Deep learning-based method for the continuous detection of a heart rate in signals from a multi-fiber Bragg grating sensor compatible with magnetic resonance imaging

Posted on 24.11.2021 - 15:55
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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Krej, Mariusz; Osuch, Tomasz; Anuszkiewicz, Alicja; Stopinski, Stanislaw; Anders, Krzysztof; Matuk, Krzysztof; et al. (2021): Deep learning-based method for the continuous detection of a heart rate in signals from a multi-fiber Bragg grating sensor compatible with magnetic resonance imaging. Optica Publishing Group. Collection. https://doi.org/10.6084/m9.figshare.c.5683663.v2
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AUTHORS (10)

Mariusz Krej
Tomasz Osuch
Alicja Anuszkiewicz
Stanislaw Stopinski
Krzysztof Anders
Krzysztof Matuk
Andrzej Weigl
Eugeniusz Tarasow
Ryszard Piramidowicz
Lukasz Dziuda

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