A method of estimating lag between brain areas based on windowed harmonic wavelet transform / 生物医学工程学杂志

Aiming at local field potential, the present paper introduces a method of estimating lag of neuron activities between brain areas based on windowed Harmonic wavelet transform (WHWT). Firstly, the WHWT of signals of two brain areas are calculated. Secondly, the instantaneous amplitude of the signals is calculated and finally, these amplitudes are cross-correlated and the lag at which the cross-correlation peak occurs is determined as the lag of neurons activities. Comparing with amplitude cross-correlation based on Gabor wavelet transform (GWT) or Hilbert transform (HT), this method is more precise and efficient in estimating the directionality and lag.

A telemetery system for neural signal acquiring and processing / 生物医学工程学杂志

Recording and extracting characteristic brain signals in freely moving animals is the basic and significant requirement in the study of brain-computer interface (BCI). To record animal's behaving and extract characteristic brain signals simultaneously could help understand the complex behavior of neural ensembles. Here, a system was established to record and analyse extracellular discharge in freely moving rats for the study of BCI. It comprised microelectrode and micro-driver assembly, analog front end (AFE), programmer system on chip (PSoC), wireless communication and the LabVIEW used as the platform for the graphic user interface.

Decoding algorithm of neural spike signals in brain-computer interface / 国际生物医学工程杂志

The core problem of the brain-computer interface (BCI) based on neural signal is estimating neural firing rate from a spike train and then using neural population decoding algorithm to decode movement trajectory.In this artical, we review the theoretical basis of both classic and current firing rate estimations and compare the advantages and drawbacks of these methods. At the same time we also review the decoding algorithm which using neural firing rate to decode movement trajectory in brain- computer interface: population vector algorithm, linear filter and kalman filter. At last, some results applying these estimators of firing rate to decode arm movement in BCI are introduced. The results show apparently different performance of the different firing rate estimators, while minimal differences are observed in the actual application of BCI.

Wavelet-based denoising algorithm for EEG signals--using scale dependent threshold based on median / 生物医学工程学杂志

We have brought forward a wavelet-based algorithm for electroencephalograph (EEG) signals--using scale dependent threshold based on median. In comparison with the universal threshold and Sure threshold, our proposed threshold, which is adaptive to the subband noise signals, preserves the noise free reconstruction property and takes lower risk than does the universal threshold; and our proposed threshold overcomes the drawback of Sure threshold. Evidently, the scale dependent threshold based on median is computationally simple and can obtain higher singal-to-noise ratio (SNR) it outperforms the universal threshold and Sure threshlold.