English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Historically, many sonification designs that have been used for data analysis purposes have been based on data characteristics and have not been explicitly based on the listener’s task. These sonification designs have often been described as annoying, confusing, or fatiguing. In the absence of a generally accepted theoretical framework for sonification design, there is a need for improvements in sonification design as well as a need for empirical evaluation of taskbased sonification designs. This research focuses on surface electromyography (sEMG) sonification and two sEMG data analysis tasks: determining which of two muscles contracts first and which of two muscles exhibits a higher exertion level. Both of these tasks were analyzed using a task analysis technique known as GOMS (Goals, Operators, Methods, Selection Rules) and two sonification designs were created based on the results of these task analyses. Two Data-based sEMG sonification designs were then taken from the sEMG sonification literature, and the four designs (2 Task-based and 2 Data-based) were empirically compared. Significant effects of sonification design on listener performance were found, with listeners scoring more accurately using the Task-based sonification designs. Based on these results, we argue for wider application of task analysis methods to sonification design and for the inclusion of task analysis methods into a generally accepted theoretical framework for sonification design.

A Comparison Between the Efficacy of Task-Based vs. Data-Based sEMG Sonification Designs