Detection of neural spikes based on the combination of wavelet transforms and nonlinear energy operator.
- Author:
Xinwen LIU
1
;
Zhiyu QIAN
;
Huinan WANG
;
Tianming YANG
Author Information
1. Dapartment of Biomedical Engineering, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. lxwlq2003@163.com
- Publication Type:Journal Article
- MeSH:
Action Potentials;
physiology;
Algorithms;
Humans;
Microelectrodes;
Neural Conduction;
physiology;
Neurons;
physiology;
Nonlinear Dynamics;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2007;24(5):981-985
- CountryChina
- Language:Chinese
-
Abstract:
The microelectrode recordings of neuron discharge, which contain noises, are very complex and apt to be disturbed by many factors during the microelectrode-guided stereotactic operations. The varying signal-to-noise ratios are obstacles to the analysis of neural spikes. A novel method based on a combination of wavelet-based and non-linear energy operator is presented for the detection of neural spikes. The method is tested for neural signals of different patients and various SNR values. The results demonstrate its performance for successful detection and effective extraction of the waveform of neural spikes.
