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Fuzzy-Logic-Based Terrain Identification with Multisensor Fusion for Transtibial Amputees

机译:基于模糊逻辑的跨传感器截肢多传感器融合地形识别

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摘要

Terrain identification is essential for the control of robotic transtibial prostheses to realize smooth locomotion transitions. In this paper, we present a real-time fuzzy-logic-based terrain identification method with multisensor fusion. Five locomotion features, including the foot inclination angle at the first strike, the shank inclination angle at the first strike, foot strike sequence, the foot inclination angle at mid-stance, and the shank inclination angle at toe-off, are used to identify different terrains and terrain transitions. These features are measured by the fusion of two triaxis gyroscopes, two triaxis accelerometers, two force sensitive resistors, and a timer, which can be embedded into the prosthesis. Based on these features, a fuzzy-logic-based identification method is proposed to identify five terrains: level ground, stair ascent, stair descent, ramp ascent, and ramp descent. Moreover, a transition constraint function is developed to improve the identification performance. The execution time of the identification method is 0.79 ms 0.02 ms (mean standard error of mean) and continuous terrain identification results show that the method can be operated online in real time. The average identification accuracy of 98.74% 0.32% is obtained from experiments with six able-bodied and three amputee subjects during steady locomotion periods (no terrain transition). In locomotion transition periods, all the eight transitions we studied are correctly identified and the average identification delay is 9.06% 3.46% of one gait cycle.
机译:地形识别对于控制机器人胫骨假体以实现平滑的运动过渡至关重要。在本文中,我们提出了一种基于实时模糊逻辑的多传感器融合地形识别方法。五个运动特征包括:第一次打击时的脚倾斜角度,第一次打击时的小腿倾斜角度,脚部打击顺序,中间姿势下的脚倾斜角度以及脚趾离开时的小腿倾斜角度不同的地形和地形过渡。这些功能是通过将两个三轴陀螺仪,两个三轴加速度计,两个力敏电阻和一个计时器融合在一起来测量的,这些计时器可以嵌入假体中。基于这些特征,提出了一种基于模糊逻辑的识别方法来识别五个地形:水平地面,楼梯上升,楼梯下降,坡道上升和坡道下降。此外,开发了过渡约束函数以提高识别性能。识别方法的执行时间为0.79 ms 0.02 ms(均值的平均标准误差),连续的地形识别结果表明该方法可以实时在线运行。通过在稳定的运动周期(无地形过渡)中对6名身体健全的受试者和3名截肢者进行的实验获得了98.74%0.32%的平均识别准确率。在运动过渡期,我们研究的所有八个过渡均已正确识别,平均识别延迟为一个步态周期的9.06%和3.46%。

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