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  4. Sensorfusion für das robuste und kontaktlose Monitoring der Vitalparameter von Frühgeborenen auf der neonatologischen Intensivstation
 
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Sensorfusion für das robuste und kontaktlose Monitoring der Vitalparameter von Frühgeborenen auf der neonatologischen Intensivstation

Citation Link: https://doi.org/10.15480/882.16153
Publikationstyp
Doctoral Thesis
Date Issued
2025
Sprache
German
Author(s)
Gleichauf, Johanna  
Advisor
Kölpin, Alexander  orcid-logo
Referee
Knopp, Tobias  
Niebler, Christine  
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2025-09-02
Institute
Hochfrequenztechnik E-3  
TORE-DOI
10.15480/882.16153
TORE-URI
https://hdl.handle.net/11420/58762
Citation
Technische Universität Hamburg (2025)
The current monitoring of vital signs of preterm neonates bears the risk to injure the little patients. Therefor, the question arises if it is possible to determine the vital parameters of neonates and preterm neonates precisely and robustly via non-contact methods. A non-contact system was developed for monitoring the respiratory and heart rates as well as the core temperature of the neonates. Different sensors such as an RGB camera, a thermal camera, several time-of-flight cameras and a radar sensor are combined or their data are fused. The region of interest detected by each sensor is automatically determined by a neural network (YOLOv3) which was trained with fused images. The necessary algorithms to calculate the vital parameters were developed or existing algorithms improved. The best approach found during the validation phase is the evaluation of ToF camera data for determining the respiratory rate and the temperature detection via thermal camera with reference temperature sensor. The evaluation of the heart rate using an RGB camera does not deliver the clinical necessary precision. It was shown that under optimal conditions a non-contact detection of the respiratory rate and the body temperature is possible with good results.
Subjects
neonates
non-contact monitoring
vital parameters
heterogeneous sensors
neural network
DDC Class
610: Medicine, Health
620: Engineering
621: Applied Physics
Funding(s)
Kontaktloses Monitoring-System für Frühgeborene auf der Neonatologischen Intensivstation
Funding Organisations
Bundesministerium für Bildung und Forschung
More Funding Information
Referenznummer: 13FH546IX6
Lizenz
https://creativecommons.org/licenses/by/4.0/
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