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HDF5-Based Data Format for Archiving Complex Neuro-monitoring Data in Traumatic Brain Injury Patients

  • Manuel CabeleiraEmail author
  • Ari Ercole
  • Peter Smielewski
Conference paper
Part of the Acta Neurochirurgica Supplement book series (NEUROCHIRURGICA, volume 126)

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.

Keywords

HDF5 Multimodal monitoring Data storage Data format 

Notes

Acknowledgements

This work was supported by a European CoER-TBI).

Conflicts of interest statement

P. Smielewski and M. Czosnyka have partial financial interest in the licensing of ICM+.

References

  1. 1.
    Franklin DF, Ostler DV. Proposed standard IEEE P1073 Medical Information Bus: medical device to host computer interface network overview and architecture. In: Eighth Annual International Phoenix Conference on Computers and Communications 1989 Conference Proceedings. IEEE Comput Soc Press; [cited 2016 Oct 26]. p. 574–8. Available from: http://ieeexplore.ieee.org/document/37448/.
  2. 2.
    Maas AIR, Menon DK, Steyerberg EW, Citerio G, Lecky F, Manley GT, et al. Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI): a prospective longitudinal observational study. Neurosurgery [Internet]. 2015 .[cited 2016 Oct 31];76(1):67–80. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25525693.
  3. 3.
    HDF5 file format specification version 3.0. Available from: https://support.hdfgroup.org/HDF5/doc/H5.format.html.
  4. 4.
    Dougherty MT, Folk MJ, Zadok E, Bernstein HJ, Bernstein FC, Eliceiri KW, et al. Unifying biological image formats with HDF5. Commun AMC. 2009;52(10):42–7.Google Scholar
  5. 5.
    Rees N, Billich HR, Koziol Q, Wintersberger E, Götz A, Pourmal E, et al. Developing HDF5 for the Synchrotron Community. 2015;WEPGF063.Google Scholar
  6. 6.
    Rübel O, Prabhat M, Denes P, Conant D, Chang E, Bouchard K. BRAINformat: a data standardization framework for neuroscience data. 2015. bioRxiv.Google Scholar
  7. 7.
    Eglen SJ, Weeks M, Jessop M, Simonotto J, Jackson T, Sernagor E, et al. A data repository and analysis framework for spontaneous neural activity recordings in developing retina. Gigascience. 2014 [cited 2016 Oct 31];3(1):3. Available from: http://gigascience.biomedcentral.com/articles/10.1186/2047-217X-3-3.
  8. 8.
    HDF5 Users Guide. [cited 2017 Feb 28]. Available from: https://support.hdfgroup.org/HDF5/doc/UG/HDF5_Users_Guide.pdf.

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Manuel Cabeleira
    • 1
    • 2
    Email author
  • Ari Ercole
    • 3
  • Peter Smielewski
    • 1
  1. 1.Brain Physics Lab, Division of Neurosurgery, Department of Clinical NeurosciencesAddenbrooke’s Hospital, University of CambridgeCambridgeUK
  2. 2.Neurosurgery UnitAddenbrooke’s HospitalCambridgeUK
  3. 3.Division of AnaesthesiaAddenbrooke’s Hospital, University of CambridgeCambridgeUK

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