Spatially Multiplexed Speckle on 1D Sensors for High-Speed 2D Sensing Applications.

Speckle pattern-based remote vibration monitoring has recently become increasingly valuable in industrial, commercial, and medical applications. The dynamic and random nature of speckle patterns offers practical applications for imaging and measurement systems. The speckle pattern is an interference pattern generated by light scattered from a rough surface onto a remote plane. It is typically sensed using area scan cameras (2D), which are limited to framerates of 2-4 kHz and can only capture a small region of interest (ROI). In this work, we propose a technique that enables the capture of synthetic 2D speckle patterns using a 1D high-acquisition-rate sensor and a diffractive optical element (DOE) to produce image replicas. The multiple replicas are scanned by the 1D sensor simultaneously at different spatial positions. This method provides an ability to sense remote vibrations in all directions, contrary to the case with a simple 1D sensing system.

Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis.

Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber's outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.

Monitoring of vital bio-signs by analysis of speckle patterns in a fabric-integrated multimode optical fiber sensor.

Continuous noninvasive measurement of vital bio-signs, such as cardiovascular parameters, is an important tool in evaluation of the patient's physiological condition and health monitoring. Based on new enabling technologies, continuous monitoring of heart and respiration rate, pulse wave velocity and blood pressure have been investigated, advanced and reflected in numerous papers published in recent years. In this paper, we introduce a new technique for noninvasive sensing of vital bio-signs based on a multimode optical fiber sensor that can be integrated into a fabric. The sensor consists of a laser, optical fiber, video camera and computer. Its operation is based on tracking of point-wise intensity variations on speckle patterns caused by interference of the light modes within the fiber subjected to deformation. The paper contains theoretical analysis and experimental validation of the proposed scheme. The main goal is to advance a simple low-cost sensor embedded in a cloth fabric to track changes in the cardiovascular condition of the wearer.

Rounding noise effects' reduction for estimated movement of speckle patterns.

The problem of resolution enhancement for speckle patterns analysis-based movement estimation is considered. In our previous publications we showed that this movement represents the corresponding tilt vibrations of the illuminated object and can be measured as a relative spatial shift between time adjacent images of the speckle pattern. In this paper we show how to overcome the resolution limitation obtained when using an optical sensor available in an optical mouse and which measures the Cartesian coordinates of the shift as an integer number of pixels. To overcome such a resolution limitation, it is proposed here to use simultaneous measurements from the same illuminated spot by a few cameras (sensors) each having imaging lenses with different amounts of defocusing. The amount of defocusing defines the proportion ratio between actual changes in the tilt plane and measured shift between speckle images. To utilize the diversity of such ratios we apply a beam-forming signal processing approach that makes it possible to achieve different design criteria and improve the measurement accuracy, respectively. The validity and properties of the proposed solution are demonstrated by a few examples of in-vivo touchless measurements of human heart beat sounds.

Large-scale clinical validation of noncontact and continuous extraction of blood pressure via multipoint defocused photonic imaging.

Blood pressure (BP) is usually measured either invasively, by an intra-arterial catheter, or noninvasively, by a cuff-based sphygmomanometer. While the invasive method is continuous and more accurate, it has the risk of infection and generally is not comfortable for the patient. On the other hand, the cuff-based measurement is safer but less reliable and infrequent. Therefore, a reliable continuous noninvasive BP measurement is highly desirable. In this work, we propose a remote optical system, based on temporal analysis of secondary reflected speckle patterns, for computing a subject's pulse transit time (PTT). Afterward, a model is proposed and clinically validated for converting the PTT value into systolic and diastolic blood pressure. A full statistical analysis is performed over a comparison to a reference device (SOMNOtouch).

Monitoring blood vital bio signs using secondary speckle patterns.

Continuous noninvasive measurement of vital bio-signs, such as cardiopulmonary parameters, is an important tool in the evaluation process of the patient's physiological condition and in the health monitoring of the patient. On the demand of new enabling technologies, some works have been done in continuous monitoring of blood pressure and pulse wave velocity. In this paper, we introduce further application of a novel technique for remote noncontact blood pulse wave velocity and pressure measurement based on tracking the temporal changes of reflected secondary speckle patterns produced in human skin when illuminated by a laser beam. The main goal of this work is to offer novel, simple and low cost measurement tool which will indicate changes in condition of the cardiovascular system after having an initial calibration.

Monitoring blood vital bio signs using secondary speckle patterns.

Continuous noninvasive measurement of vital bio-signs, such as cardiopulmonary parameters, is an important tool in the evaluation process of the patient's physiological condition and in the health monitoring of the patient. On the demand of new enabling technologies, some works have been done in continuous monitoring of blood pressure and pulse wave velocity. In this paper, we introduce further application of a novel technique for remote noncontact blood pulse wave velocity and pressure measurement based on tracking the temporal changes of reflected secondary speckle patterns produced in human skin when illuminated by a laser beam. The main goal of this work is to offer novel, simple and low cost measurement tool which will indicate changes in condition of the cardiovascular system after having an initial calibration.

Optical remote sensor for peanut kernel abortion classification.

In this paper, we propose a simple, inexpensive optical device for remote measurement of various agricultural parameters. The sensor is based on temporal tracking of backreflected secondary speckle patterns generated when illuminating a plant with a laser and while applying periodic acoustic-based pressure stimulation. By analyzing different parameters using a support-vector-machine-based algorithm, peanut kernel abortion can be detected remotely. This paper presents experimental tests which are the first step toward an implementation of a noncontact device for the detection of agricultural parameters such as kernel abortion.

Remote and low-cost intraocular pressure monitoring by deep learning of speckle patterns.

Significance: Glaucoma, a leading cause of global blindness, disproportionately affects low-income regions due to expensive diagnostic methods. Affordable intraocular pressure (IOP) measurement is crucial for early detection, especially in low- and middle-income countries. Aim: We developed a remote photonic IOP biomonitoring method by deep learning of the speckle patterns reflected from an eye sclera stimulated by a sound source. We aimed to achieve precise IOP measurements. Approach: IOP was artificially raised in 24 pig eyeballs, considered similar to human eyes, to apply our biomonitoring method. By deep learning of the speckle pattern videos, we analyzed the data for accurate IOP determination. Results: Our method demonstrated the possibility of high-precision IOP measurements. Deep learning effectively analyzed the speckle patterns, enabling accurate IOP determination, with the potential for global use. Conclusions: The novel, affordable, and accurate remote photonic IOP biomonitoring method for glaucoma diagnosis, tested on pig eyes, shows promising results. Leveraging deep learning and speckle pattern analysis, together with the development of a prototype for human eyes testing, could enhance diagnosis and management, particularly in resource-constrained settings worldwide.

Noninvasive blood glucose sensing by secondary speckle pattern artificial intelligence analyses.

Significance: Diabetes is a prevalent disease worldwide that can cause severe health problems. Accurate blood glucose detection is crucial for diabetes management, and noninvasive methods can be more convenient and less painful than traditional finger-prick methods. Aim: We aim to report a noncontact speckle-based blood glucose measurement system that utilizes artificial intelligence (AI) data processing to improve glucose detection accuracy. The study also explores the influence of an alternating current (AC) induced magnetic field on the sensitivity and selectivity of blood glucose detection. Approach: The proposed blood glucose sensor consists of a digital camera, an AC-generated magnetic field source, a laser illuminating the subject's finger, and a computer. A magnetic field is applied to the finger, and a camera records the speckle patterns generated by the laser light reflected from the finger. The acquired video data are preprocessed for machine learning (ML) and deep neural networks (DNNs) to classify blood plasma glucose levels. The standard finger-prick method is used as a reference for blood glucose level classification. Results: The study found that the noncontact speckle-based blood glucose measurement system with AI data processing allows for the detection of blood plasma glucose levels with high accuracy. The ML approach gives better results than the tested DNNs as the proposed data preprocessing is highly selective and efficient. Conclusions: The proposed noncontact blood glucose sensing mechanism utilizing AI data processing and a magnetic field can potentially improve glucose detection accuracy, making it more convenient and less painful for patients. The system also allows for inexpensive blood glucose sensing mechanisms and fast blood glucose screening. The results suggest that noninvasive methods can improve blood glucose detection accuracy, which can have significant implications for diabetes management. Investigations involving representative sampling data, including subjects of different ages, gender, race, and health status, could allow for further improvement.

Use of PC mouse components for continuous measuring of human heartbeat.

A new technology for remote measuring of vibration sources was recently developed for industrial, medical, and security-related applications [Int. Appl. Patent No: PCT/IL2008/001008]. It requires relatively expensive equipment, such as high-speed complementary metal oxide semiconductor (CMOS) sensors and customized optics. In this paper, we demonstrate how the usage of a simple personal computer (PC) mouse as an optical system composed of a low-power laser and a CMOS circuitry on the same integrated circuit package, can be used to monitor heartbeat from the wrist. The method is based on modifying the mouse optical system in such a way that it will recognize temporal change in skin's vibration profile, generated due to the heart pulses, as mouse movement. The tests that were carried out show a very good correlation between the heartbeat rate measured from human skin and the reference values taken manually.

Non-invasive blood glucose sensing by machine learning of optic fiber-based speckle pattern variation.

SIGNIFICANCE: The ability to perform frequent non-invasive monitoring of glucose in the bloodstream is very applicable for diabetic patients. AIM: We experimentally verified a non-invasive multimode fiber-based technique for sensing glucose concentration in the bloodstream by extracting and analyzing the collected speckle patterns. APPROACH: The proposed sensor consists of a laser source, digital camera, computer, multimode fiber, and alternating current (AC) generated magnetic field source. The experiments were performed using a covered (with cladding and jacket) and uncovered (without cladding and jacket) multimode fiber touching the skin under a magnetic field and without it. The subject's finger was placed on a fiber to detect the glucose concentration. The method tracks variations in the speckle patterns due to light interaction with the bloodstream affected by blood glucose. RESULTS: The uncovered fiber placed above the finger under the AC magnetic field (150 G) at 140 Hz was found to have a lock-in amplification role, improving the glucose detection precision. The application of the machine learning algorithms in preprocessed speckle pattern data increase glucose measurement accuracy. Classification of the speckle patterns for uncovered fiber under the AC magnetic field allowed for detection of the blood glucose with high accuracy for all tested subjects compared with other tested configurations. CONCLUSIONS: The proposed technique was theoretically analyzed and experimentally validated in this work. The results were verified by the traditional finger-prick method, which was also used for classification as a conventional reference marker of blood glucose levels. The main goal of the proposed technique was to develop a non-invasive, low-cost blood glucose sensor for easy use by humans.

Analysis of swallowing in infants and adults using speckle pattern analysis.

The ability to detect and evaluate ingestion is especially important in toddlers. The development of new methods for detecting and accurately measuring ingestion is therefore extremely important. One of the methods allowing such measurements is speckle pattern analyses, a well-known phenomenon in coherent imaging. The method allows extraction of various medical parameters, such as blood pulse pressure, temporal signature of heartbeats and breath. The current work contains further development and application of the speckle tracking technique for remote detection and quantification of swallowing and distinguishing between sucking and swallowing to identify feeding disorders in infants and elderly individuals.

Simultaneous remote extraction of multiple speech sources and heart beats from secondary speckles pattern.

The ability of dynamic extraction of remote sounds is very appealing. In this manuscript we propose an optical approach allowing the extraction and the separation of remote sound sources. The approach is very modular and it does not apply any constraints regarding the relative position of the sound sources and the detection device. The optical setup doing the detection is very simple and versatile. The principle is to observe the movement of the secondary speckle patterns that are generated on top of the target when it is illuminated by a spot of laser beam. Proper adaption of the imaging optics allows following the temporal trajectories of those speckles and extracting the sound signals out of the processed trajectory. Various sound sources are imaged in different spatial pixels and thus blind source separation becomes a very simple task.

Corneal thickness measurement by secondary speckle tracking and image processing using machine-learning algorithms.

Corneal thickness (CoT) is an important tool in the evaluation process for several disorders and in the assessment of intraocular pressure. We present a method enabling high-precision measurement of CoT based on secondary speckle tracking and processing of the information by machine-learning (ML) algorithms. The proposed configuration includes capturing by fast camera the laser beam speckle patterns backscattered from the corneal-scleral border, followed by ML processing of the image. The technique was tested on a series of phantoms having different thicknesses as well as in clinical trials on human eyes. The results show high accuracy in determination of eye CoT, and implementation is speedy in comparison with other known measurement methods.

Intraocular pressure remote photonic biomonitoring based on temporally encoded external sound wave stimulation.

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.

Optical realization of Viterbi decoder for communication network.

The advantages of optics that include processing speed and information throughput, modularity and versatility could be incorporated into one of the most interesting and applicable topics of digital communication related to Viterbi decoders. We aim to accelerate the processing rate and capabilities of Viterbi decoders applied for convolution codes, speech recognition, inter symbol interference (ISI) mitigation problems. The suggested configuration for realizing the decoder is based upon fast optical switches. The configuration is very modular and can easily be increased to Viterbi decoder based upon state machine with larger number of states and depth of the trellis diagram.

Approach to breast cancer early detection via tracking of secondary speckle patterns reflected from the skin with artificial intradermal impurity.

Breast cancer has become a major cause of death among women. The lifetime risk of a woman developing this disease has been established as one in eight. The most useful way to reduce breast cancer death is to treat the disease as early as possible. The existing methods of early diagnostics of breast cancer are mainly based on screening mammography or Magnetic Resonance Imaging (MRI) periodically conducted at medical facilities. In this paper the authors proposing a new approach for simple breast cancer detection. It is based on skin stimulation by sound waves, illuminating it by laser beam and tracking the reflected secondary speckle patterns. As first approach, plastic balls of different sizes were placed under the skin of chicken breast and detected by the proposed method.

Optical configuration of pigmented lesion detection by frequency analysis of skin speckle patterns.

In this paper we present a novel approach of realizing a safe, simple, and inexpensive sensor applicable to pigmented lesions detection. The approach is based on temporal tracking of back-reflected secondary speckle patterns generated while illuminating the affected area with a laser and applying periodic pressure to the surface via a controlled vibration source. 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 time varying speckle patterns 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 the classification of pigmented lesions.

Noncontact speckle-based optical sensor for detection of glucose concentration using magneto-optic effect.

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.