Impact of the Environment on Health Status of Intensive Care Unit Patients: Functional Data Analysis Using Wearable Monitoring Systems
| UDC.coleccion | Investigación | |
| UDC.departamento | Matemáticas | |
| UDC.grupoInv | Modelización, Optimización e Inferencia Estatística (MODES) | |
| UDC.institutoCentro | CITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación | |
| UDC.journalTitle | Intensive and Critical Care Nursing | |
| UDC.startPage | 104183 | |
| UDC.volume | 91 | |
| dc.contributor.author | Rodríguez-Cortés, Francisco J. | |
| dc.contributor.author | Oviedo de la Fuente, Manuel | |
| dc.contributor.author | Jiménez-Pastor, Jose M. | |
| dc.contributor.author | López-Coleto, Luna | |
| dc.contributor.author | Arévalo-Buitrago, Pedro | |
| dc.contributor.author | Cruz López-Carrasco, Juan de la | |
| dc.contributor.author | Valverde-León, Rocío | |
| dc.contributor.author | López-Soto, Pablo Jesús | |
| dc.contributor.author | Morales-Cané, Ignacio | |
| dc.date.accessioned | 2026-02-10T10:10:58Z | |
| dc.date.available | 2026-02-10T10:10:58Z | |
| dc.date.issued | 2025-12 | |
| dc.description | Supplementary data to this article available for downloading. | |
| dc.description.abstract | [Abstract]: Objectives: Environmental factors in critical care units (ICUs) can significantly impact patient health. Traditional analysis methods often struggle with the continuous temporal data from wearable monitoring devices. This study explores the novel application of functional data analysis (FDA), a methodology well suited for continuous signals, to assess how environmental exposures influence ICU patient outcomes over time. Specifically, it examines the most impactful environmental variables. It evaluates FDA’s effectiveness in analysing continuous data from wearable monitoring devices, in contrast to traditional methods that overlook temporal patterns by using average or isolated measurements. Methods: A prospective cohort study was conducted in a tertiary-level reference ICU in southern Spain, where wearable sensors were used to collect physiological and environmental data from 77 adult patients continuously. Functional data analysis (FDA) techniques were employed to explore temporal patterns in the collected signals. Results: Noise intensity (decibels) was the most significant environmental variable, correlating with Richmond Agitation-Sedation Scale (RASS) scores and heart rate (HR). Functional additive models significantly improved model performance, achieving R2 values up to 0.78 for RASS prediction in trauma patients. Effects varied across patient diagnosis subgroups. Conclusions: FDA techniques, particularly functional additive models, better model complex relationships between environmental and physiological variables in the ICU. Environmental impacts differ across patient types, suggesting the need for specialised environmental interventions based on patient condition. Implications for Clinical Practice: This study underscores the need for environmental monitoring in ICUs and highlights the potential of wearable sensors and advanced statistical analysis to optimise patient care and improve outcomes by tailoring environmental interventions to specific patient needs. | |
| dc.description.sponsorship | This research received a specific grant from the Ministry of Health and Families, Government of Andalusia (PIGE-0462–2019) and from the Ministry of Economy and Knowledge, Regional Government of Andalusia (UCO-FEDER 1381293-R). The funders were not involved in the study design, data collection, data analysis, or preparation of this manuscript. | |
| dc.description.sponsorship | Junta de Andalucía; PIGE-0462–2019 | |
| dc.description.sponsorship | Junta de Andalucía; UCO-FEDER 1381293-R | |
| dc.identifier.citation | F.J. Rodríguez-Cortés, M. Oviedo-de la Fuente, J. M. Jiménez-Pastor, L. López-Coleto, P. Arévalo-Buitrago, J. de la Cruz López-Carrasco, R. Valverde-León, P. J. Lopez-Soto, and I. Morales-Cané, "Impact of the environment on health status of intensive care unit patients: Functional data analysis using wearable monitoring systems", Intensive and Critical Care Nursing, Vol. 91, Dec. 2025, 104183, https://doi.org/10.1016/j.iccn.2025.104183 | |
| dc.identifier.doi | 10.1016/j.iccn.2025.104183 | |
| dc.identifier.issn | 1532-4036 | |
| dc.identifier.uri | https://hdl.handle.net/2183/47315 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier | |
| dc.relation.uri | https://doi.org/10.1016/j.iccn.2025.104183 | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Critical care | |
| dc.subject | Intensive care unit | |
| dc.subject | Wearable technology | |
| dc.subject | Functional data analysis | |
| dc.subject | Continuous data | |
| dc.subject | Noise pollution | |
| dc.subject | Digital Healthcare Solutions | |
| dc.subject | IoT Healthcare Solutions | |
| dc.title | Impact of the Environment on Health Status of Intensive Care Unit Patients: Functional Data Analysis Using Wearable Monitoring Systems | |
| dc.type | journal article | |
| dc.type.hasVersion | VoR | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 15997118-059a-491f-b7d3-84eadf33cec5 | |
| relation.isAuthorOfPublication.latestForDiscovery | 15997118-059a-491f-b7d3-84eadf33cec5 |
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