title: An automated carotid pulse assessment approach using Doppler ultrasound.
abstract: During cardiac arrest emergencies, lay rescuers are required to manually check the patient's carotid pulse after the delivery of defibrillation shocks to assess the cardiac resuscitation progress of the patient. As a more automated way of monitoring the resuscitation progress, a new Doppler-ultrasound-based carotid pulse assessment approach is presented in this paper. The method works by analyzing the temporal aperiodicity of Doppler shifts seen in the ultrasound echoes returned from the patient's carotid arteries. As a quantitative investigation with this method, we derived a new measure called the pulselessness indicator to assess whether a carotid pulse is absent based on the given Doppler information. To study the performance of the new carotid pulse checking method, we built a multi-channel CW Doppler prototype device to acquire Doppler data in vivo during cardiac arrest experiments conducted on five different swines and computed pulselessness indicator estimates with these data. Our results indicated that the Doppler-based pulse checking approach has good sensitivity and specificity: it had a pulselessness detection rate greater than 0.9 for a given false alarm rate of 0.05. As a further analysis, the prototype device was applied to other experiments where the swine had suffered cardiac arrest for over five minutes. It showed a consistent assessment performance on the monitoring of the swine's resuscitation progress after defibrillation and chest compressions.
authors.affiliation: Department of Electrical and Electronic Engineering, The University of Hong Kong, Chow Yei Ching Building Rm. 601, Pokfulam Road, Hong Kong SAR. alfred.yu@eee.hku.hk
authors.forename: Alfred H
authors.initials: AH
authors.lastname: Yu
authors.forename: Eric
authors.initials: E
authors.lastname: Cohen-Solal
authors.forename: Balasundar I
authors.initials: BI
authors.lastname: Raju
authors.forename: Shervin
authors.initials: S
authors.lastname: Ayati
mesh_terms: D000465:Algorithms; D000818:Animals; D002339:Carotid Arteries / Q000502:physiology*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D011674:Pulse / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013552:Swine; D018608:Ultrasonography, Doppler / Q000295:instrumentation* / Q000379:methods