ArticleBiomedical optics express2021
Deep learning-based method for the continuous detection of heart rate in signals from a multi-fiber Bragg grating sensor compatible with magnetic resonance imaging.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 13 citations in OpenAlex.
- Multimodality catheter composed of intravascular ultrasound imaging and polymer optical fiber FFR functions for the diagnosis of cardiac disease.Biomedical optics express · 2026Article
- Machine Learning Applications in Optical Fiber Sensing: A Research Agenda.Sensors (Basel, Switzerland) · 2024Review
- High-Precision Vital Signs Monitoring Method Using a FMCW Millimeter-Wave Sensor.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
10 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
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