Xinjun Sheng
Overview
Explore the profile of Xinjun Sheng including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
89
Citations
418
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Chen C, Zhao J, Yu Y, Sheng X, Zhu X
IEEE Trans Neural Syst Rehabil Eng
. 2025 Mar;
PP.
PMID: 40030544
Objective: The application of electromyography (EMG) decomposition techniques in myoelectric control has gradually increased. However, most decomposition-based control schemes rely on machine learning, lacking interpretation of the biological mechanisms underlying...
2.
Meng J, Li S, Li G, Luo R, Sheng X, Zhu X
IEEE Trans Biomed Eng
. 2025 Mar;
PP.
PMID: 40030518
The brain switch improves the reliability of asynchronous brain-computer interface (aBCI) systems by switching the control state of the BCI system. Traditional brain switch research focuses on extracting advanced electroencephalography...
3.
Geng Z, Yang Z, Xu W, Guo W, Sheng X
Biomimetics (Basel)
. 2024 Oct;
9(10).
PMID: 39451835
Future humanoid robots will be widely deployed in our daily lives. Motion planning and control in an unstructured, confined, and human-centered environment utilizing dexterity and a cooperative ability of dual-arm...
4.
Ma S, Clarke A, Maksymenko K, Deslauriers-Gauthier S, Sheng X, Zhu X, et al.
IEEE Trans Neural Netw Learn Syst
. 2024 Aug;
PP.
PMID: 39141455
Numerical models of electromyography (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of...
5.
Xia M, Chen C, Sheng X, Ding H
IEEE Trans Neural Syst Rehabil Eng
. 2024 Aug;
32:2905-2913.
PMID: 39115987
Muscles generate varying levels of force by recruiting different numbers of motor units (MUs), and as the force increases, the number of recruited MUs gradually rises. However, current decoding methods...
6.
Meng J, Li S, Li G, Luo R, Sheng X, Zhu X
J Neural Eng
. 2024 Jul;
21(4).
PMID: 39029496
Brain switches provide a tangible solution to asynchronized brain-computer interface, which decodes user intention without a pre-programmed structure. However, most brain switches based on electroencephalography signals have high false positive...
7.
Li Y, Ma S, Zhao J, Li Q, Sheng X
IEEE Trans Biomed Eng
. 2024 Jul;
71(12):3370-3382.
PMID: 38963745
In vivo muscle architectural parameters can be calculated from the fiber tracts using magnetic resonance (MR) tractography. However, the reconstructed tracts may be unevenly distributed within the muscle volume and...
8.
Ma S, Mendez Guerra I, Caillet A, Zhao J, Clarke A, Maksymenko K, et al.
PLoS Comput Biol
. 2024 Jul;
20(7):e1012257.
PMID: 38959262
Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables...
9.
Xu Y, Yu Y, Zhao Z, Sheng X
IEEE Trans Neural Syst Rehabil Eng
. 2024 Feb;
32:974-982.
PMID: 38376978
Recent developments in dexterous myoelectric prosthetics have established a hardware base for human-machine interfaces. Although pattern recognition techniques have seen successful deployment in gesture classification, their applications remain largely confined...
10.
Xu Y, Yu Y, Zhao Z, Chen C, Sheng X
IEEE J Biomed Health Inform
. 2023 Aug;
27(11):5335-5344.
PMID: 37643108
Estimating cumulative spike train (CST) of motor units (MUs) from surface electromyography (sEMG) is essential for the effective control of neural interfaces. However, the limited accuracy of existing estimation methods...