An approach to sensor fusion in medical robots

J. Avor, T. Sarkodie-Gyan
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引用次数: 15

Abstract

This paper 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). We investigated the use of an array of accelerometers, rate gyroscopes, force plates and electromyogram for the assessment of x-y-z components of the hip, thigh, shank and foot acceleration and velocity in the sagittal plane. The objective here is to determine the impact factor each body segment's acceleration has in terms of producing a functional gait. Six able-bodied subjects were employed in this experiment; and subject walked at three different speeds and his/her dynamic/kinematic behaviors of the lower limb recorded with the sensors afore mentioned. Eight distinct gait variability for each subject recorded was detected by our sensing system. Fuzzy fusion technique was employed to evaluate the empirical results and the output matrix shows the relation between the body segments in question in terms of their x-y-z acceleration components. The implementation of this fusion matrix will enhance modeling and building medical robots intended for paraplegic rehabilitation as well as intelligent mobile robots for effective industrial manufacturing.
一种医疗机器人传感器融合方法
本文提出了一种多传感器数据融合技术来确定人体运动系统的感觉、肌肉和机械成分之间的复杂相互作用(神经力学)。我们研究了使用一系列加速度计、速率陀螺仪、力板和肌电图来评估髋关节、大腿、小腿和足部矢状面加速度和速度的x-y-z分量。这里的目标是确定每个身体部分的加速度在产生功能性步态方面的影响因素。本实验采用6名身体健全的受试者;受试者以三种不同的速度行走,用上述传感器记录其下肢动态/运动学行为。我们的传感系统检测到每个受试者记录的八种不同的步态变异性。采用模糊融合技术对经验结果进行评价,输出矩阵显示了所讨论的身体部分之间的x-y-z加速度分量的关系。该融合矩阵的实现将增强建模和构建用于截瘫康复的医疗机器人以及用于有效工业制造的智能移动机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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