Patent Document ID: 20150065815
Application ID: 14353736
Patent Flag: 0

Claim One:
1. A method for automated monitoring and online assessment of chances of survival for a patient in cardiac arrest comprising: obtaining an ECG signal from the patient; preprocessing the ECG signal to remove high frequency noise and baseline jumps caused by noise and interference; performing non-linear characterization of the preprocessed ECG signal and calculating the prototype distance; performing feature extraction of the preprocessed ECG signal with complex wavelet transform; performing attribute extraction from the preprocessed ECG signal; performing attribute extraction from ETCO 2 signal; receiving distance values from non-linear characterization of the preprocessed ECG signal, extracted features of the preprocessed time-series ECG signal and attributes extracted from Dual-Tree Complex Wavelet Decomposition of the pre-processed ECG signal, and performing a feature selection with a predictive model; using machine learning to classify results of the feature selection process; generating a shock success prediction, which results in return of spontaneous circulation (ROSC); generating decompensation and re-arrest prediction; and recommending therapeutic alternatives and medications, thereby guiding therapy.