Assessing User Mental Workload for Smartphone Applications With Built-In Sensors

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.