research-article

Affective touch gesture recognition for a furry zoomorphic machine

Authors:

Karon MacLeanAuthors Info & Claims

TEI '13: Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction

Pages 25 - 32

https://doi.org/10.1145/2460625.2460629

Published: 10 February 2013 Publication History

Abstract

Over the last decade, the surprising fact has emerged that machines can possess therapeutic power. Due to the many healing qualities of touch, one route to such power is through haptic emotional interaction, which requires sophisticated touch sensing and interpretation. We explore the development of touch recognition technologies in the context of a furry artificial lap-pet, with the ultimate goal of creating therapeutic interactions by sensing human emotion through touch. In this work, we build upon a previous design for a new type of fur-based touch sensor. Here, we integrate our fur sensor with a piezoresistive fabric location/pressure sensor, and adapt the combined design to cover a curved creature-like object. We then use this interface to collect synchronized time-series data from the two sensors, and perform machine learning analysis to recognize 9 key affective touch gestures. In a study of 16 participants, our model averages 94% recognition accuracy when trained on individuals, and 86% when applied to the combined set of all participants. The model can also recognize which participant is touching the prototype with 79% accuracy. These results promise a new generation of emotionally intelligent machines, enabled by affective touch gesture recognition.

References

[1]

C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.

Digital Library

[2]

P. Brockwell and R. Davis. Introduction to time series and forecasting. In Springer-Verlag, New York, 2002.

[3]

J. Chang, K. E. MacLean, and S. Yohanan. Gesture recognition in the haptic creature. In EuroHaptics 2010, 2010.

Digital Library

[4]

R. O. Duda, P. E. Hart, and D. G. Stork. Unsupervised Learning and Clustering, Ch. 10 in Pattern classification. John Wiley and Sons, Inc., 2001.

[5]

A. Flagg, D. Tam, K. MacLean, and R. Flagg. Conductive fur sensing for a gesture-aware furry robot. In IEEE Haptics Symposium, 2012.

[6]

A. Freed. Novel and forgotten current-steering techniques for resistive multitouch, duotouch, and polytouch position sensing with pressure. In New Interfaces for Musical Expression, 2009.

[7]

B. Friedman, P. H. K. Jr., and J. Hagman. Hardware companions?: what online aibo discussion forums reveal about the human-robotic relationship. In CHI '03, pages 273--280, 2003.

Digital Library

[8]

Interlink Forse Sensing Resistors, 2012. http://www.interlinkelectronics.com/products.php.

[9]

K. Goris, J. Saldien, I. Vanderniepen, and D. Lefeber. The huggable robot probo, a multi-disciplinary research platform. In Eurobot '08, 2008.

[10]

T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, second edition, 2009.

[11]

Meka. Dextrous Mobile Manipulators and Humanoids, 2012. http://mekabot.com/?ref=Hizook-spotlight1.

[12]

H. Perner-Wilson. Stroke sensor. Plusea, www.plusea.at, May 2011.

[13]

R. Picard. Affective Computing. MIT Media Laboratory, 1997.

Digital Library

[14]

PJRC. Teensy USB Development Board, 2012. http://www.pjrc.com/teensy/.

[15]

Peratech Ltd. Quantum Tunnelling Composites, 2012. http://www.peratech.com/qtcmaterial.php.

[16]

C. Rafael and S. D'Melle. Affect detection: An interdisciplinary review of models, methods, and their applications. In IEEE Transactions on Affective Computing, 2010.

Digital Library

[17]

Roboskin. Skin-based Technologies and Capabilities for Safe, Autonomous and Interactive Robots, 2012. http://www.roboskin.eu/index.php/home.

[18]

J. Roh, A. Freed, Y. Mann, and D. Wessel. Robust and reliable fabric, piezoresistive multitouch sensing surfaces for musical controllers. In New Interfaces for Musical Expression, 2011.

[19]

A. Schmeder and A. Freed. Support vector machine learning for gesture signal estimation with a piezo resistive fabric touch surface. In New Interfaces for Musical Expression, 2010.

[20]

Y. Sefidgar. TAMER: Touch-guided Anxiety Management via Engagement with a Robotic Pet, Efficacy Evaluation and the First Steps of Interaction Design. M.Sc. Thesis, University of British Columbia, 2012.

[21]

T. Shibata, K. Inoue, and R. Irie. Emotional robot for intelligent system: Artificial emotional creature project. In Proceedings of IIZUKA, pages 43--48, 2006.

[22]

K. B. Shimoga. Finger force and touch feedback issues in dexterous telemanipulation. In Proceedings of Fourth Annual Conference on Intelligent Robotic Systems for Space Exploration, 2009.

[23]

R. Singh, T. Jaakkola, and A. Mohammad. Machine Learning. MIT OpenCourseWare, 2006.

[24]

W. Stiehl and C. Breazeal. Design of a therapeutic robotic companion for relational, affective touch. In Ro-Man-05 (Proceedings of Fourteenth IEEE Workshop on Robot and Human Interactive Communication), pages 408--415, 2005.

[25]

R. S. Sutton and A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.

Digital Library

[26]

I. H. Witten and E. Frank. Data mining: Practical machine learning tools and techniques. Morgan Kaufmann Publishers, second edition, 2005.

Digital Library

[27]

S. Yohanan, J. Hall, K. MacLean, E. Croft, M. V. der Loos, M. Baumann, J. Chang, D. Nielsen, and S. Zoghbi. Affect-driven emotional expression with the haptic creature. In Proceedings of UIST, User Interface Software and Technology, 2009.

[28]

S. Yohanan and K. MacLean. The haptic creature project: Social human-robot interaction through affective touch. In AISB '08 (Proceedings of The Reign of Katz and Dogz, 2nd AISB Symp on the Role of Virtual Creatures in a Computerized Society), pages 7--11, 2008.

[29]

S. Yohanan and K. E. MacLean. A tool to study affect touch: Goals & design of the haptic creature. In Conference on Human Factors in Computing Systems (CHI '09), 2009.

Digital Library

[30]

S. Yohanan and K. E. MacLean. The role of affective touch in human-robot interaction: Human intent and expectations in touching the haptic creature. International Journal of Social Robotics (SORO), Special Issue on Expectations, Intentions, and Actions, accepted 2011.

Cited By

Pouta EMikkonen JSalovaara A(2024)Opportunities with Multi-Layer Weave Structures in Woven E-Textile DesignACM Transactions on Computer-Human Interaction10.1145/368903931:5(1-38)Online publication date: 20-Aug-2024
https://dl.acm.org/doi/10.1145/3689039
Alhouli SAlmania NAhmad MSahoo D(2024)Towards Designing a Pet Robot for Older Adults by Young AdultsProceedings of the 12th International Conference on Human-Agent Interaction10.1145/3687272.3690899(408-410)Online publication date: 24-Nov-2024
https://dl.acm.org/doi/10.1145/3687272.3690899
McLaren DGao JYin XReis Guerra RVyas PMorton CCang XChen YSun YLi YMadden JMacLean K(2024)What is Affective Touch Made Of? A Soft Capacitive Sensor Array Reveals the Interplay between Shear, Normal Stress and IndividualityProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676346(1-31)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676346
Show More Cited By

Index Terms

Affective touch gesture recognition for a furry zoomorphic machine
1. Applied computing
  1. Computers in other domains
    1. Personal computers and PC applications
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
    2. Interaction devices
      1. Haptic devices

Recommendations

Affective Touch as Immediate and Passive Wearable Intervention

We investigated affective touch as a new pathway to passively mitigate in-the-moment anxiety. While existing mobile interventions offer great promises for health and well-being, they typically focus on achieving long-term effects such as shifting ...
Comparing Tangible and Multi-touch Interaction for Interactive Data Visualization Tasks
TEI '16: Proceedings of the TEI '16: Tenth International Conference on Tangible, Embedded, and Embodied Interaction

Interactive visualization plays a key role in the analysis of large datasets. It can help users to explore data, investigate hypotheses and find patterns. The easier and more tangible the interaction, the more likely it is to enhance understanding. This ...
Guided touch screen: enhanced eyes-free interaction
PerDis '16: Proceedings of the 5th ACM International Symposium on Pervasive Displays

Touch screen based interfaces are pervading into areas such as car and industrial machinery control systems, where more tangible, physical interfaces have historically been used. This often results in a reduction in the possibility to operate the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

TEI '13: Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction

February 2013

439 pages

ISBN:9781450318983

DOI:10.1145/2460625

Conference Chairs:
Sergi Jordà
Universitat Pompeu Fabra, Barcelona, Spain
,
Narcis Parés
Universitat Pompeu Fabra, Barcelona, Spain

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 February 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Networks of Centres of Excellence of Canada

Conference

TEI'13

Sponsor:

SIGCHI

TEI'13: Seventh International Conference on Tangible, Embedded, and Embodied Interaction

February 10 - 13, 2013

Barcelona, Spain

Acceptance Rates

TEI '13 Paper Acceptance Rate 48 of 136 submissions, 35%;

Overall Acceptance Rate 393 of 1,367 submissions, 29%

Upcoming Conference

TEI '25

Sponsor:
sigchi

Nineteenth International Conference on Tangible, Embedded, and Embodied Interaction

March 4 - 7, 2025

Bordeaux / Talence , France

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

42
Total Citations
View Citations
952
Total Downloads

Downloads (Last 12 months)61
Downloads (Last 6 weeks)8

Reflects downloads up to 29 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Pouta EMikkonen JSalovaara A(2024)Opportunities with Multi-Layer Weave Structures in Woven E-Textile DesignACM Transactions on Computer-Human Interaction10.1145/368903931:5(1-38)Online publication date: 20-Aug-2024
https://dl.acm.org/doi/10.1145/3689039
Alhouli SAlmania NAhmad MSahoo D(2024)Towards Designing a Pet Robot for Older Adults by Young AdultsProceedings of the 12th International Conference on Human-Agent Interaction10.1145/3687272.3690899(408-410)Online publication date: 24-Nov-2024
https://dl.acm.org/doi/10.1145/3687272.3690899
McLaren DGao JYin XReis Guerra RVyas PMorton CCang XChen YSun YLi YMadden JMacLean K(2024)What is Affective Touch Made Of? A Soft Capacitive Sensor Array Reveals the Interplay between Shear, Normal Stress and IndividualityProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676346(1-31)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676346
Nasiri NIsbister KSchweitzer JBorden JCottrell PShapiro D(2024)Extracting the Affective Content of Fidgeting in Adults with ADHD via Machine Learning and a Hand-held Soft Tangible DeviceExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650856(1-8)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650856
Guo SZhan LCao YZheng CZhou GGong J(2023)Touch-and-HealProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35962587:2(1-33)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3596258
Ren QHou YBelpaeme TCastellano GRiek LCakmak MLeite I(2023)Low-latency Classification of Social Haptic Gestures Using TransformersCompanion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568294.3580059(137-141)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3568294.3580059
Vyas PDesai UYamakawa KMaclean K(2023)A Descriptive Analysis of a Formative Decade of Research in Affective Haptic System DesignProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580735(1-23)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580735
Cang XIsrar AMacLean K(2023)When is a Haptic Message Like an Inside Joke? Digitally Mediated Emotive Communication Builds on Shared HistoryIEEE Transactions on Affective Computing10.1109/TAFFC.2023.324452014:1(732-746)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TAFFC.2023.3244520
Cang XBucci PRantala JMacLean K(2023)Discerning Affect From Touch and Gaze During Interaction With a Robot PetIEEE Transactions on Affective Computing10.1109/TAFFC.2021.309489414:2(1598-1612)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TAFFC.2021.3094894
Olugbade THe LMaiolino PHeylen DBianchi-Berthouze N(2023)Touch Technology in Affective Human–, Robot–, and Virtual–Human Interactions: A SurveyProceedings of the IEEE10.1109/JPROC.2023.3272780111:10(1333-1354)Online publication date: Oct-2023
https://doi.org/10.1109/JPROC.2023.3272780
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten