Open AccessThe relation between chaotic feature of surface eeg and muscle force: Case study report
Author(s) -
Fereidoun Nowshiravan Rahatabad,
Parisa Rangraz,
Masood Dalir,
Ali Motie Nasrabadi
Publication year - 2021
Publication title -
journal of medical signals and sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.337
H-Index - 21
ISSN - 2228-7477
DOI - 10.4103/jmss.jmss_47_20
Subject(s) - correlation dimension , electroencephalography , lyapunov exponent , fractal dimension , approximate entropy , entropy (arrow of time) , fractal , mathematics , correlation , chaotic , electromyography , pattern recognition (psychology) , artificial intelligence , computer science , mathematical analysis , psychology , physics , neuroscience , geometry , quantum mechanics
Nonlinear dynamics, especially the chaos characteristics, are useful in analyzing bio-potentials with many complexities. In this study, the evaluation of arm-tip force estimation method from the electroencephalography (EEG) signal in the vertical plane has been studied and chaos characteristics, including fractal dimension, Lyapunov exponent, entropy, and correlation dimension characteristics of EEG signals have been measured and analyzed at different levels of forces.