EconPapers    
Economics at your fingertips  
 

ANALYSIS OF BRAIN–MUSCLE CORRELATION IN DIFFERENT HAND MOVEMENTS

Robert Frischer, Ondrej Krejcar, Jamaluddin Abdullah, Camillo Porcaro, Dipak Kumar Ghosh and Hamidreza Namazi
Additional contact information
Robert Frischer: Skoda Auto University, Na Karmel, Mlada Boleslav, Czechia
Ondrej Krejcar: Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove 50003, Czech Republic
Jamaluddin Abdullah: School of Mechanical Engineering, Universiti Sains Malaysia, Malaysia
Camillo Porcaro: Department of Neuroscience and Padova Neuroscience Center, University of Padova, Padova, Italy5Institute of Cognitive Sciences and Technologies-National, Research Council Rome, Italy6Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
Dipak Kumar Ghosh: Department of Electrical Electronics and Communication Engineering, Galgotias University, Greater Noida 203201, Uttar Pradesh, India
Hamidreza Namazi: Skoda Auto University, Na Karmel, Mlada Boleslav, Czechia3School of Mechanical Engineering, Universiti Sains Malaysia, Malaysia8Biomedical Signal & Image Processing Lab, Galgotias University, Greater Noida 203201, Uttar Pradesh, India

FRACTALS (fractals), 2025, vol. 33, issue 07, 1-9

Abstract: Exploring the relationship between muscle and brain activity is of great importance in biomedical research, and in particular for brain–machine interfaces (BMI). This paper explores the relationship between the human brain and muscle activity for five subjects during specific hand movements, namely wrist flexion, wrist extension, and fist clenching. The fractal dimension (FD) and approximate entropy (ApEn) of electroencephalogram (EEG) and electromyography (EMG) signals were calculated for subjects performing hand movements. The results show a correlation between the complexity variations in the EMG signals and those in the EEG signals during different hand movements, suggesting a link between brain and muscle activity. Given the complex nature of physiological signals, this analytical approach proves applicable for investigating correlations between different organ activities under different conditions.

Keywords: Brain; Muscle; Correlation; Hand movement; Complexity; Fractal Dimension (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X25500641
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:33:y:2025:i:07:n:s0218348x25500641

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X25500641

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().

 
Page updated 2025-08-16
Handle: RePEc:wsi:fracta:v:33:y:2025:i:07:n:s0218348x25500641