Please use this identifier to cite or link to this item:
http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1939
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | 299983 | es_ES |
dc.contributor.other | https://orcid.org/0000-0002-7635-4687 | - |
dc.contributor.other | 0000-0002-9498-6602 | - |
dc.contributor.other | https://orcid.org/0000-0002-9498-6602 | - |
dc.coverage.spatial | Global | es_ES |
dc.creator | Galván Tejada, Carlos Eric | - |
dc.creator | Zanella Calzada, Laura Alejandra | - |
dc.creator | Gamboa Rosales, Hamurabi | - |
dc.creator | Galván Tejada, Jorge | - |
dc.creator | Chávez Lamas, Nubia | - |
dc.creator | Gracia Cortés, Ma. del Carmen | - |
dc.creator | Magallanes Quintanar, Rafael | - |
dc.creator | Celaya Padilla, José | - |
dc.date.accessioned | 2020-05-25T17:49:36Z | - |
dc.date.available | 2020-05-25T17:49:36Z | - |
dc.date.issued | 2019-01-10 | - |
dc.identifier | info:eu-repo/semantics/publishedVersion | es_ES |
dc.identifier.issn | 1574-017X | es_ES |
dc.identifier.uri | http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1939 | - |
dc.identifier.uri | https://doi.org/10.48779/zvq2-zd29 | - |
dc.description.abstract | Depression is a mental disorder which typically includes recurrent sadness and loss of interest in the enjoyment of the positive aspects of life, and in severe cases fatigue, causing inability to perform daily activities, leading to a progressive loss of quality of life. Monitoring depression (unipolar and bipolar patients) stats relays on traditional method reports from patients; however, bias is commonly present, given the patients’ interpretation of the experiences. Nevertheless, to overcome this problem, Ecological Momentary Assessment (EMA) reports have been proposed and widely used. These reports includes data of the behaviour, feelings, and other type of activities recorded almost in real time using different types of portable devices, which nowadays include smartphones and other wearables such as smartwatches. In this study is proposed a methodology to detect depressive patients with the motion data generated by patient activity, recorded with a smartband, obtained from the “Depresjon” database. Using this signal as information source, a feature extraction approach of statistical features, in time and spectral evolution of the signal, is done. Subsequently, a clever feature selection with a genetic algorithm approach is done to reduce the amount of information required to give a fast noninvasive diagnostic. Results show that the feature extraction approach can achieve a value of 0.734 of area under the curve (AUC), and after applying feature selection approach, a model comprised by two features from the motion signal can achieve a 0.647 AUC. These results allow us to conclude that using the activity signal from a smartband, it is possible | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Hindawi | es_ES |
dc.relation | https://www.hindawi.com/journals/misy/2019/8269695/ | es_ES |
dc.relation.uri | generalPublic | es_ES |
dc.source | Mobile Information Systems, Vol. 2019, Article ID 8269695, pp. 12. | es_ES |
dc.subject.classification | MEDICINA Y CIENCIAS DE LA SALUD [3] | es_ES |
dc.subject.other | Depression | es_ES |
dc.subject.other | fatigue | es_ES |
dc.subject.other | smartband | es_ES |
dc.title | Depression Episodes Detection in Unipolar and Bipolar Patients: A Methodology with Feature Extraction and Feature Selection with Genetic Algorithms Using Activity Motion Signal … | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
Appears in Collections: | *Documentos Académicos*-- M. en Ciencias del Proc. de la Info. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
8269695.pdf | 2,64 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.