Continuous Radar-based Heart Rate Monitoring using Autocorrelation-based Algorithm in Intensive Care Unit

Sepehr Seifizarei*, Ismail Elnaggar, Arman Anzanpour, Jonas Sandelin, Olli Lahdenoja, Miguel Glassee, Ivan D. Castro, Tom Torfs, Marcel C.G. Van De Poll, Antti Airola, Matti Kaisti, Tero Koivisto

*Corresponding author for this work

Research output: Contribution to journalArticleAcademic

Abstract

This study presents a radar-based algorithm for non-invasive heart rate monitoring in intensive care units (ICUs) using a 140 GHz Frequency-Modulated Continuous Wave (FMCW) radar, placed unobtrusively beneath hospital beds. Data were collected from 15 post-operative cardiac patients at Maastricht University Hospital, with an ECG device serving as the ground truth for validation. The proposed algorithm includes data preprocessing, channel selection, heart rate estimation, and post-processing, employing autocorrelation to detect rhythmic patterns and quality metrics to ensure reliable channel selection. The system achieved a mean absolute error (MAE) of 2.22 beats per minute (bpm) with 66% overall coverage, increasing to 98% during sinus rhythm periods. This approach demonstrates robust performance in challenging ICU environments by mitigating noise and motion artifacts and optimizing computational efficiency. These findings highlight the potential of radar-based systems to enhance patient care through continuous, non-invasive vital sign monitoring and validate the algorithm's effectiveness in real-world clinical scenarios.
Original languageEnglish
JournalIEEE Journal of Biomedical and Health Informatics
DOIs
Publication statusE-pub ahead of print - 1 Jan 2025

Keywords

  • Bed monitoring
  • heart rate
  • intensive care unit (ICU)
  • monitoring
  • Non-invasive
  • radar
  • signal processing
  • vital sign

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