Objectives: Emergency services personnel, family members, laypersons or patients often carry and use mobile phones on sites of emergencies. As there are reported effects on implanted pacemakers and cardioverter defibrillators, the influence of digital cellular phones on automated external defibrillators was studied.
Methods: Twelve automated external defibrillator models were bench tested for their correct decision to or not to advise a shock, while being exposed to electromagnetic interference from a handheld cellular phone with 2 W or a portable cellular phone with 8 W transmitting power. The phones were programmed by a special subscriber identity module card to maximum output power with a carrier frequency of 906.2 MHz. The tests were conducted with a burst frequency of 217 Hz in speech mode and 2-8 Hz in discontinuous transmitting exchange mode. The sensitivity and specificity of electrocardiogram analysis systems were tested, with shockable and non-shockable rhythms provided by an electrocardiogram simulator and on two human subjects with normal sinus rhythm.
Results: A total of 8640 tests were recorded, each automated external defibrillator was tested a total of 720 times. The automated external defibrillators demonstrated a sensitivity of 100% and a specificity of 100%, representing a positive likelihood ratio of 8641 and a negative likelihood ratio of 0.000. In this setting all automated external defibrillators analysed correctly even under worst-case testing conditions, and performed excellently without any single failure. In some devices, voice prompts were distorted beyond comprehension, as the coil of the automated external defibrillator speaker received the pulsed signals.
Conclusion: Shock advisory systems of automated external defibrillators are not susceptible to electromagnetic interference of 900 MHz cellular phones. Voice prompts, however, could be distorted by the operation of nearby digital mobile phones. During automated external defibrillator training this issue needs to be addressed.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1097/00063110-200404000-00004 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Can robotic arm-assisted total knee arthroplasty be applied to valgus deformity.
Arch Orthop Trauma Surg
January 2025
Department of Orthopaedic Surgery, University Hospital centre (Saint Etienne), Avenue Albert Raimond, Saint-priest-en-Jarez, 42270, France.
Introduction: Total knee arthroplasty (TKA) in valgus knees is challenging. Optimal ligament balance, implant neutral or moderate valgus alignment are crucial but conventional instrumentations usually lead to outliers. Robotic arm assisted TKA (RATKA) advantages could answer this challenge.
View Article and Find Full Text PDFContrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.
J Hepatol
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China. Electronic address:
Background & Aims: Accurate multi-classification is the prerequisite for reasonable management of focal liver lesions (FLLs). Ultrasound is the common image examination, but lacks accuracy. Contrast enhanced ultrasound (CEUS) offers better performance, but highly relies on experience.
View Article and Find Full Text PDFA STAND-ALONE TOOL FOR MOSQUITO EGG ENUMERATION.
J Am Mosq Control Assoc
January 2025
Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, 30602.
Accurate enumeration of mosquito eggs is crucial for various entomologic studies, including investigations into mosquito fecundity, life history traits, and vector control strategies. Traditional manual counting methods are labor intensive and prone to human error, highlighting the need for automated systems. This study presents a stand-alone automated mosquito egg counting system using a Raspberry Pi computer, high-quality camera, light-emitting diode ring light source, and a Python script leveraging the Open Source Computer Vision library.
View Article and Find Full Text PDFAutomated Detection of Cancer-Suspicious Findings in Japanese Radiology Reports with Natural Language Processing: A Multicenter Study.
J Imaging Inform Med
January 2025
Department of Medical Informatics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, 565-0871, Osaka, Japan.
Missed critical imaging findings, particularly those indicating cancer, are a common issue that can result in delays in patient follow-up and treatment. To address this, we developed a rule-based natural language processing (NLP) algorithm to detect cancer-suspicious findings from Japanese radiology reports. The dataset used consisted of chest and abdomen CT reports from six institutions.
View Article and Find Full Text PDFArtificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.
EBioMedicine
January 2025
CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, Republic of Korea; Ontact Health Inc., Seoul, Republic of Korea; Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Yonsei University Health System, Seoul, Republic of Korea.
Background: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for evaluating AS that is effective in both resource-limited and advanced settings.
Methods: We created a dual-pathway AI system for AS evaluation using a nationwide echocardiographic dataset (developmental dataset, n = 8427): 1) a deep learning (DL)-based AS continuum assessment algorithm using limited 2D TTE videos, and 2) automating conventional AS evaluation.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!