The document presents a novel biometric authentication system using electrocardiogram (ECG) signals, highlighting its potential in healthcare systems by providing proof of life and individual identity verification. The study utilizes discrete wavelet transform for feature extraction and random forests for classification, achieving a 100% recognition rate with a reduced feature set. It emphasizes the effectiveness and accuracy of this approach compared to traditional biometric methods.