Detecting dynamical changes in vital signs using switching Kalman filter

Conference paper


Gomes de Almeida, V. and Nabney, I. 2017. Detecting dynamical changes in vital signs using switching Kalman filter. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Jeju, South Korea 11 - 15 Jul 2017 IEEE. pp. 2223-2226 https://doi.org/10.1109/EMBC.2017.8037296
TypeConference paper
TitleDetecting dynamical changes in vital signs using switching Kalman filter
AuthorsGomes de Almeida, V. and Nabney, I.
Abstract

Vital signs contain valuable information about patients' health status during their stay in general wards, when the deterioration process begins. The use of methods to predict and detect regime changes such as switching models can help to understand how vital sign dynamics are altered in disease conditions. However, time series of vital signs are remarkably non-stationary in these scenarios. The objective of this study is to quantify the potential bias of switching models in the presence of non-stationarities, when the inputs are spectral, symbolic and entropy indices. To distinguish stationary from non-stationary periods, a test was used to verify the stability of the mean and variance over short periods. Then, we compared the results from a switching Kalman filter (SKF) model trained using indices obtained over stationary periods with a model trained solely over non-stationary periods. It was observed that indices measured over stationary and non-stationary periods were significantly different. The results of switching models were highly dependent on the indices that were used as inputs. The multi-scale entropy (MSE) approach presented the highest correlation values between non-stationary and stationary switches, an average correlation coefficient of 38%.

LanguageEnglish
Conference2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Page range2223-2226
Proceedings Title2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
SeriesIEEE Engineering in Medicine and Biology Society Conference Proceedings
ISSN1557-170X
Electronic1558-4615
ISBN
Hardcover9781509028092
PublisherIEEE
Publication dates
Print14 Sep 2017
Publication process dates
Deposited05 Mar 2018
Accepted19 Apr 2017
Output statusPublished
Accepted author manuscript
Copyright Statement

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Digital Object Identifier (DOI)https://doi.org/10.1109/EMBC.2017.8037296
Web of Science identifierWOS:000427085302162
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