Expanding automatic external defibrillators to include automated detection of cardiac, respiratory, and cardiorespiratory arrest.

Institute of Critical Care Medicine, Palm Springs, CA, USA.
Critical Care Medicine (Impact Factor: 6.15). 05/2002; 30(4 Suppl):S176-8. DOI: 10.1097/00003246-200204001-00012
Source: PubMed

ABSTRACT The new Guidelines of the American Heart Association state that lay rescuers can no longer rely on the manual pulse check to confirm cardiac arrest in an unresponsive patient. We were therefore prompted to develop a method for automated determination of the presence or absence of cardiac contraction and breathing. The technique was designed to be incorporated into conventional automated external defibrillators and to work in conjunction with the information derived from rhythm analyses by the automated defibrillator. Using conventional electrocardiographic sensing and defibrillation electrodes, the transthoracic impedance was measured by passing a constant amplitude alternating current of 5 mA through the thorax at a frequency of 35 kHz. In five anesthetized male domestic swine, we observed pulses that were coincident with cardiac contraction documented by esophageal echocardiography. In addition, we observed larger signals of lower frequency that were time related to ventilation and documented by capnography. Both signals disappeared after inducing ventricular fibrillation. The impedance measurement identified respiratory arrest in anesthetized animals and primary cardiac arrest after ventricular fibrillation was induced. The cardiac arrest detector is therefore likely to augment the current information provided by automated defibrillators and to allow for more precise verbal prompting of lay rescuers.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Several studies have shown that the carotid pulse check is time-consuming and inaccurate. The sensitivity and specificity of manual pulse check has been reported to be 90% and 55% respectively. It has been suggested that circulatory information can be acquired by measuring the thoracic impedance via the defibrillator pads. We established a dataset of thoracic impedance measurement recorded using a modified automated external defibrillator. By using features describing the impedance waveform resulting from a heart contraction in a pattern recognition framework, we were able to classify periods with systolic blood pressure above or below 80 mmHg with a sensitivity of 90% and a specificity of 82%
    Signal Processing Symposium, 2006. NORSIG 2006. Proceedings of the 7th Nordic; 07/2006
  • [Show abstract] [Hide abstract]
    ABSTRACT: Aim: To analyze the feasibility of extracting the circulation component from the thoracic impedance acquired by defibrillation pads. The impedance circulation component (ICC) would permit detection of pulse-generating rhythms (PR) during the analysis intervals of an automated external defibrillator when a non-shockable rhythm with QRS complexes is detected. METHODS: A dataset of 399 segments, 165 associated with PR and 234 with pulseless electrical activity (PEA) rhythms, was extracted from out-of-hospital cardiac arrest episodes by applying a conservative criterion. Records consisted of the electrocardiogram and the thoracic impedance signals free of artifacts due to thoracic compressions and ventilations. The impedance was processed using an adaptive scheme based on a least mean square algorithm to extract the ICC. Waveform features of the ICC signal and its first derivative were used to discriminate PR from PEA rhythms. RESULTS: The segments were split into development (83 PR and 117 PEA rhythms) and testing (82 PR and 117 PEA rhythms) subsets with a mean duration of 10.6s. Three waveform features, peak to peak amplitude, mean power, and mean area were defined for the ICC signal and its first derivative. The discriminative power in terms of area under the curve with the testing dataset was 0.968, 0.971, and 0.969, respectively, when applied to the ICC signal, and 0.974, 0.988 and 0.988, respectively, with its first derivative. CONCLUSION: A reliable method to extract the ICC of the thoracic impedance is feasible. Waveform features of the ICC or its first derivative show a high discriminative power to differentiate PR from PEA rhythms (area under the curve higher than 0.96 for any feature).
    Resuscitation 06/2013; · 3.96 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The quality of cardiopulmonary resuscitation (CPR), especially adequate compression depth, is associated with return of spontaneous circulation (ROSC) and is therefore recommended to be measured routinely. In the current study, we investigated the relationship between changes of transthoracic impedance (TTI) measured through the defibrillation electrodes, chest compression depth and coronary perfusion pressure (CPP) in a porcine model of cardiac arrest. In 14 male pigs weighing between 28 and 34kg, ventricular fibrillation (VF) was electrically induced and untreated for 6min. Animals were randomized to either optimal or suboptimal chest compression group. Optimal depth of manual compression in 7 pigs was defined as a decrease of 25% (50mm) in anterior posterior diameter of the chest, while suboptimal compression was defined as 70% of the optimal depth (35mm). After 2min of chest compression, defibrillation was attempted with a 120-J rectilinear biphasic shock. There were no differences in baseline measurements between groups. All animals had ROSC after optimal compressions; this contrasted with suboptimal compressions, after which only 2 of the animals had ROSC (100% vs. 28.57%, p=0.021). The correlation coefficient was 0.89 between TTI amplitude and compression depth (p<0.001), 0.83 between TTI amplitude and CPP (p<0.001). Amplitude change of TTI was correlated with compression depth and CPP in this porcine model of cardiac arrest. The TTI measured from defibrillator electrodes, therefore has the potential to serve as an indicator to monitor the quality of chest compression and estimate CPP during CPR.
    Resuscitation 07/2012; 83(10):1281-6. · 3.96 Impact Factor