von Luhmann Alexander, Wabnitz Heidrun, Sander Tilmann, Muller Klaus-Robert
IEEE Trans Biomed Eng. 2017 Jun;64(6):1199-1210. doi: 10.1109/TBME.2016.2594127. Epub 2016 Sep 9.
For the further development of the fields of telemedicine, neurotechnology, and brain-computer interfaces, advances in hybrid multimodal signal acquisition and processing technology are invaluable. Currently, there are no commonly available hybrid devices combining bioelectrical and biooptical neurophysiological measurements [here electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS)]. Our objective was to design such an instrument in a miniaturized, customizable, and wireless form.
We present here the design and evaluation of a mobile, modular, multimodal biosignal acquisition architecture (M3BA) based on a high-performance analog front-end optimized for biopotential acquisition, a microcontroller, and our openNIRS technology.
The designed M3BA modules are very small configurable high-precision and low-noise modules (EEG input referred noise @ 500 SPS 1.39 μV, NIRS noise equivalent power NEP = 5.92 pW, and NEP = 4.77 pW) with full input linearity, Bluetooth, 3-D accelerometer, and low power consumption. They support flexible user-specified biopotential reference setups and wireless body area/sensor network scenarios.
Performance characterization and in-vivo experiments confirmed functionality and quality of the designed architecture.
Telemedicine and assistive neurotechnology scenarios will increasingly include wearable multimodal sensors in the future. The M3BA architecture can significantly facilitate future designs for research in these and other fields that rely on customized mobile hybrid biosignal modal biosignal acquisition architecture (M3BA), multimodal, near-infrared spectroscopy (NIRS), wireless body area network (WBAN), wireless body sensor network (WBSN).
对于远程医疗、神经技术和脑机接口领域的进一步发展而言，混合多模态信号采集与处理技术的进步具有不可估量的价值。目前，尚无结合生物电和生物光学神经生理学测量（此处指脑电图（EEG）和功能性近红外光谱（NIRS））的通用混合设备。我们的目标是以小型化、可定制和无线的形式设计这样一种仪器。
我们在此展示了一种基于为生物电位采集优化的高性能模拟前端、微控制器和我们的openNIRS技术的移动、模块化、多模态生物信号采集架构（M3BA）的设计与评估。
所设计的M3BA模块是非常小的可配置高精度低噪声模块（EEG输入参考噪声@500 SPS为1.39 μV，NIRS噪声等效功率NEP = 5.92 pW，以及NEP = 4.77 pW），具有全输入线性度、蓝牙、3D加速度计且功耗低。它们支持灵活的用户指定生物电位参考设置以及无线体域网/传感器网络场景。
性能表征和体内实验证实了所设计架构的功能和质量。
远程医疗和辅助神经技术场景在未来将越来越多地包括可穿戴多模态传感器。M3BA架构可显著促进未来在这些以及其他依赖定制移动混合生物信号模态生物信号采集架构（M3BA）、多模态、近红外光谱（NIRS）、无线体域网（WBAN）、无线体传感器网络（WBSN）的领域中的研究设计。
