We present an approach for real-time respiratory rate (RR) estimation in a neonatal intensive care unit (NICU) using a pressure-sensitive mat (PSM). Real patient data were collected in an NICU from four sources simultaneously: a PSM placed under the patient, a Draeger patient monitor, a video camera placed directly above the patient, and a custom bedside event annotation application running on a tablet. The PSM data were used to develop an algorithm for estimating the patient's RR. The results were evaluated against impedance pneumography (IP) based RR measurements from the patient monitor. In comparison to the IP estimates, we achieved a mean absolute error of 4.51 breaths per minute (bpm) for 3 hours of data collected from a single patient. Moreover, we show that our newer approach performs better than the previous frequency-based approach that was developed based on patient simulator data. The estimation accuracy achieved by the new algorithm meets clinical requirements for the determination of RR.

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13th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2018
Department of Systems and Computer Engineering

Bekele, A. (Amente), Nizami, S. (Shermeen), Dosso, Y.S. (Yasmina Souley), Aubertin, C. (Cheryl), Greenwood, K. (Kim), Harrold, J. (Joann), & Green, J. (2018). Real-time Neonatal Respiratory Rate Estimation using a Pressure-Sensitive Mat. In MeMeA 2018 - 2018 IEEE International Symposium on Medical Measurements and Applications, Proceedings. doi:10.1109/MeMeA.2018.8438682