Xu Xu, McGorry Raymond W
Liberty Mutual Research Institute for Safety, 71 Frankland Road, Hopkinton, MA 01748, USA.
Liberty Mutual Research Institute for Safety, 71 Frankland Road, Hopkinton, MA 01748, USA.
Appl Ergon. 2015 Jul;49:47-54. doi: 10.1016/j.apergo.2015.01.005. Epub 2015 Feb 17.
The Kinect™ sensor released by Microsoft is a low-cost, portable, and marker-less motion tracking system for the video game industry. Since the first generation Kinect sensor was released in 2010, many studies have been conducted to examine the validity of this sensor when used to measure body movement in different research areas. In 2014, Microsoft released the computer-used second generation Kinect sensor with a better resolution for the depth sensor. However, very few studies have performed a direct comparison between all the Kinect sensor-identified joint center locations and their corresponding motion tracking system-identified counterparts, the result of which may provide some insight into the error of the Kinect-identified segment length, joint angles, as well as the feasibility of adapting inverse dynamics to Kinect-identified joint centers. The purpose of the current study is to first propose a method to align the coordinate system of the Kinect sensor with respect to the global coordinate system of a motion tracking system, and then to examine the accuracy of the Kinect sensor-identified coordinates of joint locations during 8 standing and 8 sitting postures of daily activities. The results indicate the proposed alignment method can effectively align the Kinect sensor with respect to the motion tracking system. The accuracy level of the Kinect-identified joint center location is posture-dependent and joint-dependent. For upright standing posture, the average error across all the participants and all Kinect-identified joint centers is 76 mm and 87 mm for the first and second generation Kinect sensor, respectively. In general, standing postures can be identified with better accuracy than sitting postures, and the identification accuracy of the joints of the upper extremities is better than for the lower extremities. This result may provide some information regarding the feasibility of using the Kinect sensor in future studies.
微软发布的Kinect™传感器是一款面向视频游戏行业的低成本、便携式且无需标记的运动跟踪系统。自2010年第一代Kinect传感器发布以来,已经开展了许多研究来检验该传感器在不同研究领域用于测量身体运动时的有效性。2014年,微软发布了供计算机使用的第二代Kinect传感器,其深度传感器具有更高的分辨率。然而,很少有研究对所有Kinect传感器识别的关节中心位置与其相应的运动跟踪系统识别的对应位置进行直接比较,其结果可能会为Kinect识别的节段长度、关节角度的误差以及将逆动力学应用于Kinect识别的关节中心的可行性提供一些见解。本研究的目的是首先提出一种将Kinect传感器的坐标系相对于运动跟踪系统的全局坐标系进行对齐的方法,然后检验在日常活动的8种站立姿势和8种坐姿期间Kinect传感器识别的关节位置坐标的准确性。结果表明,所提出的对齐方法可以有效地将Kinect传感器相对于运动跟踪系统进行对齐。Kinect识别的关节中心位置的准确程度取决于姿势和关节。对于直立站立姿势,第一代和第二代Kinect传感器在所有参与者和所有Kinect识别的关节中心上的平均误差分别为76毫米和87毫米。一般来说,站立姿势的识别准确性优于坐姿,并且上肢关节的识别准确性优于下肢关节。这一结果可能会为未来研究中使用Kinect传感器的可行性提供一些信息。
Int J Occup Saf Ergon. 2017-12
PLoS One. 2018-8-24
J Med Eng Technol. 2014-7
Annu Int Conf IEEE Eng Med Biol Soc. 2016-8
IEEE Trans Cybern. 2013-8-22
Sensors (Basel). 2025-1-22
BMC Med Inform Decis Mak. 2022-7-3
Sensors (Basel). 2022-4-2
Sensors (Basel). 2022-3-15
Top Spinal Cord Inj Rehabil. 2021
Int J Environ Res Public Health. 2021-8-9