A Review on Time-domain Peak Detection and Classification Algorithms for Electroencephalogram Signals

Authors

  • Asrul Adam
  • Ammar Faiz Zainal Abidin
  • Zulkifli Md Yusof
  • Norrima Mokhtar
  • Mohd Ibrahim Shapiai

DOI:

https://doi.org/10.15282/mekatronika.v1i2.4995

Keywords:

EEG signals processing, peak detection, peak classification, EEG peak model

Abstract

In this paper, the developments in the field of EEG signals peaks detection and classification methods based on time-domain analysis have been discussed. The use of peak classification algorithm has end up the most significant approach in several applications. Generally, the peaks detection and classification algorithm is a first step in detecting any event-related for the variation of signals. A review based on the variety of peak models on their respective classification methods and applications have been investigated. In addition, this paper also discusses on the existing feature selection algorithms in the field of peaks classification.

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Published

2019-07-15

How to Cite

[1]
A. Adam, A. F. Zainal Abidin, Z. Md Yusof, N. Mokhtar, and M. I. Shapiai, “A Review on Time-domain Peak Detection and Classification Algorithms for Electroencephalogram Signals”, Mekatronika: J. Intell. Manuf. Mechatron., vol. 1, no. 2, pp. 115–121, Jul. 2019.

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Section

Original Article

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