DocumentCode :
1447324
Title :
Automatic Detection of Respiration Rate From Ambulatory Single-Lead ECG
Author :
Boyle, Justin ; Bidargaddi, Niranjan ; Sarela, Antti ; Karunanithi, Mohan
Author_Institution :
Australian E-Health Res. Centre, R. Brisbane & Women´´s Hosp., Herston, QLD, Australia
Volume :
13
Issue :
6
fYear :
2009
Firstpage :
890
Lastpage :
896
Abstract :
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.
Keywords :
band-pass filters; cardiovascular system; electrocardiography; medical signal detection; pneumodynamics; RR technique; abnormal electrical behavior; ambulatory single-lead ECG; apnea; automatic detection; bandpass filter; cardiovascular system; electrocardiography; frequency 0.2 Hz to 0.8 Hz; nasal cannula respiratory monitor; respiration rate detection; time 1 h; Cardiovascular system; electrocardiography; exercise; respiratory system; Activities of Daily Living; Data Interpretation, Statistical; Electrocardiography; Heart Rate; Humans; Monitoring, Ambulatory; Reproducibility of Results; Respiratory Rate; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-7771
Type :
jour
DOI :
10.1109/TITB.2009.2031239
Filename :
5256153
Link To Document :
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