TY - GEN
T1 - Vibrotactile Similarity Perception in Crowdsourced and Lab Studies
AU - Abou Chahine, Ramzi
AU - Kwon, Dongjae
AU - Lim, Chungman
AU - Park, Gunhyuk
AU - Seifi, Hasti
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - Crowdsourcing 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 (rs= 0.9 ) and a lower but still strong correlation for Android phones (rs= 0.68 ). In addition, we found a stronger correlation between the crowdsourced iOS and Android ratings (rs= 0.78 ) compared to the correlation between the iOS and Android data in the lab (rs= 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.
AB - Crowdsourcing 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 (rs= 0.9 ) and a lower but still strong correlation for Android phones (rs= 0.68 ). In addition, we found a stronger correlation between the crowdsourced iOS and Android ratings (rs= 0.78 ) compared to the correlation between the iOS and Android data in the lab (rs= 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.
KW - Crowdsourcing
KW - Haptics
KW - Similarity perception
UR - https://www.scopus.com/pages/publications/85131139639
UR - https://www.scopus.com/pages/publications/85131139639#tab=citedBy
U2 - 10.1007/978-3-031-06249-0_29
DO - 10.1007/978-3-031-06249-0_29
M3 - Conference contribution
AN - SCOPUS:85131139639
SN - 9783031062483
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 255
EP - 263
BT - Haptics
A2 - Seifi, Hasti
A2 - Kappers, Astrid M.
A2 - Schneider, Oliver
A2 - Drewing, Knut
A2 - Pacchierotti, Claudio
A2 - Abbasimoshaei, Alireza
A2 - Huisman, Gijs
A2 - Kern, Thorsten A.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022
Y2 - 22 May 2022 through 25 May 2022
ER -