Using Confidence Intervals to Assess the Reliability of Instantaneous Heart Rate and Respiratory Rate
ARMY MEDICAL RESEARCH AND MATERIEL COMMAND FORT DETRICK MD TELEMEDICINE AND ADVANCED TECH RESEARCH CENTER
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Physiological waveform signals collected from unstructured environments are noisy, requiring automated algorithms to assess the reliability of the derived vital signs, such as heart rate HR and respiratory rate RR, before they can be used for automated decision support. We recently proposed a weighted regularized least squares method to estimate instantaneous HR HRR, which readily provides analytically based confidence intervals CIs. Accordingly, this method can be extended to the estimation of instantaneous RR RRR. In this study, we aim to investigate whether we can use CIs to select reliable HRR and RRR. We calculated HRR and RRR for 532 and 370 trauma patients, respectively, grouped the rates according to their CIs, and investigated their reliability by determining their ability to diagnose major hemorrhage. The areas under a receiver operating characteristic curve of HRR and RRR with CI 8804 5 bpm beats per minute for HR and breaths per minute for RR were 0.70 and 0.66, respectively. RRR was superior to the average output of the clinical monitor p 0.05 by DeLongs test, while HRR was equivalent. HRR and RRR provide a new approach to systematically and automatically assess the reliability of noisy, field-collected vital signs.
- Anatomy and Physiology
- Medicine and Medical Research