目的 结合踝关节在各方向上运动之间的约束关系,对其三维转动角度进行积分,得到三维运动空间的大小,用于更加准确全面地量化其灵活度和康复程度。方法 选取25例大学生志愿者,其中无踝关节损伤的健康者20例,近期有过踝关节损伤的患者5例。使用运动捕捉系统实时记录被测者脚上标记点的三维坐标。利用三角函数将这些坐标转化为转动角度并进行处理,通过使用多项式拟合,得到踝关节在各个方向上最大转动角度随跖屈和背屈角度变化的方程。对拟合得到的方程进行积分,得到踝关节三维运动空间的大小。结果 健康人群踝关节的三维运动空间为41.256,个体间差距小于10%。患者患侧三维运动空间的大小为33.163,由于康复程度的不同,个体间差距小于15%。两组之间存在显著性差异(t=8.804, P<0.01)。在同一跖屈和背屈角度下,内翻的最大转动角度比外翻大,内旋的最大转动角度比外旋大。结论 通过此算法能更准确地量化踝关节三维运动空间的大小,实现对踝关节灵活度和康复程度更全面的评估。
Objective To obtain the three-dimensional (3D) motion space of ankle by an integral for the 3D rotation angle with mutual relationships of rotation angles in different directions, which is used to evaluate the flexibility and recovery of ankle more accurately and fully.Methods Twenty-five graduate students were recruited to participate in this study, one group consisted of 20 healthy individuals without ankle injury, and the other was composed of 5 patients with ankle injury. A motion capturing system was used to simultaneously capture the 3D coordinates of the marked points on the foot. Next, these 3D coordinates were converted into rotation angles through trigonometric functions processed. The maximum rotation angles of adduction, abduction, varus, and eversion change with the rotation angles of plantar flexion and dorsal flexure were measured by using polynomial fitting. At last, the size of the ankle's 3D motion space was obtained by integrating the fitting functions.Results The ankle's 3D motion space of the healthy people was 41.256, and the variation among them was less than 10%. The ankle's 3D motion space of the patient side was 33.163, and the variation among them was less than 15% because of the different degrees of rehabilitation. There was significant difference between two groups (t=8.804, P<0.01). With the same rotation angles of plantar flexion or dorsal flexure, the maximum rotation angle of varus was larger than that of eversion, and the maximum rotation angle of adduction was larger than that of abduction.Conclusion The algorithm can be used to quantify the 3D motion space of ankle more accurately, and to achieve a more comprehensive evaluation of ankle's flexibility and rehabilitation.
[1] Czajka CM, Tran E, Cai AN, et al. Ankle sprains and instability [J]. Med Clin North Am, 2014, 98(2): 313-329.
[2] Plaza-Manzano G, Vergara-Vila M, Val-Otero S, et al. Manual therapy in joint and nerve structures combined with exercises in the treatment of recurrent ankle sprains: a randomized, controlled trial [J]. Man Ther, 2016, 26: 141-149.
[3] 关国平,孟强,牛文鑫,等. 踝关节扭伤防护及其康复研究进展[J]. 医用生物力学, 2016, 31(1): 78-82.
[4] Jamwal PK, Hussain S, Xie SQ. Review on design and control aspects of ankle rehabilitation robots [J]. Disabil Rehabil Assist Technol, 2015, 10(2): 93-101.
[5] 禹润田,方跃法,郭盛. 绳驱动并联踝关节康复机构设计及运动性能分析[J]. 机器人, 2015, 37(1): 53-73.
[6] 印松. 踝关节康复机器人设计及人-机运动映射分析[J]. 中国机械工程, 2012, 23(21): 2552-2556.
[7] Moseley AM, Beckenkamp PR, Haas M, et al. Rehabilitation after immobilization for ankle fracture: the exact randomized clinical trial [J]. JAMA, 2015, 314(13): 1376-1385.
[8] Bell-Jenje T, Olivier B, Wood W, et al. The association between loss of ankle dorsiflexion range of movement, and hip adduction and internal rotation during a step down test [J]. Man Ther, 2016, 21: 256-261.
[9] Sinclair J, Taylor PJ, Edmundson CJ, et al. Influence of the helical and six available cardan sequences on 3D ankle joint kinematic parameters [J]. Sports Biomech, 2012, 11(3): 430-437.
[10] Wadhwa V, Malhotra V, Xi Y, et al. Bone and joint modeling from 3D knee MRI: feasibility and comparison with radiographs and 2D MRI [J]. Clin Imaging, 2016, 40(4): 765-768.
[11] 吴誉兰,章小宝. 基于Kinect的动态手臂三维姿势的识别与仿真[J]. 计算机仿真, 2016, 33(7): 369-372.
[12] Zhang M, Davies TC, Xie S. Effectiveness of robot-assisted therapy on ankle rehabilitation–a systematic review [J]. J Neuroeng Rehabil, 2013, 21.
[13] Zhiyong T, Xiaodong X, Zhongcai P. Trajectory planning and mechanic's analysis of lower limb rehabilitation robot [J]. Biomed Mater Eng, 2015, 26(Suppl 1): 349-355.
[14] Deng H, Durfee WK, Nuckley DJ, et al. Complex versus simple ankle movement training in stroke using telerehabilitation: a randomized controlled trial [J]. Phys Ther, 2012, 92(2): 197-209.
[15] 李荫湘,钱晋武,沈林勇,等. 步行康复机器人轨迹控制方法研究[J]. 机电工程, 2010, 27(6): 47-51.
[16] Ridola CG, Cappello F, Marcianò V, et al. The synovial joints of the human foot [J]. Ital J Anat and Embryol, 2007, 112(2): 61-80.
[17] Leardini A, O'Connor JJ, Catani F, et al. The role of the passive structures in the mobility and stability of the human ankle joint: a literature review [J]. Foot Ankle Int, 2000, 21(7): 602-615.
[18] Yonezawa T, Onodera T, Ming Ding, et al. Development of three-dimensional motion measuring device for the human ankle joint by using parallel link mechanism [J]. Conf Proc IEEE Eng Med Biol Soc, 2014, 2014: 4358-4361.
[19] 杨久山,彭京亮,于波,等. 三维动作捕捉系统在桡骨远端骨折患者腕关节功能评价中的初步应用[J]. 中国中西医结合影像学杂志, 2013,11(3): 290-292.
[20] Sandau M, Koblauch H, Moeslund TB, et al. Markerless motion capture can provide reliable 3D gait kinematics in the sagittal and frontal plane [J]. Med Eng Phys, 2014, 36(9): 1168-1175.
[21] Tejedor J, Gutiérrez-Carmona FJ. Polynomial curve fitting of the corneal profile in 2.2-mm corneal incision phacoemulsification [J]. J Refract Surg, 2015, 31(1): 42-47.
[22] 戚非,闫勇,田应. 基于MATLAB的多项式拟合[J]. 实验室科学, 2006(5): 63-65.
[23] 颜清,彭小平. 基于蒙特卡罗最小二乘的实验数据拟合方法[J]. 计算机与应用化学, 2011, 28(11): 1473-1476.
[24] Khan K, Roberts P, Nattrass C, et al. Hip and ankle range of motion in elite classical ballet dancers and controls [J]. Clin J Sport Med, 1997, 7(3): 174-179.
[25] Rabin A, Kozol Z. Measures of range of motion and strength among healthy women with differing quality of lower extremity movement during the lateral step-down test [J]. J Orthop Sports Phys Ther, 2010, 40(12): 792-800.
