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Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors

Published: 08 February 2009 Publication History

Abstract

This paper describes a novel hand gesture recognition system that utilizes both multi-channel surface electromyogram (EMG) sensors and 3D accelerometer (ACC) to realize user-friendly interaction between human and computers. Signal segments of meaningful gestures are determined from the continuous EMG signal inputs. Multi-stream Hidden Markov Models consisting of EMG and ACC streams are utilized as decision fusion method to recognize hand gestures. This paper also presents a virtual Rubik's Cube game that is controlled by the hand gestures and is used for evaluating the performance of our hand gesture recognition system. For a set of 18 kinds of gestures, each trained with 10 repetitions, the average recognition accuracy was about 91.7% in real application. The proposed method facilitates intelligent and natural control based on gesture interaction.

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Rubik's Cube http://en.wikipedia.org/wiki/Rubik's_cube
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Cited By

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  • (2025)Developing a real-time hand exoskeleton system that controlled by a hand gesture recognition system via wireless sensorsBiomedical Signal Processing and Control10.1016/j.bspc.2024.10688699(106886)Online publication date: Jan-2025
  • (2024)MSMFNet: Multi-Modal Fusion Gesture Recognition Network with Multi-Scale Integration of AUS and sEMG2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10650249(1-9)Online publication date: 30-Jun-2024
  • (2023)An Empirical Investigation of Human Identity Verification MethodsInternational Journal of Scientific Research in Science, Engineering and Technology10.32628/IJSRSET2310012(16-38)Online publication date: 2-Jan-2023
  • Show More Cited By

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  1. Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors

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    cover image ACM Conferences
    IUI '09: Proceedings of the 14th international conference on Intelligent user interfaces
    February 2009
    522 pages
    ISBN:9781605581682
    DOI:10.1145/1502650
    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]

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    New York, NY, United States

    Publication History

    Published: 08 February 2009

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    Author Tags

    1. accelerometer
    2. electromyogram
    3. gesture recognition
    4. human computer interaction

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    IUI09
    IUI09: 14th International Conference on Intelligent User Interfaces
    February 8 - 11, 2009
    Florida, Sanibel Island, USA

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    Overall Acceptance Rate 746 of 2,811 submissions, 27%

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    Cited By

    View all
    • (2025)Developing a real-time hand exoskeleton system that controlled by a hand gesture recognition system via wireless sensorsBiomedical Signal Processing and Control10.1016/j.bspc.2024.10688699(106886)Online publication date: Jan-2025
    • (2024)MSMFNet: Multi-Modal Fusion Gesture Recognition Network with Multi-Scale Integration of AUS and sEMG2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10650249(1-9)Online publication date: 30-Jun-2024
    • (2023)An Empirical Investigation of Human Identity Verification MethodsInternational Journal of Scientific Research in Science, Engineering and Technology10.32628/IJSRSET2310012(16-38)Online publication date: 2-Jan-2023
    • (2023)A Framework and Call to Action for the Future Development of EMG-Based Input in HCIProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580962(1-23)Online publication date: 19-Apr-2023
    • (2023)Similarity Function for One-Shot Learning to Enhance the Flexibility of Myoelectric InterfacesIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2023.325368331(1697-1706)Online publication date: 2023
    • (2023)Mobile Gaming EMG-Based Brain Computer InterfaceComputer-Human Interaction Research and Applications10.1007/978-3-031-49425-3_3(40-52)Online publication date: 23-Dec-2023
    • (2023)Gesture‐Based ComputingHandbook of Human‐Machine Systems10.1002/9781119863663.ch32(397-408)Online publication date: 7-Jul-2023
    • (2022)Real-Time Multiple Gesture Recognition: Application of a Lightweight Individualized 1D CNN Model to an Edge Computing SystemIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2022.316585830(990-998)Online publication date: 2022
    • (2022)EmgAuth: Unlocking Smartphones with EMG SignalsIEEE Transactions on Mobile Computing10.1109/TMC.2022.3176651(1-1)Online publication date: 2022
    • (2022)Contrastive Domain Adaptation: A Self-Supervised Learning Framework for sEMG-Based Gesture Recognition2022 IEEE International Joint Conference on Biometrics (IJCB)10.1109/IJCB54206.2022.10008005(1-7)Online publication date: 10-Oct-2022
    • Show More Cited By

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