Patent Document ID: 9339241
Application ID: 14353736
Patent Flag: 1

Claim One:
1. A computer-implemented method for automated monitoring and online assessment of chances of survival for a patient in cardiac arrest, the method 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, in a first processor, non-linear characterization of the preprocessed ECG signal and calculating a prototype distance of the preprocessed ECG signal; performing, in a second processor, feature extraction of the preprocessed ECG signal with a complex wavelet transform; performing, in a third processor, attribute extraction from the preprocessed ECG signal; performing, in a fourth processor, attribute extraction from an end tidal CO 2 (ETCO 2 ) signal; receiving distance values from non-linear characterization of the preprocessed ECG signal, extracted features of the preprocessed time-series ECG signal, attributes extracted from the ETCO 2 signal, and attributes extracted from Dual-Tree Complex Wavelet Decomposition of the pre-processed ECG signal, and performing a feature selection using the received data 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 for guiding therapy.