Frontal Alpha EEG Asymmetry Variation of Depression Patients Assessed by Entropy Measures and Lemple–Ziv Complexity

Abstract

Purpose

As depression has been a major contributor to the global disease burden, objective and effective computer-aided diagnosis has become an urgent problem. This study aims to assess the frontal asymmetry variation of alpha electroencephalography (EEG) in different severity depression patients and to find promising biomarkers for future depression recognition.

Methods

Three-channel EEG signals from 69 depression patients (divided into three groups according to illness severity) and 14 healthy subjects were collected. Except for cross-sample entropy (CSEn), two new asymmetry indexes (Asy_SEn and Asy_LZC) based on complexity measures were proposed to quantify the difference among the four groups. One-way ANOVA was used to test the difference among all four groups, followed by the group t-test to test the difference between each two groups.

Results

All indexes show significantly increased frontal alpha asymmetry in depressive groups compared with the healthy group, and the asymmetry keeps increasing as the depression deepens. The Asy_LZC value of the confirmed depression group (0.0015 ± 0.0008) is substantially higher than the other three groups (−0.0010 ± 0.0008, −0.0006 ± 0.0008, and −0.0007 ± 0.0006). And the Asy_SEn value of the healthy group (−0.0023 ± 0.0007) is significantly lower than the two depressive groups (0.0001 ± 0.0005 and 0.0007 ± 0.0007). All healthy CSEn between each two channels is considerably lower than depressive groups with p < 0.01.

Conclusion

This study confirms the increased frontal alpha asymmetry in depression patients and suggests that two new indexes could be promising biomarkers in future clinical depression detection.

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Acknowledgements

The authors appreciate the psychiatrists and nurses from the Second Affiliated Hospital of Jining Medical College, for their long time help in patients’ data collection. We also thank the support from the Southeast–Lenovo Wearable Heart-Sleep-Emotion Intelligent Monitoring Lab.

Funding

This research was funded by the Shandong Province Natural Science Foundation (ZR2018FM027), the Key Research and Development Project of Shandong Province (2016GSF120009), the National Key Research and Development Program of China (2019YFE0113800), the Distinguished Young Scholars of Jiangsu Province (BK20190014) and the National Natural Science Foundation of China (81871444).

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Authors

Contributions

Conceptualization, LY and CL; Data curation, LZ, BL and ZS; Formal analysis, LZ; Funding acquisition, LY and CL; Investigation, LZ and CL; Methodology, LZ; Project administration, CL; Resources, LY and CL; Software, LZ; Supervision, LY and CL; Validation, LZ, LY, and BL; Writing—original draft, LZ; Writing—review & editing, LY and CL.

Corresponding authors

Correspondence to Licai Yang or Chengyu Liu.

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Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

The protocol of this study was approved by the Ethics Committee of the Second Affiliated Hospital of Jining Medical College.

Informed Consent

Written informed consent was given by all participants in accordance with the Declaration of Helsinki.

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Zhao, L., Yang, L., Li, B. et al. Frontal Alpha EEG Asymmetry Variation of Depression Patients Assessed by Entropy Measures and Lemple–Ziv Complexity. J. Med. Biol. Eng. (2021). https://doi.org/10.1007/s40846-020-00594-9

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Keywords

  • Sample entropy
  • Cross-sample entropy
  • Lemple–Ziv complexity
  • Frontal asymmetry
  • Depression