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Application of sensor fusion to human locomotor system.

机译：传感器融合在人体运动系统中的应用。

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摘要

This research study proposes a multi-sensor data fusion technique to determine the complex interactions between the sensory, muscular and mechanical components of the human locomotor systems (neuromechanics). The object in this work is to demonstrate the viability in using inertial sensors for accurate gait phase determination and to present the acceleration effect specific body segment contributes in order to establish a functional gait. The current method used in determining gait phases consist of combining ground reaction force and angular data, this method is time consuming and cannot be totally reliable. We found out that gait phases can be determined distinctively by measuring vertical and horizontal accelerations (X-Y) in the sagittal plane on the foot. The foot acceleration graph show 98% unique consistency in determining the seven gait phases, during the experiment when the subjects were walking at normal; fast; even running. Note that this foot acceleration pattern was accurate for three consecutive experiments carried out on three different days under the same experimental conditions. Although the shank, thigh and hip acceleration showed uniqueness in determining the gait phases when the subjects were walking at normal speed, we discovered irregularities in the graph pattern when the subjects were running. For 132lbs, 5.6ft male subject walking at 0.9m/s we noticed that the highest negative acceleration (-0.460g, foot y-direction in the sagittal plane) occurred at heel strike and this is due to the slowing down of the muscles as the leg stabilizes from the swing phase of the sagittal plane. The corresponding vertical acceleration was 1.226g with a vertical ground reaction force of 24N. As the right leg transitions from heel strike to toe off, a maximum ground reaction force of 619N was detected. At toe-off maximum positive acceleration in the foot y-direction was recorded (0.327g) corresponding to the second highest peek of the vertical acceleration (x-direction 0.311g). We also found out that the only lowest negative acceleration in the vertical plane occurred at the cross over (initial swing) as the foot leaves the ground and the hip flexor muscles are activated to accelerate the leg forward.;In total six able bodied subjects were involved in this research (four male and two female). The experiment was performed using rate gyroscopes and linear accelerometers attached to the right hip, right thigh, right knee, right shank, right ankle and right foot. The assumption in this work is that walking pattern in able-bodied people is symmetrical, thus we assume the same acceleration conditions and gait phases detections as well is symmetrical. The subjects were allowed to walked at their normal walking speeds, however, for comparison in some cases all subjects walked at 0.9m/s and 1.08m/s. The experiment lasted for 120s when the subjects walked on an instrumented treadmill and the setup was synchronized with ground reaction force sensor, and Simi motion capture system. The sampling frequency was 280Hz for all four sensing technologies. When the subjects walked over ground, the experiments lasted for about 5sec. Outputs from the sensors were fed into fuzzy inference system, where the concept of fuzzy similarity was applied to determined the coordinated walking pattern for each subject (CWP).
机译：这项研究提出了一种多传感器数据融合技术，以确定人类运动系统（神经力学）的感觉，肌肉和机械组件之间的复杂相互作用。这项工作的目的是证明使用惯性传感器进行准确步态相位确定的可行性，并提出特定身体部位对加速作用的贡献，以建立功能性步态。目前用于确定步态相位的方法是将地面反作用力和角度数据结合起来，这种方法既费时又不能完全可靠。我们发现，步态相位可以通过测量脚矢状平面中的垂直和水平加速度（X-Y）来确定。在实验中，当受试者正常行走时，脚加速度图显示出在确定七个步态阶段时98％的唯一一致性。快速;甚至跑步。注意，该脚加速度模式对于在相同实验条件下在三个不同天进行的三个连续实验是准确的。尽管当受试者以正常速度行走时，小腿，大腿和臀部的加速度在确定步态阶段方面显示出独特性，但当受试者跑步时，我们发现图形模式存在不规则性。对于132磅，5.6英尺的男性受试者，以0.9m / s的速度行走时，我们注意到，最大的负加速度（-0.460g，矢状面的y方向）发生在脚后跟撞击时，这是由于肌肉的减速所致。腿从矢状面的摆动阶段稳定下来。相应的垂直加速度为1.226g，垂直地面反作用力为24N。当右腿从脚跟移到脚尖过渡时，检测到最大地面反作用力为619N。在脚趾离开时，记录到在脚y方向上的最大正加速度（0.327g），对应于垂直加速度的第二最高视角（x方向0.311g）。我们还发现，当脚离开地面并且髋部屈肌被激活以使腿向前加速时，垂直方向上最小的负加速度发生在交叉（初始挥杆）处。参与了这项研究（四名男性和两名女性）。使用附在右臀部，右大腿，右膝盖，右小腿，右脚踝和右脚上的速率陀螺仪和线性加速度计进行实验。这项工作的假设是健全人的行走方式是对称的，因此我们假设相同的加速条件和步态相位检测也是对称的。允许受试者以正常的步行速度行走，但是，为了进行比较，在某些情况下，所有受试者的行走速度分别为0.9m / s和1.08m / s。当受试者在仪器的跑步机上行走时，该实验持续了120秒钟，并且该设置与地面反作用力传感器和Simi运动捕捉系统同步。所有四种传感技术的采样频率均为280Hz。当受试者在地面上行走时，实验持续了大约5秒钟。传感器的输出被送入模糊推理系统，在模糊推理系统中，应用模糊相似性的概念来确定每个对象的协调步行模式（CWP）。

著录项

  • 作者

    Avor, John Kweku.;

  • 作者单位

    The University of Texas at El Paso.;

  • 授予单位 The University of Texas at El Paso.;
  • 学科 Engineering Biomedical.;Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2009
  • 页码 81 p.
  • 总页数 81
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物医学工程;无线电电子学、电信技术;
  • 关键词

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