Betker Aimee L, Moussavi Zahra M K, Szturm Tony
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
IEEE Trans Biomed Eng. 2006 Apr;53(4):686-93. doi: 10.1109/TBME.2006.870222.
In order to maintain postural stability, the central nervous system must maintain equilibrium of the total center of body mass (COM) in relation to its base of support. Thus, the trajectory of the COM provides an important measure of postural stability. Three different models were developed to estimate the COM and the results tested on 16 subjects: namely a neural network, an adaptive fuzzy interface system and a hybrid genetic algorithm sum-of-sines model. The inputs to the models were acquired via two accelerometers, one representing the trunk segment placed on T2 and the second representing the limb segment placed on the shank below the knee joint. The portability, ease of use and low cost (compared with video motion analysis systems) of the accelerometers increases the range of clinics to which the system will be available. The subjects performed a multisegmental movement task on fixed and foam surfaces, thus covering a relatively wide dynamic scope. The results are encouraging for obtaining COM estimates that have clinical applications; the genetic sum-of-sines model was found to be superior when compared to the other two models.
为了维持姿势稳定性，中枢神经系统必须相对于支撑基础保持身体总重心（COM）的平衡。因此，COM的轨迹提供了姿势稳定性的重要度量。开发了三种不同的模型来估计COM，并在16名受试者上对结果进行了测试：即神经网络、自适应模糊接口系统和混合遗传算法正弦和模型。模型的输入通过两个加速度计获取，一个代表放置在T2的躯干部分，另一个代表放置在膝关节下方小腿上的肢体部分。加速度计的便携性、易用性和低成本（与视频运动分析系统相比）扩大了该系统可应用的临床范围。受试者在固定表面和泡沫表面上执行多节段运动任务，从而涵盖了相对较宽的动态范围。这些结果对于获得具有临床应用价值的COM估计值是令人鼓舞的；与其他两个模型相比，遗传正弦和模型被发现更具优势。
