High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications

Abstract

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

Fast blood flow monitoring in deep tissues with real-time software correlators

“…The software correlators also utilize digital counters to record TTL pulses from the photon counting detectors [43,44,52,53]. Instead of computing the correlation function with embedded programming, however, high-level programs (e.g.…”

“…LabVIEW, C++) control the counter readout and estimate the correlation function in the computer's random access memory (RAM). Proof-of-principle measurements with diffuse correlation spectroscopy via the Wiener-Khinchin theorem, i.e., the convolution of the measured temporal intensity and its time-reversed duplicate have been made with software correlators [52,53]. These studies did not optimize the correlation function computations for measurement speed, and this approach requires a large buffer to store the stream of detected photon pulses each second, e.g., data sampling rates smaller than 2 µs would fill a typical computer's buffer in less than a second [52].…”

Calibration of diffuse correlation spectroscopy blood flow index with venous-occlusion diffuse optical spectroscopy in skeletal muscle

“…DCS is a noninvasive optical method that quantitatively measures tissue BF using speckle correlation techniques. 39,40,[42][43][44][45][46] Herein, aspects of this technique relevant to our study are highlighted; for additional details, the reader should consult comprehensive reviews and papers. 7,[36][37][38][39][40] DCS measures the temporal intensity fluctuations of coherent near-infrared (NIR) light that has multiply scattered from moving red blood cells in tissue.…”

“…41 DCS is a simple noninvasive technique that derives flow information from measurements of the temporal intensity fluctuations of multiply scattered light. 39,40,[42][43][44][45][46] The DCS BFI has been validated against a plethora of gold-standard techniques; 7,[47][48][49][50][51][52] in these studies, the BFI and especially its variation were demonstrated to be approximately proportional to true BF in a range of subjects and tissue types. However, clinical interpretation of the DCS BFI is complicated by its unusual units of [cm 2 ∕s].…”

A scalable correlator for multichannel diffuse correlation spectroscopy

“…The purpose of this work is to compare our measurements with the PSOC based time tagging instrument to existing commercial devices such as the hardware correlator of correlator.com and to instruments such as the recently published raspberry pi module based correlator 4 .…”