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The impact of missing sensor information on surgical workflow management

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Objective

   Sensor systems in the operating room may encounter intermittent data losses that reduce the performance of surgical workflow management systems (SWFMS). Sensor data loss could impact SWFMS-based decision support, device parameterization, and information presentation. The purpose of this study was to understand the robustness of surgical process models when sensor information is partially missing. SWFMS changes caused by wrong or no data from the sensor system which tracks the progress of a surgical intervention were tested.

Materials and methods

   The individual surgical process models (iSPMs) from 100 different cataract procedures of 3 ophthalmologic surgeons were used to select a randomized subset and create a generalized surgical process model (gSPM). A disjoint subset was selected from the iSPMs and used to simulate the surgical process against the gSPM. The loss of sensor data was simulated by removing some information from one task in the iSPM. The effect of missing sensor data was measured using several metrics: (a) successful relocation of the path in the gSPM, (b) the number of steps to find the converging point, and (c) the perspective with the highest occurrence of unsuccessful path findings.

Results

   A gSPM built using 30 % of the iSPMs successfully found the correct path in 90 % of the cases. The most critical sensor data were the information regarding the instrument used by the surgeon.

Conclusion

   We found that use of a gSPM to provide input data for a SWFMS is robust and can be accurate despite missing sensor data. A surgical workflow management system can provide the surgeon with workflow guidance in the OR for most cases. Sensor systems for surgical process tracking can be evaluated based on the stability and accuracy of functional and spatial operative results.

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Acknowledgments

The authors thank the team that supported the performance of the study and the preparation of the article at the Innovation Center for Computer Assisted Surgery, University of Leipzig: Caroline Elzner, Michael Thiele, and Alexander Oeser. ICCAS is funded by the German Federal Ministry of Education and Research (BMBF) and the Saxon Ministry of Science and Fine Arts (SMWK) in the scope of the Unternehmen Region with grant numbers 03 ZIK 031 and 03 ZIK 032 and by funds from the European Regional Development Fund (ERDF) and the state of Saxony within the framework of measures to support the technology sector.

Conflict of Interest

The paper is not, nor was it previously, under consideration by any other journal. The funding sources had no involvement in the study design, data collection, analysis or interpretation of the results, or in the writing of the report. All authors have no conflicts of interest. The decision to submit the paper for publication was ours alone.

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Authors and Affiliations

  1. Innovation Center for Computer Assisted Surgery (ICCAS), University of Leipzig, Semmelweisstr. 14, 04103 , Leipzig, Germany

    Philipp Liebmann & Thomas Neumuth

  2. Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103 , Leipzig, Germany

    Jürgen Meixensberger

  3. Department of Ophthalmology, University Hospital Leipzig, Liebigstr. 10-14, 04103 , Leipzig, Germany

    Peter Wiedemann

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  1. Philipp Liebmann
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  2. Jürgen Meixensberger
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  3. Peter Wiedemann
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  4. Thomas Neumuth
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Correspondence to Philipp Liebmann.

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Liebmann, P., Meixensberger, J., Wiedemann, P. et al. The impact of missing sensor information on surgical workflow management. Int J CARS 8, 867–875 (2013). https://doi.org/10.1007/s11548-013-0824-8

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  • DOI: https://doi.org/10.1007/s11548-013-0824-8

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