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NIRDuino: A modular, Bluetooth-enabled, Android®-configurable fNIRS system with dual-intensity mode built on Arduino®

固件 阿杜伊诺 探测器 计算机科学 Android(操作系统) 通用串口总线 模块化设计 蓝牙 计算机硬件 嵌入式系统 试验台 可穿戴计算机 软件 无线 操作系统 电信 计算机网络
作者
Anupam Kumar,Seth B. Crawford,Tiffany-Chau Le,Ali Rahimpour Jounghani,Laura Moreno Carbonell,Alexandra Sargent Capps,Alec B. Walter,Daniel Liu,Reed Sullivan,E. Duco Jansen,S. M. Hadi Hosseini,Audrey K. Bowden
出处
期刊:Cold Spring Harbor Laboratory - medRxiv
标识
DOI:10.1101/2024.12.20.24318425
摘要

Abstract Significance We present NIRDuino: an Open-source Android ® -configurable, modular, and Bluetooth-enabled fNIRS system that allows researchers to perform neuroimaging studies with up to eight emitters and 16 detectors. The complete system (including Android tablet) can be assembled for less than $1000, and the emitters and detectors can be arranged in any configuration to achieve the desired short and long channels required for their study. Aim The system has been designed with non-engineers in mind, and the researcher only needs to design the wearable interfaces to attach the emitters and detectors to the body appropriate for their intended application. Approach The system consists of a battery-powered, wireless controller built on the Arduino® Nano ESP32 platform, a dongle with sockets for each of the eight emitters and detectors that can be connected, and individual wired probes for emitters and detectors. In accompaniment, Arduino®-based firmware and an Android ® application have also been developed and provided. The selected emitters and detectors can be arranged in any desired configuration, and the emitters can be configured to output light with both regular intensities and low intensities to collect data for “long channels” with sufficient signal quality and “short channels” without saturation. This paper details the system’s design and characterization on phantom and two physiological experiences on a human. Results The easy-to-configure hardware/software system demonstrated stability in fNIRS measurements using a single emitter-detector pair placed on a phantom, and reproduced previously published outcomes for arterial cuff measurements on the forearm and a arithmetic experiment on the forehead. Conclusion The NIRDuino circuitry and software demonstrated modularity and usability for NIRS experiments, and this low-cost platform will provide researchers globally with an affordable fNIRS system to easily adopt and adapt for their unique experimental needs.

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