Vibrotactile Similarity Perception in Crowdsourced and Lab Studies

Author:

Abou Chahine RamziORCID,Kwon DongjaeORCID,Lim ChungmanORCID,Park GunhyukORCID,Seifi HastiORCID

Abstract

AbstractCrowdsourcing can enable rapid data collection for haptics research, yet little is known about its validity in comparison to controlled lab experiments. Furthermore, no data exists on how different smartphone platforms impact the crowdsourcing results. To answer these questions, we conducted four vibrotactile (VT) similarity perception studies on iOS and Android smartphones in the lab and through Amazon Mechanical Turk (MTurk). Participants rated the pairwise similarities of 14 rhythmic VT patterns on their smartphones or a lab device. The similarity ratings from the lab and MTurk experiments suggested a very strong correlation for iOS devices ($$r_s= 0.9$$ r s = 0.9 ) and a lower but still strong correlation for Android phones ($$r_s= 0.68$$ r s = 0.68 ). In addition, we found a stronger correlation between the crowdsourced iOS and Android ratings ($$r_s=0.78$$ r s = 0.78 ) compared to the correlation between the iOS and Android data in the lab ($$r_s= 0.65$$ r s = 0.65 ). We provide further insights into these correlations using the perceptual spaces obtained from the four datasets. Our results provide preliminary evidence for the validity of crowdsourced VT similarity studies, especially on iOS devices.

Publisher

Springer International Publishing

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Clustering Social Touch Gestures for Human-Robot Interaction;Social Robotics;2023-12-03

2. Can we crowdsource Tacton similarity perception and metaphor ratings?;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

3. Can a Computer Tell Differences between Vibrations?: Physiology-Based Computational Model for Perceptual Dissimilarity Prediction;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

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