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用于机器人应用的生理震颤多步预测

Multi-step prediction of physiological tremor for robotics applications.

作者信息

Veluvolu K C, Tatinati S, Hong S M, Ang W T

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5075-8. doi: 10.1109/EMBC.2013.6610689.

Abstract

The performance of surgical robotic devices in real-time mainly depends on phase-delay in sensors and filtering process. A phase delay of 16-20 ms is unavoidable in these robotics procedures due to the presence of hardware low pass filter in sensors and pre-filtering required in later stages of cancellation. To overcome this phase delay, we employ multi-step prediction with band limited multiple Fourier linear combiner (BMFLC) and Autoregressive (AR) methods. Results show that the overall accuracy is improved by 60% for tremor estimation compared to single-step prediction methods in the presence of phase delay. Experimental results with the proposed methods for 1-DOF tremor estimation highlight the improvement.

摘要

手术机器人设备的实时性能主要取决于传感器和滤波过程中的相位延迟。由于传感器中存在硬件低通滤波器以及在后期消除阶段需要进行预滤波,在这些机器人手术过程中16 - 20毫秒的相位延迟是不可避免的。为了克服这种相位延迟,我们采用了带限多傅里叶线性组合器(BMFLC)和自回归(AR)方法的多步预测。结果表明,在存在相位延迟的情况下,与单步预测方法相比,震颤估计的整体准确率提高了60%。用于一自由度震颤估计的所提方法的实验结果突出了这种改进。

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