VENTRICULAR FIBRILLATION ABOLISHED BY ELECTRIC SHOCK

1948 ◽  
Vol 136 (4) ◽  
pp. 279 ◽  
Author(s):  
Barnett A. Greene
1994 ◽  
Vol 21 (1) ◽  
pp. 49 ◽  
Author(s):  
ID Dix ◽  
SE Jolly ◽  
LS Bufton ◽  
AI Gardiner

The Australian brushtail possum is a major pest in New Zealand, and a device to kill possums in the wild by electric shock has been proposed. This investigation was to determine the best waveform and energy level for an electric device to humanely kill possums. The criterion set was a shock which would cause ventricular fibrillation and result in irreversible unconsciousness within a few minutes. Anaesthetised possums were shocked with sinusoidal alternating currents, direct current bursts and impulse waveforms of varying intensities and durations. An electrocardiogram was used to monitor the cardiac response. Although sinusoidal waveforms of a long duration did disrupt the heartbeat and might result in death, even shocks of very high energy levels did not consistently result in ventricular fibrillation. The use of electricity to trap and kill possums appears unacceptable on humanitarian grounds.


2021 ◽  
Author(s):  
Marzieh Rasooli

Ventricular fibrillation (VF) is a lethal cardiac arrhythmia and electric shock is the only available treatment option for it. Existing works focus on predicting shock success to help improve cardiac resuscitation outcomes. It is desirable to extract information from the electrograms that relates to the current theories on VF mechanism and associate them to the prediction of shock outcomes. To this effect this study used a unique human VF database to evaluate the independent sources (ISs) extracted from Blind Source Separation approach (BSS) and a correlation of 88% was observed between the dominant ISs extracted using a single lead ECG with the number of rotors (i.e., sources identified using multi-channel spatio-temporal phase maps) supporting the hypothesis that the ISs are associated with the rotors. In predicting the shock outcomes using features extracted from the ISs for the given database, we achieved a classification accuracy of 68%.


Resuscitation ◽  
2017 ◽  
Vol 113 ◽  
pp. 8-12 ◽  
Author(s):  
Yoshihide Nakagawa ◽  
Mari Amino ◽  
Sadaki Inokuchi ◽  
Satoshi Hayashi ◽  
Tsutomu Wakabayashi ◽  
...  

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