Affiliations: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Bangi, Malaysia
Correspondence:
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Corresponding author: Nazrul Anuar Nayan, Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Bangi, Malaysia. Tel.: +603 8911 8360; Fax: +603 8911 8359; E-mail:nazrul@eng.ukm.my
Abstract: BACKGROUND: Among vital signs of acutely ill hospital patients,
respiratory rate (RR) is a highly accurate predictor of health
deterioration. OBJECTIVE: This study proposes a system that consists of a passive
and non-invasive single-lead electrocardiogram (ECG) acquisition module and
an ECG-derived respiratory (EDR) algorithm in the working prototype of a
mobile application. METHOD: Before estimating RR that produces the EDR rate, ECG
signals were evaluated based on the signal quality index (SQI). The SQI
algorithm was validated quantitatively using the PhysioNet/Computing in
Cardiology Challenge 2011 training data set. The RR extraction algorithm was
validated by adopting 40 MIT PhysioNet Multiparameter Intelligent Monitoring
in Intensive Care II data set. RESULTS: The estimated RR showed a mean absolute error (MAE) of 1.4
compared with the ``gold standard'' RR. The proposed system was used to
record 20 ECGs of healthy subjects and obtained the estimated RR with MAE of
0.7 bpm. CONCLUSION: Results indicate that the proposed hardware and
algorithm could replace the manual counting method, uncomfortable nasal
airflow sensor, chest band, and impedance pneumotachography often used in
hospitals. The system also takes advantage of the prevalence of smartphone
usage and increase the monitoring frequency of the current ECG of patients
with critical illnesses.
Keywords: Respiratory rate, single-lead ECG, algorithm, e-health system, mobile applications
