首页> 外文OA文献 >DEVELOPMENT AND EVALUATION OF AN ENHANCED WEIGHTED FREQUENCY FOURIER LINEAR COMBINER ALGORITHM USING BANDWIDTH INFORMATION IN JOYSTICK OPERATION
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DEVELOPMENT AND EVALUATION OF AN ENHANCED WEIGHTED FREQUENCY FOURIER LINEAR COMBINER ALGORITHM USING BANDWIDTH INFORMATION IN JOYSTICK OPERATION

机译:操纵杆操作中带宽信息的加权加权傅立叶线性组合器算法的开发与评估

摘要

Driving an electric powered wheelchair with a joystick is a complex task for the user who has a pathological tremor. Most powered wheelchairs use simple filtering algorithms to reduce the effects of tremor. These algorithms work well in most situations, but fall short in others. This study addresses the problems associated with pathological tremor associated with Cerebral Palsy (CP). The purpose of this study is to know more about the characteristics of CP tremor with time-frequency analysis and to improve joystick control with other advanced filtering algorithms.We used three estimated parameters, instantaneous frequency (IF), instantaneous bandwidth (IB), and instantaneous power (IP), from a time-frequency distribution (TFD), to characterize CP tremor and to tune a notch filter for canceling CP tremor noise from a joystick signal in an off-line experiment. From the off-line experiment, we showed that our CP tremor suppression system performed better with the information of IF, IB, and IP. We also conducted an on-line experiment in which we introduced two tremor suppression algorithms. One is Weighted-frequency Fourier Linear Combiner (WFLC), which estimates a tremor frequency and its weight, and the other is our modified WFLC, which adjusts a notch width with respect to the bandwidth of CP tremor additionally. We implemented both algorithms on the virtual wheelchair driving test along with a commonly used low-pass filter. We recruited ten subjects who have CP tremor and tested them in a virtual wheelchair driving environment. We observed that CP tremors in the joystick signal were suppressed greatly by the new filtering algorithms. We learned that the time-delay of a low-pass filter caused serious performance degradation of wheelchair driving and observed that most subjects performed better with new filtering methods than with a low-pass filter. Furthermore, since our modified WFLC algorithm was able to reduce more CP tremor noise than WFLC, we learned that it is important to consider the bandwidth information of CP tremor when designing a tremor suppression system.
机译:对于患有病理性震颤的使用者来说,用操纵杆驾驶电动轮椅是一项复杂的任务。大多数电动轮椅使用简单的过滤算法来减少震颤的影响。这些算法在大多数情况下都可以正常工作,但在其他情况下则不够。这项研究解决了与脑瘫(CP)相关的病理性震颤相关的问题。这项研究的目的是通过时频分析来了解CP震颤的特征,并通过其他先进的滤波算法来改善操纵杆控制。我们使用了三个估计参数:瞬时频率(IF),瞬时带宽(IB)和来自时频分布(TFD)的瞬时功率(IP),用于表征CP震颤并调整陷波滤波器,以在离线实验中从操纵杆信号中消除CP震颤噪声。通过离线实验,我们证明了CP震颤抑制系统在IF,IB和IP的信息下表现更好。我们还进行了在线实验,其中我们介绍了两种震颤抑制算法。一个是加权频率傅里叶线性组合器(WFLC),它估计震颤频率及其权重,另一个是我们的改进型WFLC,它相对于CP震颤的带宽额外调整陷波宽度。我们在虚拟轮椅驾驶测试中同时使用了两种算法以及常用的低通滤波器。我们招募了10名患有CP震颤的受试者,并在虚拟轮椅驾驶环境中对其进行了测试。我们观察到,新的滤波算法极大地抑制了操纵杆信号中的CP震颤。我们了解到,低通滤波器的时间延迟导致轮椅驾驶的性能严重下降,并且观察到大多数受试者使用新的滤波方法比使用低通滤波器表现更好。此外,由于我们改进的WFLC算法比WFLC能够减少更多的CP震颤噪声,因此我们了解到在设计震颤抑制系统时考虑CP震颤的带宽信息非常重要。

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    Nho Wonchul;

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  • 年度 2006
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