MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data

Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptabilit...

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Vydané v:Sensors (Basel, Switzerland) Ročník 22; číslo 15; s. 5849
Hlavní autori: Ollenschläger, Malte, Küderle, Arne, Mehringer, Wolfgang, Seifer, Ann-Kristin, Winkler, Jürgen, Gaßner, Heiko, Kluge, Felix, Eskofier, Bjoern M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 05.08.2022
MDPI
Predmet:
Algorithms
annotation
Documentation
Electrocardiography
Gait
gait analysis
graphical user interface
Labeling
Machine learning
Open source software
Programming languages
python
Subject specialists
time series analysis
Usability
User experience
User interface
ISSN:1424-8220, 1424-8220
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Shrnutí:Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptability, usability, and user experience. Therefore, we developed a generic open-source Python package focusing on adaptability, usability, and user experience. The developed package, Machine Learning and Data Analytics (MaD) GUI, enables developers to rapidly create a GUI for their specific use case. Furthermore, MaD GUI enables domain experts without programming knowledge to annotate time-series data and apply algorithms to it. We conducted a small-scale study with participants from three international universities to test the adaptability of MaD GUI by developers and to test the user interface by clinicians as representatives of domain experts. MaD GUI saves up to 75% of time in contrast to using a state-of-the-art package. In line with this, subjective ratings regarding usability and user experience show that MaD GUI is preferred over a state-of-the-art package by developers and clinicians. MaD GUI reduces the effort of developers in creating GUIs for time-series analysis and offers similar usability and user experience for clinicians as a state-of-the-art package.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22155849