In this paper, an innovative approach for detecting and analyzing speckle pattern signals is demonstrated, based on dynamic speckle analysis using a low-cost and low-framerate rolling shutter (RS) CMOS image sensor. The row scanning mechanism of a rolling shutter camera samples dynamic speckle patterns at a higher rate than typical Global Shutter (GS) cameras. In this research we demonstrate the detection and analysis of vibration signals that arise from an acoustic signal. We will illustrate the process of reconstructing a voice signal by analyzing a vibrating speckle pattern, with a primary focus on detecting and audibly capturing lung sounds.
SignificanceCombining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index (pCBFi) can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance (CVRi).AimAlthough current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source–detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform.ApproachTaking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS pCBFi, reducing the coefficient of variation of the recovered pulsatile waveform (pCBFi-fit) and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation (>3 cm).ResultsIn 10 healthy subjects, we verified the quality of the NIRS-PPG pCBFi-fit during common tasks, showing high fidelity against pCBFi (R2 0.98 ± 0.01). We recovered CrCP and CVRi at 0.25 Hz, >10 times faster than previously achieved with DCS.ConclusionsNIRS-PPG improves DCS pCBFi SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and CVRi.
There are currently no evidence-based methods to detect cannabis-impaired driving, and current field sobriety tests with gold-standard, drug recognition evaluations are resource-intensive and may be prone to bias. This study evaluated the capability of a simple, portable imaging method to accurately detect individuals with Δ9-tetrahydrocannabinol (THC) impairment. Comparing resting state connectivity of post-dose THC and post-dose placebo in impaired participants, we identified decreased connectivity after THC. Furthermore, using standard machine learning algorithms, we were able to predict impairment with >70% accuracy.
We present a novel system based on a four-stage fiber delay network designed for multistate time-domain diffuse correlation spectroscopy, providing three output fibers per each delay state. The fiber delay network is coupled to a custom pulsed laser at 1064 nm and four SNSPDs, allowing to measure up to 12 independent source-detector pairs simultaneously. The system delivers 300ps optical pulses, 100 mW average optical power per fiber output, operates at 62.5 MHz and each cycle provides 4 laser pulses displaced of 4 ns. The instrument has been validated on healthy human subject during functional tasks, proving state-of-the-art performance.
We present the design of an innovative time-gated 32×32 InP/InGaAs-based Single Photon Avalanche Diode (SPAD) array with sub-nanosecond gating capabilities operating up to 10MHz repetition rate specifically designed for time-domain diffuse correlation spectroscopy at 1064nm. We present the detector design, experimental characterization and preliminary validations on a liquid phantom. This testing is informing us for a revision of the photodetector which will allow to reach up to 192 optical channels towards functional blood flow changes measurements with full head coverage with improved brain sensitivity thanks to early-photons rejection.
Diffuse correlation spectroscopy (DCS) is an emerging near infrared spectroscopy modality able to measure cerebral blood flow (CBF) non-invasively and continuously in humans. We have reported a limited applicability in adults due to the significant extracerebral tissue thickness and the low signal-to-noise ratio (SNR) of the measurements. Improvements to DCS brain sensitivity and SNR can be achieved by operating DCS at 1064 and using superconducting nanowire single-photon detectors (SNSPDs). Initial human results show a 16-fold improvement in SNR and 20% improvement in depth sensitivity. This allows us to resolve changes in CBF in adult subjects more robustly and accurately than was previously achievable.
We present the design of an innovative instrument for time-gated diffuse correlation spectroscopy. It features a 1064nm pulsed sub-ns long coherence-length laser operating up to 75MHz, a 100-channel in-FPGA correlator and a novel time-gated 32×32 InP/InGaAs-based Single Photon Avalanche Diode (SPAD) array with sub-nanosecond gating capabilities operating up to 10MHz repetition rate. We present components experimental characterization and preliminary validations on a liquid phantom. This testing is informing us for a revision of the photodetector which will allow to reach up to 192 optical channels towards functional blood flow changes measurements with full head coverage.
Significance: The ability of diffuse correlation spectroscopy (DCS) to measure cerebral blood flow (CBF) in humans is hindered by the low signal-to-noise ratio (SNR) of the method. This limits the high acquisition rates needed to resolve dynamic flow changes and to optimally filter out large pulsatile oscillations and prevents the use of large source-detector separations (≥3 cm), which are needed to achieve adequate brain sensitivity in most adult subjects.
Aim: To substantially improve SNR, we have built a DCS device that operates at 1064 nm and uses superconducting nanowire single-photon detectors (SNSPD).
Approach: We compared the performances of the SNSPD-DCS in humans with respect to a typical DCS system operating at 850 nm and using silicon single-photon avalanche diode detectors.
Results: At a 25-mm separation, we detected 13 ± 6 times more photons and achieved an SNR gain of 16 ± 8 on the forehead of 11 subjects using the SNSPD-DCS as compared to typical DCS. At this separation, the SNSPD-DCS is able to detect a clean pulsatile flow signal at 20 Hz in all subjects. With the SNSPD-DCS, we also performed measurements at 35 mm, showing a lower scalp sensitivity of 31 ± 6 % with respect to the 48 ± 8 % scalp sensitivity at 25 mm for both the 850 and 1064 nm systems. Furthermore, we demonstrated blood flow responses to breath holding and hyperventilation tasks.
Conclusions: While current commercial SNSPDs are expensive, bulky, and loud, they may allow for more robust measures of non-invasive cerebral perfusion in an intensive care setting.
Significance: Time domain diffuse correlation spectroscopy (TD-DCS) can offer increased sensitivity to cerebral hemodynamics and reduced contamination from extracerebral layers by differentiating photons based on their travel time in tissue. We have developed rigorous simulation and evaluation procedures to determine the optimal time gate parameters for monitoring cerebral perfusion considering instrumentation characteristics and realistic measurement noise.
Aim: We simulate TD-DCS cerebral perfusion monitoring performance for different instrument response functions (IRFs) in the presence of realistic experimental noise and evaluate metrics of sensitivity to brain blood flow, signal-to-noise ratio (SNR), and ability to reject the influence of extracerebral blood flow across a variety of time gates to determine optimal operating parameters.
Approach: Light propagation was modeled on an MRI-derived human head geometry using Monte Carlo simulations for 765- and 1064-nm excitation wavelengths. We use a virtual probe with a source–detector separation of 1 cm placed in the pre-frontal region. Performance metrics described above were evaluated to determine optimal time gate(s) for different IRFs. Validation of simulation noise estimates was done with experiments conducted on an intralipid-based liquid phantom.
Results: We find that TD-DCS performance strongly depends on the system IRF. Among Gaussian pulse shapes, ∼300 ps pulse length appears to offer the best performance, at wide gates (500 ps and larger) with start times 400 and 600 ps after the peak of the TPSF at 765 and 1064 nm, respectively, for a 1-s integration time at photon detection rates seen experimentally (600 kcps at 765 nm and 4 Mcps at 1064 nm).
Conclusions: Our work shows that optimal time gates satisfy competing requirements for sufficient sensitivity and sufficient SNR. The achievable performance is further impacted by system IRF with ∼300 ps quasi-Gaussian pulse obtained using electro-optic laser shaping providing the best results.
Recently, we developed a time-domain diffuse correlation spectroscopy (TD-DCS) method for neurovascular sensing with higher brain sensitivity. In this paper, laser pulse shaping was designed and demonstrated for TD-DCS at 1064 nm. A quantum superconducting nanowire single-photon detector (SNSPD) with high photon detection efficiency (PDE) and low jitter collects the back-scattered light from the brain. The presented approach is the first step towards scaling up a full fiber optic cap with 96 source channels and 192 custom-made single-photon detectors which will cover most of an adult head.
The ability of diffuse correlation spectroscopy (DCS) to measure tissue perfusion paves the way for monitoring cerebral blood flow (CBF) non-invasively. However, during measurements on human forehead, the measured blood flow index (BFi) is susceptible to contamination due to the blood flow in extracerebral tissue. Time domain DCS addresses this problem by selecting photons based on their travel time to obtain BFi at various depths. We have determined the gate start time(s) and width(s) that can lead to optimal sensitivity of BFi to CBF during actual measurements on human subjects through simulations. The simulated parameters were compared with measurement data.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. Recent advances in the field have seen the introduction of iDWS/iDCS, which have allowed for the use of conventional photodetectors to replace the single photon counting detectors required to measure the traditional, homodyne DCS signal. Here we detail a high framerate, highly parallel iDCS system at 1064 nm which allows for improved signal to noise ratio at extended source detector separations.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. DCS cerebral blood flow measurements in clinical applications have shown promise, but measurements contain contamination of the signal from changes in superficial blood flow. Recent studies have shown that moving to wavelengths beyond the water absorption peak at 970 nm when making DCS measurements improves SNR and reduced influence of superficial flow. Here, we present a DCS system operating at 1064 nm utilizing two InGaAs SPADs to calculate the cross correlation to address detector non-idealities.
KEYWORDS: Blood circulation, Absorption, Scattering, Signal to noise ratio, Tissue optics, Near infrared spectroscopy, Spectroscopy, Tissues, Signal attenuation, Sensors
Significance: Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths (>1000 nm) for the DCS measurement due to a variety of biophysical and regulatory factors.
Aim: We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations.
Approach: We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers.
Results: DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source–detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS.
Conclusions: DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.
The ability to remotely extract temperature from a specific location using back scattered light analysis is very applicable. In this paper we present the first step towards remote sensing of temperature by using several approaches based upon conventional neural network analysis of the back scattered speckle patterns, analysis of the speckle patterns decorrelation time constant and Photoplethysmogram measurements.
In this paper we propose a novel approach for remote speckle-based sensing of mechanical vibrations in the Hirudo medicinalis leech central nervous system (CNS) connective tissue. Using this method, spontaneous vibrations generated at the connective tissue following partial cut injury are continuously and remotely monitored. A laser beam illuminates the connective tissue and back scattered defocused patterns at the far field are captured by the camera. The spatialtemporal spontaneous vibrations of the connective are monitored by tracking the speckle spatial-temporal trajectory. After applying correlation-based analysis we were able to detect these vibrations of the connective tissue during recovery with respect to control measurements. This approach is the first step towards understanding the possible involvement of the tissue movements for the recovering process via mechanical vibrations sensing of the leech CNS connective tissue.
We will present how one can use the spatial-temporal analysis of secondary speckle patterns that are generated when laser light is back scattered from a tissue in order to measure the nano-vibrations (tilting associated vibrations) occurring in the tissue and in order to map its elastography. In addition to the fundamental nano-vibrations sensing capability, the proposed configuration allows by applying time multiplexing approach also to perform separation of photons coming from different depths of the tissue while externally stimulating the tissue via infra-sonic vibration. This yields a tomographic capability. The proposed configuration uses a modulated laser that allows combining a speckle pattern tracking method for surface tilting changes sensing with a Mach–Zehnder interferometer-based speckle patterns configuration to achieve z-axis detection (movement of the whole surface in the z direction). We will also show several methods for setup modulation to down convert high temporal frequencies to allow their sampling with a slow rate camera. As to be demonstrated in the experimental validation, the different elastographic layers (that were represented in our experiments by different concentrations of the agarose) have different temporal flickering and thereafter different temporal-spectral distribution which allows to extract their different elastographic characters.
The optical activity of glucose in aqueous solutions offers a very high specificity in detecting the presence of glucose. In this presentation we will present several concepts for non-invasive detection of glucose, being realized in-vitro as well as in-vivo. In all cases the sensing concept is based upon analysis of time changing spatial statistics of back scattered speckle patterns when being analyzed by properly defocused optics. We will focus on an experimental approach in which we try to employ contactless measurement of acoustic excitations in solutions containing various chemical while using analysis of those time changing speckle pattern. Solutions containing glucose should response differently than those where glucose is absent. To perform this measurement, we excited acoustic waves in a solution and measured the changes in the speckle pattern. The basic concept is that while the solution is acoustically excited the acoustic waves modulate the density of the fluid under examination. This modulation will have two effects on the speckle pattern, the first is a spatial and time-varying modulation of the effective refractive index, and the second is a spatial and time-varying modulation of the optical rotation which is induced by the presence of glucose. Both of these effects should change the speckle pattern, which if recorded with an exposure time which is longer than the acoustic period, will be seen as a smearing of the pattern. By analyzing properties such as speckle size, contrast and/or correlation between images, it is possible to extract a signal which is proportional to the amplitude of the acoustic excitation.
In this work we explore the problem of multiclass classification where the classifier may abstain from classifying on some observation. We derivate a new surrogate loss function and a multiclass decision rule by using a reject threshold on posterior probabilities in the Bayes decision rule, known as Chow's rule. The goal of the decision rule is to minimize the value of given misprediction and rejection cost functions specified by the user. We suggest a general training algorithm by plug-in the surrogate loss in to Support Vector Machine (SVM) structure. We then test the algorithm on various real -life problem in the photonic medical sensing field where accuracy is critical. We present an example of a non-invasive way of detecting glucose level in blood to help patients with Diabetes mellitus diseases while the sensing is performed with speckle-based approach to analyze remote sensing of biomedical parameters. The results will show that the value of the reject threshold has importance in determining how many samples to reject and in the overall accuracy of prediction. As the threshold grow so does the number of samples rejected and overall accuracy, meaning that only samples with strong confidence are outputted in the classification process. A very important point in working with reject option is that there is a tradeoff between the number of samples being rejected and the accuracy of the labeled samples. High precision comes with high rejection rate, while low rate of rejection derogates from the general correctness of the output.
Continuous noninvasive measurement of intraocular pressure (IOP) is an important tool in the evaluation process for glaucoma. We present a methodology enabling high-precision, noncontact, reproducible, and continuous monitoring of IOP based on the value of the damping factor of transitional oscillations obtained at the surface of the eye after terminating its stimulation by a sound wave. The proposed configuration includes projection of a laser beam and usage of a fast camera for analyzing the temporal–spatial variations of the speckle patterns backscattered from the iris or the sclera following the above-mentioned sound waves external stimulation. The methodology was tested on an artificial eye and a carp fish eye under varying pressure as well as on human eyes.
Over the last few years, there is a growing interest in photoacoustic imaging using nanoparticles techniques due to the improved penetration depth and resolution. Working with such nanoparticles usually requires pulsed laser illumination to generate an acoustic signal in the right frequencies. However, these pulsed lasers are considered expensive and complicated with respect to continuous-wave (CW) illumination. We design and simulate a special nanostructure with overall dimensions of 190×50× (26–34) nm, which blinks with fast temporal periodicity of 20 to 40 ns, under CW illumination and can be used for the generation of acoustic signals. This blinking is done using the enhanced optical absorption of metallic nanoparticles due to localized surface plasmon resonance (SPR) and the thermal expansion to generate heating–cooling cycles of the nanostructure. The CW laser wavelength is adapted to the localized SPR of the metallic nanostructure at the NIR region, which provides maximum penetration depth of light into biological tissues.
In this paper we present the usage of photonic remote laser based device for sensing nano-vibrations for detection of muscle contraction and fatigue, eye movements and in-vivo estimation of glucose concentration. The same concept is also used to realize a remote optical stethoscope. The advantage of doing the measurements from a distance is in preventing passage of infections as in the case of optical stethoscope or in the capability to monitor e.g. sleep quality without disturbing the patient. The remote monitoring of glucose concentration in the blood stream and the capability to perform opto-myography for the Messer muscles (chewing) is very useful for nutrition and weight control. The optical configuration for sensing the nano-vibrations is based upon analyzing the statistics of the secondary speckle patterns reflected from various tissues along the body of the subjects. Experimental results present the preliminary capability of the proposed configuration for the above mentioned applications.
We experimentally verify a speckle-based technique for noncontact measurement of glucose concentration in the bloodstream. The final device is intended to be a single wristwatch-style device containing a laser, a camera, and an alternating current (ac) electromagnet generated by a solenoid. The experiments presented are performed in vitro as proof of the concept. When a glucose substance is inserted into a solenoid generating an ac magnetic field, it exhibits Faraday rotation, which affects the temporal changes of the secondary speckle pattern distributions. The temporal frequency resulting from the ac magnetic field was found to have a lock-in amplification role, which increased the observability of the relatively small magneto-optic effect. Experimental results to support the proposed concept are presented.
In this paper we aim to experimentally verify a speckle based technique for non-contact measurement of glucose concentration in blood stream while the vision for the final device aims to contain a single wristwatch-style device containing an AC (alternating) electro-magnet generated by a solenoid, a laser and a camera. The experiments presented in work are performed in-vitro in order to verify the effects that are responsible for the operation principle. When a glucose substance is inserted into a solenoid generating an alternating magnetic field it exhibits Faraday rotation which affects the temporal changes of the secondary speckle patterns distribution. The temporal frequency resulting from the AC magnetic field was found to have a lock-in amplification role which increased the observability of the relatively small magneto-optic effect. Experimental results to support the proposed concept are presented.
In this paper we present a novel approach of realizing a safe, simple, and inexpensive sensor applicable to bone fractures
and pigmented lesions detection. The approach is based on temporal tracking of back-reflected secondary speckle pattern
generated while illuminating the affected area with a laser and applying periodic pressure to the surface via a controlled
vibration. The use of such a concept was already demonstrated for non-contact monitoring of various bio-medical
parameters such as heart rate, blood pulse pressure, concentration of alcohol and glucose in the blood stream and intraocular
pressure. The presented technique is a safe and effective method of detecting bone fractures in populations at risk.
When applied to pigmented lesions, the technique is superior to visual examination in avoiding many false positives and
resultant unnecessary biopsies. Applying a series of different vibration frequencies at the examined tissue and analyzing
the 2-D speckle pattern trajectory in response to the applied periodic pressure creates a unique signature for each and
different pigmented lesion. Analyzing these signatures is the first step toward detection of malignant melanoma. In this
paper we present preliminary experiments that show the validity of the developed sensor for both applications: the
detection of damaged bones as well as the classification of pigmented lesions.
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