|
|
Design and Optimization of Functional Neuromuscular Stimulation Applying Surface Array Electrode |
1 Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074,China
2 Department of Anatomy,Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030,China
3 Department of Rehabilitation Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030,China |
|
|
Abstract Surface array electrode (SAE) provides high performance, which improves the stimulation selectivity and controllability. The electrode design and stimulating waveform have a marked effect on the performance of functional neuromuscular stimulation (FNS). For motor rehabilitation of hand, the simplified forearm model with different layers was established in this paper, and finite element method (FEM) was used to simulate the distribution of electric fields within the forearm while a SAE with all large contacts was separated by small ones outputs direct current signals to achieve cathodic stimulation. Moreover, the activation function (AF) indicates the effect of applied electric field on the activity of the nerve axon, and then the ratio of the maximum to the multiplication of halfwidths of AF for the deep axon in the forearm was used to evaluate the stimulation selectivity. In order to achieve a perfect performance, the particle swarm optimization (PSO) algorithm was used to optimize the design of SAE. Results show that the optimal performance is achieved for SAE when the sizes of large square contacts and small ones are 9.80 mm×9.80 mm and 10.72 mm×10.72 mm, respectirely, while the maximum of performance index for simulation selectivity is 11 252.68 V/m4. In addition, different stimulation waveforms are investigated based on the timevarying maximum of AF for the deep axon in the forearm. Compared with other stimulation waveforms, the biphasic chargebalanced rectangular pulse produced a slightly larger maximum of AF, i.e. 3.448 V/m2, which has a positive effect on the activation of axons. The FEM simulations provide foundation for the design of SAE and clinical application.
|
|
|
|
|
[1]王欣, 王宁华. 功能性电刺激在改善运动功能方面的作用 [J]. 中国康复理论与实践, 2009, 15(3): 238-241.
[2]黄涛, 徐琦, 何际平,等. 采用表面阵列电极的人体前臂电刺激仿真研究 [J].中国生物医学工程学报, 2012, 31(3): 416-421
[3]Kuhn A, Keller T, Micera S. Array electrode design for transcutaneous electrical stimulation: A simulation study [J]. Medical Engineering & Physics, 2009, 31(8): 945-951.
[4]Kuhn A, Keller T, Lawrence M, et al. A model for transcutaneous current stimulation: simulations and experiments [J]. Medical and Biological Engineering and Computing, 2009, 47(3): 279-289.
[5]Warren M, Grill J, Thomas M. Stimulus waveforms for selective neural stimulation [J]. IEEE Engineering in Medical and Biology, 1995, 14: 375-385.
[6]Dewarrat F, Falco L, Cadduff A, et al. Optimization of skin impedance sensor design with finite element simulations [C] //Proceeding of the COMOSL Conference. Hannover: COMSOL AB , 2008:903-905.
[7]Filipovic N, Nedeljkovic M, Peulic A. Finite element modeling of a transient functional electrical stimulation [J]. Journal of the Serbian Society for Computational Mechanics, 2007, 1(1): 154-163.
[8]Kajimoto H, Kawakami N, Tachi N. Optimal design method for selective nerve stimulation [J]. Electronics and Communication in Japan, 2004, 87(9): 62-72.
[9]McNeal D. Analysis of a model for excitation of myelinated nerve [J]. IEEE Trans Biomed Eng , 1976, 23(4): 329-337.
[10]蒲莉娜. 磁刺激脑内感应电场聚焦性的仿真研究与线圈优化设计 [D]. 北京:北京协和医学院, 2009.
[11]侯文生, 章毅, 郑小林, 等, BISWAJIT Das. 基于有限元法的硬脑膜外视皮层电刺激仿真研究 [J]. 中国生物医学工程学报, 2010, 29(4): 557-563.
[12]汪定伟,王俊伟,王洪峰,等. 智能优化算法 [M].北京:高等教育出版社, 2007.
[13]焦永昌,杨科,陈胜兵,等. 粒子群优化算法用于阵列天线方向图综合设计 [J]. 电波科学学报, 2006, 21(1): 16-20.
[14]章毅. 经脑硬膜对视皮层电刺激的数字仿真 [D]. 重庆: 重庆大学, 2010. |
|
|
|