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- A new compressed sensing (CS) framework is developed for monitoring heart activity using ballistocardiography (BCG) signals, featuring an optical fiber sensor and deep learning-based reconstruction.
- *The heart monitoring system compresses the BCG data for transmission, and deep learning algorithms are used to reconstruct it at the receiving end, showing effective results at various compression ratios.
- *The framework outperforms traditional reconstruction methods, achieving a mean absolute error under 1 beat-per-minute for heartbeat rate estimation, demonstrating its potential for integration into healthcare systems for both medical and home applications.
Wearable cardiorespiratory monitoring with stretchable elastomer optical fiber.
Biomed Opt Express
May 2023
Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
This work presents a stretchable elastomer optical fiber sensor incorporated into a belt for respiratory rate (RR) and heart rate (HR) monitoring. Different materials and shapes of prototypes designed were tested in terms of performance and the best choice was identified. The optimal sensor was tested by 10 volunteers to evaluate the performance.
View Article and Find Full Text PDFBallistocardiography (BCG) is a vibration signal related to cardiac activity, which can be obtained in a non-invasive way by optical fiber sensors. In this paper, we propose a modified generative adversarial network (GAN) to reconstruct BCG signals by solving signal fading problems in a Mach-Zehnder interferometer (MZI). Based on this algorithm, additional modulators and demodulators are not needed in the MZI, which reduces the cost and hardware complexity.
View Article and Find Full Text PDFClosed-Loop Multiscale Computational Model of Human Blood Circulation. Applications to Ballistocardiography.
Front Physiol
December 2021
TIPs, Université Libre de Bruxelles, Brussels, Belgium.
Cardiac mechanical activity leads to periodic changes in the distribution of blood throughout the body, which causes micro-oscillations of the body's center of mass and can be measured by ballistocardiography (BCG). However, many of the BCG findings are based on parameters whose origins are poorly understood. Here, we generate simulated multidimensional BCG signals based on a more exhaustive and accurate computational model of blood circulation than previous attempts.
View Article and Find Full Text PDFEvaluation of transit time-based models in wearable central aortic blood pressure estimation.
Biomed Phys Eng Express
March 2020
Instituto de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay.
Evidence suggests that central aortic blood pressure (CABP) may provide a more accurate prognosis of cardiovascular events than peripheral pressure. The capability of monitoring CABP in a continuous, wearable, unobtrusive way might have a significant impact on hypertension management. The purpose of this study is to experimentally explore whether a wearable device equipped with an electrocardiogram (ECG) and ballistocardiogram (BCG) acquisition system could be used to predict CABP.
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