HDF5-based data format for archiving complex neuro-monitoring data in traumatic brain injury patients

Abstract

Objectives: Modern neuro-critical care units generate high volumes of data. These data originate from a multitude of devices in various formats and levels of granularity. We present a new data format intended to store these data in an ordered and homogenous way. Material and methods: The adopted data format was based on the hierarchical model, HDF5, which is capable of dealing with a mixture of small and very large datasets with equal ease. It is possible to access and manipulate individual data elements directly within a single file, and this is extensible and versatile. Results: The file structure that was agreed divided the patient data into four different groups: ‘Annotations’ for clinical events and sporadic observations, ‘Numerics’ for all the low-frequency data, ‘Waves’ for all the high-frequency data and ‘Summaries’ for the trend data and calculated parameters. The addition of attributes to every group and dataset makes the file self-described. More than 200 files have been successfully collected and stored using this format. Conclusion: The new file format was implemented in ICM+ software and validated as part of a collaboration with participating centres across Europe.