The Relation between Chaotic Feature of Surface EEG and Muscle Force: Case Study Report
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 83
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شناسه ملی سند علمی:
JR_JMSI-11-4_002
تاریخ نمایه سازی: 28 تیر 1402
چکیده مقاله:
Background: 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. Method:
Electromyography signal was recorded with the help of the BIOPEC device (the Mp‑۱۰۰ model) and
from the forearm muscle with surface electrodes, and the EEG signals were recorded from five major
motor‑related cortical areas according to ۱۰–۲۰ standard three times in a normal healthy ۳۳‑year‑old male,
athlete and right handed simultaneously with importing a force to ۱۰ sinkers weighing from ۱۰ to ۱۰۰
Newton with step ۱۰ Newton. Results: The findings confirm that force estimation through EEG signals is
feasible, especially using fractal dimension feature. The R‑squared values for Fractal dimension, Lyapunov
exponent, and entropy and correlation dimension features for linear trend line were ۰.۹۳, ۰.۷, ۰.۸۶, and
۰.۴۱, respectively. Conclusion: The linear increase of characteristics especially fractal dimension and
entropy, together with the results from other EEG and neuroimaging studies, suggests that under normal
conditions, brain recruits motor neurons at a linear progress when increasing the force.
کلیدواژه ها:
نویسندگان
Fereidoun Nowshirvan Rahatabad
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University
Parisa Rangraz
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University
Masood Dalir
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University
Ali Motie Nasrabadi
Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran