Gareth Clegg

CONTINUOUS WAVELET TRANSFORM MODULUS MAXIMA ANALYSIS OF THE ELECTROCARDIOGRAM: BEAT CHARACTERISATION AND BEAT-TO-BEAT MEASUREMENT

The problem of automatic beat recognition in the ECG is tackled using continuous wavelet transform modulus maxima (CWTMM). Features within a variety of ECG signals can be shown to correspond to various morphologies in the CWTMM domain. This domain has an easy interpretation and offers a useful tool for the automatic characterization of the different components observed in the ECG in health and disease. As an application of this enhanced time-frequency analysis technique for ECG signals, an R-wave detector is developed and tested using patient signals recorded in the Coronary Care Unit of the Royal Infirmary of Edinburgh (attaining a sensitivity of 99.53% and a positive predictive value of 99.73%) and with the MIT/BIH database (attaining a sensitivity of 99.70% and a positive predictive value of 99.68%).

Evaluating arrhythmias in ECG signals using wavelet transforms

Recent work has attempted to utilize wavelet techniques in the analysis of biomedical signals including ECGs. Here, the authors present an energy-based method of interrogating the ECG in VF using high-resolution, log-scale continuous wavelet plots. With this method, underlying structures within the VF waveform are made visible in the wavelet time-scale half space.

R-wave detection using continuous wavelet modulus maxima

Modulus maxima derived from the continuous wavelet transform offers an enhanced time-frequency analysis technique for ECG signal analysis. Features within the ECG can be shown to correspond to various morphologies in the continuous modulus maxima domain. This domain has an easy interpretation and offers a good tool for the automatic characterization of the different components observed in the ECG in health and disease. As an application of these properties we have developed an R-wave detector and tested it using patient signals recorded in the Coronary Care Unit of the Royal Infirmary of Edinburgh (attaining a sensitivity of 99.53% and a positive predictive value of 99.73%) and with the MIT/BIH database (attaining a sensitivity of 99.7% and a positive predictive value of 99.68%).

A novel wavelet transform based analysis reveals hidden structure in ventricular fibrillation

We report a new method of interrogating the surface ECG signal using techniques developed in the field of wavelet transform analysis. Previously unreported structure within the ECG during ventricular fibrillation (VF) is found using a high-resolution decomposition of the signal employing the continuous wavelet transform. We believe that wavelet transform methods could lead to the development of powerful tools for use in the resuscitation of patients with cardiac arrest.

Finding coordinated atrial activity during ventricular fibrillation using wavelet decomposition

Until recently, the ECG recorded during ventricular fibrillation was thought to represent disorganized and unstructured electrical activity of the heart. Using a new signal analysis technique based on wavelet decomposition, we have begun to reveal previously unreported structure within the ECG tracing. We report preliminary findings that provide the first evidence linking this structure to unexpected mechanical phenomena occurring in the heart.

Analysing the ventricular fibrillation waveform

The surface electrocardiogram associated with ventricular fibrillation has been of interest to researchers for some time. Over the last few decades, techniques have been developed to analyse this signal in an attempt to obtain more information about the state of the myocardium and the chances of successful defibrillation. This review looks at the implications of analysing the VF waveform and discusses the various techniques that have been used, including fast Fourier transform analysis, wavelet transform analysis and mathematical techniques such as chaos theory.

Resuscitation feedback and targeted education improves quality of pre-hospital resuscitation in Scotland.

BACKGROUND Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality and serious neurological morbidity in Europe. Recent studies have demonstrated the adverse physiological consequences of poor resuscitation technique and have shown that quality of cardiopulmonary resuscitation (CPR) is a critical determinant of outcome from OHCA. Telemetry of the defibrillator transthoracic impedance (TTI) trace can objectively measure quality of pre-hospital resuscitation. This study aims to analyse the impact of targeted resuscitation feedback and training on quality of pre-hospital resuscitation. METHODS Prospective, single centre, cohort study over 13 months (1st December 2009-31st December 2010). Baseline pre-hospital resuscitation data was gathered over a 3-month period. Modems (n=40) were fitted to defibrillators on ambulance vehicles. Following a resuscitation attempt, the event was sent via telemetry and the TTI trace analysed. Outcome measures were time spent performing chest compressions, compression rate, the interval required to deliver a defibrillator shock and use of automatic or manual cardiac rhythm analysis. Targeted resuscitation classes were introduced and all ambulance crews received feedback following a resuscitation attempt. Pre-hospital resuscitation quality pre and post intervention were compared. RESULTS 111 resuscitation traces were analysed. Mean hands-on-chest time improved significantly following feedback and targeted resuscitation training (73.0% vs 79.3%, p=0.007). There was no significant change in compression rate during the study period. There was a significant reduction in median time-to-shock interval from 20.25s (IQR 15.50-25.50s) to 13.45 s (IQR 2.25-22.00 s) (p=0.006). Automatic rhythm recognition fell from 50% to 28.6% (p=0.03) following intervention. CONCLUSION Telemetry and analysis of the TTI trace following OHCA allows objective evaluation of the quality of pre-hospital resuscitation. Targeted resuscitation training and ambulance feedback improves the quality of pre-hospital resuscitation. Further studies are required to establish possible survival benefit from this technique.

Dispatch-assisted CPR: Where are the hold-ups during calls to emergency dispatchers? A preliminary analysis of caller–dispatcher interactions during out-of-hospital cardiac arrest using a novel call transcription technique

BACKGROUND Survival from out-of-hospital cardiac arrest (OHCA) is dependent on the chain of survival. Early recognition of cardiac arrest and provision of bystander cardiopulmonary resuscitation (CPR) are key determinants of OHCA survival. Emergency medical dispatchers play a key role in cardiac arrest recognition and giving telephone CPR advice. The interaction between caller and dispatcher can influence the time to bystander CPR and quality of resuscitation. We sought to pilot the use of emergency call transcription to audit and evaluate the holdups in performing dispatch-assisted CPR. METHODS A retrospective case selection of 50 consecutive suspected OHCA was performed. Audio recordings of calls were downloaded from the emergency medical dispatch centre computer database. All calls were transcribed using proprietary software and voice dialogue was compared with the corresponding stage on the Medical Priority Dispatch System (MPDS). Time to progress through each stage and number of caller-dispatcher interactions were calculated. RESULTS Of the 50 downloaded calls, 47 were confirmed cases of OHCA. Call transcription was successfully completed for all OHCA calls. Bystander CPR was performed in 39 (83%) of these. In the remaining cases, the caller decided the patient was beyond help (n = 7) or the caller said that they were physically unable to perform CPR (n = 1). MPDS stages varied substantially in time to completion. Stage 9 (determining if the patient is breathing through airway instructions) took the longest time to complete (median = 59 s, IQR 22-82 s). Stage 11 (giving CPR instructions) also took a relatively longer time to complete compared to the other stages (median = 46 s, IQR 37-75 s). Stage 5 (establishing the patients age) took the shortest time to complete (median = 5.5s, IQR 3-9s). CONCLUSION Transcription of OHCA emergency calls and caller-dispatcher interaction compared to MPDS stage is feasible. Confirming whether a patient is breathing and completing CPR instructions required the longest time and most interactions between caller and dispatcher. Use of call transcription has the potential to identify key factors in caller-dispatcher interaction that could improve time to CPR and further research is warranted in this area.

Esophageal temperature after out-of-hospital cardiac arrest: An observational study

INTRODUCTION Out-of-hospital cardiac arrest (OHCA) is a significant cause of death and severe neurological disability. The only post-return of spontaneous circulation (ROSC) therapy shown to increase survival is mild therapeutic hypothermia (MTH). The relationship between esophageal temperature post OHCA and outcome is still poorly defined. METHODS Prospective observational study of all OHCA patients admitted to a single centre for a 14-month period (1/08/2008 to 31/09/2009). Esophageal temperature was measured in the Emergency Department and Intensive Care Unit (ICU). Selected patients had pre-hospital temperature monitoring. Time taken to reach target temperature after ROSC was recorded, together with time to admission to the Emergency Department and ICU. RESULTS 164 OHCA patients were included in the study. 105 (64.0%) were pronounced dead in the Emergency Department. 59 (36.0%) were admitted to ICU for cooling; 40 (24.4%) died in ICU and 19 (11.6%) survived to hospital discharge. Patients who achieved ROSC and had esophageal temperature measured pre-hospital (n=29) had a mean pre-hospital temperature of 33.9 degrees C (95% CI 33.2-34.5). All patients arriving in the ED post OHCA had a relatively low esophageal temperature (34.3 degrees C, 95% CI 34.1-34.6). Patients surviving to hospital discharge were warmer on admission to ICU than patients who died in hospital (35.7 degrees C vs 34.3 degrees C, p<0.05). Patients surviving to hospital discharge also took longer to reach T(targ) than non-survivors (2h 48min vs 1h 32min, p<0.05). CONCLUSIONS Following OHCA all patients have esophageal temperatures below normal in the pre-hospital phase and on arrival in the Emergency Department. Patients who achieve ROSC following OHCA and survive to hospital discharge are warmer on arrival in ICU and take longer to reach target MTH temperatures compared to patients who die in hospital. The mechanisms of action underlying esophageal temperature and survival from OHCA remain unclear and further research is warranted to clarify this relationship.

Measuring temporal complexity of ventricular fibrillation

Abstract Temporal complexity of early ventricular fibrillation (VF) is re-assessed through measuring the correlation dimension D 2 , entropy K 2 and high-dimensional component σ from electrocardiogram (ECG) recordings using the Gaussian kernel algorithm. Seven representative ECG traces of induced VF among 53 pig subjects are selected for analysis. VF is found to have 80–90% low-dimensional deterministic dynamics with D 2 varying around 5 and 10–20% high-dimensional extents.