Sequential algorithm for life threatening cardiac pathologies detection based on mean signal strength and EMD functions

Background  

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are the most serious cardiac arrhythmias that require quick and accurate detection to save lives. Automated external defibrillators (AEDs) have been developed to recognize these severe cardiac arrhythmias using complex algorithms inside it and determine if an electric shock should in fact be delivered to reset the cardiac rhythm and restore spontaneous circulation. Improving AED safety and efficacy by devising new algorithms which can more accurately distinguish shockable from non-shockable rhythms is a requirement of the present-day because of their uses in public places.     

Morphological detection algorithms for the automatic implantable cardioverter/defibrillator (AICD).

To prevent sudden cardiac death of patients who are at risk from long standing tachyarrhythmia the implantable cardioverter defibrillator (ICD) is the first choice therapy. ICDs use a range of electrostimuli up to defibrillation, which is a non synchronous high energy shock, whereas cardioversion is synchronous with the ECG. In order to know when and how to react, a detection algorithm, which analyses an intracardial electrocardiogram (ECG) and classifies the heart rhythm, is implemented in every ICD. All detection algorithms use the heart rate to classify the different heart rhythms roughly. If a tachycardia is detected, it is important to discriminate between a ventricular tachycardia, which is life threatening and a supraventricular tachycardia, which is much less threatening. To be able to make this distinction the detection algorithms analyse the behaviour of the heart cycle intervals, the ECG-morphology or in addition to the ventricular ECG, an atrial ECG. In this paper morphological algorithms will be evaluated and newly developed algorithms will be presented. Recent algorithms use the mathematical wavelet theory. The evaluation shows that these get better results than all but one of the simpler classical morphological algorithms. A new wavelet based algorithm, developed by the authors, exhibits the best detection results.     

Acute cardiovascular failure and its treatment--value of defibrillation in preclinical management]

Ventricular fibrillation is the most common cause of cardiac arrest. The only scientifically proved therapy that guarantees a long time survival is the early electrical defibrillation. As early as 200 years ago electricity was employed in trying to regain circulation in cases of unexpected death. In the field of emergency medicine almost all rescue services are equipped with defibrillators nowadays and the personnel is trained in using them. Since the application of electricity on the myocardium can lead to damage, there are devices with a varied defibrillation pulse available since recently. The advantage of the biphasic defibrillation is a less harmful impact on the myocardium at lower shock intensity. A further novelty which enables the application by groups other than the rescue services, is the automatic external defibrillator (AED). Extending the availability of defibrillators can contribute to an increase in the presently low success rates of resuscitation.     

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

Objective

The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.

Materials and Methods

Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique.

Results

358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent > 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.

Conclusion

At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO₂) signal improves accuracy and sensitivity of the MDI prediction model.     

Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients

Objective

Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the prediction performance for subsequent shocks is still uncertain.

Methods

A total of 528 defibrillation shocks from 199 patients experienced out-of-hospital cardiac arrest were analyzed in this study. VF waveform was quantified using amplitude spectrum area (AMSA) from defibrillator''s ECG recordings prior to each shock. Combinations of AMSA with previous shock index (PSI) or/and change of AMSA (ΔAMSA) between successive shocks were exercised through a training dataset including 255shocks from 99patientswith neural networks. Performance of the combination methods were compared with AMSA based single feature prediction by area under receiver operating characteristic curve(AUC), sensitivity, positive predictive value (PPV), negative predictive value (NPV) and prediction accuracy (PA) through a validation dataset that was consisted of 273 shocks from 100patients.

Results

A total of61 (61.0%) patients required subsequent shocks (N = 173) in the validation dataset. Combining AMSA with PSI and ΔAMSA obtained highest AUC (0.904 vs. 0.819, p<0.001) among different combination approaches for subsequent shocks. Sensitivity (76.5% vs. 35.3%, p<0.001), NPV (90.2% vs. 76.9%, p = 0.007) and PA (86.1% vs. 74.0%, p = 0.005)were greatly improved compared with AMSA based single feature prediction with a threshold of 90% specificity.

Conclusion

In this retrospective study, combining AMSA with previous shock information using neural networks greatly improves prediction performance of defibrillation outcome for subsequent shocks.     

Model of control of diurnal melatonin secretion by the solar radiation

The mathematical model of the control process of diurnal melatonin secretion under the influence of solar radiation on retina photoreceptors is proposed. Invariant relations for calculating melatonin secretion rate and its concentration in blood plasma are obtained. Spectral, time and energy characteristics of solar radiation synchronizing diurnal melatonin secretion and circadian rhythms in human are defined. A possibility of using the relations obtained is shown for arbitrary combination of calendar dates, local time of any time zone and geographical coordinates of a calculated point on earth surface. The adequacy of model is confirmed by coincidence of the calculation data with the results of independent experimental studies on diurnal secretion of melatonin and circadian rhythm in human. The model proposed can be used during investigation of diurnal secretion of melatonin and circadian rhythm in human.     

A method of minimization of ECG artifacts in digital EEG

An off-line algorithm of automatic detection and minimization of ECG artifacts in digital EEG without using the ECG channel is proposed. A possibility of application of this technique for processing another high-frequency artifacts and different waveforms in biosignals is discussed.     

Defibrillation testing of the implantable cardioverter defibrillator: when, how, and by whom?

The implantable cardioverter-defibrillator (ICD) has become an integral part of treatment for a variety of patients with symptomatic, or at risk for, ventricular tachyarrhythmias. The ICD's effectiveness is attributed to its ability to promptly detect and terminate ventricular tachycardia (VT) and fibrillation (VF). The clinical trials that established the positive role of ICD therapy were based on patients who underwent some form of defibrillation testing at the time of implantation. Therefore, since its advent, intraoperative defibrillation testing of the ICD to assure reliable detection and termination of VT/VF has been a standard practice. But because of advances in defibrillator and lead technology, which now facilitates successful device implantation (i.e., low defibrillation energy requirement to allow for an adequate programmed safety margin) in the majority of patients, the necessity of defibrillation testing has been called into attention. Despite substantial progress, it is not altogether clear whether a wholesale abandonment of intraoperative ICD testing is appropriate at this point. We review pertinent data regarding pros and cons of ICD testing and offer a suggestion as to when, how, and who should test ICDs.     

Low Energy Defibrillation in Human Cardiac Tissue: A Simulation Study

We aim to assess the effectiveness of feedback-controlled resonant drift pacing as a method for low energy defibrillation. Antitachycardia pacing is the only low energy defibrillation approach to have gained clinical significance, but it is still suboptimal. Low energy defibrillation would avoid adverse side effects associated with high voltage shocks and allow the application of implantable cardioverter defibrillator (ICD) therapy, in cases where such therapy is not tolerated today. We present results of computer simulations of a bidomain model of cardiac tissue with human atrial ionic kinetics. Reentry was initiated and low energy shocks were applied with the same period as the reentry, using feedback to maintain resonance. We demonstrate that such stimulation can move the core of reentrant patterns, in the direction that depends on the location of the electrodes and the time delay in the feedback. Termination of reentry is achieved with shock strength one-order-of-magnitude weaker than in conventional single-shock defibrillation. We conclude that resonant drift pacing can terminate reentry at a fraction of the shock strength currently used for defibrillation and can potentially work where antitachycardia pacing fails, due to the feedback mechanisms. Success depends on a number of details that these numerical simulations have uncovered.     

The Gurvich waveform has lower defibrillation threshold than the rectilinear waveform and the truncated exponential waveform in the rabbit heart

Implantable cardioverter defibrillator studies have established the superiority of biphasic waveforms over monophasic waveforms. However, external defibrillator studies of biphasic waveforms are not as widespread. Our objective was to compare the defibrillation efficacy of clinically used biphasic waveforms, i.e., truncated exponential, rectilinear, and quasi-sinusoidal (Gurvich) waveforms in a fibrillating heart model. Langendorff-perfused rabbit hearts (n = 10) were stained with a voltage-sensitive fluorescent dye, Di-4-ANEPPS. Transmembrane action potentials were optically mapped from the anterior epicardium. We found that the Gurvich waveform was significantly superior (p < 0.05) to the rectilinear and truncated exponential waveforms. The defibrillation thresholds (mean +/- SE) were as follows: Gurvich, 0.25 +/- 0.01 J; rectilinear-1, 0.34 +/- 0.01 J; rectilinear-2, 0.33 +/- 0.01 J; and truncated exponential, 0.32 +/- 0.02 J. Using optically recorded transmembrane responses, we determined the shock-response transfer function, which allowed us to predict the cellular response to waveforms at high accuracy. The passive parallel resistor-capacitor model (RC-model) predicted polarization superiority of the Gurvich waveform in the myocardium with a membrane time constant (taum) of less than 2 ms. The finding of a lower defibrillation threshold with the Gurvich waveform in an in vitro model of external defibrillation suggests that the Gurvich waveform may be important for future external defibrillator designs.     

Fuzzy K-nearest neighbor classifiers for ventricular arrhythmia detection

We report a study of the efficiency of 4 classifiers (the K-nearest-neighbor and single-nearest-prototype algorithms, each as parametrized by both Fuzzy C-Means and Fuzzy Covariance clustering) in the detection of ventricular arrhythmias in ECG traces characterized by 4 features derived from 7 spectral parameters. Principal components analysis was used in conjunction with a cardiologist's deterministic classification of 90 ECG traces to fix the number of trace classes to 5 (ventricular fibrillation/flutter, sinus rhythm, ventricular rhythms with aberrant complexes and 2 classes of artefact). Forty of the 90 traces were then defined as a test set; 5 different learning sets (numbering 25, 30, 35, 40 and 45 traces) were randomly selected from the remaining 50 traces; each learning set was used to parametrize both the classification algorithms using both fuzzy clustering algorithms and the parametrized classification algorithms were then applied to the test set. Optimal K for K-nearest-neighbor algorithms and optimal cluster volumes for Fuzzy Covariance algorithms were sought by trial and error to minimize classification differences with respect to the cardiologist's classification. Fuzzy Covariance clustering afforded significantly better perception of cluster structure than the Fuzzy C-Means algorithm, and the classifiers performed correspondingly with an overall empirical error ratio of just 0.10 for the K-nearest-neighbor algorithm parametrized by Fuzzy Covariance.     

High survival rate of 43% in out-of-hospital cardiac arrest patients in an optimised chain of survival

Aims

Survival to hospital discharge after out-of-hospital cardiac arrest (OHCA) varies widely. This study describes short-term survival after OHCA in a region with an extensive care path and a follow-up of 1 year.

Methods

Consecutive patients ≥16 years admitted to the emergency department between April 2011 and December 2012 were included. In July 2014 a follow-up took place. Socio-demographic data, characteristics of the OHCA and interventions were described and associations with survival were determined.

Results

Two hundred forty-two patients were included (73 % male, median age 65 years). In 76 % the cardiac arrest was of cardiac origin and 52 % had a shockable rhythm. In 74 % the cardiac arrest was witnessed, 76 % received bystander cardiopulmonary resuscitation and in 39 % an automatic external defibrillator (AED) was used. Of the 168 hospitalised patients, 144 underwent therapeutic procedures. A total of 105 patients survived until hospital discharge. Younger age, cardiac arrest in public area, witnessed cardiac arrest, cardiac origin with a shockable rhythm, the use of an AED, shorter time until return of spontaneous circulation, Glasgow Coma Scale (GCS) ≥13 during transport and longer length of hospital stay were associated with survival. Of the 105 survivors 72 survived for at least 1 year after cardiac arrest and 6 patients died.

Conclusion

A survival rate of 43 % after OHCA is achievable. Witnessed cardiac arrest, cardiac cause of arrest, initial cardiac rhythm and GCS ≥13 were associated with higher survival.     

Smartphone and a freely available application as a new tool to record locomotor activity rhythm in large mammals and humans

ABSTRACT

Daily pattern of locomotor activity (LA), one of the most studied rhythms in humans and rodents, has not been widely investigated in large mammals. This is partly due to the high cost and breakability of used automatic devices. Since last decade, smartphones are becoming ubiquitous. Meanwhile, several applications detecting activity by using internal sensors were made available. In this study, we assumed that this device could be a cheaper and easier way to measure the LA rhythm in humans and large mammals, like camel and goat. A smartphone application (Nokia Mate Health), normally used to quantify physical activities in humans, was chosen for the study. To validate the rhythm data obtained from the smartphone, LA rhythm was simultaneously recorded using an automatic device, the Actiwatch-Mini®. Results showed that the smartphone provided a clear and significant daily rhythm of LA. The visual assessment of the superimposed LA rhythm’s curves in all three species showed that the smartphone application displayed similar rhythms as those recorded by the Actiwatch-Mini. Highly significant positive correlation (p≤ 0.0001) exists between the two recording rhythms. The daily periods were both the same at 24.0 h. Acrophases were also significantly similar and occurring around mid-day: 11:40 ± 0.35 h vs 11:41 ± 0.35 h for the camel, 11:25 ± 0.19 h vs 11:37 ± 0.25 h for the goat and 13:04 ± 0.11 h vs 13:51 ± 0.28 h for humans using smartphone and Actiwatch, respectively. The related mesor and amplitude were also close between the two recording devices. Results indicate clearly that using smartphones constitutes a reliable cheap tool to study LA rhythm for chronobiology studies, especially in laboratories facing lack of funding.     

Algorithmic sequential decision-making in the frequency domain for life threatening ventricular arrhythmias and imitative artefacts: a diagnostic system

A preliminary study to approach the problem of reliably detecting life threatening ventricular arrhythmias in real time is described. An algorithm (DIAGNOSIS) has been developed in order to classify ECG signal records on the basis of the computation of four simple parameters calculated from a representation in the frequency domain. This algorithm uses a set or rules constituting an operative classification scheme based on the comparison of the parameters with a set of pre-established thresholds. This allows us to differentiate four general categories: ventricular fibrillation-flutter, ventricular rhythms, imitative artefacts and predominant sinus rhythm.     

The future of electrical defibrillators for the heart]

The aim of electric defibrillation of the heart is to salvage a greater percentage of victims of cardiac arrest in the future. An initial decisive pathway towards this goal is to get a defibrillator to the victim as quickly as possible and apply an electric shock. This has now been implemented on a large scale--by means of the widespread propagation of (semi-)automatic external defibrillators (AED) and their PAD (Public Access Defibrillator) variant for use by laypersons. This is an initial necessary prerequisite which, however, is not sufficient to have a real impact on saving lives. For experience has shown that, despite the early use of AEDs, an appreciable proportion of the victims cannot be saved. The intention is to improve this situation by increasing the efficacy and reducing the harmful downside of the defibrillation waveforms applied. The solution is optimally dimensioned biphasic waveforms with high efficacy at low energy levels. In this connection, it is shown that the efficacy of high-energy defibrillation shocks is exceeded by their injurious effects, thus thwarting life-saving defibrillation. Examples of new waveforms of particularly high efficacy are presented. It is shown how such impulses should be physiologically dimensioned, and clinical results of cardioversion (atrial defibrillation) and initial out-of-hospital results of emergency defibrillation are discussed. In addition, new approaches for future waveforms enabling pulsed pulse-pause-modulated biphasic shocks are described. In this way, waveforms with a physiologically optimal effect on the heart can be produced which were previously impossible with portable defibrillators. Waveforms that have already been tested or are still in the research stage, justify hopes that improved survival of cardiac arrest victims may be expected. These new waveforms may also be of benefit in other types of defibrillators (e.g. cardioversion or implanted defibrillators).     

Grammatic representation of beat sequences for fuzzy arrhythmia diagnosis

The final stage of a system for automatic monitoring of cardiac arrhythmias is the diagnosis of the rhythm or arrhythmia present in the patient during the monitoring process. In this paper we approach the detection process by means of the analysis of the electrocardiographic signal (ECG) on a surface lead produced by those arrhythmias which can be recognized by identifying specific beat sequences and taking into account contextual information, mainly rhythm information. We have developed a diagnosis process for arrhythmias which uses a fuzzy classification of beats according to their etiology or focus of origin. The process we describe permits a more adequate consideration by the user of the arrhythmias diagnosed by the system, mainly in those cases in which the information derived from ECG analysis is not determinant.     

Attention samples stimuli rhythmically

Overt exploration or sampling behaviors, such as whisking, sniffing, and saccadic eye movements, are often characterized by a rhythm. In addition, the electrophysiologically recorded theta or alpha phase predicts global detection performance. These two observations raise the intriguing possibility that covert selective attention samples from multiple stimuli rhythmically. To investigate this possibility, we measured change detection performance on two simultaneously presented stimuli, after resetting attention to one of them. After a reset flash at one stimulus location, detection performance fluctuated rhythmically. When the flash was presented in the right visual field, a 4 Hz rhythm was directly visible in the time courses of behavioral performance at both stimulus locations, and the two rhythms were in antiphase. A left visual field flash exerted only partial reset on performance and induced rhythmic fluctuation at higher frequencies (6-10 Hz). These findings show that selective attention samples multiple stimuli rhythmically, and they position spatial attention within the family of exploration behaviors.     

Mechanistic inquiry into decrease in probability of defibrillation success with increase in complexity of preshock reentrant activity

Energy requirements for successful antiarrhythmia shocks are arrhythmia specific. However, it remains unclear why the probability of shock success decreases with increasing arrhythmia complexity. The goal of this research was to determine whether a diminished probability of shock success results from an increased number of functional reentrant circuits in the myocardium, and if so, to identify the responsible mechanisms. To achieve this goal, we assessed shock efficacy in a bidomain defibrillation model of a 4-mm-thick slice of canine ventricles. Shocks were applied between a right ventricular cathode and a distant anode to terminate either a single scroll wave (SSW) or multiple scroll waves (MSWs). From the 160 simulations conducted, dose-response curves were constructed for shocks given to SSWs and MSWs. The shock strength that yielded a 50% probability of success (ED(50)) for SSWs was found to be 13% less than that for MSWs, which indicates that a larger number of functional reentries results in an increased defibrillation threshold. The results also demonstrate that an isoelectric window exists after both failed and successful shocks; however, shocks of strength near the ED(50) value that were given to SSWs resulted in 16.3% longer isoelectric window durations than the same shocks delivered to MSWs. Mechanistic inquiry into these findings reveals that the two main factors underlying the observed relationships are 1) smaller virtual electrode polarizations in the tissue depth, and 2) differences in preshock tissue state. As a result of these factors, intramural excitable pathways leading to delayed breakthrough on the surface were formed earlier after shocks given to MSWs compared with SSWs and thus resulted in a lower defibrillation threshold for shocks given to SSWs.