Literature DB >> 19775978

Automatic detection of respiration rate from ambulatory single-lead ECG.

Justin Boyle1, Niranjan Bidargaddi, Antti Sarela, Mohan Karunanithi.   

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 +/-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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Year:  2009        PMID: 19775978     DOI: 10.1109/TITB.2009.2031239

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  10 in total

1.  Estimation of respiration rate from three-dimensional acceleration data based on body sensor network.

Authors:  Guan-Zheng Liu; Yan-Wei Guo; Qing-Song Zhu; Bang-Yu Huang; Lei Wang
Journal:  Telemed J E Health       Date:  2011-11       Impact factor: 3.536

2.  Effect of ECG-derived respiration (EDR) on modeling ventricular repolarization dynamics in different physiological and psychological conditions.

Authors:  M H Imam; C K Karmakar; A H Khandoker; M Palaniswami
Journal:  Med Biol Eng Comput       Date:  2014-08-27       Impact factor: 2.602

3.  Spontaneous fluctuations in neural responses to heartbeats predict visual detection.

Authors:  Hyeong-Dong Park; Stéphanie Correia; Antoine Ducorps; Catherine Tallon-Baudry
Journal:  Nat Neurosci       Date:  2014-03-09       Impact factor: 24.884

4.  Estimating Heart Rate and Respiratory Rate from a Single Lead Electrocardiogram Using Ensemble Empirical Mode Decomposition and Spectral Data Fusion.

Authors:  Iau-Quen Chung; Jen-Te Yu; Wei-Chi Hu
Journal:  Sensors (Basel)       Date:  2021-02-08       Impact factor: 3.576

5.  Wearable Respiration Monitoring: Interpretable Inference With Context and Sensor Biomarkers.

Authors:  Ridwan Alam; David B Peden; John C Lach
Journal:  IEEE J Biomed Health Inform       Date:  2021-06-04       Impact factor: 7.021

6.  Assessment of human respiration patterns via noncontact sensing using Doppler multi-radar system.

Authors:  Changzhan Gu; Changzhi Li
Journal:  Sensors (Basel)       Date:  2015-03-16       Impact factor: 3.576

7.  Cardiorespiratory system monitoring using a developed acoustic sensor.

Authors:  Reza Abbasi-Kesbi; Atefeh Valipour; Khadije Imani
Journal:  Healthc Technol Lett       Date:  2018-01-12

8.  Wearable Contactless Respiration Sensor Based on Multi-Material Fibers Integrated into Textile.

Authors:  Philippe Guay; Stepan Gorgutsa; Sophie LaRochelle; Younes Messaddeq
Journal:  Sensors (Basel)       Date:  2017-05-06       Impact factor: 3.576

Review 9.  Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.

Authors:  Peter H Charlton; Drew A Birrenkott; Timothy Bonnici; Marco A F Pimentel; Alistair E W Johnson; Jordi Alastruey; Lionel Tarassenko; Peter J Watkinson; Richard Beale; David A Clifton
Journal:  IEEE Rev Biomed Eng       Date:  2017-10-24

Review 10.  Application of Modern Multi-Sensor Holter in Diagnosis and Treatment.

Authors:  Erik Vavrinsky; Jan Subjak; Martin Donoval; Alexandra Wagner; Tomas Zavodnik; Helena Svobodova
Journal:  Sensors (Basel)       Date:  2020-05-07       Impact factor: 3.576

  10 in total

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