Spike detection based on normalized correlation with automatic template generation

Wen Jyi Hwang*, Szu Huai Wang, Ya Tzu Hsu


研究成果: 雜誌貢獻期刊論文同行評審

7 引文 斯高帕斯(Scopus)


A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized correlator. The detected spikes are then sorted by the OSortalgorithm. The mean of spikes of each cluster produced by the OSort algorithm is used as the template of the normalized correlator for subsequent detection. The automatic generation and updating of templates enhance the robustness of the spike detection to input trains with various spike waveforms and noise levels. Experimental results show that the proposed algorithm operating in conjunction with OSort is an efficient design for attaining high detection and classification accuracy for spike sorting.

頁(從 - 到)11049-11069
期刊Sensors (Switzerland)
出版狀態已發佈 - 2014 6月 23

ASJC Scopus subject areas

  • 分析化學
  • 生物化學
  • 原子與分子物理與光學
  • 儀器
  • 電氣與電子工程


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