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A survey of context recognition in surgery

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Abstract

With the introduction of operating rooms of the future context awareness has gained importance in the surgical environment. This paper organizes and reviews different approaches for recognition of context in surgery. Major electronic research databases were queried to obtain relevant publications submitted between the years 2010 and 2015. Three different types of context were identified: (i) the surgical workflow context, (ii) surgeon’s cognitive and (iii) technical state context. A total of 52 relevant studies were identified and grouped based on the type of context detected and sensors used. Different approaches were summarized to provide recommendations for future research. There is still room for improvement in terms of methods used and evaluations performed. Machine learning should be used more extensively to uncover hidden relationships between different properties of the surgeon’s state, particularly when performing cognitive context recognition. Furthermore, validation protocols should be improved by performing more evaluations in situ and with a higher number of unique participants. The paper also provides a structured outline of recent context recognition methods to facilitate development of new generation context-aware surgical support systems.

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  1. Pervasive Computing Applications, Research Studios Austria, Vienna, Austria

    Igor Pernek

  2. Institute for Pervasive Computing, Johannes Kepler University Linz, Linz, Austria

    Alois Ferscha

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Pernek, I., Ferscha, A. A survey of context recognition in surgery. Med Biol Eng Comput 55, 1719–1734 (2017). https://doi.org/10.1007/s11517-017-1670-6

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