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Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis

In the digital medicine field, biosignals, such as those of an electrocardiogram (ECG), are collected regularly for screening and diagnosis, and there continues to be an increasingly substantial shift towards collecting long-term ECG signals for remote monitoring, e.g., in smart homes. ECG signal co...

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Detalles Bibliográficos
Autor principal: Elgendi, Mohamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871964/
https://www.ncbi.nlm.nih.gov/pubmed/29495261
http://dx.doi.org/10.3390/diseases6010018
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author Elgendi, Mohamed
author_facet Elgendi, Mohamed
author_sort Elgendi, Mohamed
collection PubMed
description In the digital medicine field, biosignals, such as those of an electrocardiogram (ECG), are collected regularly for screening and diagnosis, and there continues to be an increasingly substantial shift towards collecting long-term ECG signals for remote monitoring, e.g., in smart homes. ECG signal collection is quite simple and only requires the use of inexpensive sensors, an active Internet connection, and a mobile device that acts as the medium between the sensors and the Internet (e.g., a mobile phone or laptop). Despite the ease and convenience of remote ECG data collection and transmission, the amount of time and energy required for the related remote computational processes remains a major limitation. This short note discusses a biosignal approach that uses fewer biomedical data for screening and diagnosis that is, compared to current data collection methods, equally, if not more, efficient.
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spelling pubmed-58719642018-03-29 Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis Elgendi, Mohamed Diseases Short Note In the digital medicine field, biosignals, such as those of an electrocardiogram (ECG), are collected regularly for screening and diagnosis, and there continues to be an increasingly substantial shift towards collecting long-term ECG signals for remote monitoring, e.g., in smart homes. ECG signal collection is quite simple and only requires the use of inexpensive sensors, an active Internet connection, and a mobile device that acts as the medium between the sensors and the Internet (e.g., a mobile phone or laptop). Despite the ease and convenience of remote ECG data collection and transmission, the amount of time and energy required for the related remote computational processes remains a major limitation. This short note discusses a biosignal approach that uses fewer biomedical data for screening and diagnosis that is, compared to current data collection methods, equally, if not more, efficient. MDPI 2018-02-24 /pmc/articles/PMC5871964/ /pubmed/29495261 http://dx.doi.org/10.3390/diseases6010018 Text en © 2018 by the author. 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 Short Note
Elgendi, Mohamed
Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title_full Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title_fullStr Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title_full_unstemmed Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title_short Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis
title_sort less is more in biosignal analysis: compressed data could open the door to faster and better diagnosis
topic Short Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871964/
https://www.ncbi.nlm.nih.gov/pubmed/29495261
http://dx.doi.org/10.3390/diseases6010018
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