Designing, optimizing, and assessing modular functional near-infrared brain imaging probes using an automated software workflow

Abstract

SignificanceThe exponential growth of research utilizing functional near-infrared spectroscopy (fNIRS) systems has led to the emergence of modular fNIRS systems composed of repeating optical source/detector modules. Compared to conventional fNIRS systems, modular fNIRS systems are more compact and flexible, making wearable and long-time monitoring possible. However, the large number of design parameters makes designing a modular probe a daunting task. AimWe aim to create a systematic software platform to facilitate the design, characterization, and comparison of modular fNIRS probes. ApproachOur algorithm automatically tessellates any region-of-interest using user-specified module design parameters and outputs performance metrics such as spatial channel distributions, average brain sensitivity, and sampling rate estimates of the resulting probe. Automated algorithms for spatial coverage, orientation, and routing of repeated modules are also developed. ResultsWe developed a software platform to help explore a wide range of modular probe features and quantify their performances. We compare full-head probes using three different module shapes and highlight the trade-offs resulting from various module settings. Additionally, we show that one can apply this workflow to improve existing modular probes without needing to re-design or re-manufacture them. ConclusionOur flexible modular probe design platform shows promise in optimizing existing modular probes and investigating future modular designs.