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Advancing biomedical engineering: Leveraging Hjorth features for electroencephalography signal analysis Cover

Advancing biomedical engineering: Leveraging Hjorth features for electroencephalography signal analysis

Journal of Electrical Bioimpedance
Volume 14 (2023): Issue 1 (January 2023)
By: Wissam H. Alawee,  Ali Basem and  Luttfi A. Al-Haddad  
Open Access
|Dec 2023

Figures & Tables

Fig.1:

A schematic representation of the brain regions selected for EEG signal recording [13].
A schematic representation of the brain regions selected for EEG signal recording [13].

Fig.2:

The OpenBCI Cyton with Daisy Biosensing Board and associated EEG headgear, detailing the hardware setup used in signal collection [13].
The OpenBCI Cyton with Daisy Biosensing Board and associated EEG headgear, detailing the hardware setup used in signal collection [13].

Fig.3:

The reclining chair with delineated limb angles and the monitor placement at a 1.5-meter distance, ensuring direct alignment with the participant’s field of vision [13].
The reclining chair with delineated limb angles and the monitor placement at a 1.5-meter distance, ensuring direct alignment with the participant’s field of vision [13].

Fig.4:

EEG signals over a 4-second interval with 500 instances for Subject 10 in CRH phase.
EEG signals over a 4-second interval with 500 instances for Subject 10 in CRH phase.

Fig.5:

EEG signals over a 4-second interval with 500 instances for Subject 10 in Resting phase.
EEG signals over a 4-second interval with 500 instances for Subject 10 in Resting phase.

Fig.6:

Hjorth parameters of the Resting movement, namely activity, mobility, and complexity for all electrodes.
Hjorth parameters of the Resting movement, namely activity, mobility, and complexity for all electrodes.

Fig.7:

Hjorth parameters of the CRH movement, namely activity, mobility, and complexity for all electrodes.
Hjorth parameters of the CRH movement, namely activity, mobility, and complexity for all electrodes.

Fig.8:

Activity, mobility, and complexity of electrode 14 readings for both resting and closing right hand.
Activity, mobility, and complexity of electrode 14 readings for both resting and closing right hand.

Fig.9:

Activity, mobility, and complexity of electrode 15 readings for both resting and closing right hand.
Activity, mobility, and complexity of electrode 15 readings for both resting and closing right hand.

Task abbreviations assigned to different limb movements_

TaskDescription
BEORecording a Baseline with Eyes Open
CLHClosing Left Hand: five times per run
CRHClosing Right Hand: five times per run
DLFDorsal flexion of Left Foot: five times per run
PLFPlantar flexion of Left Foot: five times per run
DRFDorsal flexion of Right Foot: five times per run
PRFPlantar flexion of Right Foot: five times per run
RestResting in between tasks: after each task
DOI: https://doi.org/10.2478/joeb-2023-0009 | Journal eISSN: 1891-5469
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Language: English
Page range: 66 - 72
Submitted on: Nov 14, 2023
Published on: Dec 31, 2023
Published by: University of Oslo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Biomedical engineering,
electroencephalography,
Hjorth features,
machine learning,
signal processing
Related subjects:
Engineering,
Bioengineering and biomedical engineering,
Biomedical electronics,
Life sciences,
Biophysics,
Medicine,
Biomedical engineering,
Physics,
Spectroscopy and metrology

© 2023 Wissam H. Alawee, Ali Basem, Luttfi A. Al-Haddad, published by University of Oslo
This work is licensed under the Creative Commons Attribution 4.0 License.

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