Hon Tsz K, Subramaniam Suba R, Georgakis Apostolos
Division of Engineering, King's College London, WC2R 2LS, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4036-9. doi: 10.1109/IEMBS.2010.5628013.
We present an advanced denoising method for non-stationary biomechanical signals with the aim of accurately estimating their second derivative (acceleration). The proposed algorithm is based on the short-time Fourier transform (STFT) representation of the signal and its subsequent modification by means of a suitable time-varying filtering function. The application of the method to experimentally acquired biomechanical signals demonstrated that the proposed algorithm is more robust against noise and achieves a more accurate acceleration-peak estimation as compared to commonly used conventional low-pass filtering.
我们提出了一种用于非平稳生物力学信号的先进去噪方法,目的是准确估计其二阶导数(加速度)。所提出的算法基于信号的短时傅里叶变换(STFT)表示,并通过合适的时变滤波函数对其进行后续修改。将该方法应用于实验获取的生物力学信号表明,与常用的传统低通滤波相比,所提出的算法对噪声更具鲁棒性,并且能够实现更准确的加速度峰值估计。