An Open Source Classifier for Bed Mattress Signal in Infant Sleep Monitoring.
NICU
bed mattress sensor
infant sleep
intensive care monitoring
non-invasive monitoring
sleep-wake cycling
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2020
2020
Historique:
received:
14
09
2020
accepted:
15
12
2020
entrez:
1
2
2021
pubmed:
2
2
2021
medline:
2
2
2021
Statut:
epublish
Résumé
To develop a non-invasive and clinically practical method for a long-term monitoring of infant sleep cycling in the intensive care unit. Forty three infant polysomnography recordings were performed at 1-18 weeks of age, including a piezo element bed mattress sensor to record respiratory and gross-body movements. The hypnogram scored from polysomnography signals was used as the ground truth in training sleep classifiers based on 20,022 epochs of movement and/or electrocardiography signals. Three classifier designs were evaluated in the detection of deep sleep (N3 state): support vector machine (SVM), Long Short-Term Memory neural network, and convolutional neural network (CNN). Deep sleep was accurately identified from other states with all classifier variants. The SVM classifier based on a combination of movement and electrocardiography features had the highest performance (AUC 97.6%). A SVM classifier based on only movement features had comparable accuracy (AUC 95.0%). The feature-independent CNN resulted in roughly comparable accuracy (AUC 93.3%). Automated non-invasive tracking of sleep state cycling is technically feasible using measurements from a piezo element situated under a bed mattress. An open source infant deep sleep detector of this kind allows quantitative, continuous bedside assessment of infant's sleep cycling.
Identifiants
pubmed: 33519357
doi: 10.3389/fnins.2020.602852
pmc: PMC7840576
doi:
Types de publication
Journal Article
Langues
eng
Pagination
602852Informations de copyright
Copyright © 2021 Ranta, Airaksinen, Kirjavainen, Vanhatalo and Stevenson.
Déclaration de conflit d'intérêts
JR was a shareholder and a part time employee in sensor manufacturer Emfit Ltd. Emfit did not have any role in study design, data analysis or publication process. This work was mostly done before JR was employed by Emfit. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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