research-article

EMPress: Practical Hand Gesture Classification with Wrist-Mounted EMG and Pressure Sensing

Authors:

Charlie McNeill,

Frederic Kerber,

Markus Löchtefeld,

Antonio KrügerAuthors Info & Claims

CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

Pages 2332 - 2342

https://doi.org/10.1145/2858036.2858093

Published: 07 May 2016 Publication History

Abstract

Practical wearable gesture tracking requires that sensors align with existing ergonomic device forms. We show that combining EMG and pressure data sensed only at the wrist can support accurate classification of hand gestures. A pilot study with unintended EMG electrode pressure variability led to exploration of the approach in greater depth. The EMPress technique senses both finger movements and rotations around the wrist and forearm, covering a wide range of gestures, with an overall 10-fold cross validation classification accuracy of 96%. We show that EMG is especially suited to sensing finger movements, that pressure is suited to sensing wrist and forearm rotations, and their combination is significantly more accurate for a range of gestures than either technique alone. The technique is well suited to existing wearable device forms such as smart watches that are already mounted on the wrist.

Supplementary Material

suppl.mov (pn0392-file3.mp4)

Supplemental video

Download
42.59 MB

MP4 File (p2332-mcintosh.mp4)

Download
169.99 MB

References

[1]

S. A. Ahmad and P. H. Chappell. 2009. Surface EMG pattern analysis of the wrist muscles at different speeds of contraction. Journal of Medical Engineering & Technology 33, 5 (2009), 376--385.

[2]

Ahmet Alkan and Mücahid Günay. 2012. Identification of EMG Signals Using Discriminant Analysis and SVM Classifier. Expert Syst. Appl. 39, 1 (Jan. 2012), 44--47.

Digital Library

[3]

Christoph Amma, Thomas Krings, Jonas Böer, and Tanja Schultz. 2015. Advancing Muscle-Computer Interfaces with High-Density Electromyography. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, NY, NY, USA, 929--938.

Digital Library

[4]

Hyun Jae Baek, Hong Ji Lee, Yong Gyu Lim, and Kwang Suk Park. 2012. Conductive Polymer Foam Surface Improves the Performance of a Capacitive EEG Electrode. Biomedical Engineering, IEEE Transactions on 59, 12 (Dec 2012), 3422--3431.

[5]

Chih-Chung Chang and Chih-Jen Lin. 2011. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2 (2011), 27:1--27:27. Issue 3. Software available at http://www.csie.ntu.edu.tw/?cjlin/libsvm.

Digital Library

[6]

Xiang Chen, Xu Zhang, Zhang-Yan Zhao, Ji-Hai Yang, V. Lantz, and Kong-Qiao Wang. 2007. Hand Gesture Recognition Research Based on Surface EMG Sensors and 2D-accelerometers. In Wearable Computers, 2007 11th IEEE International Symposium on. 11--14.

Digital Library

[7]

Artem Dementyev and Joseph A. Paradiso. 2014. WristFlex: Low-power Gesture Input with Wrist-worn Pressure Sensors. In Proceedings of the 27th Annual ACM Symposium on User Interface Software and Technology (UIST '14). ACM, NY, NY, USA, 161--166.

Digital Library

[8]

Interlink Electronics. 2015. FSR400 short. (2015). http: //www.interlinkelectronics.com/FSR400short.php.

[9]

Marco Gazzoni, Nicol Celadon, Davide Mastrapasqua, Marco Paleari, Valentina Margaria, and Paolo Ariano. 2014. Quantifying Forearm Muscle Activity during Wrist and Finger Movements by Means of Multi-Channel Electromyography. PLoS ONE 9, 10 (10 2014), e109943.

[10]

Jeremy Gummeson, Bodhi Priyanth, and Jie Liu. 2014. An Energy Harvesting Wearable Ring Platform for Gesture Input on Surfaces. In Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '14). ACM, NY, NY, USA, 162--175.

Digital Library

[11]

S. Sathiya Keerthi and Chih-Jen Lin. 2003. Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel. Neural Comput. 15, 7 (July 2003), 1667--1689.

Digital Library

[12]

12. Frederic Kerber, Pascal Lessel, and Antonio Krüger. 2015. Same-side Hand Interactions with Arm-placed Devices Using EMG. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '15). ACM, NY, NY, USA, 1367--1372.

Digital Library

[13]

David Kim, Otmar Hilliges, Shahram Izadi, Alex D. Butler, Jiawen Chen, Iason Oikonomidis, and Patrick Olivier. 2012. Digits: Freehand 3D Interactions Anywhere Using a Wrist-worn Gloveless Sensor. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology (UIST '12). ACM, NY, NY, USA, 167--176.

Digital Library

[14]

Amanda C. Myers, He Huang, and Yong Zhu. 2015. Wearable silver nanowire dry electrodes for electrophysiological sensing. RSC Adv. 5 (2015), 11627--11632. Issue 15.

[15]

Myo. 2015. How do you wear the Myo armband? (2015). https://support.getmyo.com/hc/en-us/articles/ 201169525-How-do-you-wear-the-Myo-armband-.

[16]

16. Angkoon Phinyomark, Pornchai Phukpattaranont, and Chusak Limsakul. 2012. Feature reduction and selection for {EMG} signal classification. Expert Systems with Applications 39, 8 (2012), 7420--7431.

Digital Library

[17]

Jun Rekimoto. 2001. GestureWrist and GesturePad: Unobtrusive Wearable Interaction Devices. In Proceedings of the 5th IEEE International Symposium on Wearable Computers (ISWC '01). IEEE Computer Society, Washington, DC, USA, 21. http://dl.acm.org/citation.cfm?id=580581.856565

Digital Library

[18]

Advancer Technologies. 2015. Muscle sensor v3. (2015). http://www.advancertechnologies.com/p/ muscle-sensor-v3.html.

[19]

M.T. Wolf, C. Assad, A. Stoica, Kisung You, H. Jethani, M.T. Vernacchia, J. Fromm, and Y. Iwashita. 2013. Decoding static and dynamic arm and hand gestures from the JPL BioSleeve. In Aerospace Conference, 2013 IEEE. 1--9.

Cited By

Pires NMacedo M(2025)A Bimodal EMG/FMG System Using Machine Learning Techniques for Gesture Recognition OptimizationSignals10.3390/signals60100086:1(8)Online publication date: 20-Feb-2025
https://doi.org/10.3390/signals6010008
Stanke DSimon BLöwen SRohs M(2024)CaseTouch: Occlusion-Free Touch Input by adding a Thin Sensor Stripe to the Smartwatch CaseProceedings of the International Conference on Mobile and Ubiquitous Multimedia10.1145/3701571.3701583(172-183)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1145/3701571.3701583
Ergül İÇalış TYücetürk EGür MBulut SBaykal G(2024)Co-Rhythm: Analyzing Children's Performative Gesture-based Interactions in a Music Composition ToolProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3659375(686-690)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3659375
Show More Cited By

Index Terms

EMPress: Practical Hand Gesture Classification with Wrist-Mounted EMG and Pressure Sensing
1. Human-centered computing

Recommendations

WristFlex: low-power gesture input with wrist-worn pressure sensors
UIST '14: Proceedings of the 27th annual ACM symposium on User interface software and technology

In this paper we present WristFlex, an always-available on-body gestural interface. Using an array of force sensitive resistors (FSRs) worn around the wrist, the interface can distinguish subtle finger pinch gestures with high accuracy (>80 %) and ...
EMG-based hand gesture recognition for realtime biosignal interfacing
IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces

In this paper the development of an electromyogram (EMG) based interface for hand gesture recognition is presented. To recognize control signs in the gestures, we used a single channel EMG sensor positioned on the inside of the forearm. In addition to ...
Tomo: Wearable, Low-Cost Electrical Impedance Tomography for Hand Gesture Recognition
UIST '15: Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology

We present Tomo, a wearable, low-cost system using Electrical Impedance Tomography (EIT) to recover the interior impedance geometry of a user's arm. This is achieved by measuring the cross-sectional impedances between all pairs of eight electrodes ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

May 2016

6108 pages

ISBN:9781450333627

DOI:10.1145/2858036

General Chairs:
Jofish Kaye
Yahoo
,
Allison Druin
University of Maryland / National Park Service
,
Program Chairs:
Cliff Lampe
University of Michigan
,
Dan Morris
Microsoft
,
Juan Pablo Hourcade
University of Iowa

Copyright © 2016 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 the author(s) 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: 07 May 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

EPSRC

Conference

CHI'16

Sponsor:

SIGCHI

CHI'16: CHI Conference on Human Factors in Computing Systems

May 7 - 12, 2016

California, San Jose, USA

Acceptance Rates

CHI '16 Paper Acceptance Rate 565 of 2,435 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

113
Total Citations
View Citations
1,909
Total Downloads

Downloads (Last 12 months)121
Downloads (Last 6 weeks)15

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Pires NMacedo M(2025)A Bimodal EMG/FMG System Using Machine Learning Techniques for Gesture Recognition OptimizationSignals10.3390/signals60100086:1(8)Online publication date: 20-Feb-2025
https://doi.org/10.3390/signals6010008
Stanke DSimon BLöwen SRohs M(2024)CaseTouch: Occlusion-Free Touch Input by adding a Thin Sensor Stripe to the Smartwatch CaseProceedings of the International Conference on Mobile and Ubiquitous Multimedia10.1145/3701571.3701583(172-183)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1145/3701571.3701583
Ergül İÇalış TYücetürk EGür MBulut SBaykal G(2024)Co-Rhythm: Analyzing Children's Performative Gesture-based Interactions in a Music Composition ToolProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3659375(686-690)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3659375
Kawabe TUjitoko Y(2024)Softness Perception of Visual Objects Controlled by Touchless Inputs: The Role of Effective Distance of Hand MovementsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.325452230:7(4154-4169)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2023.3254522
Liu YWang RLi YWang Y(2024)A Novel Dual-Model Adaptive Continuous Learning Strategy for Wrist-sEMG Real-Time Gesture RecognitionIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2024.350262432(4186-4196)Online publication date: 2024
https://doi.org/10.1109/TNSRE.2024.3502624
Alemu MLin YShull P(2024)EchoGest: Soft Ultrasonic Waveguides Based Sensing Skin for Subject-Independent Hand Gesture RecognitionIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2024.341413632(2366-2375)Online publication date: 2024
https://doi.org/10.1109/TNSRE.2024.3414136
Qi HXiong JCao MLai WHu Y(2024)Wrist Information Detection Sensor Based on Pinhole ImagingIEEE Photonics Journal10.1109/JPHOT.2024.343583216:6(1-6)Online publication date: Dec-2024
https://doi.org/10.1109/JPHOT.2024.3435832
Yu XLi BChen J(2024)WiFi-Enabled Gesture Recognition Using Attention-enhanced DenseNet2024 IEEE/CIC International Conference on Communications in China (ICCC)10.1109/ICCC62479.2024.10681945(1692-1697)Online publication date: 7-Aug-2024
https://doi.org/10.1109/ICCC62479.2024.10681945
Fu TJiang NHe CHe J(2024)Wrist EMG-based Gestures Recognition for Finger and Wrist Motions2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC53108.2024.10782509(1-4)Online publication date: 15-Jul-2024
https://doi.org/10.1109/EMBC53108.2024.10782509
Mao LOno KQi MHuang JWatanabe M(2024)Breadth and orientation of pie menus for mid-air interaction: effects on upper extremity biomechanics, performance, and subjective assessmentBehaviour & Information Technology10.1080/0144929X.2024.231009744:1(61-78)Online publication date: 29-Jan-2024
https://doi.org/10.1080/0144929X.2024.2310097
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