Deep learning with convolutional neural networks applied to electromyography data: a resource for the classification of movements for prosthetic hands

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Items 101–200 of 681

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2. Sliding-Window Normalization to Improve the Performance of Machine-Learning Models for Real-Time Motion Prediction Using Electromyography
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3. Deep Learning Movement Intent Decoders Trained With Dataset Aggregation for Prosthetic Limb Control
   Henrique Dantas, David J. Warren, Suzanne Wendelken, Tyler S. Davis, Gregory A. Clark, V.J. Mathews · 2019 · IEEE Transactions on Biomedical Engineering
4. Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method
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5. MFFNet: Multi-dimensional Feature Fusion Network based on attention mechanism for sEMG analysis to detect muscle fatigue
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6. Decoding HD-EMG Signals for Myoelectric Control - How Small Can the Analysis Window Size be?
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7. Intuitive Human-Robot-Environment Interaction with EMG Signals: A Review
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8. A deep Kalman filter network for hand kinematics estimation using sEMG
   Tianzhe Bao, Yihui Zhao, Syed Ali Raza Zaidi, Sheng Quan Xie, Pengfei Yang, Zhiqiang Zhang · 2021 · Pattern Recognition Letters
9. E2CNN: An Efficient Concatenated CNN for Classification of Surface EMG Extracted From Upper Limb
   Muhammad Farrukh Qureshi, Zohaib Mushtaq, Muhammad Zia‐ur‐Rehman, Ernest Nlandu Kamavuako · 2023 · IEEE Sensors Journal
10. Surface electromyography feature extraction via convolutional neural network
    Hongfeng Chen, Yue Zhang, Gongfa Li, Yinfeng Fang, Honghai Liu · 2019 · International Journal of Machine Learning and Cybernetics
11. Deep learning approach to control of prosthetic hands with electromyography signals
    Mohsen Jafarzadeh, Daniel Curtiss Hussey, Yonas T. Tadesse · 2019 · International Symposium on Measurement and Control in Robotics (ISMCR)
12. Recurrent Convolutional Neural Networks as an Approach to Position-Aware Myoelectric Prosthesis Control
    Heather E. Williams, Ahmed W. Shehata, Michael R. W. Dawson, Erik Scheme, Jacqueline S. Hebert, Patrick M. Pilarski · 2022 · IEEE Transactions on Biomedical Engineering
13. MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning
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14. A database of high-density surface electromyogram signals comprising 65 isometric hand gestures
    Nebojša Malešević, Alexander E. Olsson, Paulina Sager, Elin Andersson, Christian Cipriani, Marco Controzzi, Anders Björkman, Christian Antfolk · 2021 · Scientific Data
15. Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface
    Diu Khue Luu, Anh Tuan Nguyen, Ming Xin Jiang, Markus W. Drealan, Jian Xu, Tong Wu, Wing-kin Tam, Wenfeng Zhao, Brian Z. H. Lim, Cynthia K. Overstreet et al. · 2022 · IEEE Transactions on Biomedical Engineering
16. Semi-Supervised Learning for Surface EMG-based Gesture Recognition
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17. Hand Gesture Recognition Based on Deep Learning Method
    Kai Xing, Zhen Ding, Shuai Jiang, Xueyan Ma, Kai Yang, Chifu Yang, Xiang Li, Feng Jiang · 2018 · IEEE International Conference on Data Science in Cyberspace
18. A portable, self-contained neuroprosthetic hand with deep learning-based finger control
    Anh Tuan Nguyen, Markus W. Drealan, Diu Khue Luu, Ming Xin Jiang, Jian Xu, Jonathan Cheng, Qi Zhao, Edward W. Keefer, Zhi Yang · 2021 · Journal of Neural Engineering
19. Classification of sEMG signals of hand gestures based on energy features
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20. A Novel SE-CNN Attention Architecture for sEMG-Based Hand Gesture Recognition
    Zhengyuan Xu, Junxiao Yu, Wentao Xiang, Songsheng Zhu, Mubashir Hussain, Bin Liu, Jianqing Li · 2022 · Computer Modeling in Engineering & Sciences
21. Surface EMG-Based Intersession/Intersubject Gesture Recognition by Leveraging Lightweight All-ConvNet and Transfer Learning
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22. Sensor Fusion for Myoelectric Control Based on Deep Learning With Recurrent Convolutional Neural Networks
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23. Inferring Static Hand Poses from a Low-Cost Non-Intrusive sEMG Sensor
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24. Bio-signal based motion control system using deep learning models: a deep learning approach for motion classification using EEG and EMG signal fusion
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25. Continuous Semi-autonomous Prosthesis Control Using a Depth Sensor on the Hand
    Miguel Nobre Castro, Strahinja S. Dosen · 2022 · Frontiers in Neurorobotics
26. Research on sEMG-Based Gesture Recognition by Dual-View Deep Learning
    Yan Zhang, Fan Yang, Qi Fan, Anjie Yang, Xuan Li · 2022 · IEEE Access
27. Ground Reaction Force and Moment Estimation through EMG Sensing Using Long Short-Term Memory Network during Posture Coordination
    Sei-ichi Sakamoto, Yonatan Hutabarat, Dai Owaki, Mitsuhiro Hayashibe · 2023 · Cyborg and Bionic Systems
28. Advanced Energy Kernel-Based Feature Extraction Scheme for Improved EMG-PR-Based Prosthesis Control Against Force Variation
    Sidharth Pancholi, Amit M. Joshi · 2020 · IEEE Transactions on Cybernetics
29. Deep Learning Algorithms-based Object Detection and Localization Revisited
    Safa Riyadh Waheed, Norhaida Mohd Suaib, Mohd Shafry Mohd Rahim, Myasar Mundher Adnan, Ali Aqeel Salim Al-Shammari · 2021 · Journal of Physics Conference Series
30. Improving sEMG-based motion intention recognition for upper-limb amputees using transfer learning
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31. Spectral Image-Based Multiday Surface Electromyography Classification of Hand Motions Using CNN for Human–Computer Interaction
    Muhammad Farrukh Qureshi, Zohaib Mushtaq, Muhammad Zia‐ur‐Rehman, Ernest Nlandu Kamavuako · 2022 · IEEE Sensors Journal
32. EMG-Based Estimation of Lower Limb Joint Angles and Moments Using Long Short-Term Memory Network
    Minh Tat Nhat Truong, Amged Elsheikh Abdelgadir Ali, Dai Owaki, Mitsuhiro Hayashibe · 2023 · Sensors
33. XceptionTime: A Novel Deep Architecture based on Depthwise Separable Convolutions for Hand Gesture Classification
    Elahe Rahimian, Soheil Zabihi, S. Farokh Atashzar, Amir A. Asif, Arash Mohammadi · 2019 · arXiv (Cornell University)
34. A Multiscale Feature Extraction Network Based on Channel-Spatial Attention for Electromyographic Signal Classification
    Biao Sun, Beida Song, Jiajun Lv, Peiyin Chen, Xinlin Sun, Chao Ma, Zhongke Gao · 2022 · IEEE Transactions on Cognitive and Developmental Systems
35. Hand gesture recognition using smooth wavelet packet transformation and hybrid CNN based on surface EMG and accelerometer signal
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36. Simple and Fast Compensation of sEMG Interface Rotation for Robust Hand Motion Recognition
    Minjae Kim, Keehoon Kim, Wan Kyun Chung · 2018 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
37. EMG-based posture classification using a convolutional neural network for a myoelectric hand
    Yusuke Yamanoi, Yosuke Ogiri, Ryu Kato · 2019 · Biomedical Signal Processing and Control
38. Hilbert sEMG data scanning for hand gesture recognition based on deep learning
    Panagiotis Tsinganos, Bruno Cornelis, Jan P. Cornelis, Bart Jansen, Athanassios N. Skodras · 2020 · Neural Computing and Applications
39. Temporal Dilation of Deep LSTM for Agile Decoding of sEMG: Application in Prediction of Upper-Limb Motor Intention in NeuroRobotics
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40. Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach
    Jungpil Shin, Abu Saleh Musa Miah, Sota Konnai, Itsuki Takahashi, Koki Hirooka · 2024 · Scientific Reports
41. Electromyography-Based, Robust Hand Motion Classification Employing Temporal Multi-Channel Vision Transformers
    Ricardo Vilela de Godoy, Gustavo J. G. Lahr, Anany Dwivedi, Tharik J. S. Reis, Paulo H. Polegato, Marcelo Becker, Glauco A. P. Caurin, Minas V. Liarokapis · 2022 · IEEE Robotics and Automation Letters
42. Online Adaptive Prediction of Human Motion Intention Based on sEMG
    Zhen Ding, Chifu Yang, Zhipeng Wang, Xunfeng Yin, Feng Jiang · 2021 · Sensors
43. Mental Stress Detection Using a Wearable In-Ear Plethysmography
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44. Deep learning for waveform identification of resting needle electromyography signals
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45. Leveraging ANN and LDA Classifiers for Characterizing Different Hand Movements Using EMG Signals
    Bushra A. Saeed, Muhammad Zia-ur-Rehman, Syed Omer Gilani, Faisal Mohd Amin, Asim Waris, Mohsin Jamil, Muhammad Shafique · 2020 · Arabian Journal for Science and Engineering
46. Deep learning systems for automatic diagnosis of infant cry signals
    Salim Lahmiri, Chakib Tadj, Christian S. Gargour, Stelios D. Bekiros · 2021 · Chaos Solitons & Fractals
47. Optimal Feature Selection for EMG-Based Finger Force Estimation Using LightGBM Model
    Yuhang Ye, Chao Liu, Nabil Zemiti, Chenguang Yang · 2019 · IEEE RO-MAN
48. Linear and Non-linear Dimensionality-Reduction Techniques on Full Hand Kinematics
    Alexandra A. Portnova-Fahreeva, Fabio Rizzoglio, Ilana Nisky, Maura Casadio, Ferdinando A. Mussa-Ivaldi, Eric Rombokas · 2020 · Frontiers in Bioengineering and Biotechnology
49. Surgically Implanted Electrodes Enable Real-Time Finger and Grasp Pattern Recognition for Prosthetic Hands
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50. Transfer learning in hand movement intention detection based on surface electromyography signals
    Rahil Soroushmojdehi, Sina Javadzadeh, Alessandra Pedrocchi, Marta Gandolla · 2022 · Frontiers in Neuroscience
51. Exploring Arm Posture and Temporal Variability in Myoelectric Hand Gesture Recognition
    Bojan Milosevic, Elisabetta Farella, Simone Benatti · 2018 · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)
52. A Transformer-Based Gesture Prediction Model via sEMG Sensor for Human–Robot Interaction
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53. Compression of EMG Signals Using Deep Convolutional Autoencoders
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54. LST-EMG-Net: Long short-term transformer feature fusion network for sEMG gesture recognition
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55. Deep Learning for Enhanced Prosthetic Control: Real-Time Motor Intent Decoding for Simultaneous Control of Artificial Limbs
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56. Hand Gesture Recognition Across Various Limb Positions Using a Multimodal Sensing System Based on Self-Adaptive Data-Fusion and Convolutional Neural Networks (CNNs)
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57. Grasp Classification With Weft Knit Data Glove Using a Convolutional Neural Network
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58. Investigation of Different Approaches to Real-Time Control of Prosthetic Hands With Electromyography Signals
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59. Convolutional Neural Network for Hand Gesture Recognition using 8 different EMG Signals
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60. Semg-Based Hand Gesture Recognition Via Dilated Convolutional Neural Networks
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61. Deep Learning Based Surface EMG Hand Gesture Classification for Low-Cost Myoelectric Prosthetic Hand
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62. Comparing subject-to-subject transfer learning methods in surface electromyogram-based motion recognition with shallow and deep classifiers
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63. Lower limb motion recognition based on surface electromyography
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64. Obstructive sleep apnea event prediction using recurrence plots and convolutional neural networks (RP-CNNs) from polysomnographic signals
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65. Multi-View Fusion Network-Based Gesture Recognition Using sEMG Data
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66. NeuroCARE: A generic neuromorphic edge computing framework for healthcare applications
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67. A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition
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68. Classification of Hand Gestures Based on Multi-channel EMG by Scale Average Wavelet Transform and Convolutional Neural Network
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69. Hybrid DeepGCL model for cyber-attacks detection on cyber-physical systems
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70. Improving Robotic Hand Prosthesis Control With Eye Tracking and Computer Vision: A Multimodal Approach Based on the Visuomotor Behavior of Grasping
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71. LSTM-MSA: A Novel Deep Learning Model With Dual-Stage Attention Mechanisms Forearm EMG-Based Hand Gesture Recognition
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73. Conditional GAN based augmentation for predictive modeling of respiratory signals
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76. Pattern Classification of Hand Movements using Time Domain Features of Electromyography
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77. An Extensive Study and Comparison of the Various Approaches to Object Detection using Deep Learning
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78. Hand gestures recognition from surface electromyogram signal based on self-organizing mapping and radial basis function network
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79. Myoelectric prosthesis hand grasp control following targeted muscle reinnervation in individuals with transradial amputation
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80. Comprehensive Review of Feature Extraction Techniques for sEMG Signal Classification: From Handcrafted Features to Deep Learning Approaches
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81. Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction
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82. Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition
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83. A Recurrent Neural Network for Hand Gesture Recognition based on Accelerometer Data
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84. Hand Gesture Recognition Based on sEMG Signal and Convolutional Neural Network
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85. Decoding muscle force from individual motor unit activities using a twitch force model and hybrid neural networks
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86. Deep Heterogeneous Dilation of LSTM for Transient-Phase Gesture Prediction Through High-Density Electromyography: Towards Application in Neurorobotics
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87. Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks
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88. Stable Electromyographic Sequence Prediction During Movement Transitions using Temporal Convolutional Networks
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89. The Impact of Feature Extraction on Classification Accuracy Examined by Employing a Signal Transformer to Classify Hand Gestures Using Surface Electromyography Signals
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90. Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition
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91. Recurrent Neural Network for electromyographic gesture recognition in transhumeral amputees
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92. Real-Time Analysis of Hand Gesture Recognition with Temporal Convolutional Networks
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93. sEMG-Based Gesture Recognition With Embedded Virtual Hand Poses and Adversarial Learning
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94. Deep neural network for EMG signal classification of wrist position: Preliminary results
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95. Development of Distributed Control System for Vision-Based Myoelectric Prosthetic Hand
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96. Surface EMG-Based Hand Gesture Recognition via Hybrid and Dilated Deep Neural Network Architectures for Neurorobotic Prostheses
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98. Vision-Based Assistance for Myoelectric Hand Control
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99. Improve Inter-day Hand Gesture Recognition Via Convolutional Neural Network-based Feature Fusion
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