ASSESSMENT AND PREDICTION OF CARDIOVASCULAR STATUS DURING CARDIAC ARREST AND THE POST-RESUSCITATION PERIOD USING SIGNAL PROCESSING AND MACHINE LEARNING

摘要

Real-time, short-term analysis of ECG, by using multiple signal processing and machine learning techniques, is used to determine counter shock success in defibrillation. Combinations of measures when used with machine learning algorithms readily predict successful resuscitation, guide therapy and predict complications. In terms of guiding resuscitation, they may serve as indicators and when to provide counter shocks and at what energy levels they should be provided as well as to serve as indicators of when certain drugs should be provided (in addition to their doses). For cardiac arrest, the system is meant to run in real time during all current resuscitation procedures including post-resuscitation care to detect deterioration for guiding care such as therapeutic hypothermia.

主权项

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 ETCO2 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.