On account of the mechanical disturbance of external chest pressing to electrocardiogram (ECG) signal, the ECG rhythm cannot be identified reliably during the cardio-pulmonary resuscitation period. Whereas the possibility of successful resuscitation will be lowered due to interrupted external chest pressing, a new filtering algorithm, enhanced leastmean-square (eLMS) algorithm, was proposed and developed in our laboratory. The algorithm can filter the disturbance of external chest pressing without the support of hardware reference signal and correctly identify ventricular fibrillation (VF) rhythm and normal sinus rhythm in case of uninterrupted external chest pressing. Without other reference signals, this algorithm realizes filtering only through the interrupted electrocardiograma (cECG) signal. It was verified with ECG signal and disturbance signal under different signal to noise ratios and contrasted with other mature algorithms. The verification results showed that the identification effect of eLMS was superior to those of others under different signal to noise ratios. Furthermore, ECG rhythm can be correctly identified only through cECG signal. This algorithm not only reduces the research and development(R & D)costs of automated external defibrillator but also raises the identification accuracy of ECG rhythm and the possibility of successful resuscitation.