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Development of an interface to improve HRV analysis: combining automatic and manual processing

Llopis, Guillermo (2024) Development of an interface to improve HRV analysis: combining automatic and manual processing. Master's Thesis / Essay, Computational Cognitive Science.


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In response to the limitations of existing heart rate variability (HRV) analysis tools, we have developed a novel software that amalgamates advanced automatic correction capabilities with an intuitive user interface. Traditional HRV programs were often criticized for their outdated design, lack of userfriendliness, and overly time-consuming processes. Additionally, more modern programs rely heavily on automatic corrections without allowing users to verify or adjust these modifications, leading to potential inaccuracies. Our program addresses these issues by providing a comprehensive suite of automatic correction options while maintaining user oversight, enabling practitioners to validate and, if necessary, override automated edits to the RR interval data. The software has undergone rigorous validation against manually annotated datasets, demonstrating high concordance with expert analysis. Feedback from initial user evaluations has been instrumental in identifying further enhancements, such as refining beat detection algorithms for noisy signal environments and incorporating additional features suggested by end-users. This user-focused approach to HRV analysis not only streamlines the process but also ensures a higher level of precision and customization, catering to the specific needs of researchers and clinicians in the field.

Item Type: Thesis (Master's Thesis / Essay)
Supervisor name: Cnossen, F. and Wietzorrek, L.K.
Degree programme: Computational Cognitive Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 02 Apr 2024 12:03
Last Modified: 02 Apr 2024 12:03

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