SoC-FPGA systems for the acquisition and processing of electroencephalographic signals

Matías Javier Oliva, P. García, E. Spinelli, A. Veiga
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引用次数: 1

Abstract

Real-time acquisition and processing of electroencephalographic signals have promising applications in the implementation of brain-computer interfaces. These devices allow the user to control a device without performing motor actions, and are usually made up of a biopotential acquisition stage and a personal computer (PC). This structure is very flexible and appropriate for research, but for final users it is necessary to migrate to an embedded system, eliminating the PC from the scheme. The strict real-time processing requirements of such systems justify the choice of a system on a chip field-programmable gate arrays (SoC-FPGA) for its implementation. This article proposes a platform for the acquisition and processing of electroencephalographic signals using this type of device, which combines the parallelism and speed capabilities of an FPGA with the simplicity of a general-purpose processor on a single chip. In this scheme, the FPGA is in charge of the real-time operation, acquiring and processing the signals, while the processor solves the high-level tasks, with the interconnection between processing elements solved by buses integrated into the chip. The proposed scheme was used to implement a brain-computer interface based on steady-state visual evoked potentials, which was used to command a speller. The first tests of the system show that a selection time of 5 seconds per command can be achieved. The time delay between the user’s selection and the system response has been estimated at 343 µs.
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用于脑电图信号采集和处理的SoC-FPGA系统
脑电信号的实时采集和处理在脑机接口的实现中具有广阔的应用前景。这些设备允许用户在不执行运动动作的情况下控制设备,通常由生物电位采集阶段和个人计算机(PC)组成。这种结构非常灵活,适合于研究,但对于最终用户来说,有必要迁移到嵌入式系统,从方案中消除PC机。这种系统严格的实时处理要求证明了选择芯片上的系统来实现其现场可编程门阵列(SoC-FPGA)。本文提出了一个使用这种类型的设备采集和处理脑电图信号的平台,它结合了FPGA的并行性和速度能力以及单芯片上通用处理器的简单性。在该方案中,FPGA负责实时操作,采集和处理信号,处理器解决高级任务,处理单元之间的互连由集成在芯片中的总线解决。利用该方案实现了基于稳态视觉诱发电位的脑机接口,并利用该接口对拼写者进行指令。系统的初步测试表明,每个命令的选择时间可以达到5秒。用户选择和系统响应之间的时间延迟估计为343µs。
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