Spyers-Ashby J M, Bain P G, Roberts S J
Department of Research, Royal Hospital for Neuro-disability, London, UK.
J Neurosci Methods. 1998 Aug 31;83(1):35-43. doi: 10.1016/s0165-0270(98)00064-8.
This review outlines the theory of spectral estimation techniques based on the fast Fourier transform (FFT) and autoregressive (AR) model and their application to the analysis of human tremor data. Two FFT-based spectral estimation techniques are presented, the Blackman-Tukey and periodogram methods. Factors that influence the quality of spectral estimates are discussed including the choice of windowing function. The theory of parametric modelling is introduced and AR modelling identified as the technique best suited to the analysis of tremor data. The processes of parameter estimation and model order selection are described. The theory of AR spectral estimation is outlined and differences between the AR and FFT-based spectral estimates are summarised. A brief guide to the implementation of FFT-based and AR spectral estimation techniques is given concentrating on data analysis packages that require little or no programming expertise. This review concludes that the AR modelling approach can produce tremor spectra that are superior to those from FFT-based methods for short data sequences. Although the spectral estimates are improved, the benefits of AR modelling for providing information about the physiological mechanisms of tremor generation are not yet clear.
本综述概述了基于快速傅里叶变换（FFT）和自回归（AR）模型的谱估计技术理论及其在人体震颤数据分析中的应用。介绍了两种基于FFT的谱估计技术，即布莱克曼 - 图基法和周期图法。讨论了影响谱估计质量的因素，包括窗函数的选择。介绍了参数建模理论，并确定AR建模是最适合震颤数据分析的技术。描述了参数估计和模型阶数选择的过程。概述了AR谱估计理论，并总结了AR和基于FFT的谱估计之间的差异。给出了基于FFT和AR谱估计技术实现的简要指南，重点介绍了几乎不需要编程专业知识的数据分析软件包。本综述得出结论，对于短数据序列，AR建模方法可以产生优于基于FFT方法的震颤谱。尽管谱估计有所改进，但AR建模在提供有关震颤产生生理机制信息方面的益处尚不清楚。
