Real-time diffuse correlation spectroscopy with a chip-based correlator for measuring human cerebral blood flow and brain function
Abstract
Diffuse correlation spectroscopy (DCS) is a noninvasive optical technique that probes microvascular blood flow in deep tissues. Here, we present and validate a new on-chip hardware correlator for high-speed DCS measurements. The correlator is embedded in a custom-built 512 x 512 single-photon avalanche diode (SPAD) array named ATLAS, which computes intensity autocorrelation functions directly on-chip at a sampling rate of 116 Hz - the fastest DCS acquisition reported to date. Unlike conventional DCS systems that suffer from low light throughput and therefore cannot resolve cardiac pulsations at source-detector separations (rho) beyond 30 mm, our massively parallel on-chip architecture computes autocorrelations within each macropixel, eliminating the data-throughput bottleneck. This enables high-SNR, real-time detection of pulsatile blood flow even at rho = 50 mm on the human forehead. In phantom experiments at rho = 25 mm, ATLAS-DCS achieves a 12-fold improvement in signal-to-noise ratio over a conventional single-channel DCS instrument while operating at 116 Hz. In human subjects, we resolve functional hyperemia during a mental arithmetic task at rho = 30 mm. Furthermore, we integrate ATLAS DCS with a frequency-domain near-infrared spectroscopy (FD-NIRS) module, enabling simultaneous monitoring of blood flow and tissue oxygenation. With this combined system, we can concurrently resolve core hemodynamic parameters. The on-chip parallelized DCS design substantially improves detection speed, depth sensitivity, and real-time capability, paving the way for wearable, high-speed cerebral blood flow monitoring in both clinical and research settings.
Keywords
Cite
@article{arxiv.2503.17459,
title = {Real-time diffuse correlation spectroscopy with a chip-based correlator for measuring human cerebral blood flow and brain function},
author = {Quan Wang and Yuanyuan Hua and Chenxu Li and Zhizheng Yuan and Jing Wang and Ahmet T. Erdogan and Hanqing Chen and Xunting Huang and Maciej Wojtkiewicz and Alistair Gorman and Mingliang Pan and Yuanzhe Zhang and Yining Wang and Neil Finlayson and Renzhe Bi and Robert K. Henderson and Zhen Yuan and David Day-Uei Li},
journal= {arXiv preprint arXiv:2503.17459},
year = {2026}
}