Automatic Detection of Respiration Rate From Ambulatory Single-Lead ECG

心率 回廊的 呼吸频率 呼吸 呼吸暂停 铅(地质) 医学 心电图 QRS波群 鼻插管 马甲 心脏病学 麻醉 套管 内科学 数学 统计 外科 血压 病理 地貌学 解剖 地质学
作者
Justin Boyle,Niranjan Bidargaddi,Antti Särelä,Mohan Karunanithi
出处
期刊:IEEE Transactions on Information Technology in Biomedicine [Institute of Electrical and Electronics Engineers]
卷期号:13 (6): 890-896 被引量:96
标识
DOI:10.1109/titb.2009.2031239
摘要

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 +/-4 breaths per minute (bpm) (all activities), +/-2 bpm (lying and sitting), and +/-1 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.

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