BACKGROUND: External ventricular drains (EVD) are widely used to manage intracranial pressure (ICP) and hydrocephalus for aneurysmal subarachnoid hemorrhage (aSAH) patients. After days of use, a decision is made to remove the EVD or replace it with a shunt, involving EVD weaning and CT imaging to observe ventricular size and clinical status. This practice may lead to prolonged hospital stay, extra radiation exposure, and neurological insult due to ICP elevation. This study aims to apply a validated morphological clustering analysis of ICP pulse (MOCAIP) algorithm to detect signatures from the pulse waveform to differentiate an intact CSF circulatory system from an abnormal one during EVD weaning. METHODS: We performed a retrospective study with 50 aSAH patients with reported weaning trial admitted to our institution between 03/2013 and 08/2014. By reviewing clinical notes and pre/post-brain imaging results, 32 patients were determined as having passed the weaning trial and 18 patients as having failed the trial. MOCAIP algorithm was applied to ICP signals to form a series of artifact-free dominant pulses. Finally, pulses with similar mean ICP were identified, and amplitude, Euclidean, and geodesic inter-pulse distances were calculated in a 4-h moving window. RESULTS: While the traditional measure of mean ICP failed to differentiate the two groups of patients, the proposed amplitude and morphological inter-pulse measures presented significant differences (p ≤ 0.004). Moreover, receiver operating characteristic (ROC) analyses showed their usability to predict the outcome of the EVD weaning trial (AUC 0.85, p < 0.001). CONCLUSIONS: Patients with an impaired CSF system showed a larger mean and variability of inter-pulse distances, indicating frequent changes on the morphology of pulses. This technique may provide a method to rapidly determine if patients will need placement of a shunt or can simply have the EVD removed.