Electrical impedance tomography (EIT) holds significant promise for bedside pulmonary perfusion monitoring. However, conventional saline-bolus EIT perfusion imaging relies on subject breath-holding to suppress respiratory artifacts, limiting its application in critically ill patients unable to cooperate, such as those with cardiopulmonary dysfunction. This study proposes a novel breath-hold-free method for pulmonary perfusion signal extraction and imaging in EIT, based on Ensemble Empirical Mode Decomposition (EEMD). The feasibility of the method was validated through animal experiments. The results demonstrate that the proposed method can effectively extract pulmonary perfusion signals from EIT data acquired during normal breathing (without breath-holding). Furthermore, the reconstructed pulmonary perfusion EIT images show good clinical consistency with those obtained under breath-holding conditions.