An Artificial Neural System for Closed Loop Control of Locomotion Produced via Neuromuscular Electrical Stimulation

1995 ◽  
Vol 19 (3) ◽  
pp. 231-237 ◽  
Author(s):  
Francisco Sepulveda ◽  
Alberto Cliquet
2005 ◽  
Vol 17 (01) ◽  
pp. 19-26 ◽  
Author(s):  
CHENG-LIANG LIU ◽  
CHUNG-HUANG YU ◽  
SHIH-CHING CHEN ◽  
CHANG-HUNG CHEN

Functional electrical stimulation (FES) is a method for restoring the functional movements of paraplegic or patients with spinal cord injuries. However, the selection of parameters that control the restoration of standing up and sitting functions has not been extensively investigated. This work provides a method for choosing the four main items involved in evaluating the strategies for sit-stand-sit movements with the aid of a modified walker. The control method uses the arm-supported force and the angles of the legs as feedback signals to change the intensity of the electrical stimulation of the leg muscles. The control parameters, Ki and Kp, are vary for different control strategies. Four items are collected through questionnaires and used for evaluation. They are the maximum reactions of the two hands, the average reaction of the two hands, largest absolute angular velocity of the knee joints, and the sit-stand-sit duration time. The experimental data are normalized to facilitate comparison. Weighting factors are obtained and analyzed from questionnaires answered by experts and are added to evaluation process for manipulation. The results show that the best strategy is the closed-loop control with parameters Ki=0.5 and Kp=0.


Author(s):  
Yuu HASEGAWA ◽  
Tomoya KITAMURA ◽  
Hiroto MIZOGUCHI ◽  
Naoto MIZUKAMI ◽  
Sho SAKAINO ◽  
...  

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
John Ciancibello ◽  
Kevin King ◽  
Milad Alizadeh Meghrazi ◽  
Subash Padmanaban ◽  
Todd Levy ◽  
...  

Abstract Background Transcutaneous neuromuscular electrical stimulation is routinely used in physical rehabilitation and more recently in brain-computer interface applications for restoring movement in paralyzed limbs. Due to variable muscle responses to repeated or sustained stimulation, grasp force levels can change significantly over time. Here we develop and assess closed-loop methods to regulate individual finger forces to facilitate functional movement. We combined this approach with custom textile-based electrodes to form a light-weight, wearable device and evaluated in paralyzed study participants. Methods A textile-based electrode sleeve was developed by the study team and Myant, Corp. (Toronto, ON, Canada) and evaluated in a study involving three able-body participants and two participants with quadriplegia. A feedforward-feedback control structure was designed and implemented to accurately maintain finger force levels in a quadriplegic study participant. Results Individual finger flexion and extension movements, along with functional grasping, were evoked during neuromuscular electrical stimulation. Closed-loop control methods allowed accurate steady state performance (< 15% error) with a settling time of 0.67 s (SD = 0.42 s) for individual finger contact force in a participant with quadriplegia. Conclusions Textile-based electrodes were identified to be a feasible alternative to conventional electrodes and facilitated individual finger movement and functional grasping. Furthermore, closed-loop methods demonstrated accurate control of individual finger flexion force. This approach may be a viable solution for enabling grasp force regulation in quadriplegia. Trial registration NCT, NCT03385005. Registered Dec. 28, 2017


Author(s):  
S. Thiery ◽  
M. Zein El Abdine ◽  
J. Heger ◽  
N. Ben Khalifa

AbstractA strategy to adjust the product geometry autonomously through an online control of the manufacturing process in incremental sheet forming with active medium is presented. An axial force sensor and a laser distance sensor are integrated into the process setup to measure the forming force and the product height, respectively. Experiments are conducted to estimate the bulging behavior for different pre-determined tool paths. An artificial neural network is consequently trained based on the experimental data to continuously predict the pressure levels required to control the final product height. The predicted pressure is part of a closed-loop control to improve the geometrical accuracy of formed parts. Finally, experiments were conducted to verify the results, where truncated cones with different dimensions were formed with and without the closed-loop control. The results indicate that this strategy enhances the geometrical accuracy of the parts and can potentially be expanded to be implemented for different types of material and geometries.


PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e105389 ◽  
Author(s):  
Feng Cao ◽  
Chao Zhang ◽  
Tat Thang Vo Doan ◽  
Yao Li ◽  
Daniyal Haider Sangi ◽  
...  

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