surgery and rehabilitation.
①构建了膝关节屈曲运动加载控制系统,即通过机械臂推动膝关节进行屈曲运动,并由此设计了各类夹具,然后设计了基于LabVIEW的上位机人机交互界面,下位机通过精确控制步进电机而实现对机械臂运动方向、速度和运动时间的控制,从而达到对膝关节屈曲运动中屈膝速度、屈膝强度和运动时间的精确加载。
②设计了基于图像技术的非接触式屈曲角度测量方法及系统,即在膝关节上引入屈曲指针,在图像中通过测量屈曲指针的指向来判定屈曲角度,同时该参数作为加载系统的反馈,间接控制膝关节的屈曲范围,从而使加载系统更真实的模拟各种生理条件下对膝关节进行屈膝加载。
③设计了基于图像技术的特征点提取方法及系统,即通过适当角度方位的摄像系统记录膝关节运动视频信息和反映体表组织力学特性的标记点阵运动轨迹的图像信息,通过图像处理技术从图像中提取标记点轨迹,并计算出组织应变量,实现了在动态条件下快速提取膝关节体表特征点的目的。
④将上述各部分集成整合成完整的膝关节屈曲运动加载与测量系统,并应用该系统研究了猪后蹄髌骨(模拟人膝关节,共12例)切口区的软组织力学特性。首先将猪后蹄髌骨切口区体表引入有序的标记点阵,然后通过特征点提取系统对有序标记点的运动轨迹进行提取,进而计算关节体表在屈曲运动过程中随时间变化的表观应变。另外,采用本方法对微磁珠的图像进行了识别,从而验证了特征点提取方法的有效性。
综上可知,基于LabVIEW的膝关节屈曲运动表观应变非接触式动态快速测量方法是一种可靠性高、操作性强、易于普及与数据挖掘的膝关节生物力学试验方法,为研究膝关节生物力学特性提供了有效途径。
Knee is a major joint in the body, and its biomechanical behavior is extremely important for body stability and motion. However, the current methods to study knee biomechanics are mostly complicated and costly. Thus, it is necessary to develop new experimental methods that are easy to build and less expensive. Here, described is a new method that measures the apparent tissue strain of knee during flexion based on imaging analysis technique using LabVIEW. This method consists of three components: knee flexion loading, flexion measurement, and strain measurement via surface marker identification. With this method non-contact measurement of apparent tissue strain of knew can be done dynamically during flexion, and it is easy to operate, highly reliable, The design and building of the measurement system are described as follows.
①A loading system of knee flexion was designed. Knee was held with a variety of clamps, and driven in flexion movement by a mechanical arm and a stepper motor. The stepper motor was controlled electronically with an embedded micro-control unit (MCU) via an interactive interface on PC based on LabVIEW, thus to achieve accurate control of the direction, speed and the duration of the flexion.
②A system to measure flexion angle without contacting the knee was designed. A straight rigid dial was attached onto the moving section of the knee as a marking of its position. By analyzing the image of this marking line, the angle of flexion was obtained. In the meanwhile, the measured angle was be used as the feedback to control the loading system to drive knee flexion at the preset magnitude.
③A tissue strain measurement system was designed based on the technique of extracting image feature. A video camera system in the proper orientation was used to record images of knee surface that was marked by an array of points in an ordered list. Using image processing technology, coordinates of the marker points were identified from the recorded images, and the corresponding displacements of the marker points over time were measured. From the displacement data, the apparent tissue strain, or knee surface deformation, was calculated. In addition, the marker identification technique was tested to extract coordinates of magnetic microbeads from recorded images, and the results confirmed the effectiveness of the system.
④The flexion-loading and measuring system, tissue strain measurement system were integrated and used to study the biomechanical properties of knee tissue (swine hoof, n=12) over the area of patellar incision. The apparent tissue strain of the swine hoof during flexion was measured at different flexion magnitudes, with different methods of patellar incision and suture. By comparing the strain fields in different cases, different surgical procedures of knee incision could be quantitatively evaluated.
In summary, a new method and system of non-contact dynamic fast measurement is realized for measuring apparent strain on the surface of knee during flexion. This method is easy to operate and highly reliable, economical for popularization and data-mining, and thus provides an effective way to study biomechanical properties of knee, which is useful for clinical guidance of knee surgery and rehabilitation.
引文
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[8]颜贻站,曾云记,谢作完等.农村50岁以上5016人退行性膝关节病流行病学调查[J].浙江中西医结合杂志, 2007, (07):422-456.
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[2] Li J, Wyss UP, Costigan PA, et al. An integrated procedure to assess knee-joint kinematics and kinetics during gait using an optoelectric system and standardized X- rays[J]. J Biomed Eng, 1993, 15(5): 392- 400.
[3]孙康,王光达.膝关节生物力学与运动学专业术语[J].中国现代医学杂志, 2002,12(06):37-39.
[4] Shiavi R, Limbird T, Frazer M, et al. Helical motion analysis of the knee- II. Kinematics of uninjured and injured knees during walking and pivoting[J]. J Biomech, 1987, 20(7): 653- 665.
[5] Komistek RD, Stiehl JB, Dennis DA, et al. Mathematical model of the lower extremity joint reaction forces using Kane's method of dynamics[J]. J Biomech, 1998, 31(2): 185- 189.
[6] Scott SH, Winter DA. Internal forces of chronic running injury sites[J].Med Sci Sports Exerc, 1990, 22(3): 357- 369.
[7]林锦洪,李敏健,许智源等.社区45岁以上人群退行性膝关节病流行病学调查[J].中华风湿病学杂志, 2005, 09(12):718-720.
[8]颜贻站,曾云记,谢作完等.农村50岁以上5016人退行性膝关节病流行病学调查[J].浙江中西医结合杂志, 2007, (07):422-456.
[9]许玉林,孙允高,张春林.膝关节生物力学模型研究现状[J].医用生物力学,2003, 18(04):250-255.
[10]郭媛.全膝关节在不同运动状态下的有限元仿真研究[D].太原:太原理工大学,2009:1-3.
[11] Lu TW, Taylor SJG, O’Connor JJ, et al. Influence of muscle activity on the forces in the femur: an in vivo study[J]. J Biomechanics, 1997, 30(11):1101-1106.
[12] Tumer ST, Engin AE. Three-body segment dynamic model of the human knee[J]. J Biomedch Eng, 1993, 115(4A):350-356.
[13] Lu TW, O’Connor JJ, Taylor SJ, et al.Validation of a lower limb model with in vivo femoral forces telemetered from two subjects[J].J Biomech,1998,31(1):63-69.
[14] Komistek RD, Kanec TR, Mahfouz M, et al. Knee mechanics:a review of past and present techniques to determine in vivo loads[J]. J Biomech, 2005, 38(2):215-228.
[15]潘哲尔,黄加张,顾湘杰等.磁共振影像膝关节三维有限元模型的建立[J].中国骨与关节损伤杂志,2006, 04(21):268-270.
[16]袁平,王万春.膝关节三维有限元模型的建立及生物力学分析[J].中南大学学报(医学版), 2010,35(1):85-89.
[17]姜华亮,华锦明,许新忠等.正常人膝关节三维有限元模型的建立[J].苏州大学学报(医学版),2008,28(3):421-422.
[18]王兆星,董福慧.正常人的软组织张力测定[J].中国骨伤, 2004, 01(17):13-15.
[19]杨惊途,李永年,朱自强等.一种生物软组织二维变形实时测量系统[J].光电工程,1991, 18(03):.8-12.
[20] Drake DB, Rodeheaver PF, Edlich RF, et al. Experimental studies in swine for measurement of suture extrusion[J]. J Long Term Eff Med Implants, 2004, 14:251-259.
[21]丁楚雄,罗建文,白净.二维数字化超声软组织应变成像系统的研制[J].北京生物医学工程, 2006,25 (02):113-117.
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