KIEE
The Transactions of
the Korean Institute of Electrical Engineers
KIEE
Contact
Open Access
Monthly
ISSN : 1975-8359 (Print)
ISSN : 2287-4364 (Online)
http://www.tkiee.org/kiee
Mobile QR Code
The Transactions of the Korean Institute of Electrical Engineers
ISO Journal Title
Trans. Korean. Inst. Elect. Eng.
Main Menu
Main Menu
최근호
Current Issue
저널소개
About Journal
논문집
Journal Archive
편집위원회
Editorial Board
윤리강령
Ethics Code
논문투고안내
Instructions to Authors
연락처
Contact Info
논문투고·심사
Submission & Review
Journal Search
Home
Archive
2022-02
(Vol.71 No.2)
10.5370/KIEE.2022.71.2.443
Journal XML
XML
PDF
INFO
REF
References
1
M. Atzori, A. Gijsberts, C. Castellini, B. Caputo, A.M. Hager, S. Elsig, G. Giatsidis, F. Bassetto, H. Müller, 2014, Electromyography data for non-invasive naturally controlled robotic hand prostheses, Scientific Data, Vol. 1
2
A. Krasoulis, S. Vijayakumar, K. Nazarpour, Sept 2019, Effect of user practice on prosthetic finger control with an intuitive myoelectric decoder, Frontiers in Neuroscience
3
P. Weiner, J. Starke, F. Hundhausen, J. Beil, T. Asfour, October 2018, The KIT Prosthetic Hand: Design and Control, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, pp. 1-5
4
M. Atzori, M. Cognolato, H. Müller, 2016, Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands, Front Neurorobot
5
D. C. Oh, Y. U. Jo, 2021, Classification of Hand Gestures Based on Multi-channel EMG by Scale Average Wavelet Transform and Convolutional Neural Network, International Journal of Control, Automation and Systems, Vol. 19, No. 3, pp. 1443-1450
6
https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/bebionic-hand/
7
Omer Saad Alkhafaf, Mousa K Wali, Ali H Al-Timemy, 2020, Improved hand prostheses control for transradial amputees based on hybrid of voice recognition and electromyography, SAGE journals vol. 44, Vol. no. 7, No. pp. 509-517, pp. december 7
8
K. Gundogdu, S. Bayrakdar, I. Yucedag, 2018, Developing and modeling of voice control system for prosthetic robot arm in medical systems., no. 2, pp. 198-205
9
P. Samant, A. Ravinder, 2015, Real-time speech recognition system for prosthetic arm control, Int. J. Sensing, Computing & Control, Vol. 5, No. 1, pp. 39-46
10
M. Jafarzadeh, Y. Tadesse, 2020, End-to-End Learning of Speech 2D Feature-Trajectory for Prosthetic Hands, in 2020 Second International Conference on Transdisciplinary AI (TransAI), pp. 25-33
11
H. S. Jung, S. H. Yoon, N. S. Park, 2020, Speaker Recognition Using Convolutional Siamese Neural Networks, The Transactions of the korean Institute Electrical Engineers, Vol. 60, No. 1, pp. 164-169
12
J. H. Kim, S. P. Lee, 2021, Multi-modal Emotion Recognition using Speech Features and Text Embedding, The Transactions of the korean Institute Electrical Engineers, Vol. 70, No. 1, pp. 108-113
13
M. S. Kim, J. S. Moon, 2019, Speaker Verification Model Using Short-Time Fourier Transform and Recurrent Neural Network, Korea Institute of Information Security and Cryptology, Vol. 29, No. 6, pp. 1393-1401
14
D. H. Kim, W. K. Seong, H. K. Kim, 2015, Performance Comparison of Deep Feature Based Speaker Verification Systems, Korea Journal of Speech Science, Vol. 7, No. 4, pp. 9-16
15
S. Bunrit, T. Inkian, N. Kerdprasop, K. Kerdprasop, April 2019, Text-Independent Speaker Identifi- cation Using Deep Learning Model of Convolution Neural Network, International Journal of Machine Learning and Computing, Vol. 9, No. 2
16
Y. Yamanoi, Y. Ogiri, R. Kato, Jan 2020, EMG-based posture classification using a convolutional neural network for a myoelectric hand, Biomedical Signal Processing and Control, Vol. 55
17
P. Xia, J. Hu, Y. Peng, 2018, EMG-based estimation of limbmovement using deep learning with recurrent convolutionalneural networks, Artificial Organs, Vol. 42, No. 5, pp. e67–e77
18
S. Albawi, 2017, Understanding of a Convolutional Neural Network, ICET 2017, Vol. antalya
19
R. Ranjan, A. Thakur, 2019, Analysis of feature extraction techniques for speech recognition system, International Journal of Innovative Technology and Exploring Engineering, Vol. 8, No. 7c2, pp. 197-200