Abstract: A method of deception detection based upon ocular information of a subject provides a video camera configured to record a close-up view of a subject's eye. A cognitive state model is configured to determine a high to a low cognitive load experienced by the subject. An emotional state model is configured to determine a high to a low state of arousal experienced by the subject. After asking a question, the ocular information is processed to identify changes in ocular signals of the subject. The cognitive state and emotional state models are evaluated based solely on the changes in ocular signals where a probability of the subject being either truthful or deceptive is estimated for a binary output.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: A method to measure a cognitive load based upon ocular information of a subject includes the steps of: providing a video camera configured to record a close-up view of at least one eye of the subject; providing a computing device electronically connected to the video camera and the electronic display; recording, via the video camera, the ocular information of the at least one eye of the subject; processing, via the computing device, the ocular information to identify changes in ocular signals of the subject through the use of convolutional neural networks; evaluating, via the computing device, the changes in ocular signals from the convolutional neural networks by a machine learning algorithm; determining, via the machine learning algorithm, the cognitive load for the subject; and displaying, to the subject and/or to a supervisor, the cognitive load for the subject.

Abstract: A diagnostic test kit is provided. In one aspect, the diagnostic test kit includes a diagnostic test including a test region for indicating a test result. The diagnostic test kit also includes a scan surface including one or more control markings. The one or more control markings are representative of one or more predetermined test results for the diagnostic test. The diagnostic test can include a lateral flow immunoassay test, and the one or more control markings can include one or more lines. The one or more lines can vary in at least one of thickness, color, hue, and reflectivity.

Abstract: A method to optimize learning based upon ocular information of a subject includes providing a video camera for recording a close-up view of a subject's eye. A first electronic display shows a plurality of educational subject matter to the subject. A second electronic display shows an output to an instructor. Changes in ocular signals of the subject are processed through the use optimized algorithms. A cognitive state model determines a low to a high cognitive load experienced by the subject. The cognitive state model is evaluated based on the changes in the ocular signals for determining a probability of the low to the high cognitive load experienced by the subject. The probability of the low to the high cognitive load experienced by the subject is displayed to the instructor.

Abstract: A method for analyzing a diagnostic test may include receiving an image depicting a diagnostic test, wherein the diagnostic test comprises a test region indicating a test result, validating quality of the image, locating a test region image portion of the image depicting the test region of the diagnostic test; and predicting the test result based on the test region image portion. Furthermore, a method for facilitating analysis of a diagnostic test may include receiving one or more images depicting one or more control markings on a scan surface, wherein the one or more control markings are representative of one or more predetermined test results for the diagnostic test, and verifying detection of the one or more control markings in the one or more images using at least one computer vision technique.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: A method for analyzing a sample includes introducing the sample into a vessel including a cation-exchange resin, where the cation-exchange resin has a high affinity to one or more interferent species in the sample, directing the sample through the cation-exchange resin to thereby capture one or more interference species in the cation-exchange resin to purify the sample, and releasing the purified sample from the vessel. Additionally, a method for analyzing a sample includes receiving an image depicting a diagnostic test region and a color reference chart, converting a test region image portion of the image to an analytical color space, determining first and second coordinate values characterizing the test region image portion in the analytical color space, and providing a quantitative measurement of an analyte of interest in the sample based on the first and/or second coordinate values and a predictive formula based on the color reference chart.

Abstract: A method of deception detection based upon ocular information of a subject provides a video camera configured to record a close-up view of a subject's eye. A cognitive state model is configured to determine a high to a low cognitive load experienced by the subject. An emotional state model is configured to determine a high to a low state of arousal experienced by the subject. After asking a question, the ocular information is processed to identify changes in ocular signals of the subject. The cognitive state and emotional state models are evaluated based solely on the changes in ocular signals where a probability of the subject being either truthful or deceptive is estimated for a binary output.

Abstract: A method to optimize learning based upon ocular information of a subject includes providing a video camera for recording a close-up view of a subject's eye. A first electronic display shows a plurality of educational subject matter to the subject. A second electronic display shows an output to an instructor. Changes in ocular signals of the subject are processed through the use optimized algorithms. A cognitive state model determines a low to a high cognitive load experienced by the subject. The cognitive state model is evaluated based on the changes in the ocular signals for determining a probability of the low to the high cognitive load experienced by the subject. The probability of the low to the high cognitive load experienced by the subject is displayed to the instructor.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: Color quantification of chemical test pads and titration of analytes can be performed under different lighting conditions. In one embodiment, the lighting condition is estimated under which a digital image is captured and utilized to select a set of reference colors from which the quantified color is compared to determine the titration. In another embodiment, a plurality of comparisons are made with different lighting conditions with the result having the highest confidence level being selected to determine the titration.

Abstract: Methods and electronic devices for performing color-based reaction testing of biological materials. The method includes capturing and interpreting digital images of an unexposed and later exposed paddle at various delay times within an automatically calibrated environment. The test paddle includes a unique identification mechanism (UID), a Reference Color Bar (RCB) providing samples of standardized colors for image color calibration, compensation and corrections, and several test-specific sequences of Chemical Test Pads (CTP). The method further includes locating the paddle in the image, extracting the UID and validating the paddle, extracting the RCB and locating the plurality of CTP in each image. The method further reduces image noise in the CTP and calibrates the image automatically according to lighting measurements performed on the RCB.

Abstract: Techniques for measuring ion related metrics at a user's skin surface are disclosed. In one aspect, a method for operating a wearable device may involve determining, based on output of one or more ion selective field effect transistor sensors, various physiological conditions such as a state of hydration, a state of skin health, or the cleanliness of the wearable device or an associated garment.

Abstract: Techniques for measuring ion related metrics at a user's skin surface are disclosed. In one aspect, a method for operating a wearable device may involve determining, based on output of one or more ion selective field effect transistor sensors, various physiological conditions such as a state of hydration, a state of skin health, or the cleanliness of the wearable device or an associated garment.

Abstract: Techniques for measuring ion related metrics at a user's skin surface are disclosed. In one aspect, a method for operating a wearable device may involve determining, based on output of one or more ion selective field effect transistor sensors, various physiological conditions such as a state of hydration, a state of skin health, or the cleanliness of the wearable device or an associated garment.

Abstract: Techniques for measuring ion related metrics at a user's skin surface are disclosed. In one aspect, a method for operating a wearable device may involve determining, based on output of one or more ion selective field effect transistor sensors, various physiological conditions such as a state of hydration, a state of skin health, or the cleanliness of the wearable device or an associated garment.

Abstract: Methods and electronic devices for performing color-based reaction testing of biological materials. The method includes capturing and interpreting digital images of an unexposed and later exposed paddle at various delay times within an automatically calibrated environment. The test paddle includes a unique identification mechanism (UID), a Reference Color Bar (RCB) providing samples of standardized colors for image color calibration, compensation and corrections, and several test-specific sequences of Chemical Test Pads (CTP). The method further includes locating the paddle in the image, extracting the UID and validating the paddle, extracting the RCB and locating the plurality of CTP in each image. The method further reduces image noise in the CTP and calibrates the image automatically according to lighting measurements performed on the RCB.