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Haptic Pattern Exploration in an Arm-Mounted Solenoid Array

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HCI International 2020 - Posters (HCII 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1224))

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Abstract

A haptic device with a row of 4 solenoids was used to present 7 kinds of pattern stimuli to the forearm. Patterns were uniquely named (e.g. “choppy-motor”), with 3 variants per pattern, designed to be “bad”, “moderate”, and “good” representations of the verbally-announced sensation. Participants were asked to rank each pattern on a 5-point Likert scale, ranking how well a sensation corresponded to its name. Each participant completed two trials, separated by a 5-min break, ranking the 21 randomized pattern variants twice. The results show general likability for most of the “good” variants of the patterns. Pattern likability increased between trials, indicating that increased exposure to this modality may increase believability of patterns. Data shows a positive, near linear relationship between pattern variant quality and participant’s rankings, indicating that participants can distinguish accurate patterns from inaccurate ones.

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Acknowledgements

The authors of this paper would like to thank Carnegie Mellon University Professor Roberta Klatzky and her lab for providing research funding, guiding our experiment design, and assisting in selecting haptic patterns to test. The authors would also like to thank Carnegie Mellon University Professor Lining Yao for providing a fantastic introduction to the world of morphing matter, and for greenlighting the development of this prototype.

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Correspondence to Dean Dijour .

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Dijour, D., Krishnaprasad, A., Shei, I., Wong, E. (2020). Haptic Pattern Exploration in an Arm-Mounted Solenoid Array. In: Stephanidis, C., Antona, M. (eds) HCI International 2020 - Posters. HCII 2020. Communications in Computer and Information Science, vol 1224. Springer, Cham. https://doi.org/10.1007/978-3-030-50726-8_28

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  • DOI: https://doi.org/10.1007/978-3-030-50726-8_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50725-1

  • Online ISBN: 978-3-030-50726-8

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