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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
- Source :
- Biomed Opt Express
- Publication Year :
- 2021
- Publisher :
- Optica Publishing Group, 2021.
-
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.
- Subjects :
- Materials science
medicine.diagnostic_test
Artificial neural network
Mean squared error
business.industry
Deep learning
Limits of agreement
Magnetic resonance imaging
Fiber bragg grating sensor
Article
Atomic and Molecular Physics, and Optics
Optics
Fiber Bragg grating
Fiber optic sensor
medicine
Artificial intelligence
business
Biotechnology
Subjects
Details
- ISSN :
- 21567085
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Biomedical Optics Express
- Accession number :
- edsair.doi.dedup.....614e3c5f3c49dc2c82f2fe37c47c8fb8