Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Student works
  4. Evaluation and extension of an automated system to diagnose the health of premature babies
 
master thesis

Evaluation and extension of an automated system to diagnose the health of premature babies

Joggi, Camille  
2011

Premature babies are not fully equipped to deal with the outside world. Their immature bodies make them highly at risk to a large number of physiological complications. Therefore, while they are still immature, premature babies are taken care of in neonatology intensive care units, where they are kept in a controlled and protective environment. In these units, the babies' vital parameters, such as their heart rate and temperature, are tightly monitored. The devices used to record this data are fitted with alarms that are triggered automatically when something wrong is detected. However, the alarm systems currently used are often unable to discriminate between real physiological problems and artefacts that should be ignored (e.g. when a measurement device drops-out). As a result, these systems produce a high rate of false alarms, where the alarm is triggered when nothing is clinically wrong. The can have unwanted consequences: first, it creates a noisy environment, which may disturb the babies; second, it can lead to the alarm being ignored when there is actually something wrong. In order to address this problem, my host laboratory has constructed a system that can automatically infer the state of health of premature babies in neonatology units, based on their recorded physiological data. The new system is designed to be able to deal with artefactual changes in the measurements, hopefully resulting in a reduced number of false alarms. In this thesis, I describe my contribution to this project, which is twofold. The first part deals with the problem of evaluating the performance of the system. To do this, I developed an online feedback process, where clinicians could provide information about the true clinical interpretation of the physiological data, which could be compared to the output of the system. The feedbacks provided by the clinicians were then analysed to investigate how the system could be improved. The second part of my thesis was motivated be early feedbacks from the clinicians, which indicated that the system was unable to deal with changes in the humidity measurements that occurred when the incubator door was opened and closed. To address this, I extended the current system, so that it was able to account for these changes, thereby increasing its capability to detect "true" physiological problems during the period after the incubator door is closed.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

Joggi_thesis.pdf

Access type

openaccess

Size

54.3 MB

Format

Adobe PDF

Checksum (MD5)

e2b44469a8a6a8ae4d215f49b4d10162

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés