Department of Pediatric Orthopaedics and Traumatology, University Children's Hospital Zurich, Zurich, Switzerland; Department of Pediatric Orthopaedics, University Children's Hospital Basel, Basel, Switzerland.
Department of Pediatric Orthopaedics and Traumatology, University Children's Hospital Zurich, Zurich, Switzerland; University of Zurich, Zurich, Switzerland.
Gait Posture. 2021 Feb;84:389-394. doi: 10.1016/j.gaitpost.2021.01.005. Epub 2021 Jan 12.
Postural balance can be considered a conjoined parameter of gross motor performance. It is acquired in early childhood and honed until adolescence, but may also be influenced by various conditions. A simplified clinical assessment of balance and posture could be helpful in monitoring motor development or therapy particularly in pediatric patients. While analogue scales are considered unprecise and lab-based force-plate posturography lacks accessibility, we propose a novel kinematic balance assessment based on markerless 3D sensor technology.
Can balance and posture be assessed by tracking kinematic data using a single 3D motion tracking camera and are the results representative of normal motor development in a healthy pediatric cohort?
A proprietary algorithm was developed and tested that uses skeletal data from the Microsoft Kinect™ V2 3D motion capture camera to calculate and track the center of mass in real time during a set of balance tasks. The algorithm tracks the distance of the COM traveled over time to calculate a balance score (COM speed). For this study, 432 school children aged 4-18 years performed 5 balance tasks and the resulting balance scores were analyzed and correlated with demographic data.
Preliminary experiments demonstrated that the system was able to reliably detect differences in COM speed during different balance tasks. The method showed moderate correlation with age and sex. Athletic activity positively correlated with balance skill in the age group < 8 years, but not in older children. Body mass appeared not to be correlated with balance ability.
This study demonstrates that markerless 3D motion analysis can be used for the clinical assessment of coordination and balance and could potentially be used to monitor gross motor performance at the point-of-care.
姿势平衡可以被视为粗大运动表现的一个综合参数。它在儿童早期获得,并在青春期前不断完善,但也可能受到各种条件的影响。简化的平衡和姿势临床评估可能有助于监测运动发育或治疗,特别是在儿科患者中。虽然模拟量表被认为不够精确,而基于实验室的测力台足动描记术缺乏可及性,但我们提出了一种基于无标记 3D 传感器技术的新运动平衡评估方法。
是否可以通过使用单个 3D 运动跟踪摄像机跟踪运动学数据来评估平衡和姿势,并且结果是否代表健康儿科队列中的正常运动发育?
开发并测试了一种专有算法,该算法使用 Microsoft Kinect™ V2 3D 运动捕捉摄像机的骨骼数据来实时计算和跟踪一组平衡任务中的质心。该算法跟踪质心随时间移动的距离以计算平衡得分(质心速度)。在这项研究中,432 名 4-18 岁的学龄儿童完成了 5 项平衡任务,分析并关联了平衡得分与人口统计学数据。
初步实验表明,该系统能够可靠地检测不同平衡任务中质心速度的差异。该方法与年龄和性别具有中等相关性。在年龄<8 岁的儿童中,体育活动与平衡技能呈正相关,但在年龄较大的儿童中则不然。体重似乎与平衡能力无关。
这项研究表明,无标记 3D 运动分析可用于协调和平衡的临床评估,并且可能用于在床边监测粗大运动表现。