Tu-SML-04 - Impact of Sensor Selection on Signal Quality of Physiological Monitoring in Demanding Conditions

Event

EUROSENSORS 2026
2026-09-06 - 2026-09-09
Zurich

Band

Poster

Chapter

Signal Analysis, Machine Learning, Physics-Informed Machine Learning And Artificial Intelligence For Sensing

Author(s)

A. F. Renz, E. Maevskaia, F. Bauer, R. M. Rossi, S. Annaheim - Empa,St. Gallen (Switzerland), A. Stier - Armasuisse,Bern (Switzerland), D. Bron - Swiss Air Forces,Dubendorf (Switzerland)

Pages

702 - 703

DOI

10.5162/eurosensors2026/Tu-SML-04

ISBN

978-3-910600-12-6

Price

free

Abstract

Monitoring vital signs becomes increasingly important beyond stationary medical settings for real world applications. With the rise of wearable sensor systems, monitoring over various time windows and in dynamic environments requires new evaluation of signal quality and suitable sensor selection. In this work we highlight the importance of evaluating the signal quality of wearable electrocardiography (ECG) derived data prior to further interpretation in the highly dynamic and demanding operational environment of fighter jet pilots.