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Spike Detection Based on the Adaptive Time–Frequency Analysis

Circuits, Systems, and Signal Processing volume 39, pages 5656–5680 (2020)Cite this article

Abstract

This paper presents a novel spike detection algorithm in nonstationary signals using a time–frequency (t–f) approach. The proposed algorithm exploits the direction of signal energy in the t–f domain to detect spikes in the presence of high-frequency nonstationary signals even at low signal-to-noise ratio. The performance of the proposed approach is evaluated using synthetic nonstationary signals, synthesized signals mimicking electroencephalogram (EEG) signals, manually selected segments of speech signals, and manually selected segments of real EEG signals. The statistical measures, such as hit rate and precision, are used to demonstrate that the proposed algorithm performs better than other widely used algorithms, such as the smoothed nonlinear energy detector.

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Authors and Affiliations

  1. Department of Information Technology, University of Human Development, Sulaymaniyah, Iraq

    Mokhtar Mohammadi

  2. Electrical Engineering, Foundation University, Islamabad, Pakistan

    Nabeel Ali Khan

  3. Department of Computer Engineering and Information Technology, Shahrood University of Technology, Shahrood, Iran

    Hamid Hassanpour

  4. Department of Communication and Computer Engineering, College of Engineering, Cihan University-Erbil, Erbil, Iraq

    Adil Hussien Mohammed

Authors
  1. Mokhtar Mohammadi
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  2. Nabeel Ali Khan
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  3. Hamid Hassanpour
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  4. Adil Hussien Mohammed
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Correspondence to Mokhtar Mohammadi.

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Mohammadi, M., Ali Khan, N., Hassanpour, H. et al. Spike Detection Based on the Adaptive Time–Frequency Analysis. Circuits Syst Signal Process 39, 5656–5680 (2020). https://doi.org/10.1007/s00034-020-01427-5

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