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Measuring brain activity in a professional dance environment – a study


Authors: Elblová Roth M. 1;  Mouček R. 2
Authors‘ workplace: Hudební a taneční fakulta, Akademie múzických umění v Praze 1;  Katedra informatiky a výpočetní techniky, Fakulta aplikovaných věd, Západočeská univerzita v Plzni 2
Published in: Rehabil. fyz. Lék., 31, 2024, No. 2, pp. 84-100.
Category: Original Papers
doi: https://doi.org/10.48095/ccrhfl 202484

Overview

Summary: The connection of body and mind and their mutual conjunction is an increasingly topical topic in many fields. Objective: The aim of the work was to find out to what extent our thoughts in a professional dance environment affect the course of brain frequencies and how they are prescribed in our organism and movement. Methods: As part of the study, brain activity was measured with the Muse wearable EEG device and visual analysis of movement from the dance environment, the plié element (flexion and extension of the knee joints). The monitored and measured individuals were 16 students of the Dance Department of Music and Dance Faculty of the Music Academy of Performing Arts in Prague. We monitored brain frequencies in many phases (situations): without a specific thought (concentration) and without movement, with a specific thought without movement, movement without a specific thought, movement with a specific thought, and finally again a thought without movement, which was out of scope and research framework. Results: For 14 participants in the experiment, we obtained an EEG signal of sufficient quality so that it could be further analyzed. A change in brain frequencies distinguishing activities with lower and higher conscious concentration was demonstrated in 12 participants. Conclusion: The output describes the findings regarding the connection of thoughts, body, and movement based on measurable data. The Muse EEG device is useful for obtaining an EEG signal of sufficient quality in experiments requiring movement and taking place in real conditions. In the obtained EEG signal, it is possible to detect changes in the participant‘s brain activity during states of relaxed alertness and conscious concentration. Visual analysis of movement reflects that the synthesis of a specific thought and movement contributes to eliminating bad habits, which destroy not only the technical purity of the performance of the movement element but also optimal posture, coordination of movement, and individual anatomical structures.

Keywords:

EEG – attention – Franklin Method – movement – basic brain frequency – Muse headband


Sources

1. Fink A, Graif B, Neubauer AC. Brain correlates underlying creative thinking: EEG alpha activity in professional vs. novice dancers. Neuroimage 2009; 46 (3): 854–862. doi: 10.1016/j.neuroimage.2009.02.036.

2. Orlandi A, Zani A, Proverbio AM. Dance expertise modulates visual sensitivity to complex biological movements. Neuropsychologia 2017; 104: 168–181. doi: 10.1016/j.neuro- psychologia.2017.08.019.

3. Ushiyama J, Takahashi Y, Ushiba J. Muscle dependency of corticomuscular coherence in upper and lower limb muscles and training-related alterations in ballet dancers and weightlifters. J Appl Physiol 2010; 109 (4): 1086–1095. doi: 10.1152/japplphysiol.00869.2009.

4. Zhang Z. Cranial nerve feedback mechanism of adolescents practicing classical ballet and their psychological health. Revista Argentina de Clínica Psicológica 2020; 29 (2): 114.

5. Quadrado V, Moreira M, Ferreira H et al. Sensing technology for assessing motor behavior in ballet: a systematic review. Sports Med Open 2022; 8 (1): 39. doi: 10.1186/s40798-022-00429-8.

6. Golomer E, Bouillette A, Mertz C et al. Effects of mental imagery styles on shoulder and hip rotations during preparation of pirouettes. J Mot Behav 2008; 40 (4): 281–290. doi: 10.3200/JMBR.40.4.281-290.

7. Golomer EM, Gravenhorst RM, Toussaint Y. Influence of vision and motor imagery styles on equilibrium control during whole-body rotations. Somatosens Mot Res 2009; 26 (4): 105–10. doi: 10.3109/08990220903384968.

8. Golomer E, Toussaint Y, Bouillette A et al. Spontaneous whole body rotations and classical dance expertise: how shoulder-hip coordination influences supporting leg displacements. J Electromyogr Kinesiol 2009; 19 (2): 314–321. doi: 10.1016/j.jelekin.2007. 08.004.

9. Golomer E, Mbongo F, Toussaint Y et al. Right hemisphere in visual regulation of complex equilibrium: the female ballet dancers’ experience. Neurol Res 2010; 32 (4): 409–415. doi: 10.1179/174313209X382476.

10. Franklin EN. Frei bewegen: Mit der wissenschaftlich fundierten Franklin-Methode zu mehr Beweglichkeit und einer dynamisch perfekten Haltung. München: Riva 2020. ISBN 978-3-7423-1199-3.

11. Choosemuse.com. Muse. EEG Muse. 2023. [online]. Available from: https: //choosemuse.com/pages/science.

12. Krigolson OE, Williams CC, Norton A. Choosing MUSE: validation of a low-cost, portable EEG system for ERP research. Front Neurosci 2017; 11: 109. doi: 10.3389/fnins.2017.00109.

13. Youssef AE, Ouda HT, Azab M. MUSE: a portable cost-efficient lie detector. 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2018: 242–246. doi: 10.1109/IEMCON.2018.8614795.

14. Cannard C, Wahbeh H, Delorme A. Validating the wearable MUSE headset for EEG spectral analysis and Frontal Alpha Asymmetry. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021: 3603–3610.

15. Fink A, Grabner RH, Benedek M et al. The creative brain: Investigation of brain activity during creative problem solving by means of EEG and FMRI. Hum Brain Mapp 2009; 30 (3): 734–748. doi: 10.1002/hbm.20538

16. Neuromore.com. Integrovaná neurotechnologická platforma pro práci s daty z nositelných biosenzorů a EEG zařízení. 2023. [online]. Available from: https: //www.neuromore.com.

17. Delorme A, Makeig S. EEGLAB: an open-source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 2004; 134 (1): 9–21. doi: 10.1016/j.jneumeth.2003.10.009.

18. Franklin EN. Conditioning for dance: training for peak performance in all dance forms. Human Kinetics 2003.

19. Franklin EN. Conditioning for dance: training for whole-body coordination and efficiency. Champaign: Human Kinetics 2019.

20. Muse Developers.com. 2018. [online]. Avail- able from: https: //web.archive.org/web/201 81105231756/http: //developer.choosemuse.com/tools/available-data.

21. Krigolsonlab.com. MUSE Analysis with MATLAB and Brain Vision Analyzer. 2023. [online]. Available from: https: / / www.krigolsonlab.com/ muse-analysis.html.

Doručeno/ Submitted: 10. 10. 2023
Přijato/ Accepted: 15. 5. 2024
Korespondenční autor:
MgA. M. Roth Elblová
Hudební a taneční fakulta
Akademie múzických umění
Malostranské náměstí 258/ 13
118 00 Praha 1
e-mail: marketa.elblova@seznam.cz
Labels
Physiotherapist, university degree Rehabilitation Sports medicine
Topics Journals
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