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.