Adaptive threshold spike detection using stationary wavelet transform for neural recording implants

@article{Yang2010AdaptiveTS,
  title={Adaptive threshold spike detection using stationary wavelet transform for neural recording implants},
  author={Yuning Yang and Awais M. Kamboh and J. Mason Andrew},
  journal={2010 Biomedical Circuits and Systems Conference (BioCAS)},
  year={2010},
  pages={9-12}
}
Spike detection is an essential first step in the analysis of neural recording signals. A new spike detection hardware architecture combining absolute threshold method and stationary wavelet transform (SWT) is described. The method enables spike detection with 90% accuracy even when the signal-to-noise is −1dB. A noise monitoring block was implemented to automatically calculate the appropriate threshold value for spike detection, and the system then chooses either absolute threshold method or… CONTINUE READING
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A low-power integrated circuit for adaptive detection of action potentials in noisy signals,

  • R. R. Harrison
  • IEEE Eng. in Medicine and Biology Conf.,
  • 2003
Highly Influential
3 Excerpts

and K

  • C. Joon Hwan, J. Hae Kyung
  • Taejeong, ‘‘A new action potential detector using…
  • 2006
1 Excerpt

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