Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models

Soren M. Rasmussen; Jesper Molgaard; Camilla Haahr-Raunkjaer; Christian S. Meyhoff; Eske Aasvang; Helge B.D. Sorensen

doi:10.1109/EMBC48229.2022.9871010

Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models

Soren M. Rasmussen^*, Jesper Molgaard, Camilla Haahr-Raunkjaer, Christian S. Meyhoff, Eske Aasvang, Helge B.D. Sorensen

^*Corresponding author af dette arbejde

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

1 Citationer (Scopus)

11 Downloads (Pure)

Abstract

This project assessed the use of multivariate auto-regressive (MAR) models to create forecasts of continuous vital signs in hospitalized patients. A total of 20 hours continuous (1/60Hz) heart rate and respiration rate from eight postoperative patients, where used to fit a centered MAR model for forecasting in windows of 15 minutes. The model was fitted using Markov Chain Monte Carlo sampling, and the model was evaluated on data from five additional patients. The results demonstrate an average RMSE in the forecast window of 11.4 (SD: 7.30) beats per minute for heart rate and 3.3 (SD:1.3) breaths per minute for respiration rate. These results indicate potential for forecasting vital signs in a clinical setting.

Originalsprog	Engelsk
Titel	44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Antal sider	4
Forlag	IEEE
Publikationsdato	2022
Sider	385-388
ISBN (Elektronisk)	9781728127828
DOI	https://doi.org/10.1109/EMBC48229.2022.9871010
Status	Udgivet - 2022
Begivenhed	44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 - Glasgow, Storbritannien Varighed: 11 jul. 2022 → 15 jul. 2022

Konference

Konference	44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Land/Område	Storbritannien
By	Glasgow
Periode	11/07/2022 → 15/07/2022
Sponsor	Verasonics

Navn	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Vol/bind	2022-July
ISSN	1557-170X

Bibliografisk note

Publisher Copyright:
© 2022 IEEE.

Adgang til dokumentet

10.1109/EMBC48229.2022.9871010Licens: CC BY

FulltextForlagets udgivne version, 753 KBLicens: CC BY

Citationsformater

Rasmussen, S. M., Molgaard, J., Haahr-Raunkjaer, C., Meyhoff, C. S., Aasvang, E., & Sorensen, H. B. D. (2022). Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models. I 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 (s. 385-388). IEEE. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS Bind 2022-July https://doi.org/10.1109/EMBC48229.2022.9871010

Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models. / Rasmussen, Soren M.; Molgaard, Jesper; Haahr-Raunkjaer, Camilla; Meyhoff, Christian S.; Aasvang, Eske; Sorensen, Helge B.D.

44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022. IEEE, 2022. s. 385-388 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Bind 2022-July).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Rasmussen, SM, Molgaard, J, Haahr-Raunkjaer, C, Meyhoff, CS , Aasvang, E & Sorensen, HBD 2022, Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models. i 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022. IEEE, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, bind 2022-July, s. 385-388, 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022, Glasgow, Storbritannien, 11/07/2022. https://doi.org/10.1109/EMBC48229.2022.9871010

Rasmussen SM, Molgaard J, Haahr-Raunkjaer C, Meyhoff CS , Aasvang E, Sorensen HBD. Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models. I 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022. IEEE. 2022. s. 385-388. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Bind 2022-July). https://doi.org/10.1109/EMBC48229.2022.9871010

Rasmussen, Soren M. ; Molgaard, Jesper ; Haahr-Raunkjaer, Camilla ; Meyhoff, Christian S. ; Aasvang, Eske ; Sorensen, Helge B.D. / Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models. 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022. IEEE, 2022. s. 385-388 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Bind 2022-July).

@inproceedings{ac42185c30284101ae95ba2aa136afd6,

title = "Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models",

abstract = "This project assessed the use of multivariate auto-regressive (MAR) models to create forecasts of continuous vital signs in hospitalized patients. A total of 20 hours continuous (1/60Hz) heart rate and respiration rate from eight postoperative patients, where used to fit a centered MAR model for forecasting in windows of 15 minutes. The model was fitted using Markov Chain Monte Carlo sampling, and the model was evaluated on data from five additional patients. The results demonstrate an average RMSE in the forecast window of 11.4 (SD: 7.30) beats per minute for heart rate and 3.3 (SD:1.3) breaths per minute for respiration rate. These results indicate potential for forecasting vital signs in a clinical setting.",

author = "Rasmussen, {Soren M.} and Jesper Molgaard and Camilla Haahr-Raunkjaer and Meyhoff, {Christian S.} and Eske Aasvang and Sorensen, {Helge B.D.}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 ; Conference date: 11-07-2022 Through 15-07-2022",

year = "2022",

doi = "10.1109/EMBC48229.2022.9871010",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "IEEE",

pages = "385--388",

booktitle = "44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022",

}

TY - GEN

T1 - Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models

AU - Rasmussen, Soren M.

AU - Molgaard, Jesper

AU - Haahr-Raunkjaer, Camilla

AU - Meyhoff, Christian S.

AU - Aasvang, Eske

AU - Sorensen, Helge B.D.

PY - 2022

Y1 - 2022

N2 - This project assessed the use of multivariate auto-regressive (MAR) models to create forecasts of continuous vital signs in hospitalized patients. A total of 20 hours continuous (1/60Hz) heart rate and respiration rate from eight postoperative patients, where used to fit a centered MAR model for forecasting in windows of 15 minutes. The model was fitted using Markov Chain Monte Carlo sampling, and the model was evaluated on data from five additional patients. The results demonstrate an average RMSE in the forecast window of 11.4 (SD: 7.30) beats per minute for heart rate and 3.3 (SD:1.3) breaths per minute for respiration rate. These results indicate potential for forecasting vital signs in a clinical setting.

AB - This project assessed the use of multivariate auto-regressive (MAR) models to create forecasts of continuous vital signs in hospitalized patients. A total of 20 hours continuous (1/60Hz) heart rate and respiration rate from eight postoperative patients, where used to fit a centered MAR model for forecasting in windows of 15 minutes. The model was fitted using Markov Chain Monte Carlo sampling, and the model was evaluated on data from five additional patients. The results demonstrate an average RMSE in the forecast window of 11.4 (SD: 7.30) beats per minute for heart rate and 3.3 (SD:1.3) breaths per minute for respiration rate. These results indicate potential for forecasting vital signs in a clinical setting.

U2 - 10.1109/EMBC48229.2022.9871010

DO - 10.1109/EMBC48229.2022.9871010

M3 - Article in proceedings

C2 - 36085852

AN - SCOPUS:85138127748

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 385

EP - 388

BT - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022

PB - IEEE

T2 - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022

Y2 - 11 July 2022 through 15 July 2022

ER -