A Review of Visual Representations of Physiologic Data.

作者: Rishikesan Kamaleswaran , Carolyn McGregor

DOI: 10.2196/MEDINFORM.5186

关键词:

摘要: Background: Physiological data is derived from electrodes attached directly to patients. Modern patient monitors are capable of sampling at frequencies in the range several million bits every hour. Hence potential for cognitive threat arising information overload and diminished situational awareness becomes increasingly relevant. A systematic review was conducted identify novel visual representations physiologic that address cognitive, analytic, monitoring requirements critical care environments. Objective: The aims this were knowledge pertaining (1) support conveying event via tri-event parameters; (2) identification use variables across all representations; (3) aspects effective design principles methodology; (4) frequency expert consultations; (5) user engagement identifying heuristics future developments. Methods: completed papers published as August 2016. Titles first collected analyzed using an inclusion criteria. Abstracts resulting pass then produce a final set full papers. Each paper passed through extraction form eliciting comparative analysis. Results: In total, 39 met criteria selected review. Results revealed great diversity physiological data. Visual spanned 4 groups including tabular, graph-based, object-based, metaphoric displays. display most popular (n=19), followed by waveform displays typical single-sensor-single-indicator paradigm (n=18), finally object (n=9) utilized spatiotemporal elements highlight changes status. obtained experiments evaluations suggest specifics related optimal variables, such color, shape, size, texture have not been fully understood. Relationships between outcomes users’ involvement process also require further investigation. very limited subset (n=3) interactive functionality basic analysis, while only one allows perform analysis more than patient. Conclusions: positive when extend beyond displays; however, there remain numerous challenges. particular, challenge extensibility limits their applicability certain subsets or locations, interoperability its expressiveness data, instantaneity extent engagement. [JMIR Med Inform 2016;4(4):e31]

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