AEDNav: indoor navigation for locating automated external defibrillator

Background

In a sudden cardiac arrest, starting CPR and applying an AED immediately are the two highest resuscitation priorities. Many existing mobile applications have been developed to assist users in locating a nearby AED. However, these applications do not provide indoor navigation to the AED location. The time required to locate an AED inside a building due to a lack of indoor navigation systems will reduce the patient’s chance of survival. The existing indoor navigation solutions either require special hardware, a large dataset or a significant amount of initial work. These requirements make these systems not viable for implementation on a large-scale.

Methods

The proposed system collects Wi-Fi information from the existing devices and the path’s magnetic information using a smartphone to guide the user from a starting point to an AED. The information collected is processed using four techniques: turn detection method, Magnetic data pattern matching method, Wi-Fi fingerprinting method and Closest Wi-Fi location method to estimate user location. The user location estimations from all four techniques are further processed to determine the user’s location on the path, which is then used to guide the user to the AED location.

Results

The four techniques used in the proposed system Turn detection, Magnetic data pattern matching, Closest Wi-Fi location and Wi-Fi fingerprinting can individually achieve the accuracy of 80% with the error distance ± 9.4 m, ± 2.4 m, ± 4.6 m, and ± 4.6 m respectively. These four techniques, applied individually, may not always provide stable results. Combining these techniques results in a robust system with an overall accuracy of 80% with an error distance of ± 2.74 m. In comparison, the proposed system’s accuracy is higher than the existing systems that use Wi-Fi and magnetic data.

Conclusion

This research proposes a novel approach that requires no special hardware, large scale data or significant initial work to provide indoor navigation. The proposed system AEDNav can achieve an accuracy similar to the existing indoor navigation systems. Implementing this indoor navigation system could reduce the time to locate an AED and ultimately increase patient survival during sudden cardiac arrest.

Analyze Whilst Compressing algorithm for detection of ventricular fibrillation during CPR: A comparative performance evaluation for automated external defibrillators

OBJECTIVE

The aim of this study was to present new combination of algorithms for rhythm analysis during cardiopulmonary resuscitation (CPR) in automated external defibrillators (AED), called Analyze Whilst Compressing (AWC), designed for decreasing pre-shock pause and early stopping of chest compressions (CC) for treating refibrillation.

METHODS

Two stages for AED rhythm analysis were presented, namely, "Standard Analysis Stage" (conventional shock-advisory analysis run over 5 s after CC interruption every two minutes) and "AWC Stage" (two-step sequential analysis process during CPR). AWC steps were run in presence of CC (Step1), and if shockable rhythm was detected then a reconfirmation step was run in absence of CC (Step2, analysis duration 5 s).

RESULTS

In total 16,057 ECG strips from 2916 out-of-hospital cardiac arrest (OHCA) patients treated with AEDs (DEFIGARD TOUCH7, Schiller Médical, France) were subjected patient-wise to AWC training (8559 strips, 1604 patients) and validation (7498 strips, 1312 patients). Considering validation results, "Standard Analysis Stage" presented ventricular fibrillation (VF) sensitivity Se = 98.3% and non-shockable rhythm specificity Sp>99%; "AWC Stage" decision after Step2 reconfirmation achieved Se = 92.1%, Sp>99%.

CONCLUSION

AWC presented similar performances to other AED algorithms during CPR, fulfilling performance goals recommended by standards. AWC provided advances in the challenge for improving CPR quality by: (i) not interrupting chest compressions for prevalent part of non-shockable rhythms (66-83%); (ii) minimizing pre-shock pause for 92.1% of VF patients. AWC required hands-off reconfirmation in 34.4% of cases. Reconfirmation was also common limitation of other reported algorithms (25.7-100%) although following different protocols for triggering chest compression resumption and shock delivery.

Gender and location disparities in prehospital bystander AED usage

BACKGROUND

With bystander AED usage being critical for prehospital cardiac arrest patient outcomes, it is important to analyze if the gender and location disparities found in bystander CPR rates also exist for bystander AED usage.

METHODS

Using the National Emergency Medical Services Information System (NEMSIS) database, 1,144,969 bystander AED cases were analyzed on the basis of gender and location. Chi-squared testing checked for statistical significance and effect size was measured using relative risk (RR).

RESULTS

Using female patients as a baseline, the RR for bystander AED usage for male patients was 1.34 (95% CI [1.3310, 1.3557], p < 0.001) indicating male patients are 34% more likely to receive bystander AED usage compared to female patients. Analyzing bystander AED usage per urbanity region using urban patients as a baseline, resulted in a RR of 0.87 for suburban patients (95% CI [0.8572, 0.8833], p < 0.001), 0.39 for rural patients (95% CI [0.3849, 0.3971], p < 0.001), and 0.36 for frontier patients (95% CI [0.3515, 0.3726], p < 0.001) showing a sharp decline in the chance of bystander AED usage in rural and frontier areas.

CONCLUSIONS

Female patients are less likely to receive bystander AED usage compared to male patients. To resolve these disparities increased public awareness is necessary that supports AED usage on females as socially acceptable and necessary for patient outcomes. Furthermore, given bystander AED usage among males and females declined as cardiac arrest locations became more remote, improvements in rural and frontier AED availability and training are necessary to increase bystander AED usage rates in those regions.

Significance of automated external defibrillator in identifying lethal ventricular arrhythmias

Automated electrical defibrillator (AED) is critical in saving children who develop unexpected cardiac arrest (CA), but its diagnostic capacity is not fully acknowledged. Retrospective cohort study of patients with aborted sudden cardiac death (SCD) was performed. Twenty-five patients (14 males) aged 1.3 to 17.5 years who presented with CA survived with prompt cardiopulmonary resuscitation. Eighteen patients had no prior cardiac diagnosis. Cardiac arrest occurred in 10 patients with more than moderate exercise, in 7 with light exercise, and in 8 at rest (including one during sleep). Twenty-two patients were resuscitated with AED, all of which were recognized as a shockable cardiac rhythm. Thorough investigations revealed 6 ion channelopathies (4 catecholaminergic polymorphic ventricular tachycardia, one long QT syndrome, and one Brugada syndrome), 5 congenital heart disease (including 2 with coronary artery obstruction), 6 cardiomyopathies, 2 myocarditis, and 2 miscellaneous. Four patients had no identifiable heart disease. In 5 patients, the downloaded AED-recorded rhythm strip delineated the underlying arrhythmias and their responses to electrical shocks. Four patients who presented with generalized seizure at rest were initially managed for seizure disorder until AED recording identified lethal ventricular arrhythmias.Conclusions: AED reliably identifies the underlying lethal ventricular arrhythmias in addition to aborting SCD. What is Known: • Although infrequent in children, sudden cardiac death (SCD) is often an unexpected and tragic event. The etiology is diverse and sometimes remains unknown despite extensive investigations. • Automated external defibrillator (AED) is both therapeutic in aborting SCD and diagnostic in identifying the underlying lethal ventricular arrhythmias. However, the diagnostic aspect of AED is under-acknowledged by most medical providers. What is New: • Four of 25 patients (16%) were initially managed for possible seizure disorders until AED recording identified lethal ventricular arrhythmia. • The AED recording of the lethal arrhythmia during cardiopulmonary resuscitation (CPR) should always be obtained as it plays a crucial role in the decision-making process before ICD implantation. All medical providers should become familiar with downloading cardiac rhythm strips from AED when requested.

Circulation assessment by automated external defibrillators during cardiopulmonary resuscitation

AIM

To design and evaluate a simple algorithm able to discriminate pulsatile rhythms from pulseless electrical activity during automated external defibrillator (AED) analysis intervals, using the ECG and the transthoracic impedance (TI) acquired from defibrillation pads.

METHODS

ECG and TI signals from out-of-hospital AED recordings were retrospectively analysed. Experts annotated the cardiac rhythm during AED analysis intervals and at the end of each episode. We developed an algorithm to classify 3-s segments of non-shockable and non-asystole rhythms as either pulsatile rhythm or pulseless electrical activity. The algorithm consisted on a decision tree based on two features: the mean power of the TI segment and the mean cross-power between ECG and TI segments.

RESULTS

From the 302 annotated episodes, 167 contained segments eligible for the study. The circulation detector algorithm presented a sensitivity (ability of detecting pulsatile rhythms) of 98.3% (95% CI: 95.1-100) and a specificity (ability to detect pulseless electrical activity) of 98.4% (95% CI: 97.1-99.8) in the validation subset. Absence of pulsatile rhythm was confirmed during the first AED analysis interval in 98.9% of the episodes, and presence of a pulse was confirmed in the first 3 s of all intervals with annotated return of spontaneous circulation.

CONCLUSION

Accurate automated detection of circulation based on TI and ECG is possible during AED analysis intervals. This functionality could potentially contribute to enhance patient's care by laypersons using AEDs.

A method to differentiate between ventricular fibrillation and asystole during chest compressions using artifact-corrupted ECG alone

In recent years, numerous adaptive filtering techniques have been developed to suppress the chest compression (CC) artifact for reliable analysis of the electrocardiogram (ECG) rhythm without CC interruption. Unfortunately, the result of rhythm diagnosis during CCs is still unsatisfactory in many studies. The misclassification between corrupted asystole (ASY) and corrupted ventricular fibrillation (VF) is generally regarded as one of the major reasons for the poor performance of reported methods. In order to improve the diagnosis of VF/ASY corrupted by CCs, a novel method combining a least mean-square (LMS) filter and an amplitude spectrum area (AMSA) analysis was developed based only on the analysis of the surface of the corrupted ECG episode. This method was tested on 253 VF and 160 ASY ECG samples from subjects who experienced cardiac arrest using a porcine model and was compared with six other algorithms. The validation results indicated that this method, which yielded a satisfactory result with a sensitivity of 93.3%, a specificity of 96.3% and an accuracy of 94.8%, is superior to the other reported techniques. After improvement using the human ECG records in real cardiopulmonary resuscitation (CPR) scenarios, the algorithm is promising for corrupted VF/ASY detection with no hardware alterations in clinical practice.

[Worldwide experience with automated external defibrillators: What have we achieved? What else can we expect?]

INTRODUCTION

In Germany approximately 70,000-100,000 SCD patients die from sudden cardiac death (SCD). SCD is not caused by a single factor but is a multifactorial problem. In 50 % of SCD victims, sudden cardiac death is the first manifestation of heart disease. SCD is caused by ventricular tachyarrhythmias in approximately 90 % of patients, whereas SCD is caused by bradyarrhythmias in 5-10 % of the patients.

METHODS

Risk stratification is not possible in the majority of them prior to the fatal event. Early defibrillation is the method of choice to terminate ventricular fibrillation. Therefore, it is mandatory to install automatic external defibrillators (AED) in places with many people. There is general agreement that early defibrillation with automated external defibrillators (AED) is an effective tool to treat patients with ventricular fibrillation and will improve survival.

CONCLUSION

It seems necessary to teach cardiocompression and AED use, also to children and adolescents. AED therapy "at home" did not improve survival in patients with cardiac arrest and can not be recommended.

An investigation of thrust, depth and the impedance cardiogram as measures of cardiopulmonary resuscitation efficacy in a porcine model of cardiac arrest

OBJECTIVE

Optimising the depth and rate of applied chest compressions following out of hospital cardiac arrest is crucial in maintaining end organ perfusion and improving survival. The impedance cardiogram (ICG) measured via defibrillator pads produces a characteristic waveform during chest compressions with the potential to provide feedback on cardiopulmonary resuscitation (CPR) and enhance performance. The objective of this pre-clinical study was to investigate the relationship between mechanical and physiological markers of CPR efficacy in a porcine model and examine the strength of correlation between the ICG amplitude, compression depth and end-tidal CO2 (ETCO2).

METHODS

Two experiments were performed using 24 swine (12 per experiment). For experiment 1, ventricular fibrillation (VF) was induced and mechanical CPR commenced at varying thrusts (0-60 kg) for 2 min intervals. Chest compression depth was recorded using a Philips QCPR device with additional recording of invasive physiological parameters: systolic blood pressure, ETCO2, cardiac output and carotid flow. For experiment 2, VF was induced and mechanical CPR commenced at varying depths (0-5 cm) for 2 min intervals. The ICG was recorded via defibrillator pads attached to the animal's sternum and connected to a Heartsine 500 P defibrillator. ICG amplitude, chest compression depth, systolic blood pressure and ETCO2 were recorded during each cycle. In both experiments the within-animal correlation between the measured parameters was assessed using a mixed effect model.

RESULTS

In experiment 1 moderate within-animal correlations were observed between physiological parameters and compression depth (r=0.69-0.77) and thrust (r=0.66-0.82). A moderate correlation was observed between compression depth and thrust (r=0.75). In experiment 2 a strong within-animal correlation and moderate overall correlations were observed between ICG amplitude and compression depth (r=0.89, r=0.79) and ETCO2 (r=0.85, r=0.64).

CONCLUSION

In this porcine model of induced cardiac arrest moderate within animal correlations were observed between mechanical and physiological markers of chest compression efficacy demonstrating the challenge in utilising a single mechanical metric to quantify chest compression efficacy. ICG amplitude demonstrated strong within animal correlations with compression depth and ETCO2 suggesting its potential utility to provide CPR feedback in the out of hospital setting to improve performance.

Fully automatic rhythm analysis during chest compression pauses

AIM

Chest compression artefacts impede a reliable rhythm analysis during cardiopulmonary resuscitation (CPR). These artefacts are not present during ventilations in 30:2 CPR. The aim of this study is to prove that a fully automatic method for rhythm analysis during ventilation pauses in 30:2 CPR is reliable an accurate.

METHODS

For this study 1414min of 30:2 CPR from 135 out-of-hospital cardiac arrest cases were analysed. The data contained 1942 pauses in compressions longer than 3.5s. An automatic pause detector identified the pauses using the transthoracic impedance, and a shock advice algorithm (SAA) diagnosed the rhythm during the detected pauses. The SAA analysed 3-s of the ECG during each pause for an accurate shock/no-shock decision.

RESULTS

The sensitivity and PPV of the pause detector were 93.5% and 97.3%, respectively. The sensitivity and specificity of the SAA in the detected pauses were 93.8% (90% low CI, 90.0%) and 95.9% (90% low CI, 94.7%), respectively. Using the method, shocks would have been advanced in 97% of occasions. For patients in nonshockable rhythms, rhythm reassessment pauses would be avoided in 95.2% (95% CI, 91.6-98.8) of occasions, thus increasing the overall chest compression fraction (CCF).

CONCLUSION

An automatic method could be used to safely analyse the rhythm during ventilation pauses. This would contribute to an early detection of refibrillation, and to increase CCF in patients with nonshockable rhythms.

Factors affecting layperson confidence in performing resuscitation of out-of-hospital cardiac arrest patients in Japan

Aim

Bystander cardiopulmonary resuscitation including automated external defibrillator use increases the chance of survival after out-of-hospital cardiac arrest. However, bystanders may be distressed by witnessing out-of-hospital cardiac arrest and may hesitate to initiate cardiopulmonary resuscitation. The present study examined factors associated with layperson confidence in carrying out resuscitation of out-of-hospital cardiac arrest patients.

Methods

We carried out a cross-sectional survey in February 2012. Laypeople were asked about background characteristics, whether they had performed cardiopulmonary resuscitation, had received cardiopulmonary resuscitation training, were aware of the location of the neighborhood automated external defibrillator, and felt confident in performing resuscitation, and their potential emotional distress if a resuscitation attempt were to prove unsuccessful.

Results

Participants comprised 4,853 respondents. Of these, 2,372 (49%) had received cardiopulmonary resuscitation training, and 3,607 (74%) knew where the neighborhood automated external defibrillator was located. Confidence in performing chest compressions was reported by 2,667 (55%), confidence in performing rescue breathing by 2,498 (52%), and confidence in using an automated external defibrillator by 2,822 (58%). Potential emotional distress if a resuscitation attempt proved unsuccessful was reported by 4,247 (88%). Multivariate regression analysis showed that having carried out cardiopulmonary resuscitation, having received cardiopulmonary resuscitation training, and awareness of the neighborhood automated external defibrillator location were significantly associated with confidence in performing cardiopulmonary resuscitation.

Conclusions

Our results suggest that more extensive cardiopulmonary resuscitation training and information regarding neighborhood automated external defibrillator locations may increase layperson confidence in initiating resuscitation.

Defibrillation in the movies: a missed opportunity for public health education

AIM

To characterize defibrillation and cardiac arrest survival outcomes in movies.

METHODS

Movies from 2003 to 2012 with defibrillation scenes were reviewed for patient and rescuer characteristics, scene characteristics, defibrillation characteristics, additional interventions, and cardiac arrest survival outcomes. Resuscitation actions were compared with chain of survival actions and the American Heart Association (AHA) Emergency Cardiovascular Care (ECC) 2020 Impact Goals. Cardiac arrest survival outcomes were compared with survival rates reported in the literature and targeted by the AHA ECC 2020 Impact Goals.

RESULTS

Thirty-five scenes were identified in 32 movies. Twenty-five (71%) patients were male, and 29 (83%) rescuers were male. Intent of defibrillation was resuscitation in 29 (83%) scenes and harm in 6 (17%) scenes. Cardiac arrest was the indication for use in 23 (66%) scenes, and the heart rhythm was made known in 18 scenes (51%). When the heart rhythm was known, defibrillation was appropriately used for ventricular tachycardia or ventricular fibrillation in 5 (28%) scenes and inappropriately used for asystole in 7 (39%) scenes. In 8 scenes with in-hospital cardiac arrest, 7 (88%) patients survived, compared to survival rates of 23.9% reported in the literature and 38% targeted by an AHA ECC 2020 Impact Goal. In 12 movie scenes with out-of-hospital cardiac arrest, 8 (67%) patients survived, compared to survival rates of 7.9-9.5% reported in peer-reviewed literature and 15.8% targeted by an AHA ECC 2020 Impact Goal.

CONCLUSION

In movies, defibrillation and cardiac arrest survival outcomes are often portrayed inaccurately, representing missed opportunities for public health education.

Automatic detection of chest compressions for the assessment of CPR-quality parameters

AIM

Accurate chest compression detection is key to evaluate cardiopulmonary resuscitation (CPR) quality. Two automatic compression detectors were developed, for the compression depth (CD), and for the thoracic impedance (TI). The objective was to evaluate their accuracy for compression detection and for CPR quality assessment.

METHODS

Compressions were manually annotated using the force and ECG in 38 out-of-hospital resuscitation episodes, comprising 869 min and 67,402 compressions. Compressions were detected using a negative peak detector for the CD. For the TI, an adaptive peak detector based on the amplitude and duration of TI fluctuations was used. Chest compression rate (CC-rate) and chest compression fraction (CCF) were calculated for the episodes and for every minute within each episode. CC-rate for rescuer feedback was calculated every 8 consecutive compressions.

RESULTS

The sensitivity and positive predictive value were 98.4% and 99.8% using CD, and 94.2% and 97.4% using TI. The mean CCF and CC-rate obtained from both detectors showed no significant differences with those obtained from the annotations (P>0.6). The Bland-Altman analysis showed acceptable 95% limits of agreement between the annotations and the detectors for the per-minute CCF, per-minute CC-rate, and CC-rate for feedback. For the detector based on TI, only 3.7% of CC-rate feedbacks had an error larger than 5%.

CONCLUSION

Automatic compression detectors based on the CD and TI signals are very accurate. In most cases, episode review could safely rely on these detectors without resorting to manual review. Automatic feedback on rate can be accurately done using the impedance channel.