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Progress and Challenges in Physiological Artifacts' Detection in Electroencephalographic Readings.

Amandeep Bisht1, Preeti Singh1, Chamandeep Kaur1

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Summary
This summary is machine-generated.

This review examines electroencephalographic (EEG) artifact removal techniques, finding hybrid methods offer better performance but increase complexity. Effective processing requires balancing performance, time, and computational demands for future research.

Keywords:
EEGEMGEOGartifact removalphysiological artifactssignal processing

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electroencephalographic (EEG) recordings monitor cortical neural activity over time.
  • Physiological artifacts in EEG, while challenging to avoid, are crucial for human-computer interfaces.
  • Effective pre-processing of EEG data for artifact handling remains an active research area.

Purpose of the Study:

  • To provide a comprehensive review of current physiological artifact removal techniques for EEG signals.
  • To analyze the advantages and disadvantages of traditional and multistage artifact removal methods.
  • To discuss available EEG datasets and current trends in EEG signal processing.

Main Methods:

  • Systematic review of single-stage and multistage artifact removal techniques.
  • Comparative analysis of traditional and hybrid artifact removal approaches.
  • Examination of performance metrics and computational complexity.

Main Results:

  • Single-channel techniques reduce computational time but are less effective for physiological artifacts.
  • Hybrid techniques enhance performance by integrating features but increase time consumption and complexity.
  • A trade-off between performance, time, and computational complexity is observed in artifact processing.

Conclusions:

  • Effective EEG artifact processing necessitates balancing performance, time, and computational complexity.
  • Future research should focus on optimizing artifact handling techniques to reduce expert burden.
  • This review aims to guide researchers in developing advanced artifact mitigation strategies.