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Measurement of body joint angles for physical therapy based on mean shift tracking using two low cost Kinect images

机译:基于平均移位跟踪的物理疗法测量使用两个低成本kinect图像的物理疗法

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Range of motion (ROM) is commonly used to assess a patient's joint function in physical therapy. Because motion capture systems are generally very expensive, physical therapists mostly use simple rulers to measure patients' joint angles in clinical diagnosis, which will suffer from low accuracy, low reliability, and subjective. In this study we used color and depth image feature from two sets of low-cost Microsoft Kinect to reconstruct 3D joint positions, and then calculate moveable joint angles to assess the ROM. A Gaussian background model is first used to segment the human body from the depth images. The 3D coordinates of the joints are reconstructed from both color and depth images. To track the location of joints throughout the sequence more precisely, we adopt the mean shift algorithm to find out the center of voxels upon the joints. The two sets of Kinect are placed three meters away from each other and facing to the subject. The joint moveable angles and the motion data are calculated from the position of joints frame by frame. To verify the results of our system, we take the results from a motion capture system called VICON as golden standard. Our 150 test results showed that the deviation of joint moveable angles between those obtained by VICON and our system is about 4 to 8 degree in six different upper limb exercises, which are acceptable in clinical environment.
机译:运动范围(ROM)通常用于评估物理治疗中的患者的关节功能。由于运动捕获系统通常非常昂贵,因此物理治疗师主要使用简单的统治者来测量临床诊断中的患者的关节角度,这将遭受低精度,低可靠性和主观性。在本研究中,我们使用两组低成本Microsoft Kinect的颜色和深度图像特征来重建3D关节位置,然后计算可移动的关节角度以评估ROM。首先使用高斯背景模型来将人体从深度图像分割。关节的3D坐标从两种颜色和深度图像重建。为了更确切地说,在整个序列中跟踪关节的位置,我们采用平均移位算法在关节上找出体素的中心。这两套Kinect距离彼此有三米,并面向主题。从接头框架的位置通过框架计算联合可移动角和运动数据。要验证我们的系统结果,我们将结果从名为VICON的运动捕获系统中作为Golden Standard。我们的150个测试结果表明,在vicon和我们的系统中获得的关节可移动角度在六种不同的上肢锻炼中的偏差约为4至8度,这在临床环境中是可接受的。

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