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Brain complexity in motion
2.1 Participants
2.2 Experimental procedures
2.3 EEG recording and preprocessing
2.4 Computation of multiscale entropy estimates on preprocessed EEG data
2.5 Statistical approaches for reliability, validity, and classification accuracy
2.5.1 Test-retest reliability analysis of multiscale entropy estimates
2.5.2 Known-groups and convergent validity of multiscale entropy estimates
2.5.3 Computation of receiver operating characteristic (ROC) curves on entropy estimates and their principal components
3 Results
3.1 Accuracy performance
3.2 Test-retest reliability of multiscale entropy estimates
3.3 Differences in entropy estimates between expertise levels and their correlation with accuracy
3.4 Classification performance of entropy estimates in differentiating expertise levels
4 Discussion
4.1 Test-retest reliability of entropy estimates as a task-related complexity measure
4.2 The validity of entropy estimates in revealing dynamics between cortical complexity and motor performance
4.3 The classification performance of entropy estimates to differentiate expertise levels
4.4 Methodological limitations and recommendations for future implementation of MSE analysis in mobile settings
5 Conclusion
CRediT authorship contribution statement
Ethics
Funding
Declaration of Competing Interest
Acknowledgements
Appendix A Supporting information
References
Aufsatz in einer Zeitschrift
Brain complexity in motion : multiscale entropy analysis on mobile EEG data to assess motor performance / Daghan Piskin, Gjergji Cobani, Daniel Büchel, Tim Lehmann, Jochen Baumeister
Entstehung
Paderborn
2026
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