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基于惯性传感器的下肢康复治疗运动分析。

Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments.

机构信息

School of Mechanical & Automative Engineering, South China University of Technology, Guangzhou, Guangdong, China.

The Second People's Hospital of Shenzhen, Shenzhen, Guangdong, China.

出版信息

J Healthc Eng. 2017;2017:1949170. doi: 10.1155/2017/1949170. Epub 2017 Jul 5.

DOI:10.1155/2017/1949170
PMID:29065575
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5516720/
Abstract

The hemiplegic rehabilitation state diagnosing performed by therapists can be biased due to their subjective experience, which may deteriorate the rehabilitation effect. In order to improve this situation, a quantitative evaluation is proposed. Though many motion analysis systems are available, they are too complicated for practical application by therapists. In this paper, a method for detecting the motion of human lower limbs including all degrees of freedom (DOFs) via the inertial sensors is proposed, which permits analyzing the patient's motion ability. This method is applicable to arbitrary walking directions and tracks of persons under study, and its results are unbiased, as compared to therapist qualitative estimations. Using the simplified mathematical model of a human body, the rotation angles for each lower limb joint are calculated from the input signals acquired by the inertial sensors. Finally, the rotation angle versus joint displacement curves are constructed, and the estimated values of joint motion angle and motion ability are obtained. The experimental verification of the proposed motion detection and analysis method was performed, which proved that it can efficiently detect the differences between motion behaviors of disabled and healthy persons and provide a reliable quantitative evaluation of the rehabilitation state.

摘要

治疗师进行的偏瘫康复状态诊断可能会受到其主观经验的影响，从而可能会降低康复效果。为了改善这种情况，提出了一种定量评估方法。尽管有许多运动分析系统可用，但对于治疗师来说，它们过于复杂，难以实际应用。本文提出了一种通过惯性传感器检测包括所有自由度（DOF）的人体下肢运动的方法，该方法可以分析患者的运动能力。与治疗师的定性评估相比，该方法适用于研究对象的任意行走方向和轨迹，并且结果没有偏差。使用简化的人体数学模型，从惯性传感器获取的输入信号计算每个下肢关节的旋转角度。最后，构建旋转角度与关节位移曲线，并获得关节运动角度和运动能力的估计值。对所提出的运动检测和分析方法进行了实验验证，证明它可以有效地检测残疾人和健康人之间的运动行为差异，并提供康复状态的可靠定量评估。

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本文引用的文献

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2
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J Biomech. 2017 May 24;57:32-38. doi: 10.1016/j.jbiomech.2017.03.015. Epub 2017 Mar 21.
3
Accuracy and repeatability of single-pose calibration of inertial measurement units for whole-body motion analysis.
下肢结局指标：脊髓损伤临床试验的考量因素
Spinal Cord. 2018 Jul;56(7):628-642. doi: 10.1038/s41393-018-0097-8. Epub 2018 Apr 27.
用于全身运动分析的惯性测量单元单姿态校准的准确性和可重复性。
Gait Posture. 2017 May;54:80-86. doi: 10.1016/j.gaitpost.2017.02.029. Epub 2017 Mar 1.
4
Inertial Sensor Based Analysis of Lie-to-Stand Transfers in Younger and Older Adults.基于惯性传感器的年轻人和老年人从躺姿到站立姿势转换的分析。
Sensors (Basel). 2016 Aug 12;16(8):1277. doi: 10.3390/s16081277.
5
Examination of Inertial Sensor-Based Estimation Methods of Lower Limb Joint Moments and Ground Reaction Force: Results for Squat and Sit-to-Stand Movements in the Sagittal Plane.基于惯性传感器的下肢关节力矩和地面反作用力估计方法的研究：矢状面深蹲和从坐到站动作的结果
Sensors (Basel). 2016 Aug 1;16(8):1209. doi: 10.3390/s16081209.
6
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Med Biol Eng Comput. 2017 Apr;55(4):609-619. doi: 10.1007/s11517-016-1537-2. Epub 2016 Jul 5.
7
Measurement of scapular dyskinesis using wireless inertial and magnetic sensors: Importance of scapula calibration.使用无线惯性和磁传感器测量肩胛运动障碍：肩胛骨校准的重要性。
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8
Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis.微软Kinect与Vicon 3D动作捕捉系统在步态分析中的比较能力
J Med Eng Technol. 2014 Jul;38(5):274-80. doi: 10.3109/03091902.2014.909540. Epub 2014 May 30.
9
Comparison of kinematic and kinetic parameters calculated using a cluster-based model and Vicon's plug-in gait.使用基于聚类的模型和Vicon插件式步态计算的运动学和动力学参数的比较。
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10
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