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Embedded Brain Machine Interface based on motor imagery paradigm to control prosthetic hand

机译：基于运动图像范例的嵌入式脑机接口来控制假手

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摘要

Brain Machine Interfaces (BMI) have been developed as an alternative way to decode brain signals into control commands and communication devices. A typical BMI uses a computer to process EEG signals; however, current embedded PCs have enough computational resources for fully embedded BMI systems. In this work, the performance of the Odroid-xu4 embedded PC is evaluated as a processing and control device for BMI based on a 2-class motor imagery paradigm. Results show the best accuracy (82.1%) using SVM classifier and minimal processing times (0.11s) on the embedded device, which allows the development of a portable, low cost and trustworthy system.

机译：脑机接口（BMI）已开发为将脑信号解码为控制命令和通信设备的替代方法。典型的BMI使用计算机处理EEG信号。但是，当前的嵌入式PC具有足够的计算资源用于完全嵌入式的BMI系统。在这项工作中，基于2类运动图像范例，对Odroid-xu4嵌入式PC的性能作为BMI的处理和控制设备进行了评估。结果显示，在嵌入式设备上使用SVM分类器时，最高的准确性（82.1％）和最少的处理时间（0.11s），这使得开发便携式，低成本和可信赖的系统成为可能。

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来源
《Proceedings of the 2016 IEEE ANDESCON》|2016年|1-4|共4页
会议地点 Arequipa(PE)
作者
Kevin Acuña Condori; Erick Carranza Urquizo; David Achanccaray Diaz;
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作者单位

Grupo de Investigatión en Robótica Aplicada y Biomecánica (GIRAB), Pontificia Universidad Catolica del Perú, Lima, Perú;

Grupo de Investigatión en Robótica Aplicada y Biomecánica (GIRAB), Pontificia Universidad Catolica del Perú, Lima, Perú;

Grupo de Investigatión en Robótica Aplicada y Biomecánica (GIRAB), Pontificia Universidad Catolica del Perú, Lima, Perú;

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原文格式 PDF
正文语种 eng
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关键词
Support vector machines; Electroencephalography; Embedded systems; Linux; Manipulators; Wavelet transforms;

机译：支持向量机；脑电图；嵌入式系统； Linux；操纵器；小波变换;

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1. PRINCIPLES OF MOTOR RECOVERY IN POST-STROKE PATIENTS USING HAND EXOSKELETON CONTROLLED BY THE BRAIN-COMPUTER INTERFACE BASED ON MOTOR IMAGERY [J] . Frolov A. A., Husek D., Biryukova E. V., Neural Network World . 2017,第1期

机译：基于脑成像的脑机接口控制的手外骨骼在卒中后患者中的电机恢复原理
2. Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial [J] . Alexander A. Frolov, Olesya Mokienko, Roman Lyukmanov, Frontiers in Neuroscience . 2017,第6期

机译：基于基于运动图像的脑机接口（BCI）控制的手外骨骼的中风后康复训练：一项随机对照的多中心试验
3. Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain-Machine Interface Control [J] . Barios Juan A., Ezquerro Santiago, Bertomeu-Motos Arturo, International Journal of Neural Systems . 2019,第5期

机译：基于电机图像的脑机接口控制过程中慢速皮质节奏的同步
4. Embedded Brain Machine Interface based on motor imagery paradigm to control prosthetic hand [C] . Kevin Acu?a Condori, Erick Carranza Urquizo, David Achanccaray Diaz IEEE ANDESCON Conference . 2016

机译：基于电机图像范例的嵌入式脑机接口控制假肢手
5. A Sensorimotor Rhythm (SMR)-Based Brain-Computer Interface (BCI) Controlled Functional Electrical Stimulation (FES) for Restoration of Hand Grasping and Extension Functions. [D] . Choi, Inchul. 2017

机译：基于感觉运动节律（SMR）的脑机接口（BCI）控制的功能性电刺激（FES），用于恢复手部抓握和伸展功能。
6. Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial [O] . Alexander A. Frolov, Olesya Mokienko, Roman Lyukmanov, 2017

机译：基于基于运动图像的脑机接口（BCI）控制的手外骨骼的中风后康复训练：一项随机对照的多中心试验
7. PRINCIPLES OF MOTOR RECOVERY IN POST-STROKE PATIENTS USING HAND EXOSKELETON CONTROLLED BY THE BRAIN-COMPUTER INTERFACE BASED ON MOTOR IMAGERY [O] . A. A. Frolov, Dušan Húsek, E. V. Biryukova, 2017

机译：基于电机图像的脑电电脑接口控制后脑骨骼患者电机恢复原理

Embedded Brain Machine Interface based on motor imagery paradigm to control prosthetic hand

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