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BioWolf: A Sub-10-mW 8-Channel Advanced Brain–Computer Interface Platform With a Nine-Core Processor and BLE Connectivity

机译:BioWolf:具有九核处理器和BLE连接的低于10mW的8通道高级脑机接口平台

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Advancements in digital signal processing (DSP) and machine learning techniques have boosted the popularity of brain-computer interfaces (BCIs), where electroencephalography is a widely accepted method to enable intuitive human-machine interaction. Nevertheless, the evolution of such interfaces is currently hampered by the unavailability of embedded platforms capable of delivering the required computational power at high energy efficiency and allowing for a small and unobtrusive form factor. To fill this gap, we developed BioWolf, a highly wearable (40mm 20 mm 2 mm) BCI platform based on Mr. Wolf, a parallel ultra low power system-on-chip featuring nine RISC-V cores with DSP-oriented instruction set extensions. BioWolf also integrates a commercial 8-channel medical-grade analog-to-digital converter, and an ARM-Cortex M4 microcontroller unit (MCU) with bluetooth low-energy connectivity. To demonstrate the capabilities of the system, we implemented and tested a BCI featuring canonical correlation analysis (CCA) of steady-state visual evoked potentials. The system achieves an average information transfer rate of 1.46 b/s (aligned with the state-of-the-art of bench-top systems). Thanks to the reduced power envelope of the digital computational platform, which consumes less than the analog front-end, the total power budget is just 6.31mW, providing up to 38h operation (65mAh battery). To our knowledge, our design is the first to explore the significant energy boost of a parallel MCU with respect to single-core MCUs for CCA-based BCI.
机译:数字信号处理(DSP)和机器学习技术的进步促进了脑机接口(BCI)的普及,其中脑电图学是实现直观的人机交互的广泛接受的方法。尽管如此,目前这种接口的发展受到嵌入式平台不可用的阻碍,该嵌入式平台无法以高能效传递所需的计算能力,并且体积小且不引人注目。为了填补这一空白,我们开发了BioWolf,这是一款基于Wolf先生的高度耐磨(40mm 20 mm 2 mm)BCI平台,Wolf先生是一个并行的超低功耗片上系统,具有9个RISC-V内核以及面向DSP的指令集扩展。 BioWolf还集成了商用8通道医疗级模数转换器和具有蓝牙低能耗连接功能的ARM-Cortex M4微控制器单元(MCU)。为了演示系统的功能,我们实施并测试了BCI,该BCI具有稳态视觉诱发电位的典范相关分析(CCA)。该系统的平均信息传输速率为1.46 b / s(与最新的台式系统保持一致)。由于数字计算平台的功耗降低,其功耗小于模拟前端,因此总功耗预算仅为6.31mW,可提供长达38h的运行时间(65mAh电池)。据我们所知,我们的设计是第一个探索并行MCU与基于CCA的BCI的单核MCU相比大幅提升的功耗。

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