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A prototype of gesture-based interface

Published: 30 August 2011 Publication History

Abstract

This paper introduces a novel gesture-based human-machine interface prototype, which consists of a wearable belt embedding with four surface electromyography (SEMG) sensors, a tri-axis accelerometer and an application program running on NOKIA 5800XM. The sensor belt captures hand gestures by acquiring SEMG and acceleration (ACC) signals from forearm, and sends the m out via Bluetooth. The application program receives the data and translates them into control commands of a given interaction application. Experimental results of two test schemes conducted on hand gesture recognition and media player operation demonstrate the validity of the proposed gesture-based interface prototype.

References

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Liu, J., Zhong, L., Wickramasuriya, J. and Vasudevan, V. User Evaluation of Lightweight User Authentication with a Single Tri-Axis Accelerometer. In Proc. MobileHCI 2009.
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Liu, X., Zhou, R., Yang, L. and Li, G. Performance of various EMG features in identifying arm movements for control of multifunctional prostheses. In Proceedings of Youth Conference on Information, Computing and Telecommunication 2009, IEEE 2009, 287--290.
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Mulavara, A. P., Sastry, K. L. A. and Verstraete, M. C. Frequency characterization of EMG activity during gait. In Proceedings of the Annual Conference on Engineering in Medicine and Biology 1993, IEEE (1993), 1215--1216.
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Saponas, T. S., Tan, D. S., Morris, D., Balakrishnan, R., Turner, J. and Landay, J. A. Enabling always-available input with muscle-computer interfaces. In Proceedings of the 22nd annual ACM symposium on User interface software and technology. ACM, 167--176.
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Cited By

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  • (2023)Towards a Consensus Gesture Set: A Survey of Mid-Air Gestures in HCI for Maximized Agreement Across DomainsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581420(1-24)Online publication date: 19-Apr-2023
  • (2022)Development of an IoT-Enabled Stroke Rehabilitation SystemInternational Conference on Artificial Intelligence for Smart Community10.1007/978-981-16-2183-3_94(993-1003)Online publication date: 14-Nov-2022
  • (2021)Hand Gestures Recognition using Inertial Sensors Through Deep Learning2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT51525.2021.9579829(1-6)Online publication date: 6-Jul-2021
  • Show More Cited By

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Published In

cover image ACM Other conferences
MobileHCI '11: Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services
August 2011
781 pages
ISBN:9781450305419
DOI:10.1145/2037373
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

  • Nokia
  • Swedish Institute of Computer Science: Swedish Institute of Computer Science
  • ERICSSON

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 August 2011

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Author Tags

  1. SEMG
  2. accelerometer
  3. gesture-based interface

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  • Research-article

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MobileHCI '11
Sponsor:
  • Swedish Institute of Computer Science

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Overall Acceptance Rate 202 of 906 submissions, 22%

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Cited By

View all
  • (2023)Towards a Consensus Gesture Set: A Survey of Mid-Air Gestures in HCI for Maximized Agreement Across DomainsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581420(1-24)Online publication date: 19-Apr-2023
  • (2022)Development of an IoT-Enabled Stroke Rehabilitation SystemInternational Conference on Artificial Intelligence for Smart Community10.1007/978-981-16-2183-3_94(993-1003)Online publication date: 14-Nov-2022
  • (2021)Hand Gestures Recognition using Inertial Sensors Through Deep Learning2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT51525.2021.9579829(1-6)Online publication date: 6-Jul-2021
  • (2021)Face MovementHuman Movements in Human-Computer Interaction (HCI)10.1007/978-3-030-90004-5_2(7-21)Online publication date: 2-Dec-2021
  • (2019)GesturePodProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology10.1145/3332165.3347881(403-415)Online publication date: 17-Oct-2019
  • (2019)Myoelectric Pattern Recognition for Controlling a Robotic Hand: A Feasibility Study in StrokeIEEE Transactions on Biomedical Engineering10.1109/TBME.2018.284084866:2(365-372)Online publication date: Feb-2019
  • (2019)Offline and online myoelectric pattern recognition analysis and real-time control of a robotic hand after spinal cord injuryJournal of Neural Engineering10.1088/1741-2552/ab0cf016:3(036018)Online publication date: 16-Apr-2019
  • (2018)An IoT-Enabled Stroke Rehabilitation System Based on Smart Wearable Armband and Machine LearningIEEE Journal of Translational Engineering in Health and Medicine10.1109/JTEHM.2018.28226816(1-10)Online publication date: 2018
  • (2014)A Hand Gesture Recognition Framework and Wearable Gesture-Based Interaction Prototype for Mobile DevicesIEEE Transactions on Human-Machine Systems10.1109/THMS.2014.230279444:2(293-299)Online publication date: Apr-2014

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