Impact of body position on imaging ballistocardiographic signals
- Current works direct at the unobtrusive acquisition of vital parameters from videos. The most common approach exploits subtle color variations. The analysis of cardiovascular induced motion from videos (imaging ballistocardiography, iBCG) is another approach that can supplement the analysis of color changes. The presented study systematically investigates the impact of body position (supine vs. upright) on iBCG. Our research directs at heart rate estimation by iBCG and on the possibility to analyse ballistocardiographic waveforms from iBCG. We use own data from 30 healthy volunteers, who went through repeated orthostatic maneuvers on a tilt table. Processing is done according to common procedures for iBCG processing including feature tracking, dimensionality reduction and bandpass filtering. Our results indicate that heart rate estimation works well in supine position (root mean square error of heart rate estimation 5.68 beats per minute). The performance drastically degrades in upriCurrent works direct at the unobtrusive acquisition of vital parameters from videos. The most common approach exploits subtle color variations. The analysis of cardiovascular induced motion from videos (imaging ballistocardiography, iBCG) is another approach that can supplement the analysis of color changes. The presented study systematically investigates the impact of body position (supine vs. upright) on iBCG. Our research directs at heart rate estimation by iBCG and on the possibility to analyse ballistocardiographic waveforms from iBCG. We use own data from 30 healthy volunteers, who went through repeated orthostatic maneuvers on a tilt table. Processing is done according to common procedures for iBCG processing including feature tracking, dimensionality reduction and bandpass filtering. Our results indicate that heart rate estimation works well in supine position (root mean square error of heart rate estimation 5.68 beats per minute). The performance drastically degrades in upri ght (standing) position (root mean square error of heart rate estimation 21.20 beats per minute). With respect to analysis of beat waveforms, we found large intra-subject and inter-subject variations. Only in few cases, the resulting waveform closely resembles the ideal ballistocardiographic waveform. Our investigation indicates that the actual position has a large effect on iBCG and should be considered in algorithmic developments and testing.…
Author: | Alexander Woyczyk, Sebastian ZaunsederGND |
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URN: | urn:nbn:de:bvb:384-opus4-1073901 |
Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/107390 |
ISBN: | 978-989-758-631-6OPAC |
ISSN: | 2184-4305OPAC |
Parent Title (English): | Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023), February 16-18, 2023, Lisbon, Portugal - Volume 4: BIOSIGNALS |
Publisher: | SciTePress |
Place of publication: | Setúbal |
Editor: | Ioanna Chouvarda, Ana Fred, Hugo Gamboa |
Type: | Conference Proceeding |
Language: | English |
Year of first Publication: | 2023 |
Publishing Institution: | Universität Augsburg |
Release Date: | 2023/09/12 |
First Page: | 55 |
Last Page: | 65 |
DOI: | https://doi.org/10.5220/0011659900003414 |
Institutes: | Fakultät für Angewandte Informatik |
Fakultät für Angewandte Informatik / Institut für Informatik | |
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Diagnostische Sensorik | |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Licence (German): | CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand) |