Speckle contrast optical spectroscopy (SCOS) allows for simultaneous monitoring of blood flow and volume changes within each cardiac pulse. SCOS measurements were collected from 10 subjects at two time points and the blood flow and volume pulse waveforms (PWFs) were extracted. The eXtreme Gradient Boosting model was trained on an individual subject’s first measurement and predicted BP for that subject’s second measurement. A model trained on features extracted from both flow and volume PWFs was compared to a model trained only on features extracted from blood volume PWFs. With the addition of blood flow information, BP estimation was significantly improved.
KEYWORDS: Single photon avalanche diodes, Field programmable gate arrays, Cameras, Signal to noise ratio, Photons, Actinium, Autocorrelation, Principal component analysis, Data compression, Diffusers
SignificanceDiffuse correlation spectroscopy (DCS) is an indispensable tool for quantifying cerebral blood flow noninvasively by measuring the autocorrelation function (ACF) of the diffused light. Recently, a multispeckle DCS approach was proposed to scale up the sensitivity with the number of independent speckle measurements, leveraging the rapid development of single-photon avalanche diode (SPAD) cameras. However, the extremely high data rate from advanced SPAD cameras is beyond the data transfer rate commonly available and requires specialized high-performance computation to calculate large number of autocorrelators (ACs) for real-time measurements.AimWe aim to demonstrate a data compression scheme in the readout field-programmable gate array (FPGA) of a large-pixel-count SPAD camera. On-FPGA, data compression should democratize SPAD cameras and streamline system integration for multispeckle DCS.ApproachWe present a 192 × 128 SPAD array with 128 linear ACs embedded on an FPGA to calculate 12,288 ACFs in real time.ResultsWe achieved a signal-to-noise ratio (SNR) gain of 110 over a single-pixel DCS system and more than threefold increase in SNR with respect to the state-of-the-art multispeckle DCS.ConclusionsThe FPGA-embedded autocorrelation algorithm offers a scalable data compression method to large SPAD array, which can improve the sensitivity and usability of multispeckle DCS instruments.
Speckle contrast optical spectroscopy (SCOS) allows for simultaneous monitoring of blood flow and volume changes within each cardiac pulse. SCOS measurements were collected from 13 subjects and blood flow and volume pulse waveforms (PWFs) were extracted. The correlations between features extracted from the PWFs and blood pressure before and after an exercise activity were investigated. We found that the time delay between the blood flow and volume peaks was strongly correlated with changes in blood pressure (R = -0.73), suggesting that the combination of blood flow and volume information may improve blood pressure estimation.
KEYWORDS: Monte Carlo methods, Photons, Scattering, Speckle, Sensors, Signal to noise ratio, Performance modeling, Tissues, Blood circulation, Tissue optics
Significance: Diffuse correlation spectroscopy (DCS) is an optical technique that measures blood flow non-invasively and continuously. The time-domain (TD) variant of DCS, namely, TD-DCS has demonstrated a potential to improve brain depth sensitivity and to distinguish superficial from deeper blood flow by utilizing pulsed laser sources and a gating strategy to select photons with different pathlengths within the scattering tissue using a single source–detector separation. A quantitative tool to predict the performance of TD-DCS that can be compared with traditional continuous wave DCS (CW-DCS) currently does not exist but is crucial to provide guidance for the continued development and application of these DCS systems.
Aims: We aim to establish a model to simulate TD-DCS measurements from first principles, which enables analysis of the impact of measurement noise that can be utilized to quantify the performance for any particular TD-DCS system and measurement geometry.
Approach: We have integrated the Monte Carlo simulation describing photon scattering in biological tissue with the wave model that calculates the speckle intensity fluctuations due to tissue dynamics to simulate TD-DCS measurements from first principles.
Results: Our model is capable of simulating photon counts received at the detector as a function of time for both CW-DCS and TD-DCS measurements. The effects of the laser coherence, instrument response function, detector gate delay, gate width, intrinsic noise arising from speckle statistics, and shot noise are incorporated in the model. We have demonstrated the ability of our model to simulate TD-DCS measurements under different conditions, and the use of our model to compare the performance of TD-DCS and CW-DCS under a few typical measurement conditions.
Conclusion: We have established a Monte Carlo-Wave model that is capable of simulating CW-DCS and TD-DCS measurements from first principles. In our exploration of the parameter space, we could not find realistic measurement conditions under which TD-DCS outperformed CW-DCS. However, the parameter space for the optimization of the contrast to noise ratio of TD-DCS is large and complex, so our results do not imply that TD-DCS cannot indeed outperform CW-DCS under different conditions. We made our code available publicly for others in the field to find use cases favorable to TD-DCS. TD-DCS also provides a promising way to measure deep brain tissue dynamics using a short source–detector separation, which will benefit the development of technologies including high density DCS systems and image reconstruction using a limited number of source–detector pairs.
KEYWORDS: Signal detection, Hemodynamics, Spectroscopy, Monte Carlo methods, Brain, Blood circulation, Scattering, Time metrology, Neurophotonics, Neurons
Significance: Diffuse correlation spectroscopy (DCS) measures cerebral blood flow non-invasively. Variations in blood flow can be used to detect neuronal activities, but its peak has a latency of a few seconds, which is slow for real-time monitoring. Neuronal cells also deform during activation, which, in principle, can be utilized to detect neuronal activity on fast timescales (within 100 ms) using DCS.
Aims: We aim to characterize DCS signal variation quantified as the change of the decay time of the speckle intensity autocorrelation function during neuronal activation on both fast (within 100 ms) and slow (100 ms to seconds) timescales.
Approach: We extensively modeled the variations in the DCS signal that are expected to arise from neuronal activation using Monte Carlo simulations, including the impacts of neuronal cell motion, vessel wall dilation, and blood flow changes.
Results: We found that neuronal cell motion induces a DCS signal variation of ∼10 − 5. We also estimated the contrast and number of channels required to detect hemodynamic signals at different time delays.
Conclusions: From this extensive analysis, we do not expect to detect neuronal cell motion using DCS in the near future based on current technology trends. However, multi-channel DCS will be able to detect hemodynamic response with sub-second latency, which is interesting for brain–computer interfaces.
Laser Speckle Contrast Imaging (LSCI) measurements provide sufficient information on the changes in the tissue dynamics using spatial contrast measurements over an integration time. To allow the adoption of LSCI in humans, we propose a fiber-based LSCI system that has the potential to overcome free-space imaging of Speckle Contrast Optical Tomography (SCOT) while maintaining the high-speed imaging of LSCI. Here, we propose Dynamic Speckle Model (DSM) to develop the noise model for fiber-based LSCI (fb-LSCI) taking into account all the noise sources. We have identified operating parameter space i.e. small speckle to pixel ratio and long exposure time to minimise the impact of noise sources on the contrast measured. The performance of fb-LSCI is compared with other methods that measure changes in tissue dynamics such as DCS.
Cerebral blood flow is an important biomarker of brain health and function, as it regulates the delivery of oxygen and substrates to tissue and the removal of metabolic waste products. Diffuse Correlation Spectroscopy (DCS) is a promising noninvasive optical technique for monitoring cerebral blood flow and for measuring cortex functional activation tasks. However, the current state-of-the-art DCS adoption is hindered by a trade-off between sensitivity to the cortex and signal-to-noise ratio (SNR). Here we report on a multi-speckle DCS (mDCS) system based on a 1024-pixel single-photon avalanche diode (SPAD) camera that removes this trade-off and demonstrated a 32-fold increase in SNR with respect to traditional single-speckle DCS.
Significance: Cerebral blood flow is an important biomarker of brain health and function as it regulates the delivery of oxygen and substrates to tissue and the removal of metabolic waste products. Moreover, blood flow changes in specific areas of the brain are correlated with neuronal activity in those areas. Diffuse correlation spectroscopy (DCS) is a promising noninvasive optical technique for monitoring cerebral blood flow and for measuring cortex functional activation tasks. However, the current state-of-the-art DCS adoption is hindered by a trade-off between sensitivity to the cortex and signal-to-noise ratio (SNR).
Aim: We aim to develop a scalable method that increases the sensitivity of DCS instruments.
Approach: We report on a multispeckle DCS (mDCS) approach that is based on a 1024-pixel single-photon avalanche diode (SPAD) camera. Our approach is scalable to >100,000 independent speckle measurements since large-pixel-count SPAD cameras are becoming available, owing to the investments in LiDAR technology for automotive and augmented reality applications.
Results: We demonstrated a 32-fold increase in SNR with respect to traditional single-speckle DCS.
Conclusion: A mDCS system that is based on a SPAD camera serves as a scalable method toward high-sensitivity DCS measurements, thus enabling both high sensitivity to the cortex and high SNR.
The Deep Space Optical Communication (DSOC) project at the Jet Propulsion Laboratory aims to perform a bidirectional laser communication technology demonstration from deep space, at ranges from 0.1 - 3 AU. To support high data rates over such distances while keeping the mass and power on the spacecraft comparable to radio-frequency communication systems, extremely high-performance single photon detectors are required at the ground receiver. To this end, JPL has been developing 64-pixel tungsten silicide superconducting nanowire single photon detector (WSi SNSPD) arrays suitable for use in the DSOC ground terminal. To efficiently couple to a 5-meter telescope aperture in the presence of atmospheric seeing, the arrays are free-space coupled and have a combined 320-micron diameter active area. The development is targeting 70% system detection efficiency at an operating wavelength of 1550 nm, 150 ps time resolution, a maximum count rate approaching 109 counts per second, a numerical aperture capable of supporting an f/1.2 beam, a background-limited dark count rate, and an operating temperature of 1 Kelvin. In this paper, we will present our progress toward these goals, both in terms of focal plane array development and cryogenic readout technology.
We demonstrate a 64-pixel free-space-coupled array of superconducting nanowire single photon detectors optimized for high detection efficiency in the near-infrared range. An integrated, readily scalable, multiplexed readout scheme is employed to reduce the number of readout lines to 16. The cryogenic, optical, and electronic packaging to read out the array, as well as characterization measurements are discussed.
Superconducting circuits comprising SNSPDs placed in parallel—superconducting nanowire avalanche photodetectors, or SNAPs—have previously been demonstrated to improve the output signal-to-noise ratio (SNR) by increasing the critical current. In this work, we employ a 2-SNAP superconducting circuit with narrow (40 nm) niobium nitride (NbN) nanowires to improve the system detection efficiency to near-IR photons while maintaining high SNR. Additionally, while previous 2-SNAP demonstrations have added external choke inductance to stabilize the avalanching photocurrent, we show that the external inductance can be entirely folded into the active area by cascading 2-SNAP devices in series to produce a greatly increased active area. We fabricated series-2-SNAP (s2-SNAP) circuits with a nanowire length of 20 μm with cascades of 2-SNAPs providing the choke inductance necessary for SNAP operation. We observed that (1) the detection efficiency saturated at high bias currents, and (2) the 40 nm 2-SNAP circuit critical current was approximately twice that for a 40 nm non-SNAP configuration.
We demonstrate a 64-pixel free-space-coupled array of superconducting nanowire single photon detectors optimized for high detection efficiency in the near-infrared range. An integrated, readily scalable, multiplexed readout scheme is employed to reduce the number of readout lines to 16. The cryogenic, optical, and electronic packaging to read out the array, as well as characterization measurements are discussed.
We describe a number of methods that have been pursued to develop superconducting nanowire single-photon detectors (SNSPDs) with attractive overall performance, including three systems that operate with >70% system detection efficiency and high maximum counting rates at wavelengths near 1550 nm. The advantages and tradeoffs of various approaches to efficient optical coupling, electrical readout, and SNSPD design are described and contrasted. Optical interfaces to the detectors have been based on fiber coupling, either directly to the detector or through the substrate, using both single-mode and multimode fibers with different approaches to alignment. Recent advances in electrical interfaces have focused on the challenges of scalability and ensuring stable detector operation at high count rates. Prospects for further advances in these and other methods are also described, which may enable larger arrays and higher-performance SNSPD systems in the future. Finally, the use of some of these techniques to develop fully packaged SNSPD systems will be described and the performance available from these recently developed systems will be reviewed.
There is a growing interest in developing systems employing large arrays of SNSPDs. To make such instruments practical, it is desirable to perform signal processing before transporting the detector outputs to room temperature. We present a cryogenic eight-channel pixel combiner circuit designed to amplify, digitize, edge detect, and combine the output signals of an array of eight SNSPDs. The circuit has been fabricated and measurement results agree well with expectation. The paper will conclude with a summary of ongoing work and future directions.
We present a novel concept of photon number resolving detector based on 120-nm-wide superconducting stripes made of
4-nm-thick NbN film and connected in parallel (PNR-SSPD). The detector consisting of 5 strips demonstrate a capability
to resolve up to 4 photons absorbed simultaneously with the single-photon quantum efficiency of 2.5% and negligibly
low dark count rate.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.