abstract

Enhancing Zoom and Pan in Ultrasound Machines with a Multimodal Gaze-based Interface

Authors:

Yasmin Halwani,

Septimiu E. Salcudean,

Victoria A. Lessoway,

Sidney S. FelsAuthors Info & Claims

CHI EA '17: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems

Pages 1648 - 1654

https://doi.org/10.1145/3027063.3053174

Published: 06 May 2017 Publication History

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Abstract

We present the first iteration of a user-centred design for integrating an eye gaze tracker with ultrasound (US) machine interfaces used in routine diagnostic sonography. The aim is to speed up the interaction of the sonographer with the machine, offer a more ergonomic solution while minimizing the cognitive load and maintaining the produced image quality. In this iteration, we target pan and zoom functions. Field studies and observations have led to two design alternatives. A feasibility study of two design approaches determined from field studies is done using a functional prototype. Results from six sonographers provided evidence for the potential of a multimodal gaze-based interface for US machines. Results from the feasibility study have also led to a second design iteration that combines the advantages of both gaze-based designs.

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References

[1]

Nicholas Adams, Mark Witkowski, and Robert Spence. 2008. The Inspection of Very Large Images by Eye-gaze Control. In Proceedings of the Working Conference on Advanced Visual Interfaces (AVI '08). ACM, New York, NY, USA, 111--118.

Digital Library

Google Scholar

[2]

CIRS. 2016. Multi-purpose multi-tissue ultrasound phantom. (2016). http://www.cirsinc.com/products/ modality/67/multi-purpose-multi-tissue-ultrasound-phantom/.

Google Scholar

[3]

Gazepoint. 2016. GP3 Eye Tracker. (2016). https: //www.gazept.com/.

Google Scholar

[4]

Hartmut Glücker, Felix Raab, Florian Echtler, and Christian Wolff. 2014. EyeDE: Gaze-enhanced Software Development Environments. In Proceedings of the Extended Abstracts of the 32Nd Annual ACM Conference on Human Factors in Computing Systems (CHI EA '14). ACM, New York, NY, USA, 1555--1560.

Digital Library

Google Scholar

[5]

Robert JK Jacob. 1995. Eye tracking in advanced interface design. Virtual environments and advanced interface design (1995), 258--288.

Digital Library

Google Scholar

[6]

Manu Kumar, Andreas Paepcke, and Terry Winograd. 2007. EyePoint: practical pointing and selection using gaze and keyboard. In Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 421--430.

Digital Library

Google Scholar

[7]

Emilie Mollenbach, Thorarinn Stefansson, and John Paulin Hansen. 2008. All Eyes on the Monitor: Gaze Based Interaction in Zoomable, Multi-scaled Information-spaces. In Proceedings of the 13th International Conference on Intelligent User Interfaces (IUI '08). ACM, New York, NY, USA, 373--376.

Digital Library

Google Scholar

[8]

Andre Russo, Carmel Murphy, Victoria Lessoway, and Jonathan Berkowitz. 2002. The prevalence of musculoskeletal symptoms among British Columbia sonographers. Applied Ergonomics 33, 5 (2002), 385 -- 393.

Crossref

Google Scholar

[9]

Sophie Stellmach and Raimund Dachselt. 2012. Investigating Gaze-supported Multimodal Pan and Zoom. In Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA '12). ACM, New York, NY, USA, 357--360. 2168556.2168636

Digital Library

Google Scholar

[10]

Ultrasonix. 2016. Touch screen ultrasound system. (2016). http://www.ultrasonix.com/node/73.

Google Scholar

[11]

Shumin Zhai, Carlos Morimoto, and Steven Ihde. 1999. Manual and Gaze Input Cascaded (MAGIC) Pointing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '99). ACM, New York, NY, USA, 246--253.

Digital Library

Google Scholar

Cited By

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Gunasekaran H(2019)Multimodal enactive interface: Design principles grounded on cognitive neuroscientific basis2019 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)10.1109/CogInfoCom47531.2019.9089912(000397-000402)Online publication date: Oct-2019
https://doi.org/10.1109/CogInfoCom47531.2019.9089912
Zhu HSalcudean SRohling R(2019)A novel gaze-supported multimodal human–computer interaction for ultrasound machinesInternational Journal of Computer Assisted Radiology and Surgery10.1007/s11548-019-01964-814:7(1107-1115)Online publication date: 11-Apr-2019
https://doi.org/10.1007/s11548-019-01964-8

Index Terms

Enhancing Zoom and Pan in Ultrasound Machines with a Multimodal Gaze-based Interface
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

CHI EA '17: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems

May 2017

3954 pages

ISBN:9781450346566

DOI:10.1145/3027063

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 May 2017

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CHI '17

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SIGCHI

CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

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CHI EA '17 Paper Acceptance Rate 1,000 of 5,000 submissions, 20%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Cited By

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Gunasekaran H(2019)Multimodal enactive interface: Design principles grounded on cognitive neuroscientific basis2019 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)10.1109/CogInfoCom47531.2019.9089912(000397-000402)Online publication date: Oct-2019
https://doi.org/10.1109/CogInfoCom47531.2019.9089912
Zhu HSalcudean SRohling R(2019)A novel gaze-supported multimodal human–computer interaction for ultrasound machinesInternational Journal of Computer Assisted Radiology and Surgery10.1007/s11548-019-01964-814:7(1107-1115)Online publication date: 11-Apr-2019
https://doi.org/10.1007/s11548-019-01964-8

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Recommendations

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