Abstract: A method and device(s) for using ECG signals for biometric identification and/or authorization that includes a machine-learning based signal processing approach for significantly removing noise signals from ECG signals being used. The present invention further includes a probability-based additional approach for further enhancing the signal relative to signal segments falsely identified as an actual ECG signal. In extended applications, the same refined ECG signals can be additionally used for parallel functions, such as health and wellness monitoring.

Abstract: A method and device for using ECG signals for biometric authorization that includes a machine-learning based signal processing approach for significantly removing noise signals from ECG signals being used. The present invention further includes a probability-based additional approach for further enhancing the signal relative to signal segments falsely identified as an actual ECG signal.

Abstract: A method and device for using ECG signals for biometric authorization that includes a machine-learning based signal processing approach for significantly removing noise signals from ECG signals being used. The present invention further includes a probability-based additional approach for further enhancing the signal relative to signal segments falsely identified as an actual ECG signal.