Andersen, Hans Jorgen and Morrison, Ann and Knudsen, Lars (2012) Modeling vibrotactile detection by logistic regression. In: 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design (NordiCHI '12), 14-17 Oct 2012, Copenhagen, Denmark.
Abstract
In this study we introduce logistic regression as a method for modeling, in this case the user's detection rate, to more easily show cross-effecting factors, necessary in order to design an adaptive system. Previously such effects have been investigated by a variety of linear regression type methods but these are not well suited for developing adaptive systems. We investigate the method on a qualitative and quantitative dataset with ages spanning from seven to 79 years under indoor and outdoor experimental settings. The results show that the method is indeed a suitable candidate for quantification of, in this instance vibrotactile information, and for the future design of useradaptive vibrotactile displays. More generally the model shows potential for designing a variety of adaptive systems. Copyright © 2012 ACM.
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| Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Permanent restricted access to Published version, in accordance with the copyright policy of the publisher. |
| Faculty/School / Institute/Centre: | No Faculty |
| Faculty/School / Institute/Centre: | No Faculty |
| Date Deposited: | 06 Jul 2017 06:01 |
| Last Modified: | 16 Oct 2017 05:58 |
| Uncontrolled Keywords: | vibro tactile signals, detection rates, identifying cross-impacting factors, logistic regression, method |
| Fields of Research (2008): | 08 Information and Computing Sciences > 0806 Information Systems > 080602 Computer-Human Interaction |
| Fields of Research (2020): | 46 INFORMATION AND COMPUTING SCIENCES > 4608 Human-centred computing > 460806 Human-computer interaction |
| Identification Number or DOI: | https://doi.org/10.1145/2399016.2399092 |
| URI: | http://eprints.usq.edu.au/id/eprint/31312 |
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