A system for diagnostic testing may include a meter for performing a diagnostic test on a sample applied to a test media, the meter having a housing and an interface for receiving a signal representing coding information, and a container configured to contain test media compatible with the meter, the container having a coding element associated therewith. Additionally, the system may provide a mechanism for removing the meter from an interconnected test container and reattaching it to a new container using on-container coding methods that can recalibrate the meter for the new container of test strips.

Protecting information by partitioning data across multiple storage resources. A method includes receiving an image of a test card and an identity of a patient associated with the test card. The method includes associating the image of the test card with the identity of the patient as a data pair on a first storage resource. The method includes providing the image of the test card to a second storage resource by way of a network, wherein the first storage resource is independent of the second storage resource. The method includes receiving a result for the test card and associating the result for the test card with the identity of the patient based on the data pair stored on the first storage resource.

Test cards for agglutination assays, wherein the test cards are configured for computer-implemented image analysis. A test card includes a negative control test region for receiving a negative control fluid sample, a positive control test region for receiving a positive control fluid sample, and a test sample region for receiving a test fluid sample. The test card includes one or more unique scannable codes comprising data for instructing a processor to capture an image of the test card that is suitable for computer-implemented image analysis.

Machine learning image analysis for quantitative and qualitative analysis of agglutination samples. A method includes receiving an image of an agglutination assay comprising a negative control sample, a positive control sample, and a test sample. The method includes providing the image to a machine learning algorithm trained to classify agglutination of the test sample on a quantitative scale. The machine learning algorithm calibrates the quantitative scale based at least in part on the negative control sample and the positive control sample.

An apparatus for measuring a concentration of an analyte in a bio-sample using an electrochemical bio-sensor, includes a connector with a sample cell in which an oxidation/reduction enzyme and an electron transfer mediator are fixed and a working electrode and an counter electrode are provided; a digital-to-analog converter circuit configured to apply a constant DC voltage to start the oxidation/reduction reaction of the analyte, proceed with an electron transfer reaction, and apply a Λ-step ladder-type perturbation potential for fluctuating a potential of the sample cell after applying the constant DC voltage; and a microcontroller configured to control the digital-to-analog converter circuit and directly obtain a concentration value of the analyte from a calibration equation using the Λ-step ladder-type perturbation potential. The apparatus can improve measurement accuracy by effectively minimizing a matrix interference effect of a background material in a bio-sample, particularly an inaccuracy caused by a change in hematocrit.

A secure analysis system for analyzing a sample is disclosed. The system includes an analyzer configured to create a measurement of the sample, create a data record of the measurement, encrypt the data record to form an encrypted data file, and provide the encrypted data file. The system also includes a server communicatively coupled to the analyzer and configured to receive the encrypted data file, store the encrypted data file, retrieve at least one of an encrypted algorithm, an encrypted parameter, and a portion of an encrypted library. The server is also configured to retrieve an encryption key, decrypt at least one of the data file, the algorithm, the parameter, and the library portion using the key, analyze the measurement, and provide a result.

A method for diagnosing COVID-19 infection. The method includes drawing a blood sample from a person suspected to be infected with COVID-19 virus, separating a blood serum sample from the blood sample by centrifuging the blood sample, recording an electrochemical impedance spectroscopy (EIS) associated with the blood serum sample, calculating a charge transfer resistance (R.sub.CT) of the recorded EIS by measuring a diameter of a semicircular curved part of the recorded EIS, and detecting a COVID-19 infection of the person based on the calculated R.sub.CT if the calculated R.sub.CT is equal to or more than a threshold value.

A method for diagnosing COVID-19 infection of a person. The method includes acquiring a sputum sample of the person, measuring a level of reactive oxygen species (ROS) in the sputum sample, and detecting a COVID-19 infection status of the person based on the measured level of ROS. Measuring the level of ROS in the sputum sample includes recording a cyclic voltammetry (CV) pattern from the sputum sample and measuring a current peak of the recorded CV pattern. Detecting the COVID-19 infection status of the person based on the measured level of ROS includes detecting the person is infected with COVID-19 if the measured current peak is in a first range of current peaks and detecting the person is not infected with COVID-19 if the measured current peak is in a second range of current peaks.

A system for diagnosing COVID-19 infection. The system includes a biosensor, an electrochemical stimulator-analyzer, and a processing unit. The biosensor is configured to be put in contact with a blood serum sample of a person suspected to be infected of COVID-19 virus. The processing unit is configured to apply an AC potential amplitude to the biosensor while sweeping a frequency range utilizing the electrochemical stimulator-analyzer, recording an electrochemical impedance spectroscopy (EIS) associated with the blood serum sample utilizing the electrochemical stimulator-analyzer, calculating a charge transfer resistance (R.sub.CT) of the recorded EIS, and detecting a COVID-19 infection of the person based on the calculated R.sub.CT if the calculated R.sub.CT is equal to or more than a threshold value.

A method for diagnosing COVID-19 infection. The method includes drawing a blood sample from a person suspected to be infected with COVID-19 virus, separating a blood serum sample from the blood sample by centrifuging the blood sample, recording an electrochemical impedance spectroscopy (EIS) associated with the blood serum sample, calculating a charge transfer resistance (R.sub.CT) of the recorded EIS by measuring a diameter of a semicircular curved part of the recorded EIS, and detecting a COVID-19 infection of the person based on the calculated R.sub.CT if the calculated R.sub.CT is equal to or more than a threshold value.