Abstract
Feedback control of movements by functional electrical stimulation (FES) can be useful for restoring motor function of paralyzed subjects. However, it has not been used practically. Some of possible reasons were considered to be in designing a feedback FES controller and its parameter determination, and nonlinear characteristics with large time delay in muscle response to electrical stimulation, which are different between subjects. This study focused on the hybrid controller that consists of artificial neural network (ANN) and fuzzy feedback controller. ANN was trained by feedback error learning (FEL) to realize a feedforward controller. Although FEL can realize feedforward FES controller, target movement patterns are limited to those similar to patterns used in the training. In this paper, FEL-FES controller was tested in learning both random and cyclic movements through computer simulation of knee joint angle control with 4 different training data sets: (1) sinusoidal patterns, (2) patterns generated by low pass filtered random values, (3) using both the sinusoidal and the LPF random patterns alternatively and (4) patterns that consisted of 3 random sinusoidal components. Trained ANNs were evaluated in feedforward control of sinusoidal and random angle patterns. Training with data set (1) caused delay in controlling random patterns, and training with data set (2) caused delay in controlling sinusoidal patterns. Training with data set (3) showed intermediate performance between those with data set (1) and (2). Training with data set (4) could control adequately both random and sinusoidal patterns. These results suggested that generating movement patterns using sinusoidal components would be effective for various movement control by FEL-FES controller.
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References
Handa, Y.: Current Topics in Clinical Functional Electri-cal Stimulation in Japan. J. Electromyogr. Kinesiol. 7(4), 269–274 (1997).
Lyons, G. M., Sinkjær, T., Burridge, J. H. and Wilcox, D. J.: A Review of Portable FES-Based Neural Orthoses for the Correction of Drop Foot. IEEE Trans. Neural Sys. Rehabil. Eng., 10(4), 260–279 (2002).
Hoshimiya, N., Naito, A., Yajima, M., Handa, Y.: A multi-channel FES system for the restoration of motor functions in high spinal cord injury patients: a respiration-controlled system for multijoint upper extremity. IEEE Trans. Biomed. Eng., 36(7), 754–760 (1989).
Watanabe, T., Iibuchi, K., Kurosawa, K. and Hoshimiya, N.: Method of Multichannel PID Control of 2-Degree of Freedom of Wrist Joint Movements by Functional Electrical Stimulation. Systems and Computers in Japan, 34(5), 25–36 (2003).
Kurosawa, K., Watanabe, T., Futami, R., Hoshimiya, N. and Handa, Y.: Development of a closed-loop FES system using 3-D magnetic position and orientation measurement system. J. Automatic Control, 12(1), 23–30 (2002).
Kurosawa K, Futami R, Watanabe T, Hoshimiya N.: Joint angle control by FES using a feedback error learning controller. IEEE Trans Neural Syst Rehabil Eng. 13(3), 359–371 (2005).
Watanabe, T., Kurosawa, K. and Yoshizawa, M.: An Effective Method of Applying Feedback Error Learning Scheme to Functional Electrical Stimulation Controller. IEICE Transactions on Information and Systems, E92-D(2), 342–345 (2009).
Watanabe, T. and Sugi, Y.: Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control., J. Robotics, 2010, 908132, https://doi.org/10.1155/2010/908132 (2010).
Watanabe, T and Fukushima K.: An approach to applying feedback error learning for functional electrical stimulation (FES) controller: Computer simulation tests of wrist joint control. Advances Artificial Neural Systems, 2010, 814702, https://doi.org/10.1155/2010/814702 (2010).
Watanabe, T., Fukushima, K.: A Study on Feedback Error Learning Controller for Functional Electrical Stimulation: Generation of Target Trajectories by Minimum Jerk Model. Artificial Organs, 35(3), 270–274 (2011).
Lynch, C.L., Popovic, M.R.: A comparison of closed-loop control algorithms forregulating electrically stimulated knee movements in individuals with spinal cord injury. IEEE Trans. Neural Syst. Rehabil. Eng., 20(4), 539–548 (2012).
Alibeji, N., Kirsch, N., Farrokhi, S., Sharma, N.: Further Results on Predictor-Based Control of Neuromuscular Elec-trical Stimulation. IEEE Trans. Neural Syst. Rehabil. Eng., 23(6), 1095–1105 (2015).
Oliveira, T.R., Costa, L.R., Catunda, J.M.Y., Pino, A.V., Barbosa, W., Souza, M.N.: Time-scaling based sliding mode control for Neuromuscular Electrical Stimulation under uncertain relative degrees. Med. Eng. Phys., 44, 53–62 (2017).
Acknowledgements
This work was supported in part by the Ministry of Education, Culture, Sports, Science and Technology of Japan under a Grant-in-Aid for Scientific Research (B).
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Watanabe, T., Akaike, N. (2019). A Computer Simulation Test of Feedback Error Learning-Based FES Controller for Controlling Random and Cyclic Movements. In: Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/3. Springer, Singapore. https://doi.org/10.1007/978-981-10-9023-3_10
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