Comparison of ballistocardiogram processing methods based on fiber specklegram sensors

Reyes González, Luis Rafael; Rodríguez Cobo, Luis; López Higuera, José Miguel

doi:10.1109/JSEN.2022.3208318

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Identificadores

URI: https://hdl.handle.net/10902/26952

DOI: 10.1109/JSEN.2022.3208318

ISSN: 1530-437X

ISSN: 1558-1748

Fecha

2022-11-01

Derechos

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publicado en

IEEE Sensors Journal, 2022, 22(21), 20524-20530

Editorial

Institute of Electrical and Electronics Engineers Inc.

Enlace a la publicación

https://doi.org/10.1109/JSEN.2022.3208318

Palabras clave

Ballistocardiogram (BCG)

Fiber-optic sensors

Noninvasive physiologic monitoring

Sensor data processing

Speckle

Resumen/Abstract

The ballistocardiogram (BCG) is a graphic representation of the movements of the body associated with cardiac activity. In this article, a 10-min BCG has been captured for ten different volunteers with a polymer optical fiber (POF) specklegram sensor. This transducer, which is composed of a charge-coupled device (CCD) camera, a laser emitting diode, and two meters of POF, allows capturing the BCG by analyzing how the induced speckle pattern changes over time. These changes are related to cardiac activity. Several processing methods have been compared to determine which method achieves the best performance: complex cepstrum, power of spectral density (PSD), Pam-Tompkins algorithm, wavelet, autocorrelation, Savitzky?Golay filter, mean absolute deviation, and Hilbert transform. Accuracy and resource consumption have been characterized and compared for these methods. Hilbert, PSD, and Savitzky-Golay exhibit both small errors and computational costs. This article describes a baseline for the main frequency determination of POF-based BCG signals in real-time.