A Microcontroller Platform for the Rapid Prototyping of Functional Electrical Stimulation-Based Gait Neuroprostheses

被引:12
|
作者
de Melo, Paulo Luzio [1 ,2 ]
da Silva, Miguel Tavares [1 ]
Martins, Jorge [1 ]
Newman, Dava [2 ]
机构
[1] Univ Lisbon, Inst Super Tecn, Mech Engn, IDMEC, P-1049001 Lisbon, Portugal
[2] MIT, Man Vehicle Lab, Aeroastro Dept, Cambridge, MA 02139 USA
关键词
Functional electrical stimulation; Neuroprosthesis; Arduino microcontroller platform; Accelerometer; Inertial measurement unit; Gait; Force sensitive resistors; Closed-loop control; Drop foot; Rapid prototyping;
D O I
10.1111/aor.12400
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Functional electrical stimulation (FES) has been used over the last decades as a method to rehabilitate lost motor functions of individuals with spinal cord injury, multiple sclerosis, and post-stroke hemiparesis. Within this field, researchers in need of developing FES-based control solutions for specific disabilities often have to choose between either the acquisition and integration of high-performance industry-level systems, which are rather expensive and hardly portable, or develop custom-made portable solutions, which despite their lower cost, usually require expert-level electronic skills. Here, a flexible low-cost microcontroller-based platform for rapid prototyping of FES neuroprostheses is presented, designed for reduced execution complexity, development time, and production cost. For this reason, the Arduino open-source microcontroller platform was used, together with off-the-shelf components whenever possible. The developed system enables the rapid deployment of portable FES-based gait neuroprostheses, being flexible enough to allow simple open-loop strategies but also more complex closed-loop solutions. The system is based on a modular architecture that allows the development of optimized solutions depending on the desired FES applications, even though the design and testing of the platform were focused toward drop foot correction. The flexibility of the system was demonstrated using two algorithms targeting drop foot condition within different experimental setups. Successful bench testing of the device in healthy subjects demonstrated these neuroprosthesis platform capabilities to correct drop foot.
引用
收藏
页码:E56 / E66
页数:11
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