Muscle artifacts in multichannel EEG: Characteristics and reduction

作者：Ma Junshui^*; Tao Peining; Bayram Sevinc; Svetnik Vladimir

来源：Clinical Neurophysiology, 2012, 123(8): 1676-1686.

DOI：10.1016/j.clinph.2011.11.083

• Electroencephalography (EEG)
• Muscle artifacts
• Independent Component Analysis (ICA)
• Muscle signal characteristics
• Clinical EEG
• Clinical trial
• Pharmaco-EEG
• Drug effect
• Muscle signals
• Muscle characteristics

Objective: To study the characteristics of unintentional muscle activities in clinical EEG, and to develop a high-throughput method to reduce them for better revealing drug or biological effects on EEG.
Methods: Two clinical EEG datasets are involved. Pure muscle signals are extracted from EEG using Independent Component Analysis (ICA) for studying their characteristics. A high-throughput method called ICA-SR is introduced based on a new feature named Spectral Ratio (SR).
Results: The spectral and temporal characteristics of the muscle artifacts are illustrated using representative muscle signals. The spatial characteristics are presented at both the group-and the subject-level, and are consistent under three different electrode reference methodologies. Objectively compared with an existing method, ICA-SR is shown to reduce more artifacts, while introduce less distortion to EEG. Its effectiveness is further demonstrated in real clinical EEG with the help of a CO2-inhalation EEG recording session.
Conclusion: The characteristics of unintentional muscle activities align with the reported characteristics of controlled muscle activities. Artifact spatial characteristics can be EEG equipment dependent. The ICA-SR method can effectively and efficiently process clinical EEG.
Significance: Armed with advanced signal processing algorithms, this study expands our knowledge of muscle activities in EEG from muscle-controlled experiments to general clinical trials. The ICA-SR method provides an urgently needed solution with validated performance for efficiently processing large volumes of clinical EEG.

• 出版日期2012-8