Journal of Optoelectronics · Laser, Volume. 34, Issue 7, 723(2023)
sEMG processing method fusing multivariate empirical mode decomposition and Hilbert space-filling curves
[1] [1] MANDEEP K A,Amardeep S.A survey of hand gesture recognition[J]. International Journal of Advance Research in Computer and Management Studies,2015,3(5):266-271.
[3] [3] SCHEME E,ENGLEHART K.Electromyogram pattern recognition for control of powered upper-limb prostheses:state of the art and challenges for clinical use[J].Journal of Rehabilitation Research and Development,2011,48(6):643-660.
[6] [6] HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society A:Mathematical,Physical and Engineering Sciences,1998,454(1971):903-995.
[7] [7] CASTELLINI C,FIORILLA A E,SANDINI G.Multi-subject/dailylife activity EMG-based control of mechanical hands[J].Journal of Neuroengineering and Rehabilitation,2009,6(1):1-11.
[8] [8] PARK K H,LEE S W.Movement intention decoding based on deep learning for multiuser myoelectric interfaces[C]//International Winter Conference on Brain-computer Interface,February 22-24,2016,Gangwon,Korea (South).New York:IEEE,2016:1-2.
[9] [9] ATZORI M,COGNOLATO M,MULLER H.Deep learning with convolutional neural networks applied to electromyography data: a resource for the classification of movements for prosthetic hands[J].Frontiers in Neurorobotics,2016,10:9.
[10] [10] GENG W D,DU Y,JIN W G,et al.Gesture recognition by instantaneous surface EMG images[J].Scientific Reports,2016,6(1):1-8.
[11] [11] WEI W T,WONG Y K,DU Y,et al.A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface[J].Pattern Recognition Letters,2019,119:131-138.
[12] [12] TSINGANOS P,CORNELIS B,CORNELIS J,et al.Hilbert sEMG data scanning for hand gesture recognition based on deep learning[J].Neural Computing and Applications,2021,33(7):2645-2666.
[13] [13] HUANG G,LIU Z,VAN DER MAATEN L,et al.Densely connected convolutional networks[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),July 21-26,2017,Honolulu,HI,USA.New York:IEEE 2017:2261-2269.
[14] [14] REHMAN N,MANDIC D P.Multivariate empirical mode decomposition[J].Proceedings of the Royal Society A:Mathematical,Physical and Engineering Sciences,2010,466(2117):1291-1302.
[15] [15] ATZORI M,GIJSBERTS A,CASTELLINI C,et al.Electro-myography data for non-invasive naturally-controlled robotic hand prostheses[J].Scientific data,2014,1(1):1-13.
[16] [16] ATZORI M,GIJSBERTS A,HEYNEN S,et al.Building the NinaPro database:A resource for the biorobotics community[C]//2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob),June 24-27,2012,Rome,Italy.New York:IEEE,2012:1258-1265.
[17] [17] XU K, BA J,KIROS R, et al.Show,attend and tell:Neural image caption generation with visual attention[C]//International Conference on Machine Learning,July 6-11,2015,Lille,France.JMLR,2015:2048-2057.
[19] [19] TSINGANOS P,CORNELIS B,CORNELIS J,et al.A Hilbert curve based representation of sEMG signals for gesture recognition[C]//2019 International Conference on Systems,Signals and Image Processing (IWSSIP),June 5-7,2019,Osijek,Groatia.New York:IEEE,2019:201-206.
[20] [20] LECUN Y,BENGIO Y.Convolutional networks for images, speech, and time-series[M]//The handbook of brain theory and neural networks.Cambridge,MA,United States:MIT Press,1998:255-258.
[21] [21] LECUN Y,BOTTOU L.Gradient-based learning applied to document recognition[J].Proceedings of the IEEE,1998,86(11):2278-2324.
[22] [22] IMARD P Y,STEINKRAUS D,PLATT J C.Best practices for convolutional neural networks applied to visual document analysis[C]//Seventh International Conference on Document Analysis and Recognition,August 6,2003,Edinburgh,UK.New York:IEEE,2003:958-963.
[23] [23] KRIZHEVSKY A,SUTSKEVER I,HINTON G E.ImageNet classification with deep convolutional neural networks[J].Communications of the ACM,2012:60(6):84-90.
[24] [24] SZEGEDY C,LIU W,Jia Y,et al.Going deeper with convolutions [C]//IEEE Conference on Computer Vision and Pattern Recognition,June 7-12,2015,Boston,MA,USA.New York:IEEE,2015:1-9.
[25] [25] SIMONYAN K,ZISSERMAN A.Very deep convolutional networks for large-scale image recognition[EB/OL].(2014-09-04)[2022-05-08].https://arxiv.org/abs/1409.1556.
[26] [26] HE K M,ZHANG X Y,REN S Q,et al.Deep residual learning for image recognition [C]//IEEE Conference on Computer Vision and Pattern Recognition,June 27-30,2016,Las Vegas,NV,USA.New York:IEEE,2016:770-778.
Get Citation
Copy Citation Text
LIU Cong, MA Yutong, XU Tingting, HU Sheng, KONG Xiangbin. sEMG processing method fusing multivariate empirical mode decomposition and Hilbert space-filling curves[J]. Journal of Optoelectronics · Laser, 2023, 34(7): 723
Received: May. 8, 2022
Accepted: --
Published Online: Sep. 25, 2024
The Author Email: LIU Cong (20181008@hbut.edu.cn)