| dc.creator | Bonilla-Escribano, Pablo | |
| dc.creator | Ramírez, David | |
| dc.creator | Sedano-Capdevila, Alba | |
| dc.creator | Campaña-Montes, Juan J. | |
| dc.creator | Baca-García, Enrique | |
| dc.creator | Courtet, Philippe | |
| dc.creator | Artés-Rodríguez, Antonio | |
| dc.date | 2023-01-23T17:58:47Z | |
| dc.date | 2023-01-23T17:58:47Z | |
| dc.date | 2019 | |
| dc.date.accessioned | 2024-05-02T20:30:29Z | |
| dc.date.available | 2024-05-02T20:30:29Z | |
| dc.identifier | http://repositorio.ucm.cl/handle/ucm/4426 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9274669 | |
| dc.description | This paper introduces a novel method to assess the social activity maintained by psychiatric patients using information and communication technologies. In particular, we model the daily usage patterns of phone calls and social and communication apps using point processes. We propose a novel nonhomogeneous Poisson process model with periodic (circadian) intensity function using a truncated Fourier series expansion, which is inferred using a trust-region algorithm. We also extend the model using a mixture of periodic intensity functions to cope with the different daily patterns of a person. The analysis of the usage of phone calls and social and communication apps of a cohort of 259 patients reveals common patterns shared among patients with relatively high homogeneity and differences among patient pathologies. | |
| dc.language | en | |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | |
| dc.rights | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | |
| dc.source | IEEE Journal of Biomedical and Health Informatics, 23(6), 2247-2256 | |
| dc.subject | E-social activity | |
| dc.subject | Expectation-maximization (EM) algorithm | |
| dc.subject | Maximum likelihood (ML) | |
| dc.subject | Mixture model | |
| dc.subject | Point processes | |
| dc.title | Assessment of e-social activity in psychiatric patients | |
| dc.type | Article | |
