Detection method for shockable rhythm based on a single feature. Issue 9 (1st April 2016) - Nam, D.H.; Kang, D.W.; Myoung, H.S.; Lee, K.J.
Abstract : A method for detecting shockable rhythm was proposed. A single feature was extracted using the discrete wavelet transform from a single‐channel electrocardiogram. The extracted feature was applied to the support vector machine to determine whether the signal was a shockable or non‐shockable rhythm. To evaluate the performance, five‐fold cross validation was performed with different window lengths (WLs). As a result, a sensitivity of 97.8% and a specificity of 98.0% with 3 s WL were obtained. The results represent the proposed method shows high detection performance even with short analysis window and only a single feature.