Automatic Detection of Respiration Rate From Ambulatory Single-Lead ECG

• Published in: IEEE transactions on information technology in biomedicine Vol. 13; no. 6; pp. 890 - 896
• Main Authors: Boyle, J., Bidargaddi, N., Sarela, A., Karunanithi, M.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2009
• Subjects: Activities of Daily Living; Air flow; Band pass filters; Cardiovascular system; Data Interpretation, Statistical; Electrocardiography; Electrocardiography - instrumentation; Error analysis; exercise; Fluid flow measurement; Gold; Heart; Heart rate; Heart Rate - physiology; Humans; Legged locomotion; Monitoring, Ambulatory - instrumentation; Monitoring, Ambulatory - methods; Monitors; Patient monitoring; Patients; Recording; Reproducibility of Results; Respiration; Respiratory Rate - physiology; respiratory system; Signal Processing, Computer-Assisted - instrumentation; Stress; System testing; Walking; Waveforms
• ISSN: 1089-7771; 1558-0032
• DOI: 10.1109/TITB.2009.2031239

Ambulatory electrocardiography is increasingly being used in clinical practice to detect abnormal electrical behavior of the heart during ordinary daily activities. The utility of this monitoring can be improved by deriving respiration, which previously has been based on overnight apnea studies where patients are stationary, or the use of multilead ECG systems for stress testing. We compared six respiratory measures derived from a single-lead portable ECG monitor with simultaneously measured respiration air flow obtained from an ambulatory nasal cannula respiratory monitor. Ten controlled 1-h recordings were performed covering activities of daily living (lying, sitting, standing, walking, jogging, running, and stair climbing) and six overnight studies. The best method was an average of a 0.2-0.8 Hz bandpass filter and RR technique based on lengthening and shortening of the RR interval. Mean error rates with the reference gold standard were plusmn4 breaths per minute (bpm) (all activities), plusmn2 bpm (lying and sitting), and plusmn1 breath per minute (overnight studies). Statistically similar results were obtained using heart rate information alone (RR technique) compared to the best technique derived from the full ECG waveform that simplifies data collection procedures. The study shows that respiration can be derived under dynamic activities from a single-lead ECG without significant differences from traditional methods.