Centre for Rehabilitation and Human Performance Research, University of Salford, UK.
J Biomech. 2009 Dec 11;42(16):2678-85. doi: 10.1016/j.jbiomech.2009.08.004. Epub 2009 Sep 27.
A new method for estimating knee joint flexion/extension angles from segment acceleration and angular velocity data is described. The approach uses a combination of Kalman filters and biomechanical constraints based on anatomical knowledge. In contrast to many recently published methods, the proposed approach does not make use of the earth's magnetic field and hence is insensitive to the complex field distortions commonly found in modern buildings. The method was validated experimentally by calculating knee angle from measurements taken from two IMUs placed on adjacent body segments. In contrast to many previous studies which have validated their approach during relatively slow activities or over short durations, the performance of the algorithm was evaluated during both walking and running over 5 minute periods. Seven healthy subjects were tested at various speeds from 1 to 5 mile/h. Errors were estimated by comparing the results against data obtained simultaneously from a 10 camera motion tracking system (Qualysis). The average measurement error ranged from 0.7 degrees for slow walking (1 mph) to 3.4 degrees for running (5 mph). The joint constraint used in the IMU analysis was derived from the Qualysis data. Limitations of the method, its clinical application and its possible extension are discussed.
描述了一种从段加速度和角速度数据估计膝关节屈伸角度的新方法。该方法结合了卡尔曼滤波器和基于解剖学知识的生物力学约束。与许多最近发表的方法不同，所提出的方法不利用地球磁场，因此对现代建筑物中常见的复杂磁场扭曲不敏感。该方法通过从放置在相邻体段上的两个 IMU 测量值计算膝关节角度来进行实验验证。与许多先前的研究相比，这些研究在相对较慢的活动或较短的时间内验证了他们的方法，该算法的性能在 5 分钟的步行和跑步期间进行了评估。7 名健康受试者在 1 至 5 英里/小时的不同速度下进行了测试。通过将结果与同时从 10 个摄像机运动跟踪系统（Qualysis）获得的数据进行比较来估计误差。平均测量误差范围从缓慢行走（1 英里/小时）的 0.7 度到跑步（5 英里/小时）的 3.4 度。在 IMU 分析中使用的关节约束是从 Qualysis 数据中得出的。讨论了该方法的局限性、其临床应用及其可能的扩展。
