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NeuroHub fog: wireless network time synchronization device for multimodal brain imaging and hyperscanning research
Thesis   Open access

NeuroHub fog: wireless network time synchronization device for multimodal brain imaging and hyperscanning research

Andrew G. Dai
Master of Science (M.S.), Drexel University
Oct 2020
DOI:
https://doi.org/10.17918/00000405
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Abstract

Brain--Imaging Brain-computer interfaces Neuroergonomics Synchronization Biochemical Markers
Brain computer interfaces have a variety of applications including but not limited to neuroscience, engineering, computer science, psychology, and rehabilitation. With a wide range of disciplines and advancing technologies, there is a growing interest, especially in using multiple systems concurrently in multimodal/hybrid configurations to extract complimentary aspects of brain activity, and in measuring multiple brains using hyperscanning configurations to investigate brain activities in social interactions. The use of functional neuroimaging in brain computer interface protocols such as functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) require precise time synchronized transmission of experimental event markers and acquired data for proper analysis and interpretation. A challenge is present given the complexity of having multiple brain and body sensors and difficulty in providing a proper timing of event markers during data acquisition. As there are currently no standards for interoperability, different brain and body sensors employ different means of communication. A scalable, portable device that can act as a bridge between multiple monitoring systems with different communication protocols is one solution for ensuring practicality of these experimental setups. The original NeuroHub device, developed at Drexel University, offered time synchronization capabilities through four serial ports, a TTL port, and a parallel port. The following generation of NeuroHub was designed as a modular expansion to the original device in order to offer wireless communications to accommodate for modern computing systems with more complex options. This thesis proposes a solution that consolidates both previous generations into a single form factor and bridges different brain and body sensors in order to ensure proper time synchronizations via network communication protocols and wired hardware ports. With the goal of versatility and practicality in mind, the device ensures improved convenience of set-up procedures when attempting to coordinate devices with different communication protocols by bridging serial port communications with network-based communications while also recording the timing and traffic of event markers in a logfile. This newest generation of NeuroHub operates on a Raspberry Pi 4 Model B with an attached serial port HAT and a 3800 mAh Li battery. This new generation of NeuroHub also operates a web server-based control application to view and configure network and hardware settings, and for viewing and downloading logfiles. The device offers improved flexibility and customizability in multimodal and hyperscanning research protocols, through reliable timestamping and time synchronized marker transmission and logging, particularly for brain and body sensors that have different data transmission protocols. Verification testing confirmed 100% accuracy in transmitting markers in both single client round trip test configurations and in multiclient configurations. Testing also confirmed that the timing of single client round trip times ranged from slightly below 10 milliseconds to sub millisecond latency depending on the configuration. Multiclient configurations confirmed that the time for the NeuroHub to send a marker to a client over the network and receive one back is roughly 4 milliseconds.

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