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Article

A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor

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Department of Information and Communication Technologies, Universidad Politécnica de Cartagena (UPCT), Campus Muralla del Mar, E-30202 Cartagena, Spain
2
Department of Quantitative Methods, Law and Modern Languages, Universidad Politécnica de Cartagena (UPCT), E-30202 Cartagena, Spain
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(3), 896; https://doi.org/10.3390/s20030896
Received: 10 December 2019 / Revised: 24 January 2020 / Accepted: 4 February 2020 / Published: 7 February 2020
Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring any calibration of the raw data acquired. In addition, it has been validated with a well-accepted public electrocardiograph (ECG) data base, obtaining 87.65%, 91.84%, and 91.31% in terms of sensitivity, specificity and accuracy, respectively. View Full-Text
Keywords: biomedical sensor; RR interval; R peak, ECG; logistic regression biomedical sensor; RR interval; R peak, ECG; logistic regression
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MDPI and ACS Style

Pérez-Valero, J.; Garcia-Sanchez, A.-J.; Ruiz Marín, M.; Garcia-Haro, J. A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor. Sensors 2020, 20, 896. https://doi.org/10.3390/s20030896

AMA Style

Pérez-Valero J, Garcia-Sanchez A-J, Ruiz Marín M, Garcia-Haro J. A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor. Sensors. 2020; 20(3):896. https://doi.org/10.3390/s20030896

Chicago/Turabian Style

Pérez-Valero, Jesús, Antonio-Javier Garcia-Sanchez, Manuel Ruiz Marín, and Joan Garcia-Haro. 2020. "A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor" Sensors 20, no. 3: 896. https://doi.org/10.3390/s20030896

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