IEEE Trans Neural Syst Rehabil Eng. 2019 Aug;27(8):1529-1538. doi: 10.1109/TNSRE.2019.2929081. Epub 2019 Jul 16.
Implantable microsystems that collect and transmit neural data are becoming very useful entities in the field of neuroscience. Limited by high data rates, on-chip compression is often required to transmit the recorded data without causing power dissipation at levels that would damage sensitive brain tissue. This paper presents a data compression system designed for brain-computer interfaces (BCIs) based on undercomplete autoencoders. To the best of our knowledge, the proposed system is the first to achieve an average spike reconstruction quality of 14-dB signal-to-noise-and-distortion ratio (SNDR) at a 32× compression ratio (CR), 18-dB SNDR at a 16× CR, 22-dB SNDR at an 8× CR, and 35-dB SNDR at a 4× CR of neural spikes. The spike detection and autoencoder-based compression modules are designed and implemented in a standard 45-nm CMOS process. The post-synthesis simulation results report that the compression module consumes between 1.4 and 222.5 [Formula: see text] of power per channel and takes between 0.018 and 0.082mm of silicon area, depending on the desired CR and number of channels.
用于收集和传输神经数据的植入式微系统在神经科学领域正变得非常有用。由于数据速率较高，为了在不引起功耗的情况下传输记录的数据，往往需要在片上进行压缩，以免损坏敏感的脑组织。本文提出了一种基于欠完备自动编码器的脑机接口（BCI）数据压缩系统。据我们所知，该系统在 32×压缩比（CR）、16×CR、8×CR 和 4×CR 下，实现了平均尖峰重建质量为 14dB 信噪比和失真比（SNDR），在 18dB SNDR 下实现了 16×CR，在 22dB SNDR 下实现了 8×CR，在 35dB SNDR 下实现了 4×CR 的神经尖峰。尖峰检测和基于自动编码器的压缩模块是在标准的 45nm CMOS 工艺中设计和实现的。综合后的仿真结果表明，压缩模块每个通道消耗的功率在 1.4 到 222.5 [Formula: see text]之间，占用的硅面积在 0.018 到 0.082mm 之间，具体取决于所需的 CR 和通道数量。
