SEMG-based continuous posture recognition of elbow flexion and extension in sagittal plane

Surface electromyographic signal (sEMG) is used in some fields such as human machine interaction and measurement of human motor function, because it can reflect the activation of human muscle. Though the recognition of motion pattern of human limbs has been researched for many years, continuous recognition for human elbow motion without load is still difficult because of low signal noise ratio (SNR). In this paper, we proposed an improved weighted peaks method to process the filtered sEMG signals from the biceps muscle and adapted linear fitting method to obtain the elbow motion in sagittal plane. The experiments showed the proposed method can effectively process the sEMG signals and obtain the activation of biceps muscle. The experimental results show the similar data of elbow motion compared to the data derived from an inertia sensor.

[1]  R.Fff. Weir,et al.  A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  M.W. Jiang,et al.  A Method of Recognizing Finger Motion Using Wavelet Transform of Surface EMG Signal , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[3]  Johannes R. Sveinsson,et al.  Wavelet-package transformation as a preprocessor of EEG waveforms for classification , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[4]  Mehran Jahed,et al.  Real-time intelligent pattern recognition algorithm for surface EMG signals , 2007, Biomedical engineering online.

[5]  Rajesh P. N. Rao,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. 1 Online Electromyographic Control of a Robotic , 2022 .

[6]  Jianda Han,et al.  A novel EMG-driven state space model for the estimation of continuous joint movements , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[7]  Shuxiang Guo,et al.  Development of an upper extremity motor function rehabilitation system and an assessment system , 2011, Int. J. Mechatronics Autom..

[8]  K.R. Wheeler,et al.  Gesture-based control and EMG decomposition , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[9]  M. Hallett,et al.  EMG analysis of stereotyped voluntary movements in man. , 1975, Journal of neurology, neurosurgery, and psychiatry.

[10]  Shuxiang Guo,et al.  Study on recognition of upper limb motion pattern using surface EMG signals for bilateral rehabilitation , 2012, 2012 International Symposium on Micro-NanoMechatronics and Human Science (MHS).

[11]  Shuxiang Guo,et al.  Recognition of motion of human upper limb using sEMG in real time: Towards bilateral rehabilitation , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[12]  P. Dario,et al.  Control of multifunctional prosthetic hands by processing the electromyographic signal. , 2002, Critical reviews in biomedical engineering.

[13]  Richard Shiavi,et al.  Electromyography: Physiology, Engineering, and Noninvasive Applications [Book Review] , 2006, IEEE Engineering in Medicine and Biology Magazine.

[14]  Kongqiao Wang,et al.  Hand Gesture Recognition Research Based on Surface EMG Sensors and 2D-accelerometers , 2007, 2007 11th IEEE International Symposium on Wearable Computers.

[15]  Pornchai Phukpattaranont,et al.  A Novel Feature Extraction for Robust EMG Pattern Recognition , 2009, ArXiv.

[16]  Siddharth Swarup Rautaray,et al.  Real Time Multiple Hand Gesture Recognition System for Human Computer Interaction , 2012 .

[17]  Roberto Merletti,et al.  Electromyography. Physiology, engineering and non invasive applications , 2005 .

[18]  Shuxiang Guo,et al.  Study on the sEMG Driven Upper Limb Exoskeleton Rehabilitation Device in Bilateral Rehabilitation , 2012, J. Robotics Mechatronics.

[19]  Abdulhamit Subasi,et al.  Application of adaptive neuro-fuzzy inference system for epileptic seizure detection using wavelet feature extraction , 2007, Comput. Biol. Medicine.

[20]  Edward A. Patrick,et al.  Review of Pattern Recognition in Medical Diagnosis and Consulting Relative to a New System Model , 1974, IEEE Trans. Syst. Man Cybern..

[21]  Youngjin Choi,et al.  Real time tracking algorithm of sEMG-based human arm motion , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Zhen Wang,et al.  Study on Real-Time Control of Exoskeleton Knee Using Electromyographic Signal , 2010, LSMS/ICSEE.

[23]  Yasue Mitsukura,et al.  Recognition of EMG Signal Patterns by Neural Networks , 2003, KES.