![](/images/graphics-bg.png)
Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly
Joint Authors
Felix, Vanessa G.
Mena, Luis J.
Ostos, Rodolfo
Ochoa, Alberto
González, Eduardo
Aspuru, Javier
Velarde, Pablo
Maestre, Gladys E.
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-29
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Mobile electrocardiogram (ECG) monitoring is an emerging area that has received increasing attention in recent years, but still real-life validation for elderly residing in low and middle-income countries is scarce.
We developed a wearable ECG monitor that is integrated with a self-designed wireless sensor for ECG signal acquisition.
It is used with a native purposely designed smartphone application, based on machine learning techniques, for automated classification of captured ECG beats from aged people.
When tested on 100 older adults, the monitoring system discriminated normal and abnormal ECG signals with a high degree of accuracy (97%), sensitivity (100%), and specificity (96.6%).
With further verification, the system could be useful for detecting cardiac abnormalities in the home environment and contribute to prevention, early diagnosis, and effective treatment of cardiovascular diseases, while keeping costs down and increasing access to healthcare services for older persons.
American Psychological Association (APA)
Mena, Luis J.& Felix, Vanessa G.& Ochoa, Alberto& Ostos, Rodolfo& González, Eduardo& Aspuru, Javier…[et al.]. 2018. Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132237
Modern Language Association (MLA)
Mena, Luis J.…[et al.]. Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1132237
American Medical Association (AMA)
Mena, Luis J.& Felix, Vanessa G.& Ochoa, Alberto& Ostos, Rodolfo& González, Eduardo& Aspuru, Javier…[et al.]. Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132237
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132237