Katharina Jäger
Katharina Jäger, M. Sc.
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik
Carl-Thiersch-Straße 2b
91054 Erlangen
- Phone number: +49 9131 85 20286
- Email: katharina.jaeger@fau.de
- Website: https://www.mad.tf.fau.de/person/katharina-jager/
Academic CV
| since 09/2020 | Researcher and PhD Candidate
Machine Learning and Data Analytics Lab |
| 10/2017-05/2020 | M.Sc. in Medical Engineering, “Medical Image and Data Processing”
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Majors: Pattern Recognition, Image Processing, Biomedical Signal Processing, Deep Learning |
| 06/2019-12/2019 | Research Intern and Master’s Thesis
Bloomlife, Belgium |
| 11/2016-06/2019 | Working Student
Magnetic Resonance Imaging, Siemens Healthineers |
| 08/2015-04/2016 | Scientific Assistant
Chair of Multimedia Communications and Signal Processing |
| 10/2013-04/2017 | B.Sc. in Medical Engineering, “Medical Imaging Systems”
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Majors: Image and Signal Processing, Embedded Systems |
Research Projects
Publications
2022
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Smartphone-Based Colorimetric Analysis of Urine Test Strips for At-Home Prenatal Care
In: IEEE Journal of Translational Engineering in Health and Medicine (2022), p. 1-9
ISSN: 2168-2372
DOI: 10.1109/JTEHM.2022.3179147
BibTeX: Download - , , , , , , , :
THE STROOP COMPETITION: A SOCIAL-EVALUATIVE STROOP TEST FOR ACUTE STRESS INDUCTION
In: PSYCHOSOMATIC MEDICINE, PHILADELPHIA: 2022
BibTeX: Download - , , , , , , , :
The Stroop Competition: A Social-Evaluative Stroop Test For Acute Stress Induction
79th Annual Scientific Meeting of the American Psychosomatic Society (Long Beach, CA, 23. March 2022 - 26. March 2022)
In: Lippincott Williams & Wilkins (ed.): Psychosomatic Medicine 2022
BibTeX: Download - , , , , , , , , , :
Heart Rate Measurement Accuracy of Fitbit Charge 4 and Samsung Galaxy Watch Active2: Device Evaluation Study
In: JMIR Formative Research 6 (2022), p. e33635
ISSN: 2561-326X
DOI: 10.2196/33635
BibTeX: Download - , , , , , , , :
Prediction of Stress Coping Capabilities from Nightly Heart Rate Patterns Using Machine Learning
79th Annual Scientific Meeting of the American Psychosomatic Society (Long Beach, CA, 23. March 2022 - 26. March 2022)
In: Lippincott Williams & Wilkins (ed.): Psychosomatic Medicine, PHILADELPHIA: 2022
BibTeX: Download
2021
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Digital Maternity Records: Motivation, Acceptance, Requirements, Usability and Prototype Evaluation of an Interface for Physicians and Midwives
MuC '21: Mensch und Computer 2021 (Ingolstadt, 5. September 2021 - 8. September 2021)
In: Mensch und Computer 2021 2021
DOI: 10.1145/3473856.3473994
BibTeX: Download
Teaching
Seminar (SEM)
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Digital Psychology Lab
Voraussetzungen: Im Vordergrund des Kurses steht die Verarbeitung und Analyse von biopsychologischen Daten in Python im Vordergrund. Daher sind (gute) Kenntnisse der Programmiersprache Python und damit verbundene Programmbibliotheken (NumPy, Pandas, SciPy, Matplotlib, etc.), bzw. das Interesse, sich diese Kenntnisse als Vorbereitung oder im Laufe des Kurses anzueignen, erwünscht.
Wenn Sie Ihr Wissen prüfen oder auffrischen wollen, empfehlen wir Ihnen die folgenden Vorlesungen und Online-Ressourcen: Beachten Sie jedoch, dass einige von ihnen bei vielen Themen über die Anforderungen dieses Kurses hinausgehen!
- Udacity Kurs: Introduction to Python
- Stanford Kurs: Introduction to Scientific Python
- SciPy Lecture Notes
- Introduction to Pandas for Data Science
- American Psychological Association A brief introduction to Python for psychological science research
- Introduction to Programming for Psychological Scientists
Anmeldung: Studierende der Medizintechnik melden sich bei Interesse an der Lehrveranstaltung bitte vorab per Email an mad-dipsylab@fau.de an.
Student Theses
| Year | Name | Title |
| 2022 | Luisa Graf | Cardiac Monitoring of Heart Failure Patients using Smartwatches (Master’s Thesis) |
| 2022 | Siri Pflüger | Analyzing the Health Status of Heart Failure Patients based on Telemonitoring Data using Machine Learning (Master’s Thesis) |
| 2021 | Carlos Perez | Usability Aspects of Pregnancy Applications and Digital Maternity Records (Master’s Thesis) |
| 2021 | Simone Rahm | group:Fetal Heart Rate Extraction from Wearable Non-Invasive Electrocardiogram Devices (Master’s Thesis) |
| 2020 | Luisa Dörflinger | group:Digital Maternity Records: Physician’s Perspective on Motivation and Usability (Bachelor’s Thesis) |