Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD 20993, USA.
Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Sensors (Basel). 2022 Apr 12;22(8):2953. doi: 10.3390/s22082953.
Current literature lacks a comparative analysis of different motion capture systems for tracking upper limb (UL) movement as individuals perform standard tasks. To better understand the performance of various motion capture systems in quantifying UL movement in the prosthesis user population, this study compares joint angles derived from three systems that vary in cost and motion capture mechanisms: a marker-based system (Vicon), an inertial measurement unit system (Xsens), and a markerless system (Kinect). Ten healthy participants (5F/5M; 29.6 ± 7.1 years) were trained with a TouchBionic i-Limb Ultra myoelectric terminal device mounted on a bypass prosthetic device. Participants were simultaneously recorded with all systems as they performed standardized tasks. Root mean square error and bias values for degrees of freedom in the right elbow, shoulder, neck, and torso were calculated. The IMU system yielded more accurate kinematics for shoulder, neck, and torso angles while the markerless system performed better for the elbow angles. By evaluating the ability of each system to capture kinematic changes of simulated upper limb prosthesis users during a variety of standardized tasks, this study provides insight into the advantages and limitations of using different motion capture technologies for upper limb functional assessment.
目前的文献缺乏对不同运动捕捉系统在个体执行标准任务时跟踪上肢(UL)运动的比较分析。为了更好地理解各种运动捕捉系统在定量分析假体使用者上肢运动方面的性能,本研究比较了三种系统的关节角度,这三种系统在成本和运动捕捉机制上有所不同:基于标记的系统(Vicon)、惯性测量单元系统(Xsens)和无标记系统(Kinect)。10 名健康参与者(5 名女性/5 名男性;29.6±7.1 岁)使用安装在旁路假体上的 TouchBionic i-Limb Ultra 肌电终端设备进行了训练。当参与者完成标准化任务时,他们同时被所有系统记录。计算了右肘、肩、颈和躯干自由度的均方根误差和偏差值。IMU 系统在肩部、颈部和躯干角度上产生了更准确的运动学,而无标记系统在肘部角度上表现更好。通过评估每个系统在各种标准化任务中捕捉模拟上肢假体使用者运动变化的能力,本研究深入了解了使用不同运动捕捉技术进行上肢功能评估的优缺点。