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A proposal for a MMG-based hand gesture recognition method

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UIST Adjunct Proceedings '12: Adjunct proceedings of the 25th annual ACM symposium on User interface software and technology

Pages 89 - 90

https://doi.org/10.1145/2380296.2380336

Published: 07 October 2012 Publication History

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Abstract

We propose a novel hand-gesture recognition method based on mechanomyograms (MMGs). Skeletal muscles generate sounds specific to their activity. By recording and analyzing these sounds, MMGs provide means to evaluate the activity. Previous research revealed that specific motions produce specific sounds enabling human motion to be classified based on MMGs. In that research, microphones and accelerometers are often used to record muscle sounds. However, environmental conditions such as noise and human motion itself easily overwhelm such sensors. In this paper, we propose to use piezoelectric-based sensing of MMGs to improve robustness from environmental conditions. The preliminary evaluation shows this method is capable of classifying several hand gestures correctly with high accuracy under certain situations.

References

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D. T. Barry, Muscle Sounds are Emitted at Resonant Frequencies of Skeletal Muscle: Biomedical Engineering, IEEE Transactions on, 1990.

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Travis W. Beck and Vinzenz von Tscharner, Concentric and eccentric isokinetic muscle activity separated by paired pattern classification of wavelet transformed mechanomyograms: Biomedical Signal Processing and Control: Volume 4, Issue 2, Pages 94--101, 2009.

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Cited By

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Hao SGao DJu ZGao Q(2024)Multimodal Hand Gesture Recognition Based on the Fusion of Surface Electromyography and Vision2024 30th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)10.1109/M2VIP62491.2024.10746196(1-6)Online publication date: 3-Oct-2024
https://doi.org/10.1109/M2VIP62491.2024.10746196
Tchantchane RZhou HZhang SAlici G(2023)A Review of Hand Gesture Recognition Systems Based on Noninvasive Wearable SensorsAdvanced Intelligent Systems10.1002/aisy.2023002075:10Online publication date: 20-Jul-2023
https://doi.org/10.1002/aisy.202300207
Botros FPhinyomark AScheme E(2022)Electromyography-Based Gesture Recognition: Is It Time to Change Focus From the Forearm to the Wrist?IEEE Transactions on Industrial Informatics10.1109/TII.2020.304161818:1(174-184)Online publication date: Jan-2022
https://doi.org/10.1109/TII.2020.3041618
Show More Cited By

Index Terms

A proposal for a MMG-based hand gesture recognition method
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

UIST Adjunct Proceedings '12: Adjunct proceedings of the 25th annual ACM symposium on User interface software and technology

October 2012

114 pages

ISBN:9781450315821

DOI:10.1145/2380296

General Chair:
Rob Miller
MIT CSAIL, USA
,
Program Chairs:
Hrvoje Benko
Microsoft Research, USA
,
Celine Latulipe
University of North Carolina at Charlotte, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2012

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UIST '12

Sponsor:

UIST '12: The 25th Annual ACM Symposium on User Interface Software and Technology

October 7 - 10, 2012

Massachusetts, Cambridge, USA

Acceptance Rates

Overall Acceptance Rate 355 of 1,733 submissions, 20%

Upcoming Conference

UIST '25

Sponsor:
sigchi
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The 38th Annual ACM Symposium on User Interface Software and Technology

September 28 - October 1, 2025

Busan , Republic of Korea

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Cited By

View all

Hao SGao DJu ZGao Q(2024)Multimodal Hand Gesture Recognition Based on the Fusion of Surface Electromyography and Vision2024 30th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)10.1109/M2VIP62491.2024.10746196(1-6)Online publication date: 3-Oct-2024
https://doi.org/10.1109/M2VIP62491.2024.10746196
Tchantchane RZhou HZhang SAlici G(2023)A Review of Hand Gesture Recognition Systems Based on Noninvasive Wearable SensorsAdvanced Intelligent Systems10.1002/aisy.2023002075:10Online publication date: 20-Jul-2023
https://doi.org/10.1002/aisy.202300207
Botros FPhinyomark AScheme E(2022)Electromyography-Based Gesture Recognition: Is It Time to Change Focus From the Forearm to the Wrist?IEEE Transactions on Industrial Informatics10.1109/TII.2020.304161818:1(174-184)Online publication date: Jan-2022
https://doi.org/10.1109/TII.2020.3041618
Jiang SKang PSong XLo BShull P(2022)Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A SurveyIEEE Reviews in Biomedical Engineering10.1109/RBME.2021.307819015(85-102)Online publication date: 2022
https://doi.org/10.1109/RBME.2021.3078190
Ling YChen XRuan YZhang XChen X(2021)Comparative Study of Gesture Recognition Based on Accelerometer and Photoplethysmography Sensor for Gesture Interactions in Wearable DevicesIEEE Sensors Journal10.1109/JSEN.2021.308171421:15(17107-17117)Online publication date: 1-Aug-2021
https://doi.org/10.1109/JSEN.2021.3081714
Liu MLin YQiu ZKuo CWu C(2020)Hand Gesture Recognition by a MMG-Based Wearable DeviceIEEE Sensors Journal10.1109/JSEN.2020.301182520:24(14703-14712)Online publication date: 15-Dec-2020
https://doi.org/10.1109/JSEN.2020.3011825
Benatti SMilosevic BFarella EGruppioni EBenini L(2017)A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control StrategiesSensors10.3390/s1704086917:4(869)Online publication date: 15-Apr-2017
https://doi.org/10.3390/s17040869
McIntosh JMarzo AFraser MPhillips CMark GFussell SLampe Cschraefel mHourcade JAppert CWigdor D(2017)EchoFlexProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025807(1923-1934)Online publication date: 2-May-2017
https://dl.acm.org/doi/10.1145/3025453.3025807
Booth RGoldsmith P(2017)Detecting finger gestures with a wrist worn piezoelectric sensor array2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC.2017.8123202(3665-3670)Online publication date: Oct-2017
https://doi.org/10.1109/SMC.2017.8123202

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