Biochemical detection with ultra-wideband coherent optical comb

Abstract

Systems and methods for biochemical detection using ultra-wideband coherent optical combs are provided. An example biosensor includes an optical excitation source configured to generate an optical excitation signal, a programmable optical filter, an optical detector, and a detection circuit configured to apply coherent hybrid detection. During a biosensing operation, an optical excitation signal is applied to a biochemical sample comprising at least one target biochemical reagent, and an optical detector captures a first signal comprising a spectral response corresponding to the application of the optical excitation signal. The programmable optical filter applies optical filtering to a copy of the optical excitation signal based on a matched target reference signal of the target biochemical agent to generate a second signal. The detection circuit applies coherent hybrid detection to the first signal and the generated second signal. Applying coherent hybrid detection includes combining the first signal and the second signal line by line.

Description

Technical Field

[0001] Various aspects of the present disclosure relate to sensing-related solutions, particularly biochemical detection. More specifically, certain implementations of the present disclosure relate to methods and systems for implementing and using biochemical detection using ultra-wideband coherent light combs. Background Art

[0002] By comparing existing and conventional devices and solutions systems for biochemical testing with certain aspects of the present disclosure as set forth in the remainder of this application with reference to the accompanying figures, the limitations and disadvantages of the existing and conventional devices and solutions will become apparent to those skilled in the art. Summary of the invention

[0003] There is provided a system and method for biochemical detection using an ultra-wideband coherent light comb substantially as shown in and / or described in conjunction with at least one of the accompanying drawings, as more fully set forth in the claims.

[0004] These and other advantages, aspects and novel features of the present disclosure, as well as details of illustrated embodiments thereof, will be more fully understood from the following description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] Figure 1 An example biofluid based sensor is shown.

[0006] Figure 2 is a graph showing the spectral response of a matching response that can be used for optical (photon) detection.

[0007] Figure 3 is a block diagram illustrating an example biosensor system based on the present disclosure.

[0008] Figure 4A and Figure 4B An example use case is shown when a biosensor system is utilized according to an example implementation based on the present disclosure.

[0009] Figure 5 is a flow chart showing biochemical detection using an ultra-wideband coherent light comb according to the present disclosure. DETAILED DESCRIPTION

[0010] Figure 1 An example biofluid based sensor is shown. Figure 1 Shown are a biosensor 100, a patch-based biosensor 110, a glasses-based biosensor 120, and a watch-like biosensor 130.

[0011] In this regard, a biosensor is an analytical sensing device configured to detect specific biochemical substances or agents (e.g., biochemical compounds or molecules). Typically, a biosensor combines a biological component with a physicochemical detection component. For example, a biosensor may include a biological receptor (e.g., an enzyme, an antibody, a cell, a nucleic acid, etc.), a transducer (e.g., a semiconductor material / nanomaterial), and an electronic component for providing one or more functions (e.g., signal amplification, signal processing, etc.). In some cases, a biosensor may also include additional components for providing additional functionality, such as a transceiver for transmitting data to / receiving data from the biosensor, an input / output (I / O) component for enabling user input / output, and the like. Where applicable, the components of a biological sensor may include appropriate circuits and other physical subcomponents for implementing various aspects of the functions performed by these components.

[0012] One example type of biosensor is a glucose biosensor, which is used to sense (measure) glucose in the human body. In this regard, biosensor 100, patch-based biosensor 110, glasses-based biosensor 120, and watch-like biosensor 130 may correspond to different example implementations of such a glucose biosensor. Each of these biosensors may be configured to operate by sensing a specific biological fluid in order to measure glucose in the body.

[0013] For example, the biosensor 100 may represent the most common implementation for biofluid sensing, including a physical sensor in an appropriate housing configured to measure glucose in a fluid (e.g., sweat or blood). In this regard, in some cases, the biosensor 100 may be configured to pierce or otherwise penetrate the skin, thereby enabling the measurement of glucose. Other biosensors represent alternative solutions in which sensing (and measurement) is performed without having to pierce the skin. For example, the watch-like biosensor 130 may be an electrochemical glucose meter configured to sense interstitial fluid (ISF), i.e., to sense and measure glucose in sweat expelled on the skin surface in the area below the watch-like biosensor 130. Similarly, the wearable patch-based biosensor 110 may be a glucose monitor configured for ISF sensing, i.e., to sense and measure glucose in sweat expelled on the skin surface in the area below the patch-based sensor 110. The glasses-based biosensor 120 may be a glucose monitor configured to capture the optical properties of the ISF in the eye or tears, and to sense and measure glucose therein. Other types of glucose monitors may also be used, such as integrated contact lens glucose sensors for sensing tears, temporary tattoo-based glucose monitors configured for ISF sensing, and the like.

[0014] As previously mentioned, while some biosensors, such as biofluid-based sensors, may need to be used in an invasive manner (e.g., piercing the skin), it is preferred to perform biosensing in a non-invasive manner. Therefore, some biosensors may incorporate detection technologies that can operate in a non-invasive manner. In some cases, biosensing may be achieved using, for example, optical-based detection, such as by measuring and evaluating a matching response to detect the presence, and optionally the amount, of a specific biochemical substance or agent (e.g., a specific biochemical compound, molecule, etc.). For example, Figure 1 As shown, each of the biosensor 100, the patch-based biosensor 110, the glasses-based biosensor 120, and the watch-like biosensor 130 can be configured to perform its assigned glucose biosensing function using optical-based detection. Nevertheless, the present disclosure is not limited to glucose biosensors, and solutions based on the present disclosure can be used in any appropriate biosensor that can utilize optical detection.

[0015] Optical based detection can be accomplished using matched response based photon detection. This can be accomplished by applying a light source (e.g., a laser source) to a specific biofluid or any appropriate biochemical material and then detecting and measuring the spectral response. The spectral response can then be matched to available known response data, e.g., the absorption properties of identified biochemicals at specific wavelengths, to identify the biochemical compounds or molecules that may be present. See Figure 2 , photon detection based on matched responses is described in more detail.

[0016] Figure 2 is a graph showing the spectral response of a matching response that can be used for optical (photon) detection. Figure 2 Shown are graph 200 and graph 210 .

[0017] In this regard, graph 200 includes data representing an absorption response (y-axis) based on a near infrared spectrum (NIR) as a function of wavelength (x-axis). In particular, the data captured in graph 200 corresponds to different biochemical substances / molecules, such as urea, lactic acid, triacetin, ascorbic acid (vitamin C), alanine, and glucose. As shown in graph 200, although there is no or almost no obvious resonance in the first overtone region, different molecules exhibit different absorption behaviors across the spectrum. Graph 210 includes data representing an absorption response (y-axis) based on a mid-infrared (Mid-IR) spectrum as a function of wavelength (x-axis). In particular, the data captured in graph 200 shows the light absorption rate of human blood, particularly by (unoxidized) hemoglobin and oxidized hemoglobin. As shown in graph 210, the data is obtained using illumination of a specific wavelength range (e.g., 2.5-25µm or 2.5-10µm), such as using a quantum cascade laser. As shown in graph 210, hemoglobin exhibits a peak absorption response at ~3.3 µm to ~7.1 µm, with a stronger signal absorption at ~8.3-10 µm. Nevertheless, across the spectrum, unoxidized hemoglobin exhibits different absorption behavior than oxidized hemoglobin.

[0018] As described above, biosensors incorporating matched response-based detection can utilize known spectral responses (e.g., as shown in graphs 200 and 210). In this regard, in a solution utilizing optical (photonic) detection based on response matching, a laser is projected onto the sample being tested, and then the spectral response is measured and analyzed (e.g., with respect to such known spectral response). Doing this over a wide band of the spectrum allows for the construction of a spectral response that can be matched to the spectral response of a known molecule.

[0019] Conventional solutions based on matching responses of amplitudes detected at multiple wavelengths may be used, which may have some limitations and / or disadvantages. In this regard, various designs can be used to implement optical (photon) detection based on response matching. For example, in some implementations, multiple narrow linewidth lasers can be used to map the intensity response over a wide spectral range (at different frequencies or wavelengths) to identify the target biochemical agent based on the predetermined absorption spectral response of the reference agent. In this regard, the target (e.g., a sample of a biological fluid, etc.) can be illuminated, for example, by using an array of lasers with known wavelengths. An array-based implementation may include an array of lasers (with high power consumption), each of which is locked to a specified wavelength. Alternatively, a tunable laser can be used to sample the spectral response of different wavelengths, such as by scanning at least a portion of the spectrum line by line (e.g., at different frequencies or wavelengths) over a period of time. However, this may bring some problems because the target absorption intensity at each wavelength point may vary with time, temperature, size, etc. The agent may also move, so the longer the scanning and detection time, the greater the uncertainty that may be introduced. In addition, measuring the spectral response may usually require measuring both phase and amplitude. However, in existing solutions, it may not be possible to capture both phase and amplitude data simultaneously. In this regard, capturing the phase response of a target biochemical agent (e.g., a molecule) may not be possible because the target absorption spectrum may be masked by many surrounding materials with similar ensemble responses.

[0020] Solutions based on the present disclosure can address some of the limitations and shortcomings of existing solutions. In this regard, implementations based on the present disclosure can combine various features to provide improved detection of biochemical agents (e.g., compounds, molecules, etc.) even in the presence of surrounding materials with similar responses. For example, a highly correlated dense optical frequency laser comb source can be utilized to enable recording of the correlated intensity and phase responses of a target agent over a wide spectral range, and simultaneously in a short-time snapshot to avoid the movement of the agent. Coherent detection can be provided, for example, by mixing spectral comb lines of the optical response of the absorption from an unknown sample with a pre-trained reference optical comb response carrying the spectral response of the target biochemical agent (e.g., molecule), which can be obtained via a reference path. In particular, the sample signal can be spectrally mixed with the spectral response reference signal line by line, such as in a photodetector that emphasizes the spectral product of the response of the target agent and the correlation of the reference, while distinguishing between background and noise. An optical frequency laser comb source, such as a mode-locked or gain-switched laser, can be used as an optical excitation source to illuminate the target agent and the pre-trained reference filter in the reference path to be mixed into the detector. Alternatively, real samples of the target agent can be utilized instead of the programmed / trained optical filters used in the reference path. Since the line-by-line frequency responses of the target agent and the reference filter are derived from the same source, they are coherently mixed in one detector to collect the ensemble similarity of amplitude and phase of each comb line across the entire spectral range. This coherent detection using one detector avoids the need to lock the laser frequency to a known frequency standard and a bank of detectors to collect the line-by-line frequency response in conventional methods.

[0021] A spectral response reference signal can be coherently created by passing a portion of the same excitation laser comb source through a prescribed optical filter whose spectral shape and response (also referred to as a "reference filter response") is programmed to simulate a target biochemical agent (e.g., molecule). The reference filter response can be constructed to simulate collected library data (e.g., trained using a validated data set) or trained to fit the response using a known agent as a target sample (e.g., trained using a known physical reference material). In some cases, advanced processing techniques, such as through processing based on artificial intelligence (AI) (e.g., machine learning (ML)), can be used to control various aspects of the detection process, such as the construction of the reference filter response, to improve the simulation accuracy under controlled environmental noise. Example implementations of biosensors based on the present disclosure, such as Figure 3 Shown and referenced Figure 3 Give a description.

[0022] Figure 3is a block diagram illustrating an example biosensor system based on the present disclosure. Figure 3 A biosensor system (or a portion thereof) 300 is shown.

[0023] The biosensor system 300 may include appropriate circuitry for performing optical biosensing-based functions according to the present disclosure. In particular, the biosensor system 300 may be configured to perform enhanced biochemical detection using an optical excitation signal (e.g., a laser signal), such as using a set of ultra-wideband coherent light combs, as described herein. Figure 3 As shown in the illustrated example implementation, the biosensor system 300 includes an optical excitation source 310 , a control and spectral library block 320 , a programmable optical filter 330 , an optical filter 340 , and an associated coherent mixing detection block 350 .

[0024] The optical excitation source 310 may include appropriate circuitry for generating and outputting an excitation signal that satisfies certain predetermined characteristics. In particular, the optical excitation source 310 is configured to generate an optical excitation signal having an emission spectrum consisting of a series of discrete frequency lines. In this regard, it is not necessary to have equal spacing between the comb lines. In an example implementation, two responses for each frequency line for each single line can be obtained, and then the row-by-row results can be added together in a detector. This can be referred to as self-referenced row-by-row mixing. In an example implementation, the optical excitation source 310 may include a pulse comb laser source configured to emit a laser excitation signal that satisfies certain predetermined characteristics, such as an excitation signal emitted from a mode-locked laser, a gain-switched laser, or a set of coherent comb lines generated by a nonlinear medium.

[0025] The control and spectral library block 320 may include appropriate circuitry for providing optical shaping functions associated with the control of optical filters and for maintaining a spectral library of reference signals that simulate various known reagents for use during processing in the biosensor system 300. In this regard, the control and spectral library block 320 may be configured to generate and transmit control signals for controlling the operation of the optical response of one or more other reference components in the biosensor system 300. In addition, the control and spectral library block 320 may provide a reference optical response of a comb source that is ready for coherent detection with a target biochemical reagent. In this regard, the control and spectral library block 320 may maintain a spectral library of one or more reagents. The control and spectral library block 320 may be configured to generate and / or update spectral related data to simulate (including, for example, reference signals) one or more reagents. In some cases, the control and spectral library block 320 may be configured to update the spectral library based on feedback data obtained from processing a specific reagent learned in the biosensor system 300.

[0026] In some cases, the control and spectral library block 320 can be configured to use advanced processing techniques in combination, such as AI / ML-based processing. In this regard, AI / ML-based processing can be used, for example, to construct and / or modify data (e.g., reference signals) in a spectral library. For example, a machine learning (ML) algorithm can be used to construct and update a reference matched response spectral signal. Such machine learning (ML) algorithms may include, for example, algorithms based on linear regression, algorithms based on nonlinear regression, algorithms based on logistic regression, and algorithms based on decision tree ensembles (e.g., gradient enhancement or random forests), algorithms based on neural networks, algorithms based on recursive neural networks, long short-term memory networks, Gaussian process algorithms, Bayesian algorithms, graph neutral networks, hyperdimensional computing, generative adversarial networks, transformers, Chat-GPT, large language models, and the like.

[0027] The programmable optical filter 330 may include appropriate circuitry for performing optical filtering. In this regard, the programmable optical filter 330 may be configured to filter the input signal based on a pre-programmed filter spectrum shape and response (i.e., a reference filter response of the programmable optical filter 330). The reference filter response may be programmed based on a reference signal provided by the control and spectral library block 320.

[0028] The optical amplifier 340 may include appropriate circuitry for performing optical amplification on the input signal. In this regard, the optical amplifier 340 may be configured to apply a predefined gain and / or time delay to the input signal to calibrate and optimize coherent detection based on hardware differences in the test setup between the two signal paths through the sample and reference filters. In some cases, the optical amplifier 340 may be programmable, and the applied gain and delay are thereby calibrated (e.g., in coordination with the control and spectral library block 320 or any other controller in the system).

[0029] The correlated coherent mixing detection block 350 may include appropriate circuitry for performing optical detection, and may specifically perform optical detection based on correlated coherent mixing as described herein.

[0030] In operation, the biosensor system 300 can be used to perform biochemical detection. In this regard, the optical excitation source 310 can provide an excitation signal source (e.g., a laser) for biochemical sensing. The excitation signal is adaptively configured to enable recording of intensity and phase responses over a wide spectral range, and is so recorded while (or at least in parallel) passing through the target agent and the reference optical filter in parallel. In particular, the excitation signal generated by the optical excitation source 310 can include a signal (e.g., a laser pulse signal) having a spectrum consisting of a series of discretely spaced combs (frequency lines). A portion of the excitation signal passes through the target (e.g., body contact) 360, and the corresponding spectral response is captured, such as by the photodetector 352. In this regard, in addition to the spectral response of the target biochemical agent, the spectral response can also include other spectral responses corresponding to surrounding materials (thereby effectively constituting noise).

[0031] Another portion of the excitation signal (i.e., as an input signal) is also provided to the programmable optical filter 330, which can be configured to apply a pre-trained optical filtering response based on a preset standard of a reference reagent. Specifically, the programmable optical filter 330 can be programmed by the control and spectral library block 320. In this regard, to facilitate programming, the control and spectral library block 320 can provide control and programming of the filter so that a spectral response that simulates the reference reagent is produced by the programmable optical filter 330. Therefore, the programmable optical filter 330 generates as an output a signal representing the spectral response of the matched target spectral reference signal at the output of the programmed optical filter. The output of the programmable optical filter 330 is then amplified via an optical amplifier 340, and the output of the optical amplifier 340 is then input into an associated coherent mixing detection block 350 for coherent mixing simultaneously with the captured spectral response. An example use case in the biosensor system 300 is shown in FIG. Figure 4A and Figure 4B A more detailed explanation and description is given in.

[0032] Figure 4A and Figure 4B An example use case when utilizing a biosensor system according to an example implementation based on the present disclosure is shown. Figure 4A and Figure 4B Shown are signals that may be generated in the biosensor system 300 during an example use case scenario.

[0033] In this regard, the optical excitation source 310 generates an excitation signal 400 that is adaptively configured to enable recording of the intensity and phase responses of a frequency comb set to cover a wide spectral range, and to do so simultaneously (or at least in parallel). Figure 4AAs shown, the excitation signal 400 can be one or a group of pulse signals covering multiple frequency bands (as shown in the time domain diagram, a group of pulses is used for one frequency band), and each pulse processes a spectrum consisting of a series of related discrete, equidistant combs (related frequency lines), as shown in the frequency domain diagram. The excitation signal 400 is applied to a target (e.g., body contact), which may include target biochemical materials (reagents) and background (non-target) materials. Example spectral profiles of target biochemical materials and background materials are shown in graphs 420 and 430, respectively. Therefore, applying a portion of the excitation signal 400 to the target results in spectral responses corresponding to the target biochemical materials and background materials. In this regard, the spectral responses of the target biochemical materials and background materials are shown in graphs 440 and 450, respectively. As shown, each spectral response includes multiple lines with corresponding amplitudes and phases, which are set (adjusted) based on the corresponding spectral profiles of the target biochemical materials and background materials (graphs 420 and 430). As such, the combined spectral response signal 470 (as captured by the photodetector 352) includes the spectral responses of the target biochemical material and the background material.

[0034] At the same time, the remaining portion of the excitation signal 400 is used to generate a spectral response reference signal 480. In this regard, the spectral response reference signal 480 is simultaneously created by applying the excitation signal 400 to an optical filter configured to produce a prescribed filtered spectral shape and response, such as by using a pre-trained matched spectral reference signal of the target agent 460 (which can be provided by control parameters from the pre-trained spectral library block 320). In this regard, the matched target spectral reference signal 460 corresponds to a pre-trained spectral representation of the target material stored (e.g., built) in the system. Thus, optical filtering allows the excitation signal 400 to be configured according to the pre-trained spectral characteristics corresponding to the target biochemistry, i.e., the amplitude and phase at each discrete frequency line are prescribed. The output of the optical filtering is then optically amplified (e.g., via the optical amplifier 340) to balance the path loss differences and delays of the test setup, thereby generating the spectral response reference signal 480. Thus, when subjected to the excitation signal 400 in the absence of any background material, the spectral response reference signal 480 effectively represents an amplified copy of the spectral response of the target material.

[0035] The spectral response reference signal 480 and the combined spectral response signal 470 are then subjected to correlated coherent mixing detection (e.g., via correlated coherent mixing detection block 350). In this regard, the correlated coherent mixing detection includes coherently combining (e.g., by multiplication) the spectral response reference signal 480 and the combined spectral response signal 470 line by line, so that for each comb line, when the frequency response of the target agent is similar to the frequency response from the reference filter, a larger response (impulse) is generated if the ensemble from all comb lines is constructively added together over the spectral range compared to the uncorrelated frequency response from the background material; thereby allowing the background material to be filtered out. In this regard, because the amplitude and phase of each comb line are not matched over the spectral range, the ensemble response corresponding to the background material will be destructively combined and significantly reduced.

[0036] In some cases, the results of the relevant coherent mixing detection can be used to update the spectral profile of the target material or to establish a new target material. For example, when a known material is used as the target material, the results of the relevant coherent mixing detection can be fed back to optimize the control parameters of the optical filter, thereby updating the existing reference element library into the spectral library block 320.

[0037] In some implementations, the same processing pathways described herein can be used to construct and / or calibrate a spectral library. For example, a sample of a particular biochemical reagent can be tested in a controlled environment, that is, without any background material. The corresponding captured spectral response can then enable the creation of a new reference signal in the spectral library, or the updating of an existing reference signal.

[0038] Figure 5 is a flow chart showing biochemical detection using an ultra-wideband coherent light comb according to the present disclosure. Figure 5 Shown is a flowchart 500 including a number of example steps (represented as blocks 502-512) that may be implemented in a suitable system (e.g., Figure 3 The invention is implemented in a biosensor system 300) to provide enhanced biochemical detection using an ultra-wideband coherent light comb.

[0039] In step 502, an excitation signal is generated (e.g., by one or more pulse comb laser sources). The number of laser sources with associated frequency lines will be selected to provide a spectral range or band in which a particular material or agent of interest exhibits significant spectral characteristics. A portion of the excitation signal is then applied to an object including a target biochemical agent / material, and possibly a different kind of background material. Another portion of the excitation signal is simultaneously provided to an optical filter that is configured based on a matching response spectral reference (signal) corresponding to the target biochemical agent / material.

[0040] In step 504, a spectral response from applying an excitation signal to a target is captured, for example, to generate a combined spectral response signal including spectral responses corresponding to the target biochemical agent / material and background material.

[0041] In step 506, the optically filtered response from the replica of the excitation signal is shaped to match the response as a pre-trained spectral reference for the target agent, and in step 508, optical amplification is applied to the output of the optical filtering to generate a reference comb signal carrying the reference spectral response of the target agent.

[0042] In step 510, the spectral response reference signal is coherently mixed with the captured spectral response from the sample (eg, into a combined spectral response for each frequency line), and in step 512, detection is performed based on the ensemble results of the coherently mixed frequency lines.

[0043] Therefore, the solution based on the present disclosure provides many advantages over existing solutions. In particular, the implementation based on the present disclosure allows the use of amplitude and phase information for positive discrimination. When multiple independent excitation laser sources are used, this can allow more accurate correlation spectral responses to frequencies within a wide spectral coverage range line by line without knowing or being locked to a specific frequency grid. These implementations can also have high sensitivity. In this regard, matched filter operations can reduce random noise and responses from unwanted background materials, and / or the use of coherent gain provided by amplified and shaped reference light from the same excitation laser source. In addition, the need for frequency measurement in these implementations can be eliminated, such as using a frequency grid or frequency locking. This is due to the accuracy of coherent self-reference detection within the photon lifetime of the source laser. In addition, a small number of low-cost gain-switched or mode-locked pulsed lasers can also be used to cover a large spectral range. In addition, these implementations can be combined with advanced processing techniques, such as using cognitive learning and AI / ML tracking. In this regard, the use of these techniques can allow multi-domain identification of multiple biological agents with complex spectral responses. In addition, such technology can also allow adaptation to changes in the physical channel from changes in contacts and environment.

[0044] An example system for biosensing according to the present disclosure includes: an optical excitation source configured to generate an optical excitation signal; a programmable optical filter configured to apply optical filtering; an optical detector; and a detection circuit configured to apply coherent mixing detection; wherein the system is configured such that during a biosensing operation: the optical excitation signal is applied to a biochemical sample, the biochemical sample including at least one target biochemical reagent; the optical detector captures a first signal, the first signal including a spectral response corresponding to the application of the optical excitation signal to the biochemical sample; the programmable optical filter applies optical filtering to a copy of the optical excitation signal based on a matched target reference signal, the matched target reference signal including a spectral response profile of at least one target biochemical reagent; and the detection circuit applies coherent mixing detection to the first signal and a second signal generated based on applying the optical filtering to the copy of the optical excitation signal, wherein applying the coherent mixing detection includes combining the first signal and the second signal row by row.

[0045] In one example embodiment, the optical excitation source comprises a pulsed comb laser source.

[0046] In one example implementation, the system further includes an optical amplifier configured to apply optical amplification to enhance coherent mixing gain in the detector, wherein the optical amplifier applies the optical amplification to an output of the programmable optical filter to generate a second signal.

[0047] In one example embodiment, the system further includes control and spectral library circuitry configured to provide a reference signal for use in detecting one or more target biochemical agents.

[0048] In one example implementation, the control and spectral library circuit is configured to provide a matched target reference signal to the programmable optical filter.

[0049] In one example implementation, the control and spectral library circuitry is configured to provide control data to the detection circuitry to apply coherent mixing detection.

[0050] In one example implementation, the control and spectral library circuitry is configured to maintain a spectral library including one or more reference signals corresponding to one or more target biochemical agents.

[0051] In one example embodiment, the control and spectral library circuit is configured to generate or update at least one of the reference signals in the spectral library.

[0052] In one example implementation, the control and spectral library circuitry is configured to generate or update at least one reference signal using artificial intelligence (AL) based processing.

[0053] In one example implementation, the control and spectral library circuitry is configured to apply machine learning (ML) when using artificial intelligence (AL) based processing.

[0054] An example method for biosensing according to the present disclosure includes: generating an optical excitation signal via an optical excitation source; applying the optical excitation signal to a biochemical sample, the biochemical sample including at least one target biochemical reagent; capturing a first signal via an optical detector, the first signal including a spectral response to the biochemical sample to which the optical excitation signal is applied; applying optical filtering to a copy of the optical excitation signal via a programmable optical filter based on a matched target reference signal, the matched target reference signal including a spectral response profile of the at least one target biochemical reagent; and applying coherent mixing detection to the first signal and a second signal generated based on applying the optical filtering to the copy of the optical excitation signal; wherein applying the coherent mixing detection includes combining the first signal and the second signal row by row.

[0055] In one example implementation, the optical excitation signal comprises a pulse comb laser signal.

[0056] In one example embodiment, the method further comprises applying optical amplification to the output of the optical filtering to generate a second signal.

[0057] In one example implementation, the method further includes configuring optical filtering based on the matched target reference signal.

[0058] In one example embodiment, the method further includes configuring optical filtering to reshape the replica of the optical excitation signal based on the matched target reference signal.

[0059] In an example embodiment, the method further comprises generating control data for controlling the application of the coherent hybrid detection.

[0060] In an example embodiment, the method further includes maintaining a spectral library including one or more reference signals corresponding to one or more target biochemical agents.

[0061] In one example embodiment, the method further comprises generating or updating at least one of the reference signals in the spectral library.

[0062] In one example embodiment, the method further comprises generating or updating at least one reference signal using artificial intelligence (AL) based processing.

[0063] In one example embodiment, the method further comprises, when using artificial intelligence (AL) based processing, applying machine learning (ML).

[0064] As used herein, "and / or" refers to any one or more items in a list connected by "and / or". For example, "x and / or y" refers to any element in the three-element set {(x), (y), (x, y)}. In other words, "x and / or y" means "one or both of x and y". For another example, "x, y and / or z" refers to any element in the seven-element set {(x), (y), (z), (x,y), (x, z), (y, z), (x, y, z)}. In other words, "x, y and / or z" means "one or more of x, y and z". As used herein, the term "exemplary" refers to serving as a non-limiting example, instance, or illustration. As used herein, the terms "for example" and "such as" list one or more non-limiting examples, instances, or illustrations.

[0065] As used herein, the terms "circuit" and "circuitry" refer to physical electronic components (e.g., hardware) and any software and / or firmware ("code") that can configure the hardware, be executed by the hardware, or otherwise be associated with the hardware. As used herein, for example, a particular processor and memory (e.g., a volatile or non-volatile storage device, a general-purpose computer-readable medium, etc.) may include a first "circuit" when executing a first line or more lines of code, and may include a second "circuit" when executing a second line or more lines of code. In addition, a circuit may also include analog and / or digital circuits. For example, such a circuit may operate on analog and / or digital signals. It should be understood that a circuit may be in a single device or chip, on a single motherboard, in a single chassis, in multiple packages in a single geographic location, distributed in multiple packages in multiple geographic locations, and so on. Similarly, the term "module" may refer to, for example, physical electronic components (e.g., hardware) and any software and / or firmware ("code") that can configure the hardware, be executed by the hardware, or otherwise be associated with the hardware.

[0066] As utilized herein, a circuit or module is “operable” to perform a function so long as the circuit or module includes the necessary hardware and code (if any is necessary) to perform the function, regardless of whether performance of the function is disabled or not enabled (e.g., by user-configurable settings, factory adjustments, etc.).

[0067] Other embodiments of the present invention may provide a non-temporary computer-readable medium and / or storage medium, and / or a non-temporary machine-readable medium and / or storage medium having machine code and / or a computer program stored thereon, the computer program having at least one code segment executable by a machine and / or computer, thereby causing the machine and / or computer to perform the process described herein.

[0068] Therefore, various embodiments according to the present invention can be implemented by hardware, software or a combination of hardware and software. The present invention can be implemented in at least one computing system in a centralized manner, or in a distributed manner, wherein different elements are distributed in multiple interconnected computing systems. Any type of computing system or other device suitable for executing the methods described herein is applicable. A typical implementation may include one or more application-specific integrated circuits (ASICs), one or more field programmable gate arrays (FPGAs), and / or one or more processors (e.g., x86, x64, ARM, PIC and / or any other suitable processor architecture) and associated support circuits (e.g., memory, DRAM, FLASH, bus interface circuits, etc.). Each discrete ASIC, FPGA, processor or other circuit may be referred to as a "chip", and multiple such circuits may be referred to as a "chipset". Another implementation may include a non-temporary machine-readable (e.g., computer-readable) medium (e.g., a FLASH drive, an optical disk, a magnetic storage disk, etc.), on which one or more lines of code are stored, which, when executed by a machine, enable the machine to execute the process described in the present disclosure. Another implementation may include a non-transitory machine-readable (e.g., computer-readable) medium (e.g., a FLASH drive, an optical disk, a magnetic storage disk, etc.) having stored thereon one or more lines of code that, when executed by the machine, may cause the machine to be configured (e.g., software and / or firmware is loaded into its circuits) to operate as the system described in the present disclosure.

[0069] The embodiments according to the present invention may also be embedded in a computer program product, which includes all functions capable of implementing the methods described herein and can execute these methods when loaded into a computer system. The computer program herein refers to a set of instructions expressed in any language, code or symbol, the purpose of which is to enable a system with information processing capabilities to perform specific functions directly or after either or both of the following: a) conversion into another language, code or symbol; b) reproduction in a different material form.

[0070] Although the present method and / or system has been described with reference to certain implementations, it will be appreciated by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present method and / or system. In addition, many modifications may be made to adapt particular circumstances or materials to the teachings of the present disclosure without departing from the scope of the present disclosure. Therefore, the present method and / or system is not intended to be limited to the specific implementations disclosed, but rather the present method and / or system will include all implementations falling within the scope of the appended claims.

Claims

1. A system for biosensing, the system comprising: an optical excitation source configured to generate an optical excitation signal; a programmable optical filter configured to apply optical filtering; Optical detectors; as well as a detection circuit configured to apply coherent hybrid detection; Wherein, the system is configured such that during a biosensing operation: applying the optical excitation signal to a biochemical sample, the biochemical sample comprising at least one biochemical agent of interest; the optical detector capturing a first signal comprising a spectral response corresponding to application of the optical excitation signal to the biochemical sample; The programmable optical filter applies optical filtering to a copy of the optical excitation signal based on a matched target reference signal, the matched target reference signal comprising a spectral response profile of the at least one target biochemical agent; and The detection circuit applies coherent mixing detection to the first signal and a second signal produced based on applying the optical filtering to the copy of the optical excitation signal, wherein applying coherent mixing detection includes combining the first signal and the second signal row by row.

2. The system according to claim 1, wherein: The optical excitation source includes a pulse comb laser source.

3. The system of claim 1 , further comprising an optical amplifier configured to apply optical amplification, and wherein: The optical amplification applies optical amplification to an output of the programmable optical filter to generate the second signal.

4. The system of claim 1, further comprising control and spectral library circuitry configured to provide a reference signal for use in detecting one or more target biochemical agents.

5. The system according to claim 4, wherein: The control and spectral library circuit is configured to provide the matched target reference signal to the programmable optical filter.

6. The system according to claim 4, wherein: The control and spectral library circuit is configured to provide control data to the detection circuit to apply the coherent mixing detection.

7. The system according to claim 4, wherein: The control and spectral library circuitry is configured to maintain a spectral library including one or more reference signals corresponding to the one or more target biochemical agents.

8. The system according to claim 7, wherein: The control and spectral library circuit is configured to generate or update at least one of the reference signals in the spectral library.

9. The system according to claim 8, wherein: The control and spectral library circuitry is configured to generate or update the at least one reference signal using artificial intelligence AL based processing.

10. The system according to claim 9, wherein: The control and spectral library circuitry is configured to apply machine learning ML when using the artificial intelligence AL based processing.

11. A method for biosensing, the method comprising: generating an optical excitation signal via an optical excitation source; applying the optical excitation signal to a biochemical sample, the biochemical sample comprising at least one biochemical agent of interest; capturing, via an optical detector, a first signal comprising a spectral response corresponding to application of the optical excitation signal to the biochemical sample; applying optical filtering to a copy of the optical excitation signal via a programmable optical filter based on a matched target reference signal comprising a spectral response profile of the at least one target biochemical agent; as well as applying coherent mixing detection to the first signal and a second signal generated based on applying the optical filtering to the copy of the optical excitation signal; Therein, applying coherent hybrid detection comprises combining the first signal and the second signal row by row.

12. The method according to claim 11, wherein: The optical excitation signal includes a pulse comb laser signal.

13. The method of claim 11, further comprising applying optical amplification to the optically filtered output to generate the second signal.

14. The method of claim 11, further comprising configuring the optical filtering based on the matched target reference signal.

15. The method of claim 14, further comprising configuring the optical filtering to reshape the replica of the optical excitation signal based on the matched target reference signal.

16. The method of claim 11, further comprising generating control data for controlling application of the coherent hybrid detection.

17. The method of claim 11, further comprising maintaining a spectral library comprising one or more reference signals corresponding to one or more target biochemical agents.

18. The method of claim 17, further comprising generating or updating at least one of the reference signals in the spectral library.

19. The method of claim 18, further comprising generating or updating the at least one reference signal using artificial intelligence (AL) based processing.

20. The method according to claim 19, further comprising applying machine learning (ML) when using the artificial intelligence (AL) based processing.

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