Suitability of Single-channel Acoustic Myography for Classification of Individual Finger Movements

2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR) ◽

10.1109/icievicivpr48672.2020.9306593 ◽

2020 ◽

Author(s):

Amirul Karim Tanim ◽

K M Talha Nahiyan ◽

M.A.R. Ahad

Keyword(s):

Single Channel ◽

Finger Movements ◽

Individual Finger ◽

Acoustic Myography

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EMG-driven hand model based on the classification of individual finger movements

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2019.101834 ◽

2020 ◽

Vol 58 ◽

pp. 101834 ◽

Author(s):

Maria V. Arteaga ◽

Jenny C. Castiblanco ◽

Ivan F. Mondragon ◽

Julian D. Colorado ◽

Catalina Alvarado-Rojas

Keyword(s):

Finger Movements ◽

Model Based ◽

Individual Finger

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LSTM Classification of sEMG Signals For Individual Finger Movements Using Low Cost Wearable Sensor

2020 International Symposium on Community-centric Systems (CcS) ◽

10.1109/ccs49175.2020.9231515 ◽

2020 ◽

Author(s):

Christopher Millar ◽

Nazmul Siddique ◽

Emmett Kerr

Keyword(s):

Low Cost ◽

Wearable Sensor ◽

Finger Movements ◽

Individual Finger ◽

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Classification of multichannel ECoG related to individual finger movements with redundant spatial projections

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2011.6091341 ◽

2011 ◽

Author(s):

I. Onaran ◽

N. F. Ince ◽

A. E. Cetin

Keyword(s):

Finger Movements ◽

Individual Finger

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Enhanced Classification of Individual Finger Movements with ECoG

2019 53rd Asilomar Conference on Signals, Systems, and Computers ◽

10.1109/ieeeconf44664.2019.9048649 ◽

2019 ◽

Author(s):

Lin Yao ◽

Mahsa Shoaran

Keyword(s):

Finger Movements ◽

Individual Finger

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Empirical Mode Decomposition Algorithms for Classification of Single-Channel EEG Manifesting McGurk Effect

Intelligent Human Computer Interaction - Lecture Notes in Computer Science ◽

10.1007/978-3-030-44689-5_5 ◽

2020 ◽

pp. 49-60

Author(s):

Arup Kumar Pal ◽

Dipanjan Roy ◽

G. Vinodh Kumar ◽

Bipra Chatterjee ◽

L. N. Sharma ◽

...

Keyword(s):

Empirical Mode Decomposition ◽

Single Channel ◽

Mcgurk Effect ◽

Decomposition Algorithms ◽

Mode Decomposition

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Automatic Classification of Sleep Stages Based on Raw Single-Channel EEG

Pattern Recognition and Computer Vision - Lecture Notes in Computer Science ◽

10.1007/978-3-030-60639-8_30 ◽

2020 ◽

pp. 356-368

Author(s):

Kailin Xu ◽

Siyu Xia ◽

Guang Li

Keyword(s):

Single Channel ◽

Automatic Classification ◽

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Single‐channel EEG classification of sleep stages based on REM microstructure

Healthcare Technology Letters ◽

10.1049/htl2.12007 ◽

2021 ◽

Author(s):

Irene Rechichi ◽

Maurizio Zibetti ◽

Luigi Borzì ◽

Gabriella Olmo ◽

Leonardo Lopiano

Keyword(s):

Single Channel ◽

Sleep Stages ◽

Eeg Classification

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Estimation of Dexterous Individual Finger Movements from the Ultrasound Image Using Convolutional Neural Networks

2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) ◽

10.1109/cisp-bmei48845.2019.8965921 ◽

2019 ◽

Author(s):

Hyeong-Kil Joo ◽

Ki-Seung Lee

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Ultrasound Image ◽

Finger Movements ◽

Individual Finger

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Deep convolutional neural network for classification of sleep stages from single-channel EEG signals

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2019.108312 ◽

2019 ◽

Vol 324 ◽

pp. 108312 ◽

Author(s):

Z. Mousavi ◽

T. Yousefi Rezaii ◽

S. Sheykhivand ◽

A. Farzamnia ◽

S.N. Razavi

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Single Channel ◽

Deep Convolutional Neural Network ◽

Sleep Stages ◽

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Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees

Neural Networks ◽

10.1016/j.neunet.2016.09.004 ◽

2017 ◽

Vol 85 ◽

pp. 51-68 ◽

Author(s):

Khairul Anam ◽

Adel Al-Jumaily

Keyword(s):

Extreme Learning Machine ◽

Finger Movements ◽

Learning Machine

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