Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting

Niels Kant, Guido Maarten Peters, Brenda Jantine Voorthuis, C. Oudshoorn, Mark V. Koning, Bart P.L. Witteman, Myra Rinia-Feenstra, Carine Doggen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. Agreement was defined as the mean absolute difference between both monitoring devices. Bland Altman plots and Clarke Error Grid analysis (CEG) were used to visualise differences. Sensor reliability was reflected by the amount, duration and causes of data loss. The mean absolute difference for HR was 1.26 beats per minute (bpm) (SD 0.84) during surgery and 1.84 bpm (SD 1.22) during recovery, and never exceeded the 8 bpm limit of agreement. The mean absolute difference for RR was 1.78 breaths per minute (brpm) (SD 1.90) during surgery and 4.24 brpm (SD 2.75) during recovery. The Biosensor’s RR measurements exceeded the 2 brpm limit of agreement in 58% of the compared measurements. Averaging 15 min of measurements for both devices improved agreement. CEG showed that 99% of averaged RR measurements resulted in adequate treatment. Data loss was limited to 4.5% of the total duration of measurements for RR. No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems.
Original languageEnglish
Number of pages11
JournalJournal of clinical monitoring and computing
Early online date8 Dec 2021
DOIs
Publication statusE-pub ahead of print/First online - 8 Dec 2021

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