DailyHeart
DailyHeart – A Unobtrusive Vertigo Assessment System for Long Term Monitoring in Daily-life Environments
Project leader: Björn Eskofier, Eva Dorschky
Project members: Nils Roth, Jochen Klucken, Björn Eskofier
Start date: 15. August 2014
End date:
Abstract
DailyHeart is a system for vertigo assessment during daily-life activities. It addresses the whole pipeline from data acquisition (via unobtrusive body-worn sensors) over data processing to data visualization and potential feedback (via Android application).
The main idea is to assess the autonomous nervous system (ANS) during the orthostatic reaction, characterized by an increase in heart rate after posture transitions, e.g. from lying or sitting to standing. Whereas the ANS of healthy subjects can easily adapt to these posture changes, people suffering from ANS disorders (e.g. Parkinson’s Disease) experience a considerably heart rate response and a decrease in blood pressure, potentially leading to vertigo and syncope.
Clinical results have shown that multiple measurements throughout the day can already indicate a possible disorder of the ANS. For that reason, DailyHeart aims to transfer the clinical assessment into the home environment by detecting posture changes during daily-life activities and thus trigger an HRV and BP analysis for effectively assessing vertigo and thus provide a recommendation of consulting a medical expert.
Visualization of sensor positions and acquired biosignals |
Visualization of orthostatic reaction: Course of heart rate during posture change for a healthy person (blue) and a PD patient (red) |
Screenshots of DailyHeart for Android |
Screenshots of DailyHeart for Android Wear |
Publications
- Richer R., Blank P., Schuldhaus D., Eskofier B.:
Real-Time ECG and EMG Analysis for Biking Using Android-Based Mobile Devices
2014 IEEE 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (Zürich, 16. June 2014 - 19. June 2014)
In: 2014 IEEE 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2014
DOI: 10.1109/BSN.2014.20
URL: https://www.mad.tf.fau.de/files/2018/04/2014-Richer-BSN-Bikey.pdf
BibTeX: Download - Richer R., Maiwald T., Pasluosta CF., Hensel B., Eskofier B.:
Novel Human Computer Interaction Principles for Cardiac Feedback using Google Glass and Android Wear
2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (Cambridge, MA, 9. June 2015 - 12. June 2015)
In: IEEE (ed.): 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2015
DOI: 10.1109/BSN.2015.7299363
URL: https://www.mad.tf.fau.de/files/2018/04/2015-Richer-BSN-DailyHeart.pdf
BibTeX: Download - Richer R., Groh B., Blank P., Dorschky E., Martindale C., Klucken J., Eskofier B.:
Unobtrusive Real-time Heart Rate Variability Analysis for the Detection of Orthostatic Dysregulation
2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (San Francisco, CA, 14. June 2016 - 17. June 2016)
In: IEEE (ed.): 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2016
DOI: 10.1109/BSN.2016.7516257
URL: https://www.mad.tf.fau.de/files/2017/06/2016-Richer-BSN-URH.pdf
BibTeX: Download
Related Theses
- Sophia Leierseder (Bachelor’s Thesis, 2018):
Continuous Blood Pressure Measurement During Daily-life Activities Using Pulse Transit Time - Daniel Krauß (Bachelor’s Thesis, 2019):
Heart Rate Variability Analysis for Unsupervised Tilt Table Testing during Daily-life Activities