Abstract
Isolated caregivers in remote environments frequently request medical advice or decision support from distant experts. Among the multiple difficulties arising from this configuration, exchanging timely and pertinent information under pressure between the two parties poses a considerable challenge. Cognitive Work Analysis and notably the Turing Machine Task Analysis (TMTA) method that enables task processing simulation represent a methodological framework that can guide the specification of remote assistance systems. Within this perspective, TMTA was used to specify assistance functions within a case study of acute abdominal pain occurring on a remote location. Using previous studies and medical knowledge, a work domain analysis of acute abdominal pain was conducted. Based on this analysis, a Turing machine state space was formalized. Applying this method provides two main outcomes helping specify medical assistance functions: a global architecture of medical assistance for isolated caregivers and guidance to define the kind of assistance functions that could be implemented, notably owing to the simulation of Turing machine scenarios. Associated with the abstraction hierarchy technique, the Turing machine simulation process provides a model of the dynamics of interaction between agents and work domain within the framework of adaptive assistance.
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Acknowledgments
The authors are grateful to E. Frénod, LMBA laboratory, R. Querrec, and E. Bevacqua, Labsticc CERV, for their fruitful discussions on this study. This work was supported by the French National Research Agency (ANR) as part of the VR.MARS project and by the Brittany Region through a Ph.D. grant.
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Bernard, C.I., Thierry, S. & Morineau, T. Turing machine task analysis: specifying emergency assistance functions for a telemedicine system. Cogn Tech Work 23, 771–781 (2021). https://doi.org/10.1007/s10111-020-00651-y
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DOI: https://doi.org/10.1007/s10111-020-00651-y