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Presenting Automatic Analysis Of Uroflowmetry Curves

Slagman, Hermannus (2020) Presenting Automatic Analysis Of Uroflowmetry Curves.

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Abstract:The department of Urology at the University Medical Centre (UMC) of Utrecht has developed a classification algorithm to find and recognize symptoms in Uroflow measurement data for patients with Lower Urinary Tract Symptoms (LUTS). Our aim with this research is to create a dashboard that visualizes and explains the finding of said classification algorithm, and to implement the classification algorithm in a modular way to pave the way for further development. During this research, codesign based on concepts with the algorithms creator was implemented in addition to feedback from the head of Urology at the UMC to ensure the best possible result. The end product was evaluated using the System Usability Scale test and achieved a total score of 86.8, suggesting that the Uroflow Dashboard is clear and easy to use. The evaluation of the stakeholders and department of Urology was mostly positive, informing us that the Uroflow Dashboard did give them more insight into the classification algorithms workings. This being said, they would like to see more visual cues in the curve visualization to nudge the user to a correct flow description, even without additional textual feedback from the dashboard.
Item Type:Essay (Bachelor)
Clients:
UMC, Utrecht, The Netherlands
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:44 medicine, 54 computer science
Programme:Creative Technology BSc (50447)
Link to this item:http://purl.utwente.nl/essays/80522
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