https://www.selleckchem.com/pr....oducts/glutaraldehyd
The results show that the proposed approach has obtained an accuracy of 99.036%, 99.800%, and 81.250% for the classification of shockable vs non-shockable, VF vs Non-VF, and VT vs VF, respectively using 8 s ECG frames with 10-fold cross-validation (CV) strategy. Our proposed approach has obtained an average accuracy value of 97.592% using 8 s ECG frames with subject-specific CV. The hardware implementation of the proposed SVCA detection approach can be done using an Internet of things (IoT) driven patient monitoring system. To in
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