Influence of Sensor Position and Body Movements on Radar-Based Heart Rate Monitoring

Herzer L, Mücke A, Richer R, Albrecht NC, Heyder M, Jäger K, König V, Koelpin A, Rohleder N, Eskofier B (2022)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Original Authors: Liv Herzer, Annika Muecke, Robert Richer, Nils C. Albrecht, Markus Heyder, Katharina M. Jaeger, Veronika Koenig, Alexander Koelpin, Nicolas Rohleder, Bjoern M. Eskofier

Series: 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

Event location: Ioannina GR

URI: https://www.mad.tf.fau.de/files/2022/11/herzer_muecke22_validation_mis.pdf

DOI: 10.1109/BHI56158.2022.9926775

Abstract

Cardiac parameters are important indicators for health assessment. Radar-based monitoring with microwave interferometric sensors (MIS) is a promising alternative to conventional measurement methods, as it enables completely contactless cardiac function diagnostics. In this study, we evaluated the effects of sensor positioning and movement on the accuracy of radar-based heart rate measurements with MIS. For this purpose, we recruited 29 participants which performed semi-standardized movements, a reading task, and a standardized laboratory stress test in a seated position. Furthermore, we compared three different sensor positions (dorsal, upper pectoral, and lower pectoral) to a gold standard 1-channel wearable ECG sensor node. The dorsal positioning achieved the best results with a mean error (ME) of 0.2±5.4 bpm and a mean absolute error (MAE) of 3.5±4.1 bpm for no movement and also turned out to be most robust against motion artifacts with an overall ME of 0.1±14.1 bpm (MAE: 9.5±10.4 bpm). No correlation was found between movement intensity and measurement error. Instead, movement type and direction were identified as primary impact factors. This study provides a valuable contribution towards the applicability of radar-based vital sign monitoring with MIS in real-world scenarios. However, further research is needed to sufficiently prevent and compensate for movement artifacts.

Authors with CRIS profile

Annika Mücke Machine Learning and Data Analytics Lab Robert Richer Machine Learning and Data Analytics Lab Nils Christian Albrecht Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung Markus Heyder Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung Katharina Jäger Machine Learning and Data Analytics Lab Veronika Ringgold Machine Learning and Data Analytics Lab Nicolas Rohleder Lehrstuhl für Gesundheitspsychologie Björn Eskofier Machine Learning and Data Analytics Lab

Additional Organisation(s)

Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung

Related research project(s)

Kardiovaskuläres respiratorisches Mikrowelleninterferometer (SFB 1483 EmpkinS A04) Empatho-Kinaesthetic Sensor Technology (SFB 1483 EmpkinS) July 1, 2021 - June 30, 2025 Berührungslose Messung von Stress, seiner Determinanten und Konsequenzen (SFB 1483 EmpkinS D03) Empatho-Kinaesthetic Sensor Technology (SFB 1483 EmpkinS) July 1, 2021 - June 30, 2025 Empatho-Kinaesthetic Sensor Technology (SFB 1483 EmpkinS) July 1, 2021 - June 30, 2025

Involved external institutions

Technische Universität Hamburg-Harburg (TUHH) DE Germany (DE)

How to cite

APA:

Herzer, L., Mücke, A., Richer, R., Albrecht, N.C., Heyder, M., Jäger, K.,... Eskofier, B. (2022). Influence of Sensor Position and Body Movements on Radar-Based Heart Rate Monitoring. In IEEE (Eds.), Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). Ioannina, GR.

MLA:

Herzer, Liv, et al. "Influence of Sensor Position and Body Movements on Radar-Based Heart Rate Monitoring." Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Ioannina Ed. IEEE, 2022.

BibTeX: Download