Sudden Cardiac Death - Engineering Solutions Abdallah El-FalouI. INTRODUCTION Cardiac arrest (SCA) is a leading cause of death and can affect an individual at any time and place, regardless of whether or not they have a diagnosed heart disease. Sudden cardiac arrest occurs due to ventricular fibrillation (VF) [1], a type of cardiovascular disease (CVD). CVD is caused by disorders of the heart and blood vessels and mainly affects people over the age of 65 [2] [3]. CVD is primarily diagnosed by using the electrocardiogram (ECG) to measure and record the electrical activity of the heart from the body surface. However, since ECG recording sessions are generally short, rare symptoms are easily and often missed [3].II. LITERATURE REVIEW Defibrillators have developed significantly since the 1950s, when defibrillation of the heart was performed as a major open-chest surgery. Subsequently, defibrillation technology was significantly improved. Manual external defibrillators (MEDs) used by doctors could be used less invasively, eliminating the need for open-chest surgery. However, due to the nature of CVD, the chances of successfully treating CVD decrease significantly by the minute, and therefore a faster and simpler tool was needed to treat patients immediately, before any doctor can reach the site [1 ].Automated external defibrillators (AEDs) were the solution to such problems. The AED has simplified treatment by providing a basic portable defibrillator that can be used by untrained non-medical personnel such as police officers, security guards, flight attendants, and the general public. Audible and/or visual instructions guide the operator through the process, while a microprocessor within the defibrillator automatically scans the patient… in the center of the paper… Cited[1] WL Lim, CC Hang, and KB Neo, " Framework of Discontinuous Innovations: A Review of Automated External Defibrillators in Healthcare,” in Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference, 2008, pp. 356-361.[2] E. Villalba, MT Arrendondo, S. Guillen, and E. Hoyo-Barbolla, “A new solution for a heart failure monitoring system based on wearable and computing technologies,” in Wearable and Implantable Body Sensor Networks, 2006. BSN 2006. International Workshop on, 2006, pp. 4 pp.-153.[3] Zhanpeng Jin, Yuwen Sun, and AC Cheng, “Predicting cardiovascular disease from real-time electrocardiographic monitoring: an adaptive machine learning approach on a mobile phone,” in Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of 'IEEE, 2009, pp. 6889-6892.