The investigators wish to build up a database of clinical data and physiological signals with a view to developing a predictive algorithm based on continuous analysis of the intracranial pressure waveform and other parameters commonly used in intensive care to predict the occurrence of an episode of intracranial hypertension (HTIC). This algorithm will be designed using supervised learning statistical methods based on innovative statistical analysis methods (artificial intelligence). These methods are classically used to exploit massive data such as sensor data.

Inclusion Criteria:

• More than 18 years
• admission to intensive care for less than 3 days for a neurological lesion
• Sensor placement for intracranial pressure monitoring

Exclusion Criteria:

• patient under judicial protection
• refusal to participate
• patients under 18 years of age

Any neuro-injured patient admitted to intensive care

All collected data that underlie results in a publication

Data will be available beginning three month and ending five years following the publication

Data access requests will be reviewed by the internal committee of Brest UH. Requestors will be required to sign and complete a data access agreement.