title: Curve fitting of spikes in neural signals.
abstract: Find an optimal function model of spikes of high signal-to-noise ratio (SNR) spontaneous signals in the spinal cord of a rat, and use it to recognize the patterns of spikes of low SNR signals in the sciatic nerve of the rat.
  
  
  METHODS
  Firstly, several function models of spikes of high SNR spontaneous signals in the spinal cord of a rat are calculated under the rule of least square. By choosing an optimal function model based on minimum standard deviation (SD) of error of fitting, it is contrasted with the waveform of classical action potential (AP). Then, this model is used as a pattern to recognize spikes of low SNR signals in the sciatic nerve of the rat.
  
  
  RESULTS
  The optimal function model of spikes of high SNR spontaneous signals in the spinal cord of a rat is a proportional model whose numerator is a 5-order polynomial while the denominator is a 4-order polynomial. The waveform of a typical AP can be obtained from this model. It can also achieve good performance by recognizing the pattern of spikes of signals whose SNR is lower than 8 dB in sciatic nerve of the rat.
authors: State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, China. dongchen@seu.edu.cn
authors: Dong
authors: D
authors: Chen
authors: Xiaoying
authors: X
authors: Lu
authors: Zhigong
authors: Z
authors: Wang
authors: Haixian
authors: H
authors: Pan
mesh_terms: D000200:Action Potentials; D009474:Neurons / Q000502:physiology*