Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Molina-Cantero, Alberto J., Castro-García, Juan A., Lebrato-Vázquez, Clara, Gómez-González, Isabel M., Merino-Monge, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949041/
https://www.ncbi.nlm.nih.gov/pubmed/29596394
http://dx.doi.org/10.3390/s18041033
_version_ 1783322677611593728
author Molina-Cantero, Alberto J.
Castro-García, Juan A.
Lebrato-Vázquez, Clara
Gómez-González, Isabel M.
Merino-Monge, Manuel
author_facet Molina-Cantero, Alberto J.
Castro-García, Juan A.
Lebrato-Vázquez, Clara
Gómez-González, Isabel M.
Merino-Monge, Manuel
author_sort Molina-Cantero, Alberto J.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5949041
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-59490412018-05-17 Real-Time Processing Library for Open-Source Hardware Biomedical Sensors Molina-Cantero, Alberto J. Castro-García, Juan A. Lebrato-Vázquez, Clara Gómez-González, Isabel M. Merino-Monge, Manuel Sensors (Basel) Article 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. MDPI 2018-03-29 /pmc/articles/PMC5949041/ /pubmed/29596394 http://dx.doi.org/10.3390/s18041033 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Molina-Cantero, Alberto J.
Castro-García, Juan A.
Lebrato-Vázquez, Clara
Gómez-González, Isabel M.
Merino-Monge, Manuel
Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title_full Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title_fullStr Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title_full_unstemmed Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title_short Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
title_sort real-time processing library for open-source hardware biomedical sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949041/
https://www.ncbi.nlm.nih.gov/pubmed/29596394
http://dx.doi.org/10.3390/s18041033
work_keys_str_mv AT molinacanteroalbertoj realtimeprocessinglibraryforopensourcehardwarebiomedicalsensors
AT castrogarciajuana realtimeprocessinglibraryforopensourcehardwarebiomedicalsensors
AT lebratovazquezclara realtimeprocessinglibraryforopensourcehardwarebiomedicalsensors
AT gomezgonzalezisabelm realtimeprocessinglibraryforopensourcehardwarebiomedicalsensors
AT merinomongemanuel realtimeprocessinglibraryforopensourcehardwarebiomedicalsensors