Assessment of Variability in Irregularly Sampled Time Series: Applications to Mental Healthcare

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Show simple item record Bonilla Escribano, Pablo Ramírez García, David Porras Segovia, Alejandro Artés Rodríguez, Antonio 2021-06-11T08:45:08Z 2021-06-11T08:45:08Z 2021-01-01
dc.identifier.bibliographicCitation Bonilla-Escribano, P., Ramírez, D., Porras-Segovia, A., & Artés-Rodríguez, A. (2021). Assessment of Variability in Irregularly Sampled Time Series: Applications to Mental Healthcare. Mathematics, 9(1), 71.
dc.identifier.issn 2227-7390
dc.description.abstract Variability is defined as the propensity at which a given signal is likely to change. There are many choices for measuring variability, and it is not generally known which ones offer better properties. This paper compares different variability metrics applied to irregularly (nonuniformly) sampled time series, which have important clinical applications, particularly in mental healthcare. Using both synthetic and real patient data, we identify the most robust and interpretable variability measures out of a set 21 candidates. Some of these candidates are also proposed in this work based on the absolute slopes of the time series. An additional synthetic data experiment shows that when the complete time series is unknown, as it happens with real data, a non-negligible bias that favors normalized and/or metrics based on the raw observations of the series appears. Therefore, only the results of the synthetic experiments, which have access to the full series, should be used to draw conclusions. Accordingly, the median absolute deviation of the absolute value of the successive slopes of the data is the best way of measuring variability for this kind of time series.
dc.format.extent 18
dc.language.iso eng
dc.publisher MDPI
dc.rights © 2020 by the authors. Creative Commons Attribution (CC BY) license (
dc.rights Atribución 3.0 España
dc.subject.other Ecological momentary assessment (EMA)
dc.subject.other Hawkes process
dc.subject.other Irregularly sampled time series
dc.subject.other Variability
dc.title Assessment of Variability in Irregularly Sampled Time Series: Applications to Mental Healthcare
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TEC2017-86921-C2-2-R
dc.relation.projectID Gobierno de España. TEC2017-92552-EXP
dc.relation.projectID Comunidad de Madrid. Y2018/TCS-4705
dc.relation.projectID Gobierno de España. RTI2018-099655-B-I00
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 1
dc.identifier.publicationissue 71
dc.identifier.publicationlastpage 18
dc.identifier.publicationtitle Mathematics
dc.identifier.publicationvolume 9 (1)
dc.identifier.uxxi AR/0000027981
dc.contributor.funder Ministerio de Economía y Competitividad (España)
dc.affiliation.dpto UC3M. Departamento de Teoría de la Señal y Comunicaciones
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Tratamiento de la Señal y Aprendizaje (GTSA)
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