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Updated: Oct 7, 2025

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
Published on: April 26, 2024
Deep learning-based method for the continuous detection of heart rate in signals from a multi-fiber Bragg grating
Mariusz Krej1, Tomasz Osuch2,3, Alicja Anuszkiewicz2,4
1Military Institute of Aviation Medicine, Department of Psychophysiological Measurements and Human Factor Research, Krasinskiego 54/56, 01-755 Warsaw, Poland.
Abstract:
A method for the continuous detection of heart rate (HR) in signals acquired from patients using a sensor mat comprising a nine-element array of fiber Bragg gratings during routine magnetic resonance imaging (MRI) procedures is proposed. The method is based on a deep learning neural network model, which learned from signals acquired from 153 MRI patients. In addition, signals from 343 MRI patients were used for result verification. The proposed method provides automatic continuous extraction of HR with the root mean square error of 2.67 bpm, and the limits of agreement were -4.98-5.45 bpm relative to the reference HR.
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