Pilot Study on Using Hybrid-Cascade Filtering on Brain Signals for the Control Purposes

We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so that their frequency domain properties would allow e.g. widely understood diagnostics, here we focus on the study...

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Bibliographic Details
Published in2023 27th International Conference on Methods and Models in Automation and Robotics (MMAR) pp. 251 - 255
Main Authors Pelc, Mariusz, Mikolajewski, Dariusz, Gorzelanczyk, Edward Jacek, Wieczorek, Anna, Racheniuk, Henryk, Sudol, Adam, Latifzadeh, Kayhan, Leiva, Luis A., Kawala-Sterniuk, Aleksandra
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.08.2023
Subjects
Automation
Biological system modeling
biomedical signals
Brain modeling
cascade filtering
Filtering
Frequency-domain analysis
Functional near-infrared spectroscopy
Kalman filters
Near-infrared spectroscopy
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Summary:We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so that their frequency domain properties would allow e.g. widely understood diagnostics, here we focus on the study of time-domain signal characteristics, which is relevant for potential control purposes. Taking into account various kinds of artifacts, we propose a novel cascade 1D Kalman filter to handle fNIRS signals.
ISSN:2835-2807
DOI:10.1109/MMAR58394.2023.10242444