Patent Description:
A biosensor (e.g., a lateral flow device, such as a lateral flow assay (LFA)) is a device that is capable of detecting a condition, disease, etc., in a human or animal based on a sample (e.g., a blood sample, a saliva sample, a urine sample, etc.) from the human or animal. LFAs have been used to detect the presence of a target analyte to determine pregnancy, presence of HIV, presence of Ebola, presence of different toxins, etc.
<CIT> describes a multiplex lateral flow device array that can include a number of immobilisation zones arranged in a pattern such that digits can be formed for observation by a user. <CIT> describes a multi-assay immunochromatographic chip that can include a number of detection zones in a fixed pattern. <CIT> describes a lateral flow device with two-dimensional features that can include a number of reagent dots for detecting multiple analytes. <CIT> describes a microfluidic device that can include a number of capture regions in a fixed pattern. <CIT> describes a lateral flow test or immunochromatographic device that can include a number of trapping areas.

The figures are not to scale. Instead, the thickness of the layers or regions may be enlarged in the drawings. In general, the same reference numbers will be used throughout the drawing(s) and accompanying written description to refer to the same or like parts. As used in this patent, stating that any part (e.g., a layer, film, area, region, or plate) is in any way on (e.g., positioned on, located on, disposed on, or formed on, etc.) another part, indicates that the referenced part is either in contact with the other part, or that the referenced part is above the other part with one or more intermediate part(s) located therebetween. Connection references (e.g., attached, coupled, connected, and joined) are to be construed broadly and may include intermediate members between a collection of elements and relative movement between elements unless otherwise indicated. As such, connection references do not necessarily infer that two elements are directly connected and in fixed relation to each other. Stating that any part is in "contact" with another part means that there is no intermediate part between the two parts. Although the figures show layers and regions with clean lines and boundaries, some or all of these lines and/or boundaries may be idealized. In reality, the boundaries and/or lines may be unobservable, blended, and/or irregular.

A biosensor or test strip device (e.g., lateral flow immunoassay (LFA)) is a device or diagnostic test strip that includes a first region to obtain a sample (e.g., blood, urine, saliva, etc.) and a second region that changes color when a target analyte corresponding to a particular disease or condition is present in the sample. For example, a user applies the sample to a sample pad of a test strip device, or simply "test strip" (e.g., an LFA, etc.). Once applied, the sample migrates along the test strip to a conjugate pad that contains conjugates (e.g., detectable labels, tags, linkers, antibodies, antigens, etc.) specific to the target analyte. If the sample includes the target analyte, a chemical reaction will occur on the conjugate pad to bind the target analyte with the conjugates. The test strip also includes a test line that contains immobilized antibodies and/or antigens specific to the target analyte, which bind the first set of conjugate molecules (e.g., probe molecules) from the conjugate pad. For example, if the analyte of interest is an antibody, the positive test area includes immobilized antigen. If the analyte of interest is an antigen, the positive test area includes immobilized antibody. The labeled substance or conjugate includes a first binding component that is able to bind the analyte of interest and a second visualization component. Accordingly, when the sample (e.g., including the bounded target analyte) flows to a test zone (e.g., a reaction zone), the antibodies or antigens of the test line bind to the bounded target analyte, thereby immobilizing the target analyte. In some test strips, the immobilized target analytes result in a visual output that identifies that the target analyte was present in the sample. Accordingly, an optical scanner or user can identify whether the target analyte (e.g., corresponding to a condition or disease) is present in the sample based on the color of the test zone.

"Target analyte", "analyte" or "analyte of interest" refers to the compound or the composition to be detected or measured from the sample, which has at least one epitope or binding site. The analyte can be any substance for which there exists a naturally occurring analyte-specific binding member or for which an analyte-specific binding member can be prepared. Analytes include, but are not limited to, toxins, organic compounds, proteins, peptides, microorganisms, amino acids, nucleic acids, hormones, steroids, vitamins, drugs (including those administered for therapeutic purposes as well as those administered for illicit purposes), and/or metabolites of or antibodies to any of the above substances. The term "analyte" also includes any antigenic substances, haptens, antibodies, macromolecules, and/or combinations thereof.

"Label" refers to any substance which is capable of producing a signal that is detectable by visual and/or instrumental means. Various labels suitable for use in examples disclosed herein include labels that produce signals through chemical and/or physical means. Examples include enzymes and substrates, chromagens, fluorescent compounds, chemiluminescent compounds, colored or colorable organic polymer latex particles, liposomes, and/or other vesicles containing directly visible substances. In some examples radioactive labels, colloidal metallic particles, and/or colloidal non-metallic particles are employed. In some examples, labels include colloidal gold and latex particles.

"Labeled substance" or "conjugate" refers to a substance that includes a detectable label attached to a specific binding member. The attachment may be covalent or non-covalent binding and may include nucleic acid hybridization. The label allows the labeled substance to produce a detectable signal that is directly or indirectly related to the amount of analyte in a test sample. The specific binding member component of the labeled substance is selected to bind directly or indirectly to the analyte.

"Specific binding member" refers to a member of a specific binding pair (e.g., two different molecules wherein one of the molecules specifically binds to the second molecule through chemical or physical means). If the specific binding member is an immunoreactant it can be, for example, an antibody, antigen, hapten, or complex thereof, and if an antibody is used, it can be a monoclonal or polyclonal antibody, a recombinant protein or antibody, a chimeric antibody, a mixture(s) or fragment(s) thereof, as well as a mixture of an antibody and other specific binding members. Specific examples of specific binding members include biotin and avidin, an antibody and its corresponding antigen (both having no relation to a sample to be assayed), a single stranded nucleic acid and its complement, and the like.

A "test strip" or "LFA" can include one or more bibulous or non-bibulous materials. If a test strip includes more than one material, the one or more materials are preferably in fluid communication. One material of a test strip may be overlaid on another material of the test strip, such as for example, filter paper overlaid on nitrocellulose. Additionally or alternatively, a test strip may include a region including one or more materials (e.g., media) followed by a region including one or more different materials. In this case, the regions are in fluid communication and may or may not partially overlap one another. Suitable materials for test strips include, but are not limited to, materials derived from cellulose, such as filter paper, chromatographic paper, nitrocellulose, and cellulose acetate, as well as materials made of glass fibers, nylon, dacron, polyvinyl chloride (PVC), polyacrylamide, cross-linked dextran, agarose, polyacrylate, ceramic materials, and the like. The material or materials of the test strip may optionally be treated to modify their capillary flow characteristics or the characteristics of the applied sample. For example, the sample application region of the test strip may be treated with buffers to correct the pH or specific gravity of an applied urine sample, to ensure optimal test conditions.

The material or materials can be a single structure such as a sheet cut into strips or it can be several strips or particulate material bound to a support or solid surface such as found, for example, in thin-layer chromatography and may have an absorbent pad either as an integral part or in liquid contact. The material can also be a sheet having lanes thereon, capable of spotting to induce lane formation, wherein a separate assay can be conducted in each lane. The material can have a rectangular, circular, oval, triagonal or other shape provided that there is at least one direction of traversal of a test solution by capillary migration. Other directions of traversal may occur such as in an oval or circular piece contacted in the center with the test solution. However, the main consideration is that there be at least one direction of flow to a predetermined site. In the following discussion test strips will be described by way of illustration and not limitation.

The support for the test strip, where a support is desired or necessary, will normally be water insoluble, frequently non-porous and rigid but may be elastic, usually hydrophobic, and porous and usually will be of the same length and width as the strip but may be larger or smaller. The support material can be transparent, and, when a test device disclosed herein is assembled, a transparent support material can be on the side of the test strip that can be viewed by the user, such that the transparent support material forms a protective layer over the test strip where it may be exposed to the external environment, such as by an aperture in the front of a test device. A wide variety of non-mobilizable and non-mobilizable materials, both natural and synthetic, and combinations thereof, may be employed provided only that the support does not interfere with the capillary action of the material or materials, or non-specifically bind assay components, or interfere with the signal producing system. Illustrative polymers include polyethylene, polypropylene, poly (<NUM>-methylbutene), polystyrene, polymethacrylate, poly (ethylene terephthalate), nylon, poly (vinyl butyrate), glass, ceramics, metals, and the like. Elastic supports may be made of polyurethane, neoprene, latex, silicone rubber and the like. Throughout this description, LFAs are described with the understanding that description of the LFAs applies to other types of test strips.

In some conventional LFAs, the test results appear as faint color changes that result in an increase in user error when reading. For example, although an LFA may output a color corresponding to a positive result, if the color is faint and/or the lighting conditions are poor, a user may interpret the test as negative. Examples disclosed herein generates an enhanced LFA that is machine readable that reduces and/or otherwise eliminates false positives and/or false negatives due to human error.

Because resources may be limited in particular regions of the world, dedicated LFA readers may be too expensive for use in such regions. Accordingly, examples disclosed herein provide an enhanced LFA that can be read using a smartphone application, as opposed to a dedicated reader. Although there are some smartphone applications that may be capable of reading the result of an LFA-based test, such smartphone applications are not robust due to alignment and/or environment light issues. For example, if the relative position of a smartphone camera to the LFA test is not within a threshold range, the smartphone application will not be able to determine valid results. In another example, if there is too much light reflection and/or low light conditions when the smartphone captures an image, the smartphone application will not be able to determine valid results.

Examples disclosed herein generate the enhanced LFA to address the alignment and environment light issues that correspond to inaccurate results of the conventional LFA readers. To reduce and/or otherwise eliminate alignment issues, examples disclosed herein include a calibration image and/or pattern on the LFA housing. In this manner, a sensor in the smartphone can scan the calibration image and/or pattern and calibrate itself to read the results of the LFA testing zones regardless of the position of the LFA with respect to the sensor of the smartphone. Additionally, regulations (e.g., medical device regulation (MDR) and/or in vitro diagnostic device regulations (IVDR)) and/or regulating entities may require that smartphones meet particular validation requirements (e.g., optical system specifications), examples disclosed herein can utilize the calibration image and/or pattern to verify whether a sensor of the smartphone meets the validation requirements based on an image of the calibration pattern captured by the sensor.

To reduce and/or otherwise eliminate environment light issues, examples disclosed herein add redundancy to the test zones (e.g., targets) of the LFA. For example, instead of having one test line or test zone corresponding to a particular target analyte, examples disclosed herein have multiple test zones corresponding to the same target analyte. Accordingly, if a sample includes a target analyte, most multiple test zones present evidence of the presence of the target analyte (e.g., by presenting an optical signal such as, for example, a color change, a presence or absence of fluorescence, a presence or absence of one or more letters, numbers, and/or symbols). Examples disclosed herein determine if the test is positive or negative by determining how many of the multiple test zones present a positive test result. For example, if there are five test zones that correspond to a target analyte, and a smartphone application determines that four of the five zones present a positive result (e.g., where the fifth zone presents a negative result due to poor lighting, a reflection, a smudge on the sensor, etc.), the smartphone application will determine that the test was positive for the particular analyte. In this manner, if a particular region is too faint, the light is poor, and/or there is a reflection over the particular region, affecting the result of one test zone, there are other test zones that can compensate for any reading error of the one test zone. Accordingly, the higher redundancy increases the reliability of the results from the smartphone application.

At times, fraudulent entities may target LFAs for counterfeiting and/or forgery. For example, a counterfeiter may obtain a particular LFA and generate counterfeit LFAs to distribute for profit. Examples disclosed herein integrate security features in the enhanced LFA to reduce counterfeiting. Examples disclosed herein segment L number of test lines of an LFA corresponding to N target analytes into M parts distributed to the L lines to generate L*M target zones in a two dimensional grid structure. A two dimensional grid structure includes at least two spatially distinct rows and at least two spatially distinct columns. Examples disclosed herein randomly assign N target analytes to one or more (e.g., more for redundancy) of the L*M target zones in a test grid pattern. Additionally, examples disclosed herein leave one or more of the target zones blank and dedicate one or more of the target zones for one or more control zones (e.g., that capture excess probes resulting from the sample flowing through the testing zones). A blank zone (BZ) is a zone that i) includes antibodies or antigens which do not bind specifically to any target of the sample of ii) does not include immobilized antigens or antibodies. Thus, a blank zone will not change colors regardless of whether there are target analytes in the sample. A control zone (CZ) is a zone that changes color when the LFA test is ready to be read. In this manner, the total number of random distributions of test zones, control zones, and blank zones is equal to (M!)N, when L = M or, more generally, (N!/(L-M)!)N. Examples disclosed herein use all, or a portion of, the total number of random distributions to generate different test grid patterns for different enhanced LFAs. In this manner, when the smartphone applications that read the LFAs identify that a particular test grid pattern is being used more than the others, examples disclosed herein can flag the pattern as having been reproduced by counterfeiters and used to make counterfeit LFAs. Action can be taken to eliminate the counterfeiting including, for example, the smartphone application providing a message that the LFA is not authentic or genuine and/or the smartphone application blocking presentation of the results of the test(s) conducted on the LFA.

<FIG> is an example environment <NUM> including an example enhanced LFA generator <NUM> to generate an example enhanced LFA chip, strip, or device <NUM> (illustrated in an overhead view). The example enhanced LFA generator <NUM> includes an example test grid generator <NUM>. The example enhanced LFA device <NUM> includes an example sample pad <NUM>, an example conjugate release pad <NUM>, an example porous media <NUM>, an example test grid <NUM>, and an example wicking pad <NUM>. The environment <NUM> of <FIG> further includes an example reader <NUM> to determine the test results of a sample being applied to the example enhanced LFA device <NUM>. The example reader <NUM> includes an example enhanced LFA reader application <NUM>, an example sensor <NUM>, and an example user interface <NUM>.

The example enhanced LFA generator <NUM> of <FIG> generates the example enhanced LFA device <NUM>. For example, the enhanced LFA generator <NUM> generates the enhanced LFA device <NUM> to include the example sample pad <NUM>, the example conjugate release pad <NUM>, the example porous media <NUM>, the example test grid <NUM>, and the example wicking pad <NUM> included in a housing structure (not shown). Additionally, the enhanced LFA generator <NUM> may include a code (e.g., an identifier (e.g., a data matrix code (DMC)), a pattern or image corresponding to the identifier, and/or a calibration pattern and/or image on or within the housing structure of the enhanced LFA device <NUM>, a barcode, a QR code, etc.) and/or a component that may transmit the code (e.g., a radio frequency transmitter (RFID) transmitter, a near field communication (NFC) transmitter, etc.). A DMC may be a number or code that reflects a production date, an expiry date, a unique identification production identifier (UDI-PI), etc..

The example enhanced LFA generator <NUM> of <FIG> includes the example test grid generator <NUM> to generate the example test grid <NUM> and/or the identifier (e.g., the DMC), the pattern or image corresponding to the identifier, and/or the calibration pattern and/or image on the housing structure of the enhanced LFA device <NUM>. As further disclosed herein, the example test grid generator <NUM> generates the test grid <NUM> to include multiple testing zones corresponding to one or more controls, one or more target analytes, and one or more blanks in a two dimensional grid. A test zone corresponding to a target analyte is included in multiple zones of the test grid, thereby providing redundancy to increase reliability and/or robustness of the LFA results. The example test grid generator <NUM> incorporates a test grid pattern into the test grid <NUM>. The test grid pattern corresponds to an identifier (e.g., DMC) of the enhanced LFA device <NUM>. For example, the test grid generator <NUM> may compute a function (e.g., a modulo function, a checksum, etc.) of the DMC resulting in a number that corresponds to a test grid pattern. Accordingly, the test grid generator <NUM> structures the test grid <NUM> based on the resulting number. For example, if the enhanced LFA generator <NUM> generates <NUM>,<NUM> LFAs with <NUM>,<NUM> different test grid patterns, when the enhanced LFA generator <NUM> generates the <NUM>,<NUM>th LFA, the test grid generator <NUM> selects the test grid pattern corresponding to number <NUM> (e.g., <NUM>,<NUM> modulo <NUM> = <NUM>). In this matter, when the enhanced LFA reader application <NUM> interacts with the enhanced LFA device <NUM>, the enhanced LFA reader application <NUM> can determine which test grid pattern to use to analyze the test grid <NUM> based on the same function (e.g., modulo, checksum, etc.). The example test grid generator <NUM> is further disclosed below in conjunction with <FIG>.

The example enhanced LFA device <NUM> of <FIG> is a device that includes the sample pad <NUM> (e.g., a sample pad, a sample region, a sample area, a sample zone, etc.). For example, the LFA device <NUM> may be a porous membrane device, a porous media device, a fluid transporting media device, a test strip device, a lateral flow test strip device, and/or any fluid sample device. The sample pad <NUM> is structured to act as a sponge to hold a sample of fluid applied to the sample pad <NUM>. In some examples, the sample pad <NUM> includes buffer components (e.g., salts, surfactants, etc.) to ensure that target analytes that may be in the sample are capable of binding with components of the conjugate release pad <NUM>. When the sample pad <NUM> is soaked, the fluid held in the sample pad <NUM> flows to the conjugate release pad <NUM>. The conjugate pad <NUM> includes a labeled substance or conjugate configured to bind a target analyte. For example, the conjugate release pad <NUM> includes conjugates or probes (e.g., gold, latex, fluorophore, etc.) labeled with detectable labels, tags, linkers, antibodies, antigens, etc. specific to one or more target analyte. The target analyte is a component that corresponds to a particular condition or disease. Accordingly, presence of the target analyte in the sample corresponds to presence of the corresponding condition and/or disease in the patient who provided the sample. If the sample includes the one or more of the target analytes, the conjugates and/or probes labelled with the detectable labels, tags, linkers, antibodies, antigens, etc. will attach to the corresponding target analytes. The sample (e.g., including the probes if corresponding target analytes are present in the sample) continues to flow through the example porous media <NUM> (e.g., a membrane, a paper, and/or other compartment-free or compartmentless substrate) of the enhanced LFA device <NUM> toward the wicking pad <NUM>.

While the sample flows across the media <NUM> of <FIG>, the sample will flow across the test grid <NUM>. The test grid <NUM> includes test zones and/or control zones. The test zones include specific immobilized antibodies or antigens that react with the corresponding analytes attached with the probes and conjugates. Accordingly, when the target analyte corresponding to a particular test zone is present in the sample, the target analyte will react with the antibodies resulting in an optical signal such as, for example, a change in color (e.g., from white to red). In some examples, the test grid <NUM> includes control zones that change color when excess conjugates flow past the control zones. Excess conjugates flowing to the control zones indicate that sufficient conjugate has flowed through the test zones. Thus, the optical signal changes in the control zones identify when it is appropriate to read the test results (e.g., when the test is complete). In other examples, the media <NUM> may include a control line and/or zone located between the test grid <NUM> and the wicking pad <NUM>. Because the test grid <NUM> corresponds to one of a plurality of test grid patterns, if the test grid patterns are not shared with the patients and/or users, it is not possible to determine the results of the LFA test by looking at the results. For example, the results will appear random to the patient and/or user because the patient and/or user will not know which zone(s) correspond(s) to test zone(s), which zone(s) correspond(s) to a control zone(s), and which zone(s) correspond(s) to blank zone(s). Accordingly, in such an example, the test grid <NUM> can only be read by the example enhanced LFA reader application <NUM>, thereby reducing, or otherwise eliminating, user error caused by faint optical results and/or poor lighting conditions. An example implementation of the test grid <NUM> is further disclosed below in conjunction with <FIG>.

The example wicking pad <NUM> is an absorbent material that wicks the liquid through the LFA. In some examples, the wicking pad <NUM> includes cellulose filters. The wicking pad <NUM> prevents backflow of the liquid. Also, in some examples, the wicking pad <NUM> acts as a waste container.

In some examples, silver amplification may be applied to the example enhanced LFA <NUM> to increase the visibility of the results. In such examples, the enhanced LFA generator <NUM> may apply an autocatalytic silver enhancement (e.g., silver ion and reducing agent, such as hydroquinone, aminophenols, ascorbic acid) to the test grid <NUM> so that the silver reacts with the conjugate and amplifies in size, thereby generating a stronger visual signal. The enhanced LFA generator <NUM> may structure the enhanced LFA <NUM> to include an inlet so that the silver enhancement may be applied to the example test grid <NUM> during or after the sample is applied.

The example reader <NUM> of <FIG> is a smartphone that includes the enhanced LFA reader application <NUM>, the example sensor <NUM>, and the example user interface <NUM>. Alternatively, the example reader <NUM> may be a tablet, personal digital assistant, a laptop, a standalone LFA reader device, and/or any other processing device that includes, or is otherwise in communication with, the example enhanced LFA reader application <NUM>, the example sensor <NUM>, and/or the example user interface <NUM>. The example enhanced LFA reader application <NUM> is an application that can be installed, downloaded, or coded within the example reader <NUM>. In some examples, the example enhanced LFA reader application <NUM> can be supplied via a near field communication tag or Bluetooth device.

The example enhanced LFA reader application <NUM> of <FIG> identifies the results of an LFA-based test by interacting with the example LFA structure. The enhanced LFA reader application <NUM> controls the components of the reader <NUM> to obtain identification information (e.g., a DMC or test grid pattern identifier) corresponding to the enhanced LFA device <NUM>. The enhanced LFA reader application <NUM> obtains identification information from the enhanced LFA device <NUM> to determine which test grid pattern is applied to the example test grid <NUM>. For example, the enhanced LFA reader application <NUM> may obtain an LFA identifier and/or a DMC from the user interface <NUM> (e.g., by prompting the user to enter the information) or from the sensor <NUM> (e.g., by processing an image captured by the sensor <NUM> that corresponds to the information). In some example, the enhanced LFA reader application <NUM> performs an operation (e.g., a modulo operation, a checksum, etc.) on the identification information to determine which test grid pattern is implemented on the enhanced LFA device <NUM>, as further described above. Once the test grid pattern of the test grid <NUM> is determined, the enhanced LFA reader application <NUM> determines the results of the test by determining the optical signal (e.g., color) of the test zones corresponding to the test grid pattern. Once the test results are determined, the enhanced LFA reader application <NUM> displays the results using the example user interface <NUM>, stores the results in a local database, and/or transmits the results to a monitoring entity for monitoring and/or statistical analysis. In this manner, the manufacturer or other party can process the results, perform diagnostics, and/or identify if a particular test grid pattern may be counterfeited (e.g., if more than a threshold number of results from an LFA with the test grid pattern has been determined). In some examples, the LFA reader application <NUM> transmits raw data. Additionally or alternatively, in some examples, the LFA reader application <NUM> transmits processed data or data resulting from one or more levels of analysis. The example enhanced LFA reader application <NUM> is further disclosed below in conjunction with <FIG>.

<FIG> illustrates an implementation of the example test grid <NUM> of <FIG>. The example test grid <NUM> includes twenty-five examples zones <NUM> (e.g., five rows (A-E) and five columns (<NUM>-<NUM>)). Alternatively, any number of zones in combination of rows and/or columns may be used to implement the example test grid <NUM>.

In the example test grid <NUM> of <FIG>, the zones including 'T1' correspond to test zones for a first disease or condition (e.g., that present an optical signal such as, for example, a change in color when a first particular target analyte is present in a sample), the zones including the 'T2' correspond to test zones for a second disease or condition, the zones including the 'T3' correspond to test zones for a third disease or condition, the zones including 'CZ' correspond to a positive control zone (e.g., which present an optical signal such as, for example, a change in color when the test is ready), and the zones including 'BZ' correspond to a blank zone.

The example test grid <NUM> represents one combination of the zones. Because there are five targets (e.g., three test and two control) segmented into five rows (e.g., parts) across five columns (e.g., lines), the total number of different combinations that can be used in the example test grid <NUM> is <NUM>,<NUM>,<NUM>,<NUM> (e.g., (<NUM>!)<NUM>). However, as described above, the number of combinations are different based on how many tests and controls are implemented in the grid, how many rows and/or columns are used for the grid, and the zones of the grids left intentionally blank.

Some LFAs are subject to a depletion effect. A depletion effect is a situation when targets are bound, captured, and/or consumed and the first capture zones in the flow direction show high signal. If a depletion effect is an issue, the example test grid <NUM> may be structured to include a test zone for a particular analyte in one or more rows but only one column to overcome the depletion effect. Accordingly, in the example test grid <NUM> of <FIG>, each test and control zone occurs in every row but only once in each column. Alternatively, the test and control zones may occur in less numbers of rows.

<FIG> is a block diagram of the example test grid generator <NUM> of <FIG>. The example test grid generator <NUM> includes an example test grid applicator <NUM>, an example user interface <NUM>, an example modulo determiner <NUM>, and an example test grid pattern storage <NUM>.

The example test grid applicator <NUM> of <FIG> determines the structure of the test grid <NUM> of the enhanced LFA device <NUM> of <FIG> and/or 1B. For example, the test grid applicator <NUM> may determine how many different target analytes are to be implemented in the enhanced LFA device <NUM> and determine how many zones to include in the test grid <NUM> to meet a threshold number of different combinations that can be implemented in the test grids of LFAs. Additionally or alternatively, the example test grid applicator <NUM> may receive instructions identifying the number of test, controls, and/or structure of the test grid <NUM> from a user and/or manufacturer via the example user interface <NUM>. Additionally, the test grid applicator <NUM> may determine how many different combinations of test grids to use when generating the multiple LFAs.

Additionally, the test grid applicator <NUM> of <FIG> may determine how the testing pattern will be indicated to the reader <NUM>. For example, if the test grid applicator <NUM> is generating <NUM> different test grid patterns for newly generated LFAs, the test grid applicator <NUM> determines how to indicate which test grid pattern is implemented on each LFA so that the reader <NUM> can determine how to read the test grid <NUM>. In some examples, the test grid applicator <NUM> selects one of the test grid patterns stored in the test grid pattern storage <NUM> and applies an identifier (e.g., a number or a code identifying the test pattern) of the test grid structure on the housing structure of the LFA. In some examples, the test grid applicator <NUM> obtains a modulo or other value of the DMC from the enhanced LFA generator corresponding to the LFA being generated. In such examples, the test grid applicator <NUM> may select a test grid pattern from the example test grid pattern storage <NUM> corresponding to the result of the modulo. For example, if the DMC is <NUM> and there are <NUM> test grid patterns stored in the test grid pattern storage <NUM>, the example modulo determiner <NUM> determines the modulo to be <NUM> (<NUM> mod <NUM>). In such an example, the test grid pattern storage <NUM> selects the test pattern corresponding to identifier <NUM> to implement the test grid <NUM>.

The example user interface <NUM> of <FIG> interfaces with a user and/or manufacturer to obtain instructions regarding how to structure the test grid structure. For example, the user interface <NUM> may receive instructions regarding how many tests to perform, how many test grid patterns to implement, how many columns and/or row to utilize, how many blank spaces to include, how many control zones to include, etc..

The example modulo determiner <NUM> of <FIG> performs a modulo function based on the code (e.g., the DMC code) of the LFA that is currently being generated and the number of test grid patterns in the example test grid pattern storage <NUM> and/or the number of test grid patterns used per user instructions. For example, if the DMC is <NUM> and there are <NUM> test grid patterns stored in the test grid pattern storage <NUM>, the example modulo determiner <NUM> determines the modulo to be <NUM> (<NUM> mod <NUM>). In this manner, the example reader <NUM> of <FIG> can perform the same modulo function based on the DMC pattern to identify the corresponding test grid pattern when analyzing the results of an LFA-based test. Additionally or alternatively, the modulo determiner <NUM> may be another type of function generator to generate a value that corresponds to a test grid pattern.

The example test grid pattern storage <NUM> of <FIG> stores different test grid patterns in conjunction with an identifier. The test grid patterns correspond to which zones of the test grid correspond to different tests, controls, and blanks. In this manner, the example test grid applicator <NUM> can apply one of the stored test grid patterns to the test grid <NUM> of the example enhanced LFA device <NUM> corresponding to an identifier that can be determined at the reader <NUM>.

<FIG> is a block diagram of the example enhanced LFA reader application <NUM> of <FIG>. The example test grid generator <NUM> includes an example component interface <NUM>, an example image processor <NUM>, an example test grid determiner <NUM>, an example test grid determiner <NUM>, an example modulo determiner <NUM>, an example test grid pattern storage <NUM>, an example comparator <NUM>, and an example results storage <NUM>.

The example component interface <NUM> of <FIG> interfaces with the other components of the example reader <NUM>. For example, the component interface <NUM> may transmit prompts, text, and/or images to the example user interface <NUM> to display to a user. Additionally, the example component interface <NUM> receives data entered by the user via the user interface <NUM>. For example, if the user enters the DMC code printed on the housing of the enhanced LFA device <NUM> into the user interface <NUM>, the example component interface <NUM> obtains the entered DMC code from the user interface <NUM>. Additionally, the example component interface <NUM> interfaces with the sensor <NUM> to obtain images that the sensor <NUM> captured. In some examples, the component interface <NUM> interfaces with a transmitter of the reader <NUM> to transmit results of an LFA-based test reading to an entity that monitors the results. The results may include which tests are positive, which tests are negative, which test grid pattern was used, identification information of the LFA (e.g., DMC), and/or contextual information obtained from the reader <NUM> and/or a user (e.g., timestamp, location data, patient information and/or demographics, etc.). In this manner, if the entity that monitors the results determines that more than a threshold number of percent of a particular LFA or test grid has been used, the LFA and/or test grid can be flagged as possibly being counterfeit and subsequent actions can be taken to prevent further counterfeiting and/or reliance on test results from a counterfeit device. If a network connection is not available after a test is performed, the component interface <NUM> may transmit the results after receiving an indication that a network connection is available.

The example image processor <NUM> of <FIG> processes images obtained from the sensor <NUM> via the example component interface <NUM>. In some examples, the sensor <NUM> obtains an image of a code (e.g., text, QR code, etc.) printed or otherwise included in and/or on the housing of the enhanced LFA device <NUM> and/or in and/or on paperwork included with the LFA device <NUM>, and the image processor <NUM> processes the image to identify the corresponding information. As described above, the housing or interior of the enhanced LFA device <NUM> may include a DMC code, or other identifier, and/or an image (e.g., QR code) that corresponds to the DMC code or other identifier. Accordingly, if an image is taken of the text and/or code printed on the housing, the image processor <NUM> can identify the DMC code and/or any other identification information based on the image of the text and/or code. Additionally or alternatively, the enhanced LFA device <NUM> may include a wireless transmitter (e.g., RFID, NFC, etc.) to transmit the code and/or identifier to the example reader <NUM>.

Additionally, in some examples, the example image processor <NUM> of <FIG> processes an image of a calibration pattern. In this manner, the example image processor <NUM> can calibrate the sensor <NUM> according to the obtained image of the calibration pattern. Additionally, the example image processor <NUM> can process the image of the calibration pattern to determine if the quality of the sensor <NUM> is sufficient to meet minimum optimal system specifications. If the example image processor <NUM> determines that the processing of a calibration pattern results in a failure of the optimal system specifications, the image processor <NUM> prevents processing of an LFA-based test. In some examples, the image processor <NUM> may attempt to improve the optical system settings by, for example, turning on a light of the reader <NUM> (e.g., using the component interface <NUM>) and/or prompting the user (e.g., using the user interface <NUM> via the component interface <NUM>) to turn on a light (e.g., a light of the reader <NUM> or a light separate from the reader <NUM>) to improve the lighting conditions to retest the optical system specification under better lighting conditions.

Additionally, the example image processor <NUM> of <FIG> processes images of the test grid <NUM> of the enhanced LFA device <NUM> to determine which zones of the test grid <NUM> presented a positive result and which zones presented a negative result. As described above, if a target analyte is present in a sample, corresponding zone(s) of the test grid <NUM> will present optical signals (e.g., changing such as from white to another color). Accordingly, the image processor <NUM> processes an image of the test grid <NUM> to determine which zones correspond to color(s) corresponding to a positive result and which zones correspond to color(s) corresponding to a negative result.

As further disclosed herein, the example test grid determiner <NUM> may identify which test grid pattern was used to generate the test grid <NUM>. Accordingly, the image processor <NUM> will know the structure (e.g., the number and/or dimensions of columns and rows) of the test grid <NUM>. In some examples, the structure of the test grid <NUM> may be preset (e.g., all LFAs having the same test grid structure).

The example test grid determiner <NUM> of <FIG> determines which test grid is used for the example test grid <NUM> of <FIG>. As described above, the user may provide identification information (e.g., using the user interface <NUM>) and/or the identification information may be obtained by the image processor <NUM> based on an image taken of the identification information. The identification information may be a test grid identifier, a DMC, etc. If the identification information is a test grid identifier, the example test grid determiner <NUM> identifies the corresponding test grid in the test grid pattern storage <NUM> based on the test grid identifier. If the identification information is a DMC code, a pattern and/or image that corresponds to a code, and/or any other identification code, the modulo determiner <NUM> performs a modulo function based on the DMC code of the enhanced LFA device <NUM> and the number of test grid patterns in the example test grid pattern storage <NUM> and/or the number of test grid patterns preprogrammed into the enhanced LFA reader application <NUM>. For example, if the DMC is <NUM> and there are <NUM> test grid patterns stored in the test grid pattern storage <NUM>, the example modulo determiner <NUM> determines the modulo to be <NUM> (<NUM> mod <NUM>). The example modulo determiner <NUM> operates in a similar fashion as the modulo determiner <NUM> of <FIG>. In this manner, the enhanced LFA reader application <NUM> can determine which test grid pattern was used by the enhanced LFA generator <NUM> to generate the test grid <NUM> of the enhanced LFA device <NUM>. Additionally or alternatively, the modulo determiner <NUM> may be another type of function generate to generate a value that corresponds to a test grid pattern.

The example test grid pattern storage <NUM> of <FIG> stores different test grid patterns in conjunction with an identifier. The test grid patterns correspond to which zones of the test grid correspond to different tests, controls, and blanks. The test grid pattern storage <NUM> stores the same test grid patterns in conjunction with the same identifiers as the test grid pattern storage <NUM> of <FIG>. In this manner, the example test grid determiner <NUM> can identify which test grid pattern is used in the test grid <NUM> of the enhanced LFA device <NUM>.

The example comparator <NUM> of <FIG> compares the results of multiple zone(s) that correspond to the same target analyte to determine whether the test result is positive or negative. For example, if there are six zones on the test grid <NUM> that correspond to HIV, the comparator <NUM> compares the number of positive results and/or the number of negative results of the six zones to one or more thresholds. In such an examples, the comparator <NUM> may determine that the test resulted positive for HIV if four or more zones presented a positive result, that the test resulted negative for HIV if four or more zones presented a negative result, and that the test resulted indeterminate for HIV if three zones were presented a positive result and three zones presented a negative result. In some examples, the threshold number of zones may be based on the type of analyte to be detected, industry and/or government regulations, user preferences, manufacturer preferences or recommendations, and/or a combination of criteria.

The example results storage <NUM> of <FIG> stores the results of an LFA test (e.g., which tests presented positive results, negative results, or indeterminate results, and/or any corresponding information) in conjunction with any identification information (e.g., DMC, test grid identifiers, etc.). In some examples, a user can enter patient information via the user interface <NUM>. In such examples, some or all of the patient information may be added to the result information (e.g., the results storage <NUM> stores a record of the test result in conjunction with the patient information). Additionally or alternatively, the example component interface <NUM> may gather contextual information when the test is performed that may be stored in the example results storage <NUM> in conjunction with the results (e.g., location information, time of day information, etc.).

While an example manner of implementing the example test grid generator <NUM> of <FIG> is illustrated in <FIG> and an example manner of implementing the example enhanced LFA reader application <NUM> of <FIG> is illustrated in <FIG>, one or more of the elements, processes and/or devices illustrated in <FIG> and/or <NUM> may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, the example test grid applicator <NUM>, the example user interface <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, and/or, more generally, the example test grid generator <NUM> of <FIG> and the example component interface <NUM>, the example image processor <NUM>, the example test grid determiner <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, the example comparator <NUM>, the example results storage <NUM>, and/or, more generally, the example enhanced LFA reader application <NUM> may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of the example test grid applicator <NUM>, the example user interface <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, and/or, more generally, the example test grid generator <NUM> of <FIG> and the example component interface <NUM>, the example image processor <NUM>, the example test grid determiner <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, the example comparator <NUM>, the example results storage <NUM>, and/or, more generally, the example enhanced LFA reader application <NUM> could be implemented by one or more analog or digital circuit(s), logic circuits, programmable processor(s), programmable controller(s), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to cover a purely software and/or firmware implementation, at least one of the example test grid applicator <NUM>, the example user interface <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, and/or, more generally, the example test grid generator <NUM> of <FIG> and the example component interface <NUM>, the example image processor <NUM>, the example test grid determiner <NUM>, the example modulo determiner <NUM>, the example test grid pattern storage <NUM>, the example comparator <NUM>, the example results storage <NUM>, and/or, more generally, the example enhanced LFA reader application <NUM> is/are hereby expressly defined to include a non-transitory computer readable storage device or storage disk such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc. including the software and/or firmware. Further still, the example test grid generator <NUM> of <FIG> and the example enhanced LFA reader application <NUM> of <FIG> may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated in <FIG> and <FIG>, and/or may include more than one of any or all of the illustrated elements, processes and devices. As used herein, the phrase "in communication," including variations thereof, encompasses direct communication and/or indirect communication through one or more intermediary components, and does not require direct physical (e.g., wired) communication and/or constant communication, but rather additionally includes selective communication at periodic intervals, scheduled intervals, aperiodic intervals, and/or one-time events.

Flowcharts representative of example hardware logic, machine readable instructions, hardware implemented state machines, and/or any combination thereof for implementing the test grid generator <NUM> and/or the enhanced LFA reader application <NUM> of <FIG> and/or <NUM> are shown in <FIG>, <FIG>, and <FIG>. The machine readable instructions may be one or more executable programs or portion(s) of an executable program for execution by a computer processor such as the processor <NUM>, <NUM> shown in the example processor platform <NUM>, <NUM> discussed below in connection with <FIG> and/or <NUM>. The program may be embodied in software stored on a non-transitory computer readable storage medium such as a CD-ROM, a floppy disk, a hard drive, a DVD, a Blu-ray disk, or a memory associated with the processor <NUM>, <NUM> but the entire program and/or parts thereof could alternatively be executed by a device other than the processor <NUM>, <NUM> and/or embodied in firmware or dedicated hardware. Further, although the example program is described with reference to the flowcharts illustrated in <FIG>, <FIG>, and/or 5B many other methods of implementing the example test grid generator <NUM> and/or the example enhanced LFA reader application <NUM> may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined. Additionally or alternatively, any or all of the blocks may be implemented by one or more hardware circuits (e.g., discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to perform the corresponding operation without executing software or firmware.

The machine readable instructions described herein may be stored in one or more of a compressed format, an encrypted format, a fragmented format, a compiled format, an executable format, a packaged format, etc. Machine readable instructions as described herein may be stored as data (e.g., portions of instructions, code, representations of code, etc.) that may be utilized to create, manufacture, and/or produce machine executable instructions. For example, the machine readable instructions may be fragmented and stored on one or more storage devices and/or computing devices (e.g., servers). The machine readable instructions may require one or more of installation, modification, adaptation, updating, combining, supplementing, configuring, decryption, decompression, unpacking, distribution, reassignment, compilation, etc. in order to make them directly readable, interpretable, and/or executable by a computing device and/or other machine. For example, the machine readable instructions may be stored in multiple parts, which are individually compressed, encrypted, and stored on separate computing devices, wherein the parts when decrypted, decompressed, and combined form a set of executable instructions that implement a program such as that described herein.

In another example, the machine readable instructions may be stored in a state in which they may be read by a computer, but require addition of a library (e.g., a dynamic link library (DLL)), a software development kit (SDK), an application programming interface (API), etc. in order to execute the instructions on a particular computing device or other device. In another example, the machine readable instructions may need to be configured (e.g., settings stored, data input, network addresses recorded, etc.) before the machine readable instructions and/or the corresponding program(s) can be executed in whole or in part. Thus, the disclosed machine readable instructions and/or corresponding program(s) are intended to encompass such machine readable instructions and/or program(s) regardless of the particular format or state of the machine readable instructions and/or program(s) when stored or otherwise at rest or in transit.

As mentioned above, the example processes of <FIG>, <FIG>, and/or 5B may be implemented using executable instructions (e.g., computer and/or machine readable instructions) stored on a non-transitory computer and/or machine readable medium such as a hard disk drive, a flash memory, a read-only memory, a compact disk, a digital versatile disk, a cache, a random-access memory and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media.

<FIG> illustrates an example flowchart representative of machine readable instructions <NUM> that may be executed to implement the example testing grid generator <NUM> of <FIG> to generate the test grid <NUM> of the example enhanced LFA device <NUM> of <FIG>. Although the instructions <NUM> of <FIG> are described in conjunction with the example test grid <NUM> of the example enhanced LFA device <NUM> of <FIG>, the example instructions <NUM> may be described and/or implemented in conjunction with any type of test grid and/or LFA of any structure.

At block <NUM>, the example test grid applicator <NUM> determines the number of tests to apply on the LFA device <NUM>. For example, the enhanced LFA generator <NUM> may provide instructions regarding how many tests corresponding to target analytes should be applied on the test grid <NUM>. Additionally or alternatively, a user or administrator may provide the number of tests via the example user interface <NUM>.

At block <NUM>, the example test grid applicator <NUM> determines a total number of row columns for the test grid. In some examples, the test grid applicator <NUM> may determine the total number of rows and columns for the test grid based on instructions (e.g., from the enhanced LFA generator <NUM> and/or from a user via the user interface <NUM>). In some examples, the number of rows and/or columns is preset. In some examples, the number of rows and/or columns corresponds to the number of tests (e.g., if there are three tests, there are three or more rows and/or columns). In some examples, the number of rows and/or columns is more than a preselected minimum amount (e.g., that may be set by a user, administrator, and/or regulations).

At block <NUM>, the example test grid applicator <NUM> determines if the test grid pattern corresponds to a DMC. For example, the enhanced LFA generator <NUM> may generate a DMC including information corresponding to the currently generated LFA. The enhanced LFA generator <NUM> may instruct the test grid applicator <NUM> to select a test grid from the test grid pattern storage <NUM> randomly or based on the DMC. If the example test grid applicator <NUM> determines that the test grid pattern does not correspond to a DMC (block <NUM>: NO), control continues to block <NUM>, as further described below. If the example test grid applicator <NUM> determines that the test grid pattern does correspond to a DMC (block <NUM>: YES), the example test grid applicator <NUM> obtains the DMC from the enhanced LFA generator <NUM> (block <NUM>).

At block <NUM>, the example modulo determiner <NUM> identifies the test grid pattern corresponding to the DMC and selects the test grid pattern from the example test grid pattern storage <NUM>. As disclosed above in conjunction with <FIG>, the modulo determiner <NUM> may perform a modulo operation or another type of operation (e.g., checksum) on the DMC to generate a number that corresponds to a test grid pattern stored in the example test grid pattern storage <NUM>. At block <NUM>, the example test grid applicator <NUM> applies the immobilized antibodies and/or antigens corresponding to a target analyte to a zone of the test grid <NUM> of the enhanced LFA device <NUM> according to the selected test grid pattern. In some examples, the test grid applicator <NUM> additionally applies immobilized antibodies and/or antigens corresponding to control zones to attach to excess antibodies and/or control antibodies.

If the example test grid applicator <NUM> determines that the test grid pattern does not correspond to a DMC (block <NUM>: NO), the example test grid applicator <NUM> selects a test grid pattern from the example test grid pattern storage <NUM> (block <NUM>). The test grid applicator <NUM> may select a test grid pattern randomly, sequentially, and/or based on any other pattern. At block <NUM>, the example test grid applicator <NUM> applies the immobilized antibodies and/or antigens corresponding to a target analyte to a zone of the test grid <NUM> of the enhanced LFA device <NUM> according to the selected test grid pattern. In some examples, the test grid applicator <NUM> additionally applies immobilized antibodies and/or antigens corresponding to control zones to attach to excess antibodies and/or control antibodies.

At block <NUM>, the example test grid applicator <NUM> applies a test target pattern identifier (e.g., text, a QR code, etc.) to and/or within the housing of the enhanced LFA device <NUM>, and/or to another component and/or paper associated with the LFA device <NUM>. In this manner, the enhanced LFA reader application <NUM> can identify which test grid is used on the enhanced LFA device <NUM> for test reading purposes. At block <NUM>, the example test grid applicator <NUM> applies a calibration pattern to the LFA. The calibration pattern allows the enhanced LFA reader application <NUM> to determine whether the sensor <NUM> of the reader <NUM> has sufficient optical system specification and/or to calibrate the sensor <NUM> for an LFA-based reading.

<FIG> and <FIG> illustrate an example flowchart representative of machine readable instructions <NUM> that may be executed to implement the example enhanced LFA reader application <NUM> of <FIG> to read test results of the example enhanced LFA device <NUM> of <FIG>. Although the instructions <NUM> of <FIG> are described in conjunction with the example enhanced LFA device <NUM> of <FIG>, the example instructions <NUM> may be described and/or implemented in conjunction with type of LFA of any structure.

At block <NUM>, the example component interface <NUM> prompts a user (e.g., via the user interface <NUM>) to enter (e.g., using the user interface <NUM>) or scan (e.g., using the sensor <NUM>) identification information (e.g., a DMC, test grid identification information, etc.) from the enhanced LFA device <NUM>. In some examples, if the identification information is scanned (e.g., by obtaining an image of the identification information), the example image processor <NUM> determines the identification information by processing the image. Additionally or alternatively, the identification information may be a code that corresponds to a test grid pattern. In some examples, the component interface <NUM> may obtain a code and/or identification information from a receiver (e.g., when the code and/or identification information is transmitted via RFID, NFC, etc.). The identification information is passed to the example test grid determiner <NUM>.

At block <NUM>, the example test grid determiner <NUM> determines the test grid pattern based on the identification information. For example, if the test grid information is an identifier of a test grid, the example test grid determiner <NUM> obtains the test grid corresponding to the identifier from the test grid pattern storage <NUM>. If the test grid information is a DMC, the example modulo determiner <NUM> performs a modulo function, or other function, on the DMC to determine the test grid identifier, and the test grid determiner <NUM> obtains the test grid corresponding to the identifier from the test grid pattern storage <NUM>.

At block <NUM>, the example component interface <NUM> instructs the sensor <NUM> to scan the calibration pattern on the housing of the enhanced LFA device <NUM>. The calibration pattern may be a pattern that can only be read and/or processed if the optical system specifications of the reader <NUM> are above minimum requirements. At block <NUM>, the example image processor <NUM> determines if the calibration pattern was able to be scanned correctly. If the image processor <NUM> determines that the calibration pattern was not able to be scanned correctly (block <NUM>: NO), the example component interface <NUM> transmits a prompt to a user via the user interface <NUM> to display an error message (block <NUM>). The component interface <NUM> transmits the prompt because if the calibration pattern was not able to be scanned correctly, then the sensor <NUM> is not sufficient to meet the minimum optical system specifications. As described above in conjunction with <FIG>, the component interface <NUM> may take additional actions to attempt to increase the optical system specifications.

If the image processor <NUM> determines that the calibration pattern was able to be scanned correctly (block <NUM>: YES), the example image processor <NUM> calibrates (e.g., via instructions sent by the component interface <NUM>) the sensor <NUM> based on the calibration pattern (block <NUM>). At block <NUM>, image processor <NUM> (e.g., using the component interface <NUM>) instructs the sensor <NUM> to scan the test grid <NUM>. For example, the component interface <NUM> may prompt the user to scan (e.g., capture an image of) the test grid using the sensor <NUM>. Thus, in this example, the test results represented by the test grid <NUM> are read without inserting the LFA device <NUM> into a reader or other machine.

At block <NUM>, the example image processor <NUM> selects a target analyte corresponding to one or more test zones of the test grid <NUM>. For example, if an LFA corresponds to diagnostic testing of three diseases, the example image processor <NUM> selects the target analyte for a first one of the diseases.

At block <NUM>, the example image processor <NUM> identifies the target zones of the test grid pattern that correspond to the selected target.

For example, using the example test grid <NUM> of <FIG>, if the image processor <NUM> has selected a first target analyte for a disease corresponding to test zones marked with 'x,' then the example image processor identifies the A-<NUM>, B-<NUM>, D-<NUM>, A-<NUM>, and A-<NUM> zones as target zones that correspond to the selected target analyte (e.g., 'x'). At block <NUM>, the example image processor <NUM> determines the results of the selected tests based on the identified target zones. Using the above example, the image processor <NUM> analyzes the optical signals (e.g., colors) of the A-<NUM>, B-<NUM>, D-<NUM>, A-<NUM>, and A-<NUM> zones to determine the results. For example, if zones A-<NUM>, B-<NUM>, D-<NUM>, and A-<NUM> are red and zone A-<NUM> is white, the example image processor <NUM> determines a positive result for zones A-<NUM>, B-<NUM>, D-<NUM>, and A-<NUM> and a negative result for zone A-<NUM>.

At block <NUM>, the example comparator <NUM> determines if there are more than a first threshold number of zones that present positive results. The threshold number may be based on the type of analyte being analyzed, user preferences, administrator preferences, industry standards, and/or regulations. If the example comparator <NUM> determines that more than a threshold number of zones present positive results (block <NUM>: YES), the comparator <NUM> flags the selected test for the target analyte as positive (block <NUM>), and control continues to block <NUM>. If the example comparator <NUM> determines that more than a threshold number of zones present results that are not positive (block <NUM>: NO), the comparator <NUM> determines if more than a second threshold number of zone present negative results (block <NUM>). The first threshold of block <NUM> may be the same or different than the second threshold of block <NUM>. If the example comparator <NUM> determines that more than the threshold number of zones present negative results (block <NUM>: YES), the example comparator <NUM> flags the selected test for the target analyte as negative (block <NUM>), and control continues to block <NUM>.

If the example comparator <NUM> determines that more than the threshold number of zones present results that are not negative (block <NUM>: NO), the example comparator <NUM> flags the selected test for the target analyte as indeterminate (block <NUM>). At block <NUM>, the example image processor <NUM> determine if there is/are additional target analyte(s) to process. If the example image processor <NUM> determines that there is/are additional target analyte(s) to process (block <NUM>: YES), control returns to block <NUM> of <FIG> to determine the result of the additional target analyte. If the example image processor <NUM> determines that there are no additional target analytes to process (block <NUM>: NO), the example component interface <NUM> transmits instructions to the example user interface <NUM> to display the results based on the flag(s) (block <NUM>).

At block <NUM>, the example component interface <NUM> transmits instructions to a transmitter of the reader <NUM> to transmit the results and corresponding LFA identification information and/or contextual information to a monitoring entity and/or the example results storage <NUM> stores the results and corresponding LFA identification information and/or contextual information. If the results and corresponding information is transmitted to a monitoring entity, the monitoring entity can process the results and/or perform statistical analysis to determine whether there is an outbreak of disease, identify whether LFAs are being counterfeited, etc., based on multiple received results from one or more enhanced LFA reader applications. If a network connection is not currently present, the example component interface <NUM> may delay instructions to the transmitter until a network connection is established. Additionally or alternatively, the example component interface <NUM> may transmit results from the results storage <NUM> periodically, aperiodically, and/or based on a trigger (e.g., a result request from a measuring entity).

<FIG> illustrates an example implementation of the example enhanced LFA device <NUM> of <FIG>. <FIG> includes five images <NUM>, <NUM>, <NUM>, <NUM>, <NUM> of an example implementation of the example enhanced LFA device <NUM> of <FIG> during an example testing operation. The example images illustrate the example sample pad <NUM>, the example test grid <NUM>, and an example LFA housing <NUM>. Although the illustrated example includes a particular number of test zones in a particular formation, <FIG> may be described in conjunction with any number of test zone in any formation.

The first image <NUM> of <FIG> (a photograph taken without a flash) includes two enhanced LFAs (e.g., that correspond to the LFA <NUM>), and the second image <NUM> (a photograph taken with a flash) includes two enhanced LFAs (e.g., that corresponds to the LFA <NUM>). The images <NUM>, <NUM> are of two enhanced LFAs after a sample was applied to the sample pad <NUM>. The line(s) on the images <NUM>, <NUM> are red due to gold nanoparticles being bound to the corresponding test lines due to the target being present in the sample. The third image <NUM> (a photograph taken with a flash) includes the example enhanced LFAs after a sample has been applied to the example sample pad <NUM> and silver amplification has been used to amplify the visual cue of the result (e.g., as shown in the change of color at the sample pad <NUM>). The third image <NUM> has had a silver amplification process applied to strengthen the visual indications on the example enhanced LFAs.

The fourth image <NUM> and fifth image <NUM> show a close-up view of the test grid <NUM> of the respective enhanced LFAs of the third image <NUM>. The fourth image <NUM> illustrates the depletion effect described above in conjunction with <FIG>. As described above, if a depletion effect is an issue, the example test grid <NUM> may be structured to include a test zone for a particular analyte in one or more rows but only one column to overcome the depletion effect. Accordingly, in the example test grid <NUM> of <FIG>, each test and control zone occur in every row but only once in each column. Alternatively, the test and control zones may occur in a fewer number of rows.

<FIG> is a block diagram of an example processor platform <NUM> structured to execute the instructions of <FIG> to implement the test grid generator <NUM> of <FIG>. The processor platform <NUM> can be, for example, a server, a personal computer, a workstation, a self-learning machine (e.g., a neural network), an Internet appliance, or any other type of computing device.

For example, the processor <NUM> can be implemented by one or more integrated circuits, logic circuits, microprocessors, GPUs, DSPs, or controllers from any desired family or manufacturer. The hardware processor may be a semiconductor based (e.g., silicon based) device. In this example, the processor implements the example test grid applicator <NUM>, the example user interface <NUM>, and the example modulo determiner <NUM>.

The example local memory <NUM> implements the example test grid pattern storage <NUM>.

The machine executable instructions <NUM> of <FIG> may be stored in the mass storage device <NUM>, in the volatile memory <NUM>, in the non-volatile memory <NUM>, and/or on a removable non-transitory computer readable storage medium such as a CD or DVD.

<FIG> is a block diagram of an example processor platform <NUM> structured to execute the instructions of <FIG> to implement the enhanced LFA reader application <NUM> of <FIG>. The processor platform <NUM> can be, for example, a personal computer, a workstation, a self-learning machine (e.g., a neural network), a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPad™), a personal digital assistant (PDA), a personal video recorder, or any other type of computing device.

For example, the processor <NUM> can be implemented by one or more integrated circuits, logic circuits, microprocessors, GPUs, DSPs, or controllers from any desired family or manufacturer. The hardware processor may be a semiconductor based (e.g., silicon based) device. In this example, the processor implements the example component interface <NUM>, the example image processor <NUM>, the example test grid determiner <NUM>, the example modulo determiner <NUM>, and the example comparator <NUM>.

The volatile memory <NUM> may be implemented by SDRAM, DRAM, RDRAM® and/or any other type of random access memory device. The example local memory <NUM> implements the example test grid pattern storage <NUM> and the example results storage <NUM>.

The interface circuit <NUM> may be implemented by any type of interface standard, such as an Ethernet interface, a USB, a Bluetooth® interface, an NFC interface, and/or a PCI express interface.

The output devices <NUM> can be implemented, for example, by display devices (e.g., an LED, an OLED, an LCD, a CRT display, an IPS display, a touchscreen, etc.), a tactile output device, a printer and/or speaker.

The communication can be via, for example, an Ethernet connection, a DSL connection, a telephone line connection, a coaxial cable system, a satellite system, a line-of-site wireless system, a cellular telephone system, etc..

Examples of such mass storage devices <NUM> include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, RAID systems, and DVD drives.

Claim 1:
A device for use with a fluid sample, the device comprising:
a conjugate pad including conjugates for a target analyte; and
a test grid including a plurality of zones in a two-dimensional grid, the test grid including:
a first test zone in the plurality of zones including at least one of first immobilized antibodies or first immobilized antigens to attach to the target analyte labeled with a first conjugate of the conjugates;
a second test zone in the plurality of zones including at least one of second immobilized antibodies or second immobilized antigens to attach to the target analyte labeled with a second conjugate of the conjugates;
a control zone in the plurality of zones including at least one of third immobilized antibodies or third immobilized antigens to attach to conjugates not bound to the target analyte; and
a blank zone in the plurality of zones that does not include immobilized antibodies or immobilized antigens;
wherein a location of the first test zone and the second test zone within the test grid is according to a test grid pattern that is related to identifying information of the device, wherein in the test grid pattern the test zones, control zone and blank zone are randomly distributed such that results appear random to a user.