Montano Murillo, Roberto, Han, Teng, Irani, Pourang, Martinez Plasencia, Diego and Subramanian, Sriram (2019) Designer led computational approach to generate mappings for devices with low gestural resolution. Interact 2019: 17th IFIP TC.13 International Conference on Human-Computer Interaction, Paphos, Cyprus, 2 - 6 September 2019. Published in: Lecture Notes in Computer Science. Springer Verlag ISSN 0302-9743 (Accepted)

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Abstract

We present an approach for the semi-automatic generation of gesture mappings for devices with low gestural resolution such as the Myo Armband, an off-the-shelf EMG capture device. As an exemplar interactive task, we use text-entry: a pervasive and highly complex interaction. We quantify data related to interaction combining systematic studies (i.e., error, speed, accuracy) and semi-structured workshops with experts (e.g., cognitive load, heuristics). We then formalize these factors in a mathematical model and use optimization algorithms (i.e. simulated annealing) to find an optimum gesture mapping. We demonstrated our method in a text-entry application (i.e., complex interactive dialogue) comparing our approach with other computationally determined mappings using naive cost functions. Our results showed that the designers mapping (with all factors weighted by designers) presented a good balance on performance in all factors involved (speed, accuracy, comfort, memorability, etc.), consistently performing better than purely computational mappings. The results indicate that our hybrid approach can yield better results than either pure user-driven methodologies or pure data-driven approaches, for our application context featuring a large solution space and complex high-level factors.

Item Type:	Conference Proceedings
Keywords:	gestural interaction, semi-automated interaction design, optimization, computational approaches
Schools and Departments:	School of Engineering and Informatics > Informatics
Research Centres and Groups:	Creative Technology
Related URLs:	Organisation
Depositing User:	Lucy Arnold
Date Deposited:	07 Jun 2019 14:30
Last Modified:	08 Aug 2019 11:13
URI:	http://sro.sussex.ac.uk/id/eprint/84152

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