Development of three methods for extracting respiration from the surface ECG: A review

Helfenbein, Eric; Firoozabadi, Reza; Chien, Simon C.; Carlson, Eric; Babaeizadeh, Saeed

doi:10.1016/j.jelectrocard.2014.07.020

Cited by 72 publications

(76 citation statements)

References 13 publications

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“…This method has now been reported using a single-channel ECG [15] and can detect obstructive apnoea and changes in tidal volume [16]. However it still appears less accurate when compared to airflow and movement methods of RR measurement [17].…”

Section: Electrocardiogram Derived Measurementmentioning

confidence: 99%

Medical Devices for Measuring Respiratory Rate in Children: a Review

Daw

Kingshott

Saatchi

et al. 2016

J. Advs. Biomed. Eng. Techno.

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Abstracts: Respiratory rate is an important vital sign used for diagnosing illnesses in children as well as prioritising patient care. All children presenting acutely to hospital should have a respiratory rate measured as part of their initial and ongoing assessment. However measuring the respiratory rate remains a subjective assessment and in children can be liable to measurement error especially if the child is uncooperative. Devices to measure respiratory rate exist but many provide only an estimate of respiratory rate due to the associated methodological complexities. Some devices are used within the intensive care, post-operative or more specialised investigatory settings none however have made their way into the everyday clinical setting. A non-contact device may be better tolerated in children and not cause undue stress distorting the measurement. Further validation and adaption to the acute clinical setting is needed before such devices can supersede current methods.

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Section: Electrocardiogram Derived Measurementmentioning

confidence: 99%

Medical Devices for Measuring Respiratory Rate in Children: a Review

Daw

Kingshott

Saatchi

et al. 2016

J. Advs. Biomed. Eng. Techno.

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show abstract

“…These fluctuations of the R-peak amplitude were exploited to generate the ECG-amplitude-based respiratory curve (ERSa). 23 The second method used the respiratory breathing arrhythmia which, in general, causes an increase of heart rate during inspiration and a decrease during expiration. However, an adverse effect of isoflurane anesthesia on this effect has been described in rodents, 24 as was observed in our study.…”

Section: Data Processing-ecg-based Respiratory Signal (Ers)mentioning

confidence: 99%

“…Nevertheless, the variation of the heartbeat duration, estimated from the interval between two R-peaks in the ECG signal, was utilized to generate the alternative ECG-based respiration curve (ERSt). 23 ECG-based respiratory trigger events were then derived from the peaks in these two respiratory signals.…”

Section: Data Processing-ecg-based Respiratory Signal (Ers)mentioning

confidence: 99%

“…Similar techniques are already in use for patient monitoring. 23,33,34 As stated in the introduction, respiratory motion and heart contraction can be extracted directly from the PET emission data, according to published methods. 6 Since extraction of the organ movement depends on the tracer uptake, the acquired data must entail sufficiently high count statistics for this method to work adequately.…”

Section: Applicability In Humans and Outlookmentioning

confidence: 99%

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Derivation of a respiration trigger signal in small animal list-mode PET based on respiration-induced variations of the ECG signal

Todica¹,

Lehner²,

Wang³

et al. 2016

Journal of Nuclear Cardiology

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“…Thus, there is a growing interest in alternative diagnosis approaches, such as portable holter Electrocardiogram (ECG) monitoring [12,13]. By using modern computing machinery and state of the art algorithms, it is possible to extract respiration waveforms from ECG signals [14]. Such systems can be used in OSA analysis.…”

Section: Introductionmentioning

confidence: 99%

A Review of Ecg-Based Diagnosis Support Systems for Obstructive Sleep Apnea

Faust

Acharya

et al. 2016

J. Mech. Med. Biol.

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Humans need sleep. It is important for physical and psychological recreation. During sleep our consciousness is suspended or least altered. Hence, our ability to avoid or react to disturbances is reduced. These disturbances can come from external sources or from disorders within the body. Obstructive Sleep Apnea (OSA) is such a disorder. It is caused by obstruction of the upper airways which causes periods where the breathing ceases. In many cases, periods of reduced breathing, known as hypopnea, precede OSA events. The medical background of OSA is well understood, but the traditional diagnosis is expensive, as it requires sophisticated measurements and human interpretation of potentially large amounts of physiological data. Electrocardiogram (ECG) measurements have the potential to reduce the cost of OSA diagnosis by simplifying the measurement process. On the down side, detecting OSA events based on ECG data is a complex task which requires highly skilled practitioners. Computer algorithms can help to detect the subtle signal changes which indicate the presence of a disorder. That approach has the following advantages: computers never tire, processing resources are economical and progress, in the form of better algorithms, can be easily disseminated as updates over the internet. Furthermore, Computer-Aided Diagnosis (CAD) reduces intra- and inter-observer variability. In this review, we adopt and support the position that computer based ECG signal interpretation is able to diagnose OSA with a high degree of accuracy.

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Development of three methods for extracting respiration from the surface ECG: A review

Cited by 72 publications

References 13 publications

Medical Devices for Measuring Respiratory Rate in Children: a Review

Medical Devices for Measuring Respiratory Rate in Children: a Review

Derivation of a respiration trigger signal in small animal list-mode PET based on respiration-induced variations of the ECG signal

A Review of Ecg-Based Diagnosis Support Systems for Obstructive Sleep Apnea

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