Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study
Joint Authors
Gómez-Pozos, Heberto
Sánchez-DelaCruz, Eddy
Weber, Roberto
Biswal, R. R.
Mejía, Jose
Hernández-Chan, Gandhi
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building.
In other words, machine learning enables an automaton to make its own decisions based on a previous training process.
Machine learning has revolutionized every research sector, including health care, by providing precise and accurate decisions involving minimal human interventions through pattern recognition.
This is emphasized in this research, which addresses the issue of “support for diabetic neuropathy (DN) recognition.” DN is a disease that affects a large proportion of the global population.
In this research, we have used gait biomarkers of subjects representing a particular sector of population located in southern Mexico to identify persons suffering from DN.
To do this, we used a home-made body sensor network to capture raw data of the walking pattern of individuals with and without DN.
The information was then processed using three sampling criteria and 23 assembled classifiers, in combination with a deep learning algorithm.
The architecture of the best combination was chosen and reconfigured for better performance.
The results revealed a highly acceptable classification with greater than 85% accuracy when using these combined approaches.
American Psychological Association (APA)
Sánchez-DelaCruz, Eddy& Weber, Roberto& Biswal, R. R.& Mejía, Jose& Hernández-Chan, Gandhi& Gómez-Pozos, Heberto. 2019. Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1130542
Modern Language Association (MLA)
Sánchez-DelaCruz, Eddy…[et al.]. Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1130542
American Medical Association (AMA)
Sánchez-DelaCruz, Eddy& Weber, Roberto& Biswal, R. R.& Mejía, Jose& Hernández-Chan, Gandhi& Gómez-Pozos, Heberto. Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1130542
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130542