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Paul S Addison

Publications and source records attributed to Paul S Addison.

10 recordsLinked to original sources
PubMed2006

Measurement of respiratory rate from the photoplethysmogram in chest clinic patients.

OBJECTIVE: We studied the application of our algorithm for the robust extraction of respiratory information from the pulse oximeter signal acquired from a selection of patients attending the chest clinic. METHODS: Photoplethysmograms were obtained from 16 individuals: 13 patients with various conditions in the respiratory ward and three healthy subjects. Wavelet transforms were generated from which respiratory information was extracted to obtain a measure of respiratory rate. This measured rate was compared with the respiratory rate determined by one of a variety of other means (a digital end tidal CO(2) signal, the output from a non-invasive ventilation device, or a switch actuated by the patient or observer.) RESULTS: Respiratory rates varied from 6.2 to 35.8 breaths per minute (bpm). The oximeter rate determined through our method matched the marker rate obtained for all patients to within 1 bpm. CONCLUSION: The technique allows the measurement of respiratory rate directly from the photoplethysmogram of a pulse oximeter, and leads the way for development of a simple non-invasive combined respiration and saturation monitor useful for patients with all forms of breathlessness.

Adult↗
PubMed2006

A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram.

OBJECTIVE: To determine if an automatic algorithm using wavelet analysis techniques can be used to reliably determine respiratory rate from the photoplethysmogram (PPG). METHODS: Photoplethysmograms were obtained from 12 spontaneously breathing healthy adult volunteers. Three related wavelet transforms were automatically polled to obtain a measure of respiratory rate. This was compared with a secondary timing signal obtained by asking the volunteers to actuate a small push button switch, held in their right hand, in synchronisation with their respiration. In addition, individual breaths were resolved using the wavelet-method to identify the source of any discrepancies. RESULTS: Volunteer respiratory rates varied from 6.56 to 18.89 breaths per minute. Through training of the algorithm it was possible to determine a respiratory rate for all 12 traces acquired during the study. The maximum error between the PPG derived rates and the manually determined rate was found to be 7.9%. CONCLUSION: Our technique allows the accurate measurement of respiratory rate from the photoplethysmogram, and leads the way for developing a simple non-invasive combined respiration and saturation monitor.

Adult↗
PubMed2006

An automated algorithm for determining respiratory rate by photoplethysmogram in children.

BACKGROUND: We have developed an automated algorithm to allow the measurement of respiratory rate directly from the photoplethysmogram (pulse oximeter waveform). AIM: To test the algorithm's ability to determine respiratory rate in children. METHODS: A convenience sample of patients attending a paediatric Accident and Emergency Department was monitored using a purpose-built pulse oximeter and the photoplethysmogram (PPG) recorded. Respiration was also recorded by an observer activating a push-button switch in synchronization with the child's breathing. The switch marker signals were processed to derive a manual respiratory rate that was compared with the wavelet-based oximeter respiratory rate derived from the PPG signal. RESULTS: Photoplethysmograms were obtained from 18 children aged 18 mo to 12 y, breathing spontaneously at rates of 17 to 27 breaths per minute. There was close correspondence between the wavelet-based oximeter respiration rate and the manual respiratory rate, with the difference between them being less than one breath per minute in all children. CONCLUSION: Our automated algorithm allows the accurate determination of respiratory rate from photoplethysmograms of a heterogeneous group of children. We believe that our automated wavelet-based signal-processing techniques could soon be easily incorporated into current pulse oximetry technology.

Algorithms↗
PubMed2005

Wavelet transforms and the ECG: a review.

The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.

Arrhythmias, Cardiac↗
PubMed2005

Oxygen saturation determined using a novel wavelet ratio surface.

A wavelet-based method is presented for oxygen saturation measurement using photoplethysmogram signals from a standard pulse oximeter device. The transform moduli of both red and infrared signals are used to derive a novel wavelet ratio surface. Projection of the pulse component onto this surface allows optimal derivation of oxygen saturation.

Algorithms↗
PubMed2004

An algorithm for the detection of individual breaths from the pulse oximeter waveform.

OBJECTIVES: To determine if wavelet analysis techniques can be used to reliably identify individual breaths from the photoplethysmogram (PPG). METHODS: Photoplethysmograms were obtained from 22 healthy adult volunteers timing their respiration rate in synchronisation with a metronome. A secondary timing signal was obtained by asking the volunteers to actuate a small push button switch, held in their right hand, in synchronisation with their respiration. Each PPG was analyzed using primary wavelet decomposition and two new, related, secondary decompositions to determine the accuracy of individual breath detection. RESULTS: The optimal breath capture was obtained by manually polling the three techniques, allowing detection of 466 out of the 472 breaths studied; a detection rate of 98.7% with no false positive breaths detected. CONCLUSION: Our technique allows the accurate capture of individual breaths from the photoplethysmogram, and leads the way for developing a simple non-invasive combined respiration and saturation monitor.

Algorithms↗
PubMed2004

Improved prediction of defibrillation success for out-of-hospital VF cardiac arrest using wavelet transform methods.

We report an improved method for the estimation of shock outcome prediction based on novel wavelet transform-based time-frequency methods. Wavelet-based peak frequency, energy, mean frequency, spectral flatness and a new entropy measure were studied to predict shock outcome. Of these, the entropy measure provided optimal results with 60 +/- 6% specificity at 91 +/- 2% sensitivity achieved for the prediction of return of spontaneous circulation (ROSC). These results represent a major improvement in shock prediction in human ventricular fibrillation.

Electric Countershock↗
PubMed2004

Wavelet-based analysis of heart-rate-dependent ECG features.

BACKGROUND: Wavelet-based methods of analyzing ECG signals have been used to identify specific features in cardiac arrhythmias. Since some of these features are rate dependent, it is a requirement that they are examined across a range of physiological heart rates. The wavelet transform is a signal analysis tool that can elucidate spectral and temporal information simultaneously from complex signals, including the ECG. The aim of this study was to identify the local frequency characteristics of the ECG using a real-time wavelet scalogram and to study the rate dependence of these features. METHODS: We examined the spectral temporal behavior of the local characteristics of the electrocardiogram (ECG) of 10 patients, in whom precise control of heart rate was achieved using right atrial pacing. Temporary reprogramming was used to adjust the paced atrial rate to predetermined values so that a rate-controlled rhythm was produced that closely resembled sinus rhythm. RESULTS: Rate-dependent features are seen on time-frequency scalograms. As the rate increases, the temporal spacing of features decrease and the frequency bands shift upward on the plot. Two patients with abnormal atrioventricular conduction demonstrate features of Wenckebach conduction and fusion. CONCLUSIONS: Characterization of the rate-dependent features of the ECG in a paced atrial rhythm by wavelet transform techniques has revealed some additional information not readily seen on single lead ECG analysis. This model provides a surrogate for changes that might be expected during rate changes in physiological sinus rhythm. It is envisaged that this method will offer advantages in detecting features of clinical significance that may not be readily seen by existing methods.

Arrhythmias, Cardiac↗