Zobrazeno 1 - 10
of 805
pro vyhledávání: '"gait phase"'
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-16 (2024)
Abstract Gait phase prediction is important in controlling assistive robotic devices such as exoskeletons, where the control unit must differentiate between gait phases to provide the necessary assistance when the user is wearing the exoskeleton. To
Externí odkaz:
https://doaj.org/article/0e7085a1f6cc4726b430a2b84f34d970
Autor:
Hui Chen, Xiangyang Wang, Yang Xiao, Beixian Wu, Zhuo Wang, Yao Liu, Peiyi Wang, Chunjie Chen, Xinyu Wu
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionWearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data
Externí odkaz:
https://doaj.org/article/3a9b6675b2934495b8b7141e245fc919
Autor:
Xinyao Hu, Qingsong Duan, Junpeng Tang, Gengshu Chen, Zhong Zhao, Zhenglong Sun, Chao Chen, Xingda Qu
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 12, Pp 84-96 (2024)
This paper presents a novel low-cost and fully-portable instrumented shoe system for gait phase detection. The instrumented shoe consists of 174 independent sensing units constructed based on an off-the-shelf force-sensitive film known as the Velosta
Externí odkaz:
https://doaj.org/article/22fd92bf6ec34e9882e53c622f3bdb57
Autor:
Ji Su Park, Choong Hyun Kim
Publikováno v:
Sensors, Vol 24, Iss 19, p 6318 (2024)
Existing studies on gait phase estimation generally involve walking experiments using inertial measurement units under limited walking conditions (WCs). In this study, a gait phase estimation algorithm is proposed that uses data from force sensing re
Externí odkaz:
https://doaj.org/article/27a7aa39db03405985c94283257ff4e2
Autor:
Partha Sarati Das, Daniella Skaf, Lina Rose, Fatemeh Motaghedi, Tricia Breen Carmichael, Simon Rondeau-Gagné, Mohammed Jalal Ahamed
Publikováno v:
Sensors, Vol 24, Iss 9, p 2944 (2024)
Gait phase monitoring wearable sensors play a crucial role in assessing both health and athletic performance, offering valuable insights into an individual’s gait pattern. In this study, we introduced a simple and cost-effective capacitive gait sen
Externí odkaz:
https://doaj.org/article/eb5ce3031ac74d0980d80c47050b6283
Publikováno v:
Sensors, Vol 24, Iss 8, p 2390 (2024)
This work presents a real-time gait phase estimator using thigh- and shank-mounted inertial measurement units (IMUs). A multi-rate convolutional neural network (CNN) was trained to estimate gait phase for a dataset of 16 participants walking on an in
Externí odkaz:
https://doaj.org/article/e81c9eb137294d18885e09b16cf69c46
Publikováno v:
Pakistan Journal of Engineering & Technology, Vol 6, Iss 3 (2023)
Human knee plays a vital role in performing day-to-day activities. For healthy person it is easy to perform locomotion activities but for people with transfemoral amputation, it is very difficult task. To overcome this issue prosthetic knees are deve
Externí odkaz:
https://doaj.org/article/81907dc1742446a6bfcda0d0ff99fc23
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2448-2456 (2023)
Developing personalized gait phase prediction models is difficult because acquiring accurate gait phases requires expensive experiments. This problem can be addressed via semi-supervised domain adaptation (DA), which minimizes the discrepancy between
Externí odkaz:
https://doaj.org/article/8a917dc4a0ec4715994eaa501c0d6f8b
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 628-635 (2023)
Human gait phase estimation has been studied in the field of robotics due to its importance in controlling wearable devices (e.g., robotic prostheses or exoskeletons) in a synchronized manner with the user. Researchers have attempted to estimate the
Externí odkaz:
https://doaj.org/article/5e20208a88d94270a414c653a6a71eb5
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 1119-1127 (2023)
Many patients experience motor and sensory impairments after stroke, leading to gait disturbances. Analysis of muscle modulation mode during walking can provide evidence for neurological changes after stroke, while how stroke affects individual muscl
Externí odkaz:
https://doaj.org/article/bbf4bc182cbd4c278d07a661022c8df2