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Chapter 22 Safety-Critical Systems And Engineering Design: Cardiac And Blood-Related Devices
Published in B H Brown, R H Smallwood, D C Barber, P V Lawford, D R Hose, Medical Physics and Biomedical Engineering, 2017
Our second detailed example of a safety-critical system is the defibrillator. Defibrillators are devices that are used to apply a large electric shock to the heart. They are used to restore a normal sinus rhythm to a heart which is still active but not contracting in a co-ordinated fashion. The cause of fibrillation is commonly ischaemia of heart tissue but less common causes are electric shock, drugs, electrolyte disorders, drowning and hypothermia. The use of a defibrillator on a patient following a heart attack is an emergency procedure, as the pumping action of the heart has to be restarted within a few minutes if the patient is to survive. The defibrillator is therefore a ‘safety-critical’ device; if it fails to work when required then the patient will die.
Electrocardiogram
Published in Kayvan Najarian, Robert Splinter, Biomedical Signal and Image Processing, 2016
Kayvan Najarian, Robert Splinter
When ventricular depolarization occurs chaotically, the situation is called ventricular fibrillation. This is reflected in the ECG, which demonstrates coarse irregular undulations without QRS complex. The cause of fibrillation is the establishment of multiple reentry loops usually involving diseased heart muscle. In this type of arrhythmia, the contraction of the ventricular muscle is also irregular, and, therefore, the timing is ineffective at pumping blood. The lack of blood circulation leads to almost immediate loss of consciousness and even death within minutes. The ventricular fibrillation may be stopped with an external defibrillator pulse and appropriate medication.
New Technology and the Future
Published in Ervan Garrison, A History of Engineering and Technology Artful Methods, 2018
The defibrillator is used when the heart’s activity becomes wholely unsynchronized, a condition results termed fibrillation. It is characterized by rapid irregular contractions of the myocardium. It can occur in the atria or ventricles. Ventricular fibrillation is the most dangerous with death occurring in minutes. The most successful development in countering fibrillation is the defibrillator. The first devices applied a brief (0.25 – 1 s) burst of 60-Hz ac of 6 ampere countershock resynchronizes the heart. This technique is termed ac defibrillation.
The potential for photoplethysmographic (PPG)-based smart devices in atrial fibrillation detection
Published in Expert Review of Medical Devices, 2020
Stephanie L. Harrison, Deirdre A. Lane, Yutao Guo, Gregory Y. H. Lip
Diagnosing atrial fibrillation (AF) involves detection of the typical AF rhythm pattern using an electrocardiogram (ECG). Opportunistic screening for untreated AF is recommended in people aged >65 years by pulse taking or ECG rhythm strip [1]. Recurrent or extended ECG monitoring can improve detection of AF, but this is not always practical given the time inconvenience and associated costs. Photoplethysmography (PPG)-based smart devices may provide an opportunity for large-scale screening of AF by maximizing convenience and minimizing costs and time. An overview of the current available evidence regarding the accuracy and feasibility of using PPG-based smart devices for AF detection will be described in this editorial, although it is not a comprehensive review.
Recent advances in the tools available for atrial fibrillation ablation
Published in Expert Review of Medical Devices, 2022
Ahmed Kotb, Shui Hao Chin, G. Andre Ng
Atrial fibrillation (AF) remains a huge challenge to modern medicine with a major impact on public health. It is the most common sustained cardiac arrhythmia with more than 40 million worldwide living with the condition [1]. It is estimated that one in four adults over the age of 40 will present with AF at some point during their lifetime [2]. Catheter ablation for atrial fibrillation has progressed significantly over the years, from an investigational procedure to mainstream therapy in patients with symptomatic atrial fibrillation [1].
A Deep Belief Network Model for Automatic Atrial Fibrillation Detection
Published in IETE Journal of Research, 2023
Classification techniques are applied to identify the ECG signal as normal or atrial fibrillation, also improving the diagnosis of the system. The classification of the feature is carried out with help of a deep-learning classifier. In this method, a Chimp Optimization algorithm-based [28] parameter-optimized Deep Belief model for atrial fibrillation diagnosing in wearable ECG monitoring devices is proposed.