Implementation of real-time filter using an open-source platform oriented to R-wave detection

Javier, Gonzalez; Galvis, Eduard; Velandia, Cristian Camilo López

doi:10.1109/stsiva.2016.7743351

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Dentro de las tendencias de monitoreo simple, se encuentran desarrollos nacientes de ambientes educativos, que diseñan componentes básicos de un sistema de monitoreo de FC, entre estos: circuitos para la obtención de señales del corazón, plataformas web para la visualización de la información, diseño de filtros para mejora en la calidad de las señales del corazón [18], [19].…”

Section: El Monitoreo Simpleunclassified

Aplicaciones de Monitoreo de Frecuencia Cardiaca sobre plataformas Open Source: Una revisión sistemática

Bustamante

Ochoa

Iriarte

et al. 2020

BILO

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Introducción: Los desarrollos tecnológicos que se implementan en plataformas de código abierto (Open Source) han crecido considerablemente en la última década, ofreciendo soluciones fáciles de desarrollar, flexibles y de bajo costo. En el caso de las aplicaciones biomédicas desarrolladas sobre plataformas Open Source, el monitoreo de la frecuencia cardiaca es una de las aplicaciones con mayor desarrollo. Objetivo: en este documento se presenta una revisión sistemática de la literatura, en la que se analizan los desarrollos actuales en Sistemas de Monitoreo de Frecuencia Cardiaca (SMFC) sobre plataformas Open Source. Se identifican los desarrollos más significativos, y las plataformas comúnmente usadas. Metodología: Se realiza una revisión sistemática de la literatura de tipo Cochrane. Resultados: Se presentan las tendencias en investigación acerca de los sistemas de monitoreo de frecuencia cardiaca usando plataformas Open Source. Conclusiones: existe un gran desarrollo de las aplicaciones que implican el monitoreo de la frecuencia cardiaca. Sin embargo, su estudio no está dado por terminado. Puesto que, con la gran cantidad de datos disponibles gracias a esas aplicaciones, es posible aún, profundizar en la implementación de estudios estadísticos.

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Section: El Monitoreo Simpleunclassified

Aplicaciones de Monitoreo de Frecuencia Cardiaca sobre plataformas Open Source: Una revisión sistemática

Bustamante

Ochoa

Iriarte

et al. 2020

BILO

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“…Arduino boards have been used as single signal acquisition elements that deliver data to a computer where the digital signal algorithm is executed [ 25 , 26 , 27 ] or as processing units as well. Arduino boards containing 32-bit processors, such as Due or Uno32 have been used for different real-time applications: audio [ 28 ], finite or infinite impulsive impulse digital filters [ 29 ], image compressing [ 30 ] or for detecting R waves in electrocardiogram signals [ 31 ]. Nevertheless, boards based on 8-bit processors have been successfully used in biomedical applications such as cardio monitoring [ 32 ], online heart-rate detection [ 33 ], amputee rehabilitation [ 34 ], or for movement detection in people with disabilities based on the processing of signals delivered by accelerometers or flexometers [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

Molina

Castro-García

Lebrato-Vázquez

et al. 2018

Sensors

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Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.

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Analysis of the ECG Signal to Understand the Effect of Regional State Anthem of Odisha in Young Reproductively Active Odia Females

Subhadarshini

Nayak

Ray

et al. 2017

2017 14th IEEE India Council International Conference (INDICON)

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Implementation of real-time filter using an open-source platform oriented to R-wave detection

Cited by 3 publications

References 22 publications

Aplicaciones de Monitoreo de Frecuencia Cardiaca sobre plataformas Open Source: Una revisión sistemática

Aplicaciones de Monitoreo de Frecuencia Cardiaca sobre plataformas Open Source: Una revisión sistemática

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

Analysis of the ECG Signal to Understand the Effect of Regional State Anthem of Odisha in Young Reproductively Active Odia Females

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