Assessing User Mental Workload for Smartphone Applications with Built-in Sensors

Wang, L, Gu, T, Liu, A, Yao, H, Tao, X and Lu, J 2018, 'Assessing User Mental Workload for Smartphone Applications with Built-in Sensors', IEEE Pervasive Computing, vol. 18, no. 1, pp. 59-70.


Document type: Journal Article
Collection: Journal Articles

Title Assessing User Mental Workload for Smartphone Applications with Built-in Sensors
Author(s) Wang, L
Gu, T
Liu, A
Yao, H
Tao, X
Lu, J
Year 2018
Journal name IEEE Pervasive Computing
Volume number 18
Issue number 1
Start page 59
End page 70
Total pages 12
Publisher IEEE
Abstract This work proposes a novel three-dimensional model to represent users' mental workload when using smartphone applications. We validate this model by studying the factors' perceptual independence and interactions using data collected from 22 participants. By analyzing the correlations between the factors of mental workload and tap strength captured by smartphones' built-in sensors, we discover tap strength is significantly affected by and can potentially be used to infer the hidden states of mental workload. We build a prototype system and show the effectiveness of assessing mental workload using tap strength without additional human or device costs in both laboratory and real-world settings.
Subject Mobile Technologies
Networking and Communications
Ubiquitous Computing
DOI - identifier 10.1109/MPRV.2018.2873851
Copyright notice © 2018 IEEE
ISSN 1536-1268
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