Literature DB >> 30137006

At a Glance: Pixel Approximate Entropy as a Measure of Line Chart Complexity.

Gabriel Ryan, Abigail Mosca, Remco Chang, Eugene Wu.   

Abstract

When inspecting information visualizations under time critical settings, such as emergency response or monitoring the heart rate in a surgery room, the user only has a small amount of time to view the visualization "at a glance". In these settings, it is important to provide a quantitative measure of the visualization to understand whether or not the visualization is too "complex" to accurately judge at a glance. This paper proposes Pixel Approximate Entropy (PAE), which adapts the approximate entropy statistical measure commonly used to quantify regularity and unpredictability in time-series data, as a measure of visual complexity for line charts. We show that PAE is correlated with user-perceived chart complexity, and that increased chart PAE correlates with reduced judgement accuracy. 'We also find that the correlation between PAE values and participants' judgment increases when the user has less time to examine the line charts.

Entities:  

Year:  2018        PMID: 30137006     DOI: 10.1109/TVCG.2018.2865264

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

1.  A Novel Hybrid Approach for Partial Discharge Signal Detection Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Approximate Entropy.

Authors:  Haikun Shang; Yucai Li; Junyan Xu; Bing Qi; Jinliang Yin
Journal:  Entropy (Basel)       Date:  2020-09-17       Impact factor: 2.524

Review 2.  Approximate Entropy and Sample Entropy: A Comprehensive Tutorial.

Authors:  Alfonso Delgado-Bonal; Alexander Marshak
Journal:  Entropy (Basel)       Date:  2019-05-28       Impact factor: 2.524

  2 in total

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