electromyogram (EMG) Archives - Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

June 4, 2021

FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography

Author(s)3: Elahe Rahimian, Soheil Zabihi, Amir Asif, Dario Farina, Seyed Farokh Atashzar, Arash Mohammadi

FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography https://www.embs.org/tnsre/wp-content/themes/movedo/images/empty/thumbnail.jpg 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) //www.embs.org/tnsre/wp-content/uploads/sites/15/2022/06/ieee-tnsre-logo2x.png June 4, 2021 March 4, 2022

This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their widespread applications in human-machine interfaces. DNNs have been recently used for detecting the intended hand…

April 12, 2018

Simultaneous Recognition and Assessment of Post-Stroke Hemiparetic Gait by Fusing Kinematic, Kinetic, and Electrophysiological Data

Author(s)3: Chengkun Cui, Gui-Bin Bian, Zeng-Guang Hou, Jun Zhao, Guodong Su, Hao Zhou, Liang Peng, Weiqun Wang

Simultaneous Recognition and Assessment of Post-Stroke Hemiparetic Gait by Fusing Kinematic, Kinetic, and Electrophysiological Data https://www.embs.org/tnsre/wp-content/uploads/sites/15/2018/04/Simultaneous-Recognition.png 780 890 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) //www.embs.org/tnsre/wp-content/uploads/sites/15/2022/06/ieee-tnsre-logo2x.png April 12, 2018 March 4, 2022

Gait analysis for the patients with lower limb motor dysfunction is a useful tool in assisting clinicians for diagnosis, assessment, and rehabilitation strategy making. Implementing accurate automatic gait analysis…

September 8, 2016

Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces

Author(s)3: Ki-Hee Park, Heung-Il Suk, Seong-Whan Lee

Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces https://www.embs.org/tnsre/wp-content/uploads/sites/15/2016/09/lee.jpg 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) //www.embs.org/tnsre/wp-content/uploads/sites/15/2022/06/ieee-tnsre-logo2x.png September 8, 2016 March 4, 2022

In this decade, myoelectric interfaces based on pattern recognition have gained considerable attention thanks to their naturalness enabling human intentions to be conveyed to and in control of a machine.…

January 6, 2015

Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed With Experimental and Simulated Data

Author(s)3: Chenyun Dai, Yejin Li, Anita Christie, Paolo Bonato, Kevin C. McGill, Edward A. Clancy

Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed With Experimental and Simulated Data https://www.embs.org/tnsre/wp-content/uploads/sites/15/2015/01/clancy-feat.jpg 556 235 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) Transactions on Neural Systems and Rehabilitation Engineering (TNSRE) //www.embs.org/tnsre/wp-content/uploads/sites/15/2022/06/ieee-tnsre-logo2x.png January 6, 2015 March 4, 2022

Abstract The reliability of clinical and scientific information provided by algorithms that automatically decompose the electromyogram (EMG) depends on the algorithms’ accuracies. We used experimental and simulated data to assess…