Adaptive wavelet extreme learning machine (Aw-Elm) for index finger recognition using two-channel Electromyography

被引：0
|
作者：
Khairul, Khairul Anam [1 ,2 ]
Al-Jumaily, Adel [2 ]
机构：
[1] University of Jember, Indonesia
[2] University of Technology Sydney, Australia
来源：
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8834卷
关键词：
Activation functions - Adaptation mechanism - Adaptive - Adaptive wavelets - Extreme learning machine - Finger motion recognition - Index finger - Two channel;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper proposes a new structure of wavelet extreme learning machine i.e. an adaptive wavelet extreme learning machine (AW-ELM) for finger motion recognition using only two EMG channels. The adaptation mechanism is performed by adjusting the wavelet shape based on the input information. The performance of the proposed method is compared to ELM using wavelet (W-ELM0 and sigmoid (Sig-ELM) activation function. The experimental results demonstrate that the proposed AW-ELM performs better than W-ELM and Sig-ELM. © Springer International Publishing Switzerland 2014.
引用
收藏
页码：471 / 478
相关论文
共 22 条
  • [1] Adaptive Wavelet Extreme Learning Machine (AW-ELM) for Index Finger Recognition Using Two-Channel Electromyography
    Anam, Khairul
    Al-Jumaily, Adel
    NEURAL INFORMATION PROCESSING (ICONIP 2014), PT I, 2014, 8834 : 471 - 478
  • [2] GRASPING FORCE ESTIMATION FROM TWO-CHANNEL ELECTROMYOGRAPHY SIGNALS USING EXTREME LEARNING MACHINE
    Pibul, Supornpit Na
    Phukpattaranont, Pornchai
    BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2024, 36 (01):
  • [3] Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
    Ravinesh C. Deo
    Mukesh K. Tiwari
    Jan F. Adamowski
    John M. Quilty
    Stochastic Environmental Research and Risk Assessment, 2017, 31 : 1211 - 1240
  • [4] Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
    Deo, Ravinesh C.
    Tiwari, Mukesh K.
    Adamowski, Jan F.
    Quilty, John M.
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2017, 31 (05) : 1211 - 1240
  • [5] Real-time Classification of Finger Movements using Two-channel Surface Electromyography
    Anam, Khairul
    Al-jumaily, Adel
    NEUROTECHNIX: PROCEEDINGS OF THE INTERNATIONAL CONGRESS ON NEUROTECHNOLOGY, ELECTRONICS AND INFORMATICS, 2013, : 218 - 223
  • [6] Handwritten character recognition using wavelet energy and extreme learning machine
    Chacko, Binu P.
    Krishnan, V. R. Vimal
    Raju, G.
    Anto, P. Babu
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2012, 3 (02) : 149 - 161
  • [7] Handwritten character recognition using wavelet energy and extreme learning machine
    Binu P. Chacko
    V. R. Vimal Krishnan
    G. Raju
    P. Babu Anto
    International Journal of Machine Learning and Cybernetics, 2012, 3 : 149 - 161
  • [8] The field terrain recognition based on extreme learning machine using wavelet features
    Liu, Caixia
    Fang, Jianjun
    Liu, Yanxia
    Lu, Yujiao
    2017 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA), 2017, : 1947 - 1951
  • [9] Fault severity recognition based on self-adaptive particle swarm optimisation using wavelet kernel extreme learning machine
    Zhou, Zaichao
    Bo, Lin
    Liu, Xiaofeng
    Tang, Tao
    Lv, Kai
    INSIGHT, 2019, 61 (01) : 35 - 43
  • [10] FASTA-ELM: A fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition
    Mahmood, Saif F.
    Marhaban, Mohammad Hamiruce
    Rokhani, Fakhrul Zaman
    Samsudin, Khairulmizam
    Arigbabu, Olasimbo Ayodeji
    NEUROCOMPUTING, 2017, 219 : 312 - 322
123