electromyogram (EMG)

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 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

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…

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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 780 890 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

        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…

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Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces

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 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

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.…

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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 556 235 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

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…

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TNSRE serves the community of biomedical engineers and clinical researchers who work at the intersection of neuroscience and physical medicine. We publish novel approaches and technologies for better understanding neural systems, human movement, and the relationships between them, with a focus on assistive devices that improve life for patients, for practicing clinicians, and for everyday use.

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