Multifractal Multiscale Analysis of Human Movements during Cognitive Tasks
Andrea Faini1,2, Laurent M Arsac3, Veronique Deschodt-Arsac3
1Department of Cardiovascular, Neural and Metabolic Sciences, Istituto Auxologico Italiano, IRCCS, 20149 Milan, Italy.
Entropy (Basel, Switzerland)
|February 23, 2024
Summary
Multiscale multifractal analysis (MFMS-DFA) effectively detects cognitive load effects on human movement dynamics. Collaborative gameplay significantly reduced cognitive load impacts on pedal control, highlighting MFMS-DFA
Area of Science:
- Movement Science
- Complex Systems Analysis
- Cognitive Neuroscience
Background:
- Human movement adaptation relies on multifractality, a complex fractal process.
- Multifractal spectrum analysis can reveal adaptive processes in perception, cognition, and action.
- Multiscale multifractal analysis based on DFA (MFMS-DFA) was developed for cardiovascular dynamics.
Purpose of the Study:
- To assess the utility of MFMS-DFA for identifying multiscale structures in human movement dynamics.
- To investigate how cognitive demand, specifically playing Tetris, affects movement multifractality.
- To explore the interplay between skill, cognitive demand, and movement control.
Main Methods:
- Thirty-six participants pedaled under three conditions: reference cycling, cycling while playing Tetris alone, and collaboratively.
- Pedal revolution period (PRP) series were analyzed using MFMS-DFA.
- Results were compared against linearized surrogates to confirm multifractality.
Main Results:
- MFMS-DFA confirmed multifractality in pedal movement dynamics across various scales.
- Playing Tetris significantly altered multifractality at scales of approximately 16 and 64 seconds.
- Collaborative Tetris play attenuated these alterations, particularly in skilled players.
Conclusions:
- MFMS-DFA is sensitive to cognitive demand in human movement dynamics.
- The method can assess the interplay between skill and task demands.
- MFMS-DFA shows potential for studying brain-movement coordination and diagnosing neurological disorders.
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