Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Xinxing Chen"'
Autor:
Ruimin Peng, Zhenbang Du, Changming Zhao, Jingwei Luo, Wenzhong Liu, Xinxing Chen, Dongrui Wu
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 831-839 (2024)
Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually r
Externí odkaz:
https://doaj.org/article/39b83de23b964f989a967fe6a65261cb
Publikováno v:
地震科学进展, Vol 53, Iss 4, Pp 159-164 (2023)
This paper summed up the interference factors of Quanzhou seismic station g-phone gravimeter observation data. It is considered that the change of working state and the influence of meteorological factors are the main interference factors. The change
Externí odkaz:
https://doaj.org/article/deb48f2fe0da46d0b69a902e29ce9101
Autor:
Jingfeng Xiong, Chuheng Chen, Yuanwen Zhang, Xinxing Chen, Yuepeng Qian, Yuquan Leng, Chenglong Fu
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4591-4600 (2023)
Prediction of foot placement presents great potential in better assisting the walking of people with lower-limb disability in daily terrains. Previous researches mainly focus on foot placement prediction in level ground walking, however these methods
Externí odkaz:
https://doaj.org/article/867e5a0abbab4d1f86de5a946b38faeb
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 3687-3698 (2023)
Grasp intention recognition plays a crucial role in controlling assistive robots to aid older people and individuals with limited mobility in restoring arm and hand function. Among the various modalities used for intention recognition, the eye-gaze m
Externí odkaz:
https://doaj.org/article/919f6ec882154429ba361c3a259a18ca
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 1350-1360 (2022)
Powered lower-limb prostheses with vision sensors are expected to restore amputees’ mobility in various environments with supervised learning-based environmental recognition. Due to the sim-to-real gap, such as real-world unstructured terrains and
Externí odkaz:
https://doaj.org/article/f89e0d66f3114b8b9b1cc4902f735636
Publikováno v:
Journal of Orthopaedic Surgery and Research, Vol 16, Iss 1, Pp 1-9 (2021)
Abstract Objective The present meta-analysis was conducted to evaluate the efficacy and safety of the application of tranexamic acid (TXA) in patients undergoing high tibial osteotomy (HTO). Methods PubMed (MEDLINE), EMBASE, and Cochrane Library were
Externí odkaz:
https://doaj.org/article/56f847be5ae74afa969a14d01ec19d44
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
Fuzzy inference systems have been widely applied in robotic control. Previous studies proposed various methods to tune the fuzzy rules and the parameters of the membership functions (MFs). Training the systems with only supervised learning requires a
Externí odkaz:
https://doaj.org/article/6af34df0a7274715a9dea3ff565d139e
Publikováno v:
Energies, Vol 15, Iss 23, p 9196 (2022)
Building-integrated photovoltaic (BIPV) façades are a promising technique for improving building energy performance. This study develops energy simulation models of different photovoltaic-integrated shading devices (PVSDs) in single-story and multi-
Externí odkaz:
https://doaj.org/article/29cc8323b86c4fd7ac0eabe39c6d27a8
Publikováno v:
Journal of Orthopaedic Surgery and Research, Vol 16, Iss 1, Pp 1-3 (2021)
Externí odkaz:
https://doaj.org/article/f6587c61faa641ca8d345df6ae716c44
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 17 (2020)
Safe lane changing of the dynamic industrial park and port scenarios with autonomous trucks involves the problem of planning an effective and smooth trajectory. To solve this problem, we propose a new trajectory planning method based on the Dijkstra
Externí odkaz:
https://doaj.org/article/31c21fac3bac4cb080c22df9ff01f2b9