Biofluid Analysis and Personalized Hydration Assessment System

Abstract

A method for measuring analytes in a bodily fluid sample and combining measurement data from multiple users may involve initiating a wireless connection between a handheld analyzer and a smart computing device having an analyte analysis application downloaded thereto, and inserting a test strip into the handheld analyzer. The method may further involve collecting a sample of the bodily fluid on the test strip, measuring the concentration of at least one analyte in the sample with the handheld analyzer, wirelessly communicating the measured concentrations from the handheld analyzer to the smart computing device, and displaying the measured concentrations on the smart computing device. Finally, the method may involve transmitting the measured concentrations to a database and compiling data including the measured concentrations and at least one additional measured analyte concentration from at least one additional user on the database.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application was filed as a PCT International Patent Application on July 1, 2020, and claims priority to U.S. Provisional Patent Application No. 62 / 869,210, entitled "Biological Fluid Analysis System," filed July 1, 2019, U.S. Provisional Patent Application No. 62 / 876,263, entitled "Personalized Hydration Assessment and Fluid Replenishment," filed July 19, 2020, and U.S. Provisional Patent Application No. 62 / 957,527, entitled "Personalized Hydration Assessment and Fluid Replenishment," filed January 6, 2020. The entire disclosures of all above-referenced provisional patent applications are incorporated herein by reference.

[0002] This application describes biomedical systems and methods. More particularly, this application describes systems and methods for analyzing biological fluids, such as saliva and sweat, and using one or more biomarkers to assess water and electrolyte losses in a human subject and recommend a fluid replacement protocol. [Background technology]

[0003] Sweating (or "sweating") is a technique used by the human body to regulate its body temperature. During periods of physical exercise and / or environmental heat stress, sweat is excreted by the skin, thereby causing cooling via evaporation on the skin surface. Sweat is composed of approximately 99% water, but sweat also typically contains other compounds, such as metabolites and ions. Sweat excretion rates and composition are unique to each individual and subject to biological variation. Excretion rates and sweat composition can also vary significantly based on age, diet, activity, current fitness level, and environmental conditions.

[0004] Adequate hydration in the human body is essential for health and proper functioning of the body's organs. Water is lost from the body during breathing, sweating, and urination. The loss of body mass associated with water loss of only a few percent can adversely affect cardiovascular function, heat dissipation, and exercise performance. Dehydration can cause headaches, lightheadedness, dizziness, fainting, and in extreme cases, delirium, unconsciousness, and even death. A significant loss of body mass (e.g., greater than 5%) can result in heat exhaustion, heat stroke, loss of consciousness, organ damage, and even death. Furthermore, the loss of ions, primarily sodium, through sweating can result in fatigue and muscle cramps if not effectively replenished through ingested fluids. Because there is a large amount of inter- and intra-individual variability in the amount and composition of sweat loss, fluid replacement strategies should ideally be tailored individually to ensure that both water and sodium losses are replenished to minimize the deleterious effects of physical exercise and / or heat stress on health and performance. Hyponatremia ("too much fluid") can also adversely affect bodily functions, especially during exercise, and in extreme cases may even lead to death.

[0005] Dehydration is the excessive loss of bodily fluids. Physiologically speaking, dehydration can involve a lack of water in an organism. Dehydration can be caused by losing too much water, not drinking enough water, or both. Vomiting, diarrhea, and excessive sweating without adequate fluid intake are other causes of dehydration and can be particularly worrisome for athletes and those working in hot, dry conditions. There are three main types of dehydration: hypotonic (mainly loss of electrolytes, especially sodium), hypertonic (mainly loss of water), and isotonic (equal loss of water and electrolytes). Isotonic dehydration is the most common, but the distinction between the three types of dehydration can be important to manage proper fluid replacement strategies.

[0006] Relying on thirst as a feedback mechanism to trigger a need for fluid intake may not be adequate to maintain optimal hydration levels because a sense of thirst sufficient to induce the subject to drink is often not triggered until the subject is already dehydrated. Unfortunately, there are currently no practical, affordable, non-invasive devices for measuring a person's hydration level. Measurement devices that use blood or urine to measure hydration are impractical, invasive, and / or prohibitively expensive.

[0007] Many other physiological parameters and levels of various substances in the human or animal body are frequently tested or desirable to test. Unfortunately, it is often necessary to sample other body substances, such as blood, urine, or cerebrospinal fluid, in order to measure the desired parameters. Some physiological parameters involve even more invasive or costly measurement techniques.

[0008] It would therefore be highly beneficial to have a practical, affordable, non-invasive system and method for measuring a person's hydration status and quantifying the amount of fluid and electrolytes that need to be replaced following dehydration. It would also be highly desirable to have a practical, affordable, non-invasive system and method for testing other parameters within the body.

[0009] Point-of-care testing systems allow for the measurement of biomarkers (e.g., metabolites, hormones, electrolytes) in biological samples outside of a laboratory, such as in a clinic or private residence. By reducing labor and transportation costs, point-of-care testing is an attractive alternative to laboratory testing, especially for frequent and / or routine testing.

[0010] Point-of-care testing systems typically consist of a handheld meter that interfaces with a single-use test strip that is chemically reactive to an analyte (e.g., glucose). Typically, the handheld meter performs all steps necessary for sample analysis (signal generation, signal measurement, data processing) and displays the results on an integrated screen. Some more advanced testing systems are capable of measuring multiple analytes using different test strips based on the same detection method (e.g., amperometric detection of glucose and beta-hydroxybutyrate) and / or wirelessly communicating test results to a phone or tablet for data logging.

[0011] Currently available point-of-care testing systems are adequate for individual users who monitor only one or two of their own biomarkers (e.g., a diabetic patient who measures blood glucose daily). However, such systems are less ideal for large organizations (e.g., hospitals where hundreds of patients are tested daily by multiple health professionals for one or more biomarkers) where many different biomarkers are analyzed by multiple operators on dozens or hundreds of different subjects. In these organizations, test administrators must collect and compile results from many different devices, each measuring a different biomarker using a different detection method.

[0012] It would therefore be desirable to have an analytical system that is versatile enough to test for a wide range of biomarkers using a single testing system. Ideally, such a testing system would allow multiple users to conveniently administer and analyze test results while minimizing user error.

[0013] Sweat testing to determine sweat volume and composition is an increasingly popular method of generating personalized rehydration strategies. This service is primarily used by athletes to determine their fluid needs and gain a competitive edge. Typically, these services involve a one-time collection of activity-induced or chemically-induced sweat through a patch applied to the skin. The collected sweat is then evaluated by a chemical analysis system to determine sweat sodium concentration (in millimoles or parts per million). These measurements are paired with exercise-induced body mass changes when following an exercise protocol to determine sweat rate and fluid loss (e.g., liters / hour). With this information, personalized rehydration protocols are developed to assist with rehydration during and / or after exercise.

[0014] A significant deficiency of this method is the assumption that both sweat electrolyte content and sweat rate are constant for an individual under all conditions. In reality, both sweat composition and sweat rate can vary dramatically based on a number of factors, including the activity undertaken, the degree of exercise, the environmental conditions, and how accustomed the individual is to these conditions. To ascertain this information for an individual, multiple measurements are required across several conditions. With conventional approaches for estimating sweat composition and sweat rate, this is extremely time consuming.

[0015] It would therefore be highly beneficial to have a practical, affordable, non-invasive system and method for measuring a person's hydration status and quantifying the amount of fluid and electrolytes that need to be replenished to prevent or treat dehydration. It would also be highly desirable to have a practical, affordable, non-invasive system and method for testing other parameters within the body. It would also be desirable to develop an accurate, fast method for determining individual fluid volume and composition requirements on a case-by-case basis. Ideally, such a method would be relatively easy to adopt and cost-effective so as to be accessible to a large number of users. The present application addresses at least some of these objectives. [Prior art documents] [Patent documents]

[0016] [Patent Document 1] U.S. Patent Application No. 16 / 197,530 (U.S. Publication No. 2019 / 0150836) [Patent Document 2] U.S. Patent Application No. 16 / 598,000 (U.S. Publication No. 2019 / 0150836) [Patent Document 3] U.S. Provisional Patent Application No. 62 / 872,339 [Patent Document 4] U.S. Provisional Patent Application No. 62 / 961,438 [Patent Document 5] U.S. Provisional Patent Application No. 62 / 967,694 Summary of the Invention [Means for solving the problem]

[0017] Saliva may be an ideal body substance for use in measuring hydration and dehydration. Saliva is a minimally invasive and easily obtained, yet complex, fluid. Approximately 99% of saliva is water, with the remaining 1% comprising large organic molecules (such as proteins), small organic molecules (such as urea), and electrolytes (such as sodium and potassium). Whole saliva, when considered as the total fluid contents of the mouth, contains numerous other components, including serum components, blood cells, bacteria, bacterial products, epithelial cells, cellular products, food debris, and bronchial secretions. Thus, processing saliva to measure an individual's hydration level is challenging, but if done effectively, can be extremely beneficial.

[0018] The assignee of the present application has filed prior patent applications describing systems, methods, and devices for testing, measuring, and analyzing saliva to measure a subject's hydration level, as well as for measuring other substances and / or physiological parameters in a human or animal subject. These prior patent applications include U.S. Patent Application No. 16 / 197,530, entitled "Saliva Testing System," filed on November 21, 2018 (U.S. Publication No. 2019 / 0150836), and U.S. Patent Application No. 16 / 598,000, entitled "Ion Selective Sensor," filed on October 10, 2019 (U.S. Publication No. 2019 / 0150836). These applications also include U.S. Provisional Patent Application No. 62 / 872,339, entitled "Saliva Test Strip and Method," filed July 10, 2019, U.S. Provisional Patent Application No. 62 / 961,438, entitled "Assessment of Biomarker Concentration in a Fluid," filed January 15, 2020, and U.S. Provisional Patent Application No. 62 / 967,694, entitled "Biological Fluid Sample Assessment," filed January 30, 2020. All of the above-referenced patent applications are hereby incorporated by reference into this application and are collectively referred to herein as the "Incorporated Applications." This application advances the art in the incorporated applications by describing a biological fluid analysis system and method that addresses at least some of the objectives set forth above in the Background section.

[0019] This application also advances the technology in the incorporated applications by describing a system and method for assessing hydration levels and electrolyte deficits and recommending hydration protocols before, during, and after physical exercise. Specifically, this application describes a system and method for determining a personalized reference data set based on measurements of salivary osmolarity, body mass loss, exercise-induced fluid sweat rate, and salt (electrolyte) loss under various conditions. This reference data set is used to establish an algorithm that can predict an individual's fluid and sodium replacement requirements specific to environmental conditions, and may include biometric measurements (e.g., salivary osmolarity) and degree of exercise based on activity and / or a standard Rating of Perceived Exertion (RPE) scale. These requirements are then communicated to the individual to provide detailed guidance on when and what to consume to compensate for fluid and sodium losses during exercise, and on a case-by-case basis, to replenish and restore fluid and sodium losses after exercise or heat stress.

[0020] In one aspect of the disclosure, an analytical system includes a portable handheld analyzer and one or more analyte-specific test strips used to monitor multiple analytes from human or animal bodily fluids. The handheld analyzer can perform impedimetric, potentiometric and / or amperometric analysis and can determine the concentration of multiple analytes using the analyte-specific test strips. To improve ease of use, the handheld analyzer can automatically detect the test strip type and batch and automatically apply temperature compensation to adapt to ambient conditions. In one embodiment, the handheld analyzer can be used independently in a stand-alone mode. In another embodiment, the handheld analyzer can be wirelessly connected to a phone, tablet, etc. to upload measurement data to a cloud database. The cloud database can be accessed using a phone or tablet to view and analyze data from multiple users and devices. To improve validity and accuracy, the system can integrate methods for measurement interpretation personalized to individual users, methods for detection of abnormal readings, error detection algorithms, and / or methods for compensating for temperature effects on measurements.

[0021] In another aspect of the disclosure, a method of measuring analytes in a bodily fluid sample and combining measurement data from multiple users may first involve initiating a wireless connection between a handheld analyzer and a smart computing device on which an analyte analysis application has been downloaded, and inserting a test strip into the handheld analyzer. The method may also involve collecting a sample of bodily fluid on a test strip, measuring a concentration of at least one analyte in the sample with the handheld analyzer, wirelessly communicating the measured concentration from the handheld analyzer to the smart computing device, and displaying the measured concentration on the smart computing device. Finally, the method may involve transmitting the measured concentration to a database, and organizing the data including the measured concentration and at least one additional measured analyte concentration from at least one additional user on the database. The order of these method steps may be changed in various alternative embodiments.

[0022] In some embodiments, the method may further involve initiating a wireless connection between the smart computing device and the Internet, where the database is located on a cloud storage location, and where transmitting the measured concentrations to the database involves wirelessly transmitting the measured concentrations from the smart computing device to the cloud storage location via the Internet. In some embodiments, the data is organized based on groups of users belonging to multiple organizations. In some embodiments, the method may also involve initiating the measuring step via the smart computing device, where initiating the measuring step may involve logging into an operator account on the specimen analysis application, selecting a particular source from which a sample will be taken, and verifying the wireless connection between the handheld analyzer and the smart computing device.

[0023] The method may optionally further include automatically downloading and storing the test strip type and batch data on the handheld analyzer. For example, in some embodiments, automatically downloading and storing the test strip type and batch data may involve measuring resistance-encoded test strip identification information on the test strip and comparing the test strip identification information to data in the memory of the handheld analyzer to determine the test strip type and batch data. In some cases, such a method may further involve communicating the test strip type and batch data to a smart computing device and alerting a user through an error message on the handheld analyzer and the smart computing device if the test strip type is an unknown test strip type.

[0024] In some embodiments, the method may also involve preventing the use of a used or faulty test strip by determining that the test strip has already been used or is faulty and prompting the user in at least one of the handheld analyzer or smart computing device to discard the test strip. The method may also optionally involve providing instructions to the user on how to collect the sample using the application and / or the handheld analyzer. Also optionally, the method may involve using the handheld analyzer to determine the ambient temperature, apply a detection technique based on the ambient temperature, and determine the concentration of the analyte using a batch-specific calibration factor and the ambient temperature. The method may also involve determining that the measurement is inaccurate by measuring signal inconsistency with the handheld analyzer and detecting an abnormally high or low signal for the test strip. In some embodiments, the method may further involve analyzing the measured concentration to aid user interpretation using the smart computing device. In some embodiments, the smart computing device relates the raw measured concentrations to previously established individual-specific reference values.

[0025] In another aspect of the present disclosure, a method of measuring at least one analyte in a bodily fluid sample from a subject may involve inserting a test strip into a handheld analyzer, collecting a bodily fluid sample on the test strip by contacting the test strip with a body part of the subject where bodily fluid is present, removing the test strip from contact with the body part after the handheld analyzer indicates that a sufficient amount of the bodily fluid sample has been collected, applying an electrical signal to the test strip, measuring a response of the combination of the test strip and the bodily fluid sample to the applied electrical signal with the handheld analyzer, analyzing the response with the handheld analyzer to determine that the bodily fluid sample is a valid sample, measuring a concentration of at least one analyte in the bodily fluid sample, and displaying the measured concentration on the handheld analyzer and / or transferring the measured concentration to another device to display the measured concentration, generate further calculations, and / or store the measured concentration. Again, the order of these steps may be altered without departing from the scope of the present invention.

[0026] In another aspect of the present disclosure, a handheld analyzer for determining a concentration of one or more analytes in a bodily fluid may include a housing, a test strip port in the housing, a display screen on the housing, a temperature sensor in the housing, and a number of electronic components in the housing, which may include at least one of a direct digital synthesis (DDS) chip or a digital-to-analog converter (DAC) chip, an analog-to-digital converter (ADC) chip, a wireless communication chip, a processing circuit, and a computer memory.

[0027] In some embodiments, the test strip port is configured to accept a test strip selected from the group consisting of analyte-specific test strips and test strips capable of measuring multiple analytes. In some embodiments, the electronic components are configured to automatically transfer test strip configuration settings to the computer memory when the handheld analyzer is connected to the database via the mobile application. In some embodiments, the handheld analyzer is configured to determine test strip type and batch data using resistively encoded identification information on the test strip and data stored in the computer memory. In some embodiments, the electronic components are configured to automatically adjust detection methods, excitation waveforms, and gain settings for the multiple types of test strips. In some embodiments, the temperature sensor is configured to measure an ambient temperature, and the processing circuitry is configured to process the measured ambient temperature using a temperature detection algorithm. In some embodiments, the electronic components are configured to automatically detect and interpret application of a bodily fluid sample to the test strip using a moisture detection algorithm and at least one of initiating a measurement or ensuring sample integrity.

[0028] In some embodiments, the processor is configured to compare the measured concentration and the measured temperature to reference data specific to the test strip type and batch to determine the analyte concentration. In some embodiments, the processor is configured to analyze the raw measurements with an error detection algorithm to ensure sample consistency and measurement integrity. In some embodiments, the handheld analyzer is configured to display an error message on a display screen if a test strip is inserted while the handheld analyzer is charging. In some embodiments, the processor is configured to count the number of measurements performed with the handheld analyzer and provide alerts to perform routine maintenance procedures on the device. In some embodiments, the handheld analyzer is configured to perform auto-calibration and self-testing to account for manufacturing variations.

[0029] In another aspect of the disclosure, a method for interpreting an analyte concentration for a subject may involve taking at least one measurement of the analyte at least once from the subject under controlled conditions, determining a personalized reference range for the analyte specific to the subject under controlled conditions using an algorithm, and providing a specific measurement interpretation customized for the subject using the personalized reference range.

[0030] In some embodiments, the method may further involve using a protocol to establish physiological conditions under which controlled measurements may be collected as required by the user. In some embodiments, the method may further involve using a protocol to establish physiological conditions under which measurements are specifically outlined as part of the protocol. In some embodiments, the method may further involve outlining specific conditions under which controlled measurements may be performed. In some embodiments, the method may further involve using multiple protocols to establish multiple personalized reference ranges for a single analyte. In some embodiments, the method may further involve using at least one personalized reference range from a single analyte to provide an individual-specific interpretation of subsequent measurements. In some embodiments, the method may further involve using personalized reference ranges for multiple analytes to provide an individual-specific interpretation of subsequent measurements.

[0031] In another aspect of the disclosure, a method for assessing the integrity of a measurement may involve applying at least one signal to a test strip by a handheld analyzer, using the handheld analyzer to monitor the at least one signal for inconsistencies, and classifying the measurement as normal or abnormal based on whether there is a signal inconsistency. In some embodiments, the signal includes a plurality of signals. The signal comprises a portion of the measurement signal. In some embodiments, the signal is independent of the measurement signal. In some embodiments, the measurement inconsistency is used to categorize the measurement as low confidence, and the operator is instructed to discard the measurement. In some embodiments, the measurement inconsistency is used to categorize the measurement as low confidence, and the measurement is not reported to the operator. Some embodiments may further involve using the measurement inconsistency to categorize the measurement as low confidence and reporting the low confidence measurement to a user. Some embodiments further involve using the measurement inconsistency to categorize the measurement as low confidence and automatically prompting the user to perform another measurement. In some cases, the method may further involve using the measurement inconsistency to modify at least one of the method of detection or measurement interpretation algorithms applied by the handheld analyzer.

[0032] In another aspect of the disclosure, a method of compensating for temperature when measuring an analyte may involve monitoring the temperature with a temperature sensor, determining an ambient temperature using an algorithm stored in the handheld analyzer, and using the determined ambient temperature to modify at least one of a signal generation parameter, a signal detection parameter, or a signal interpretation for measuring the analyte.

[0033] In some embodiments, the temperature is monitored by a handheld analyzer with an integrated temperature sensor. In some embodiments, the temperature is monitored by a handheld analyzer with an external temperature sensor. In some embodiments, the rate of change in temperature is used to determine the ambient temperature. In some embodiments, the method may further involve using at least one of the ambient temperature or the rate of change in temperature to determine the time needed for the sample to equilibrate to the target temperature before the detection method is applied.

[0034] In another aspect of the present disclosure, a method of generating a personalized reference data set of fluid loss for a human subject may involve following a protocol or set of protocols or performing a series of exercise sessions; collecting first data related to a sweat salt content biomarker reflecting the amount of salt in sweat collected from the human subject; collecting second data related to a body mass change biomarker reflecting changes in the human subject's body mass through fluid loss; and processing the first data and the second data with an algorithm to generate the reference data set.

[0035] In various embodiments, the sweat salt content biomarkers may include, but are not limited to, sweat osmolarity, sweat conductivity, and / or sweat electrolyte concentration. In various embodiments, the body mass change biomarkers may include, but are not limited to, salivary osmolarity, salivary conductivity, salivary electrolyte concentration, urine osmolarity, urine specific gravity, urine color, and / or direct measurements of body mass. In some embodiments, the method may further involve calibrating the salivary biomarkers for water loss using a set of paired measurements of the salivary biomarkers and the change in water loss as determined by the change in the body weight of the human subject. In some embodiments, the salivary biomarkers for water loss are measured before and / or after the protocol or exercise session, and the sweat biomarkers are measured during and / or after the protocol or exercise session.

[0036] In some embodiments, the protocol involves engaging in an activity for a set duration at a particular level of exertion as determined by a perceived exertion scale or a heart rate-based metric of exertion under at least one defined environmental condition. In some embodiments, the protocol involves engaging in a series of activity sessions after which the human subject reports the level of exertion and at least one environmental condition. In some embodiments, the protocol is determined using parameters defined by the human subject. In some embodiments, the exercise level is automatically logged using a personal activity monitor. In some embodiments, blood biomarkers, sweat biomarkers, and / or saliva biomarkers may be used to assess the degree of exertion. In some embodiments, the method further includes collecting at least one environmental condition via manual input from the human subject. In some embodiments, the method may further include collecting at least one environmental condition via automatic input from a weather monitoring service or device.

[0037] In another aspect of the present disclosure, a method of personalizing fluid replacement guidelines for a human subject after the human subject engages in an activity, in which a set of baseline values ​​for fluid loss and salt content have been previously established for the human subject, may involve establishing a change in the human subject's body mass through fluid loss related to the degree of exercise and at least one environmental condition using a body mass change biomarker of fluid loss, predicting the amount and chemical composition of fluid lost from the human subject using an algorithm, and providing advice to the human subject regarding the amount and composition of fluid needed for replenishment and recovery, and the time period over which fluid should be ingested.

[0038] In various embodiments, the body mass change biomarkers may include, but are not limited to, salivary osmolality, salivary conductivity, salivary electrolyte concentration, urine osmolality, urine specific gravity, urine color, and / or direct measurements of body mass. In some embodiments, the degree of exercise is self-reported by the human subject. In some embodiments, the degree of exercise is established using a personal activity monitor or a heart rate monitor. In some embodiments, the method may further involve determining the degree of exercise using biomarkers, such as, but not limited to, blood biomarkers, sweat biomarkers, and / or saliva biomarkers.

[0039] In some embodiments, the environmental conditions are self-reported by the human subject. In some embodiments, the environmental conditions are determined using a weather monitoring service or device. In some embodiments, the advice is provided via a computer application for at least one of a smartphone or a tablet computing device. In some embodiments, providing the advice involves providing prompts to the human subject via the computer application regarding when to consume fluid and at least one type of fluid to drink.

[0040] In another aspect of the present disclosure, a method of personalizing fluid replacement guidelines for a human subject engaged in an activity, in which a set of baseline values ​​for fluid loss and salt content have been previously established for the human subject, may involve establishing a degree of exercise for the human subject engaged in the activity, establishing at least one environmental condition, using an algorithm together with the established degree of exercise and the at least one environmental condition to predict the amount and chemical composition of fluid lost by the human subject during the activity, and providing advice to the human subject regarding the amount and composition of fluid needed for recovery and the time period over which fluid should be ingested.

[0041] In another aspect of the disclosure, a method of personalizing hydration guidelines for a human subject prior to engaging in an activity, in which a set of baseline values ​​for fluid loss and / or salt content have been previously established for the human subject, may involve establishing at least one environmental condition, establishing a degree of exercise as expected by the human subject, predicting the amount and chemical composition of fluid lost by the human subject during the activity using an algorithm with the at least one environmental condition and the degree of exercise, and providing advice to a user regarding the amount and composition of fluid for maintaining hydration during exercise for the human subject and for recovery after exercise. In some embodiments, the method may further involve using hydration biomarkers to establish the hydration state of the human subject prior to engaging in the activity, and using the hydration biomarkers to customize the advice.

[0042] In another aspect of the present disclosure, a method of personalizing fluid replacement guidelines for a human subject after engaging in an activity, in which a set of baseline values ​​for fluid loss and / or salt content have been previously established for the human subject, may involve measuring salivary osmolality after an exercise event and providing advice to a user regarding the amount and composition of fluid for post-exercise recovery for the human subject.

[0043] In some cases, the method may further involve using hydration biomarkers, such as salivary osmolality, to establish the hydration state of the human subject after engaging in the activity, and using the hydration biomarkers to customize rehydration advice. In other embodiments, the method may involve using hydration biomarkers to establish the hydration state of the human subject after engaging in the activity, and using markers of long-term (temporal) hydration biomarkers to customize and adapt advice based on how quickly the human subject's hydration is returning to a desired level. The time between hydration biomarker measurements is determined by the difference between the desired hydration status and the current hydration status.

[0044] In another aspect of the disclosure, a method for determining sodium content of a sweat sample from a human subject may involve collecting a sweat sample from the human subject, performing an electrochemical test on the sweat sample using a portable handheld testing system to take measurements of at least one of the conductivity, impedance, or osmolality of the sweat sample, and converting the measurements to sodium content using a calibration curve. In some embodiments, collecting the sweat sample involves collecting a small amount of sweat directly from the skin of the human subject using a single-use test strip of the handheld portable testing system. In some embodiments, collecting the sweat sample involves collecting sweat from the skin of the human subject via an adhesive patch applied directly to the skin, extracting the sweat from the patch, and collecting the sweat sample from the extracted sweat using a single-use test strip of the handheld portable testing system.

[0045] In some embodiments, the sweat sample is collected using an adhesive patch including at least one of electrodes and microfluidics, which provides an on-skin analysis of sodium content through a physical connection with a handheld portable testing system. In some embodiments, the sweat sample is collected using an adhesive patch including electrodes, microfluidics, and / or electronic components, which performs an electrochemical test and wirelessly communicates raw data from the electrochemical test to the handheld portable testing system. In some embodiments, the portable testing system is further configured to perform an analysis of at least one additional biomarker of sweat, saliva, or blood to establish body mass changes and / or physical exercise of the human subject.

[0046] These and other aspects and embodiments are described in more detail below with reference to the accompanying drawings. [Brief description of the drawings]

[0047] [Figure 1] FIG. 1 is a diagram of a biological fluid analysis system, according to one embodiment. [Diagram 2] FIG. 1 is a diagram of a handheld analyzer, according to one embodiment. [Diagram 3] 1 is a flow chart of a method for independently using a biological fluid handheld analyzer as a point-of-care device, according to one embodiment. [Figure 4] 1 is a flowchart of a method for using a biological fluid handheld system, including pairing with a phone or tablet, according to one embodiment. [Diagram 5] FIG. 1 is a diagram of a system for creating a reference data set for hydration and sweat loss for human subjects, according to one embodiment. [Figure 6] 1 is a flowchart illustrating a method for assessing sweat loss and recommending a rehydration protocol, according to one embodiment. [Figure 7] 11 is a flow chart illustrating a method for assessing sweat loss and recommending a rehydration protocol according to an alternative embodiment. [Figure 8] 13 is a flow chart illustrating a method for assessing sweat loss and recommending a rehydration protocol according to another alternative embodiment. [Figure 9] 1 is a flow chart showing a protocol for rehydrating and monitoring hydration after exercise. [Figure 10] 1 is a flow chart showing a fluid replacement algorithm based on the measurement of saliva osmolality. [Figure 11] 1 is a flow chart illustrating a sodium replacement algorithm based on measuring sweat sodium concentration. [Figure 12] FIG. 11 is a flow diagram showing a method for assessing sweat loss, recommending a rehydration protocol, and feeding back data into a baseline data set, according to another embodiment. [Figure 13] FIG. 1 is a system diagram illustrating a sweat collection and analysis system, according to one embodiment. [Figure 14A] FIG. 1 illustrates a method for collecting and analyzing sweat, according to one embodiment. [Figure 14B] FIG. 1 illustrates a method for collecting and analyzing sweat, according to one embodiment. [Figure 14C] FIG. 1 illustrates a method for collecting and analyzing sweat, according to one embodiment. [Figure 14D] FIG. 1 illustrates a method for collecting and analyzing sweat, according to one embodiment. [Figure 15] 1 is a chart showing the correlation between osmolality and sodium concentration of sweat samples, according to one embodiment. [Figure 16] FIG. 11 is a flow diagram showing a method for assessing sweat loss, recommending a rehydration protocol, and feeding back data into a baseline data set, according to another embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0048] This application describes various embodiments and features of biological fluid analysis systems and methods. With reference to Figure 1, one embodiment of a biological fluid analysis system 10 includes a handheld analyzer 12, a number of test strips 14a-14e, and an application 16 for use on a phone, tablet, or other smart computing device. The system 10 may further include a database 18 (or multiple databases) for storing data that may be accessed by the application 16. The database 18 may be located in the cloud, or any other suitable location.

[0049] Test Strips In various embodiments, the biological fluid analyzing system 10 may include any suitable number and combination of types of test strips 14a-14e. In some embodiments, for example, a panel of test strips 14a-14e may be provided, with each strip 14a-14e chemically sensitive to a particular analyte (e.g., electrolyte, metabolite, hormone) or panel of analytes (e.g., electrolytes). The test strips 14a-14e are single-use, disposable, and configured to test for a particular biological sample type (e.g., blood, saliva, sweat, urine) or non-biological sample type (e.g., pool water, wastewater). The test strips 14a-14e may be visually distinct and / or include resistor-encoded identification codes in some embodiments. The test strips 14a-14e may use one or more of a variety of detection methods.

[0050] Test strips 14a-14e may vary significantly in size, shape, and design, but may share common design elements that allow for compatibility with a single analyzer 12. In one embodiment, test strips 14a-14e include a sampling port and four untreated carbon electrodes, three of which are used for impedimetric measurements, and a fourth of which is a resistance-encoded identification code that represents the test strip type and batch. In another embodiment, test strips 14a-14e include a sampling port and three carbon electrodes, two of which are configured to allow potentiometric measurements of an analyte, and a third of which is a resistance-encoded identification code that represents the test strip type and batch. Common to both of these embodiments of test strips 14a-14e are the electrode structure for interfacing with handheld analyzer 12, and the test strip identification information. All other features are configured for a given analyte (or set of analytes) and sample type.

[0051] 1, four types of test strips 14a-14e are shown as part of the biological fluid analysis system 10. (Multiple strips of each type may be provided, or alternatively, any other suitable number of test strip types may be provided.) In this embodiment, the analysis system includes test strip 14a for specimen #1, strip 14b for specimen #2, strip 14c for specimen #3, strip 14d for specimens #1 and #2, and strip 14e for specimens #1 and #3. Of course, specimens #1, #2, and #3 may be any suitable specimens, according to various embodiments.

[0052] analyzer In some embodiments, the analyzer 12 of the biological fluid analysis system 10 is a handheld, point-of-care analyzer 12 capable of signal generation, measurement, and processing. The handheld analyzer 12 may automatically determine the type of test strip 14a-14e inserted into it, for example, by reading a register-encoded identification code on the test strip 14a-14e. The handheld analyzer 12 may use the identification information to configure detection methods, excitation waveforms, and gain settings, as well as to apply batch-specific calibration curves when processing raw measurement data.

[0053] 2, one embodiment of the handheld analyzer 12 is shown in detail. In this embodiment, the handheld analyzer 12 includes a microcontroller 20 with an on-board Bluetooth low energy chip 22 for wireless communication and an analog-to-digital converter (ADC) chip 24 for measurement of analog signals. The analyzer further includes an antenna 26 for wireless communication, a real-time clock 28, a memory 30 for storage of test strip identification information and batch calibration data, a user interface 32 including a screen, buttons, and LEDs, a temperature sensor 34 for monitoring ambient temperature, a direct digital synthesis chip 36 for digital signal generation, a digital-to-analog converter chip 38 for analog signal generation, a low noise analog switch 40 for regulating transfer of the signal generation to the sensor circuitry 42, and a gain setting circuit 44.

[0054] The handheld analyzer may also include three multiplexers ("MUX") 46, 48, 50. The first multiplexer 46 is configured to regulate a connection between the sensor circuitry 42 and a sensor port 54. The second multiplexer 48 is configured to regulate a connection between the sensor circuitry 42 and a high-resolution ADC 52. The third multiplexer 50 is configured to regulate a connection between the sensor circuitry 42 and the microcontroller 20.

[0055] Features of this embodiment of the handheld analyzer 12 allow a diverse range of analytical techniques to be employed with a single analyzer 12. Specifically, the multiplexing of signal generation, gain settings, and a second high resolution ADC enable impedimetric, amperometric, and potentiometric analysis.

[0056] FIG. 3 illustrates one exemplary method 100 for independently using the handheld analyzer 12 as a point-of-care analysis device. In this embodiment, the method begins in step 102 by starting (e.g., powering on) the analyzer 12. In step 104, the user is prompted to insert a test strip. The user inserts a test strip into the analyzer 12 in step 106, and the handheld analyzer 12 automatically detects the test strip type and batch in steps 108 and 110 to ensure that the test strip is not used or defective. For example, in one embodiment, the impedance of the test strip is used to determine whether the test strip is used or defective. In another embodiment, a one-way fuse is used to ensure that the test strip is not reused.

[0057] Error detection algorithms can be used to identify questionable readings. In one embodiment, a periodic stimulation signal is applied and consistency between measurements is used to assess the accuracy of the results. In another embodiment, the periodic signal is applied at multiple distinct frequencies and these are interrogated. Reference ranges of values ​​can also be used to determine whether the results are in the appropriate range for a given analyte or sample type.

[0058] If step 108 or step 110 indicates that a "bad" strip has been inserted, the analyzer provides an error code or other prompt to the user (steps 112 and 114) so ​​that the user knows to remove the test strip from the analyzer 12 and begin the method again. If the test strip is accepted by the analyzer 12, the user receives a prompt to apply a moisture sample to the test strip in step 116. Instructions for sample collection, and error messages may be relayed to the user on an integral display screen. In step 118, the analyzer 12 applies a moisture detection algorithm to the moisture sample to determine if the sample is adequate. If the sample is insufficient, the user receives another prompt to add more moisture to the test strip (repeat step 116). If the sample is adequate, the analyzer may provide another prompt to indicate that moisture has been detected and to wait for the results (step 120). In step 122, data processing is performed on the handheld analyzer 12, and in step 124, an error detection algorithm is applied. If the analyzer 12 detects an error, the user is prompted accordingly, the test strip is removed and replaced with a new strip, and the method begins again, at step 126. If the error detection algorithm confirms a good reading of the moisture sample, the results of the measurement are displayed to the user on the analyzer and / or a smart device coupled to the analyzer, at step 128. In some embodiments, the handheld analyzer 12 may include integrated cellular or wireless capabilities. In such embodiments, the handheld analyzer 12 may upload the measurement results for storage in a cloud server or other database.

[0059] The handheld analyzer 12 may record the number of measurements performed on its internal memory. Using this information, the user is prompted to perform routine maintenance at certain milestones. In one embodiment, the user is prompted to replace the test strip port after a certain number of measurements have been performed. In some embodiments, the handheld analyzer also includes an internal reference load, which may be used to perform start-up calibration and account for manufacturing variations.

[0060] Phone / Tablet Application 1, the application 16 provided with the biofluid analysis system 10 may be configured for use on a smartphone, tablet, and / or other computing device. The application 16 facilitates step-by-step operator instruction, subject selection, and measurement interpretation. Measurements made by the handheld analyzer 12 may be automatically uploaded to a cloud database 18 via the application 16.

[0061] Referring to FIG. 4, a method 200 of phone / tablet application operation with handheld analyzer 12 is shown. In this method, the application is started at 202 and the user logs in at 204. The user selects a test subject at 203. The app prompts the user to turn on the analyzer at 206. The user starts the analyzer at 224 and the analyzer prompts the user to turn on the app at 226. Obviously, the order of these steps may be reversed and the prompts are optional. The app checks to see if it is paired with the analyzer at 208 and the analyzer checks to see if it is paired with the app using the data logging application at 228. Once paired, any new type / batch data may be transferred to the handheld analyzer memory (steps 210 and 230). The user then selects a profile to begin measurements.

[0062] The user is then prompted to insert a test strip into the handheld analyzer (steps 212 and 232), which the user does, and the analyzer guides the user through similar or identical steps to those described with respect to FIG. 3 (steps 234, 236, 238, 240, 242, 244, 246, 248). Instructions may be displayed on the handheld analyzer and / or the phone / tablet to instruct the user on how to collect the sample. (See, for example, steps 216, 218, 220 for display on the app). Sample analysis and data processing are performed on the handheld analyzer. Ambient temperature may be used to calibrate the measurement technique or to assist in processing the data. Results are communicated to the application (step 250), displayed on the phone / tablet (step 220), and logged in the user profile. Interpretation information may be displayed on the phone application screen. The results may be automatically uploaded to a cloud server if an internet connection is available (step 222) and / or may be stored locally for uploading when a connection is available. Finally, the user may be prompted to remove the used test strip at 252.

[0063] In some embodiments, a user-specific reference panel may be established in advance through a protocol or set of protocols. This information may be used to provide user-specific interpretation information.

[0064] Database Referring again to FIG. 1 , the biological fluid analysis system 10 may also include one or more databases 18 for storing any suitable data related to the system 10 and methods. In some embodiments, the system 10 may include a database 18 located in the cloud. The database 18 may be distributed and may store information for operation of the system 10, including test strip characteristics (type, batch, calibration factor), operator profile, subject profile, and test results. The cloud database 18 may be accessed through a web browser by an operator to review, analyze, and export test results. Users with necessary permissions may view test results collected by multiple users and / or multiple analyzers for multiple tests.

[0065] This application describes various embodiments and features of hydration assessment systems and methods for determining a human subject's level of hydration and recommending hydration protocols. Although the following disclosure focuses on the analysis of sweat and / or saliva, the embodiments described below, or variations of those embodiments, may be used for the analysis of any other bodily fluids, such as blood, urine, etc.

[0066] Reference Data Set 5 illustrates a hydration measurement system 300 for creating a reference dataset 302 of information related to sweat loss and hydration of a human subject. The reference dataset 302 includes a panel of measured parameters collected over multiple measurement sessions 312 using one or more measurement devices. The parameters may include, but are not limited to, environmental conditions 304 (e.g., temperature, humidity, wind speed, altitude), body mass change and / or salivary osmolality change 306, sweat electrolyte content 308, and / or one or more physical movement measurements 310 (e.g., heart rate, respiration rate, etc.). Each of the various parameters 304, 306, 308, 310 may be measured using its own separate measurement device, or in some cases, using one measurement device to measure multiple parameters. For example, as shown generally in Figure 5, a smartphone may be used to collect environmental condition data 304, a saliva measuring device may be used to measure body mass change and / or saliva osmolality 306, a sweat measuring device may be used to measure sweat osmolality / sweat sodium content 308, and a heart rate monitor may be used to measure physical movement 310. In alternative embodiments, for example, the saliva measurements 306 and sweat measurements 308 may be collected using the same handheld measuring device and the same or different test strips. These types of devices are described in more detail in the incorporated references.

[0067] Environmental condition data 304 may be collected, for example, by manual logging of parameter data from external devices, automatic data logging from dedicated testing systems, or automatic logging of these parameters from weather monitoring services based on time and location data. The degree of physical exertion 310 may be determined, for example, through self-reporting on a standard Rating of Perceived Exertion (RPE) rating scale and / or inferred from one or more measured biomarkers of physical exertion (e.g., activity, heart rate, V02 max, lactate concentration in blood, sweat, or saliva). These measurements may be manually reported and / or automatically logged using a personal monitoring device such as a fitness watch or heart rate chest strap. Percentage body mass loss 306 may be established, for example, through direct measurement of body mass before and after a period of exercise, taking into account any water ingested or lost through urination, or inferred from biomarkers of change in body mass (e.g., increased salivary osmolality or salinity, urine osmolality, or urine specific gravity). The sweat sodium content 308 may be established through direct measurement of sweat sodium content 308 using a chemical analysis system, or may be estimated from the conductivity or osmolality of the sweat sample.

[0068] Thus, the hydration assessment system 300 may include multiple data capture devices (or programs or applications on the devices) to collect, for example, environmental conditions 304, body mass loss 306, sweat sodium content 308, and / or heart rate or other measures of exercise 310. Each measurement device is used over multiple measurement sessions 312 to collect various types of data 304, 306, 308, 310 and provide the data to the reference dataset 302, which may be located in a database stored on a computer or in the cloud. The reference dataset 302 may be generated, for example, by following a set of predefined exercise protocols that specify the duration and intensity of exercise prior to the collection of measurements, or by taking measurements over time during normal activity. In the illustrated example, data is collected over four trial measurement sessions 312 (trials 1-4). A human subject runs for 60 minutes during each session at different outdoor temperatures and at different RPEs. The data collected from all four measurement sessions 312 is fed into the reference dataset 302. The reference data set 302 may then be used to establish an algorithm, which may be used to estimate sweat rate and / or sweat sodium composition of human subjects under a variety of conditions.

[0069] In the embodiment of FIG. 5, a set of four exercise trial measurement sessions 312 are defined outlining environmental conditions (cool and hot) and intensity (RPE3-4 (light-moderate activity) and RPE7-8 (vigorous activity)). Environmental conditions 304 are manually logged by the user into the phone application. Saliva osmolality 306 is measured before and after exercise using a handheld testing device (such as the device described in the incorporated application), which wirelessly communicates the results to the phone application. Changes in saliva osmolality 306 can be used to estimate changes in body mass during each trial. Sweat can be collected using an adhesive patch (or, in alternative embodiments, other collection device) during each trial. Sweat osmolality 308 is measured using a handheld testing device (such as the device described in the incorporated application), which wirelessly communicates the results to the phone application. Sweat osmolality 308 or conductivity can be used to estimate sweat sodium content. Heart rate may be monitored using a chest strap monitor and wirelessly communicated to a phone application. Average heart rate may be used to determine the intensity of the exercise 310.

[0070] Fluid replacement guidelines 6, a method 320 is outlined for using the reference data set 302 to generate a rehydration protocol 324 including hydration guidelines for a human subject. These guidelines may assist in compensating for fluid and sodium losses during heat stress or physical exercise, and to replenish and restore fluid and sodium to return to resting levels after exercise or heat stress. Once the reference data set 302 is established, the method 320 may involve using an algorithm to predict sweat sodium loss at 322, and then using the predicted sweat sodium loss to generate a rehydration protocol 324. Instructions in the rehydration protocol 324 may define the amount of fluid needed to replace the loss, the sodium composition of the fluid needed to replace the loss, and / or the time during which these fluids should be ingested. The algorithm may be implemented at 322, and the rehydration protocol 324 may be generated via a processor stored in a computer, an application stored on a smartphone or smart tablet, a processor in the cloud, or the like. The application may provide alerts to assist in following the protocol.

[0071] In the embodiment shown in FIG. 6, environmental conditions 304 are monitored using a portable weather monitoring system 334 and wirelessly communicated to the phone application. Exercise levels 310 during the exercise session are monitored using a chest strap heart rate monitor 340 and wirelessly communicated to the phone application. Salivary osmolality 306 is measured before and after exercise using a handheld testing device 336, which wirelessly communicates the results to the phone application. Changes in salivary osmolality 306 are used to estimate changes in body mass during exercise. The baseline data set 302 is used to predict sweat composition at 322 based on the recorded information. The phone application generates a hydration protocol 324 that outlines what and how much to drink after exercise to aid in hydration and recovery.

[0072] FIG. 7 illustrates another embodiment of a method 350 for assessing hydration and providing a rehydration protocol 366. In this embodiment, environmental conditions 354 are determined using an online weather monitoring service 356 and the user's location. Exercise level 360 during the exercise session is monitored using a heart rate monitor 362, e.g., a wrist-based monitor integrated into a smartwatch, and wirelessly communicated to a phone application. The reference data set 352 is used to predict changes in body mass and sweat composition based on the recorded and measured information at 364. The phone application generates a rehydration protocol 366 outlining what to drink to aid recovery after exercise, and periodically alerts the user through a mobile notification to reinforce the drinking behavior. Again, the sweat composition prediction step 364 and the step of generating a rehydration protocol 366 may be performed by any suitable processor, such as an application for a smart device, a processor in a computing device, a cloud processor, etc.

[0073] FIG. 8 illustrates another embodiment of a method 370 for assessing hydration and providing a rehydration protocol 392. In this embodiment, environmental conditions 374 are determined using an online weather monitoring service 384 and the user's location. Exercise level 380 is predicted by the user specifying the expected intensity of the exercise (e.g., race day / high intensity) at 382. Salivary osmolality 376 is measured before the exercise with a handheld testing device 386, which wirelessly communicates the results to the phone application. Salivary osmolality 376 is used to estimate a starting hydration status. The baseline data set 372 is used to predict changes in body mass and sweat composition based on the recorded information at 390. The phone application generates a rehydration protocol 392 that outlines what to drink to help maintain hydration during exercise and to help rehydrate and recover after exercise. The user is periodically alerted during exercise to drink beverages to help stay hydrated and to make up for fluid loss.

[0074] In another embodiment, salivary osmolality is measured after exercise. The baseline data set is used to predict the final salivary osmolality, or the change in salivary osmolality before and after the event, or the difference between the individual's optimal hydration zones, as well as the change in body mass. Sodium and electrolyte losses are estimated from sweat composition based on the recorded information. The phone application generates a protocol outlining what to drink, how much to drink, and when to drink to aid in hydration recovery after exercise.

[0075] In another embodiment, the user may be periodically alerted during post-exercise recovery to measure their salivary osmolality. These other salivary measurements are used to estimate the effectiveness of the initial hydration protocol and to allow the hydration protocol to be adapted to increase its effectiveness and return the individual to a desired hydration status.

[0076] In another embodiment, a user may be periodically alerted during post-exercise recovery to measure their salivary osmolality, with the time period between prompts being based on how far the individual's salivary osmolality and hydration status is from the individual's desired hydration status.

[0077] FIG. 9 illustrates one embodiment of a rehydration protocol 400 (or "recovery protocol"). In this embodiment, salivary osmolality is measured before exercise at 402 and after exercise at 404, the change in osmolality is calculated at 406, and the change is used to estimate body mass loss at 408 using a rehydration algorithm 450, such as algorithm 450 shown in FIG. 10. Sweat sodium is either measured directly at 410 or estimated from a reference panel using environmental and / or exercise parameters and a protocol for salt replacement generated using a sweat replacement algorithm 470, such as algorithm 470 shown in FIG. 11. Salivary osmolality is used to monitor rehydration until the individual has adequately achieved their desired hydration status.

[0078] In the embodiment shown in FIG. 9, the rehydration protocol first involves determining at 414 whether the fluid loss was less than 500 milliliters. If less than 500 mL, the protocol instructs the user to replenish fluid as a single bolus at an amount of 150% of the fluid lost at 416. If the fluid loss was 500 mL or more, the user is instructed at 418 to replenish up to 150% of the fluid lost, up to a maximum of 800 mL / hour. The protocol then involves waiting about 10 minutes after rehydration and measuring salt osmolarity at 420. If the osmolarity further increases compared to the pre-exercise measurement at 422, the method returns to step 406. If the osmolarity returns to pre-exercise levels at 424, the rehydration protocol stops at 426. Of course, this is only one example.

[0079] 10 illustrates one embodiment of a hydration algorithm 450 that may be used as part of the rehydration protocol generation method described herein. In this embodiment, the hydration algorithm 450 calculates 406 the change in saliva and / or sweat osmolality, or alternatively, the algorithm 450 may receive the change in osmolality after it has been calculated. The algorithm then categorizes 452 the change in osmolality into one of four categories based on the size of the change. The change is then multiplied by a multiplier at 454 and a percentage of body mass loss is calculated at 456. The body mass loss is multiplied at 458 by the user's weight to calculate fluid loss 460, which is used to generate a hydration protocol 462.

[0080] 11 illustrates one embodiment of a salt replacement algorithm 470 that may be used as part of the rehydration protocol generation method described herein. In this embodiment, the salt replacement algorithm 470 may begin with environmental and / or athletic data 472 and sweat data 476 from a reference panel. Alternatively, the salt replacement algorithm 470 may begin with measured sweat 474. The algorithm 470 calculates salt loss based on the fluid loss and sweat data at 478. The algorithm 470 then divides the salt loss over the rehydration time at 480 and determines whether the salt loss occurred greater than or less than 1200 mg / hr at 482. The algorithm 470 then generates a salt replacement protocol based on the amount of salt loss at 484.

[0081] Testing method Currently, chemical analysis of sweat is performed using laboratory tools. These are large and expensive, and require large samples for analysis. Because the reference data set described above requires multiple sweat measurements to be performed across multiple training sessions, laboratory-style analysis of samples may be impractical. To facilitate the methods described herein for hydration assessment and hydration recommendations, the present application also describes a method for rapid assessment of sweat sodium content through measurements of sweat conductivity, impedance or osmolality using a handheld portable testing system.

[0082] Referring now to the schematic flow chart of FIG. 12, one embodiment of a method 500 for measuring a sweat sample is shown. In this embodiment, the method 500 involves a user 502 attaching an adhesive absorbent patch 503 to the skin. The user then exercises (or otherwise exerts) at 504 and collects sweat using the patch 503. After exercise, sweat 506 is extracted from the patch 503, for example, by squeezing the sweat 506 from within the patch 503 into a collection reservoir 507. A small sample of sweat 506 is then collected from the collection reservoir 507 using a disposable, one-time use test strip 508. The test strip 508 is then inserted into a portable, handheld test system 510 (such as the systems described in the incorporated applications). The test system 510 then calculates the sweat sodium concentration from the impedance (or osmolality) of the sweat sample 506. In an alternative embodiment, the test strip 508 may be inserted into the handheld test system 510 prior to applying sweat 506 to the test strip 508. Once the test system 510 has been used to generate any desired data related to the sweat 506, some or all of the data may be sent (e.g., wirelessly) to a reference data set 512 for the user.

[0083] FIG. 13 is an illustration of one embodiment of a sweat measurement system 520 that may be used alone or as part of any of the method embodiments described above. In this embodiment, the sweat measurement system 520 includes a sweat collection kit 521, which may be provided in a pouch, tray, or any other suitable packaging. The kit 521 includes one or more adhesive sweat collection patches 522 (e.g., adhesive gauze pads), one or more alcohol wipes 524 (or other antiseptic skin wipes) for cleaning the skin before applying the patch 522, one or more sweat collection trays 526 and / or sweat collection storage tubes 530, a syringe 528, and three (or alternatively any other number) sweat test strips 532. The sweat collection tray 526 may be used if the sweat is to be tested immediately or immediately after collection. The sweat collection tube 530 may be used if the sweat is to be tested, stored, and / or transferred at a later time. In some embodiments, the adhesive patch 522 may be placed into the barrel of a syringe 528, and the plunger of the syringe 528 may be used to express sweat from the adhesive patch 522 into a collection tray 526 or tube 530. A designated end of the test strip 532 may then be placed into the collection tray 526 or tube 530 to allow a sufficient sweat sample to be collected at that end of the test strip 532. The system 520 may include any number of test strips 532, where one end of each strip 532 is used to collect a sweat sample and the other end is inserted into a handheld measurement device 534 that is also part of the system 520. Finally, the system 520 includes a computer application 536 for a smartphone 538, tablet, or the like. The handheld measurement device 534, as further described in the incorporated references, analyzes the sweat sample and wirelessly transmits the sweat sample data to the computer application 536, which may perform further analysis or generate further data, such as a rehydration protocol.

[0084] 14A-14D illustrate a method for using the system 520 shown in FIG. 13 to collect and analyze sweat samples. As shown in FIG. 14A, step 550 involves a test subject (or "user") wiping one of their inner forearms clean with an alcohol wipe 524 from a sweat collection kit 521. Then, as shown in FIG. 14B, step 552 involves the user applying an adhesive sweat collection patch 522 to the forearm in the cleansed area. The user will then exercise for a suitable amount of time to collect sweat on the patch 522, for example, in one embodiment, about 30-60 minutes. (Alternatively, shorter or longer time periods may be sufficient.) The user then removes the sweat collection patch 522 and places it into the barrel of the syringe 528, and as shown in FIG. 14C, step 554, the user presses down on the plunger of the syringe 528 to express sweat from within the patch 522 into the collection tray 526 (or alternatively, the collection tube 530). As shown in FIG. 14D, the user then places one collection end (or "free end") of the test strip 532 into the sweat sample present in the collection tray 526. In this embodiment, the opposite end of the test strip 532 has already been inserted into the handheld measurement device 534, so the user would hold the handheld device 534 while inserting the free end of the test strip 532 into the collected sweat sample. Alternatively, the test strip 532 may be inserted into the sweat sample and then into the handheld device 534.

[0085] After the measurement device 534 takes a measurement from the first test strip 532, the user removes the first test strip 532, inserts the second test strip 532 into the handheld measurement device 534, inserts the free end of the test strip 532 into the sweat sample, and takes a second measurement. These final steps of the method are repeated for the third test strip 532. In alternative embodiments, fewer than three test strips 532 or more than three test strips 532 may be used for one measurement set. Using three strips 532 may be advantageous to allow averaging of the three measurements and thus increase the accuracy of the test results compared to using only one or two test strips 532. The handheld measurement device 534 may provide measurements of sweat sodium concentration, sweat osmolality, and / or other sweat properties. The measurement data may then be used in any of the methods and algorithms described herein. For example, sweat osmolality and / or sodium concentration can be used to help a test subject determine how much fluid they should consume, and what type of fluid (e.g., what amounts and types of electrolytes).

[0086] 15 shows the correlation between osmolality and sodium concentration of various sweat samples. The handheld sweat measurement device 534 wirelessly communicates the results to a phone application for integration into a reference data set.

[0087] 16, another embodiment of a sweat sample collection method 560 is shown. In this embodiment, a user first applies a single-use patch 562 to the forearm or other collection area on the skin. The patch 562, in this embodiment, includes integrated microfluidics and electrodes. In one embodiment, for example, the single-use patch may include a test strip such as or the same as the test strip 532 shown in FIG. 13. Alternative embodiments may include different configurations. The user then engages in an exercise or other physical activity at 564, and sweat is collected by the patch 562. For the next step 566, during or after the exercise, while still attached to the test subject's body, the patch 562 (e.g., including the test strip 532) is connected to a handheld sweat measurement device 534 to perform measurements of sweat osmolality, conductivity, etc. The handheld device 534 then wirelessly communicates the sweat data to a phone application for integration into a reference data set 568. In some embodiments, the handheld device 534 may also be used to perform other measurements to establish the baseline data set 568, such as, but not limited to, saliva osmolality changes and blood lactate concentrations.

[0088] In another embodiment, saliva samples are collected directly from the tongue using integrated microfluidics and electrodes. The handheld device 534 wirelessly communicates the saliva data to a phone application for integration into a baseline data set. This same system may be capable of performing other measurements to establish a baseline data set, such as, but not limited to, saliva osmolality changes and blood lactate concentrations.

[0089] In another embodiment, the saliva sample is collected by the test subject providing the saliva sample to a container. The sample is then analyzed using integrated microfluidics and electrodes. The handheld device 534 wirelessly communicates the saliva data to a phone application for integration into a reference data set. This same system may be capable of performing other measurements to establish a reference data set, such as, but not limited to, saliva osmolality change and blood lactate concentration.

[0090] While the above description is believed to be complete and accurate, various modifications may be made to any of the embodiments and features described herein without departing from the scope of the invention. [Explanation of symbols]

[0091] 10. Biofluid Analysis System 12 Analyzer 14a Test strip for sample #1 14b Strips for Sample #2 14c Strips for Sample #3 14d Strips for specimens #1 and #2 14e Strips for specimens #1 and #3 16 Applications 18 Database 20 Microcontrollers 22 On-board Bluetooth Low Energy chip 24 Analog-to-Digital Converter (ADC) chip 26 Antenna 28 Real Time Clock 30 Memory 32 User Interface 34 Temperature Sensor 36 Direct Digital Synthesis Chip 38 Digital to Analog Converter Chip 40 Low noise analog switch 42 Sensor Circuit 44 Gain setting circuit 46 First Multiplexer 48 Second Multiplexer 50 Third Multiplexer 52 High resolution ADC 54 Sensor Port 300 Hydration measurement system, hydration evaluation system 302, 352, 372, 512, 568 Reference Data Sets 304 Environmental conditions 306 Body mass changes and / or salivary osmolality changes 308 Sweat electrolyte content 310 Physical Activity Measurements 312 Measurement Sessions 324, 366, 392 Rehydration Protocol 334 Portable Weather Monitoring System 336, 386 Handheld Inspection Devices 340 Chest Strap Heart Rate Monitor 354, 374 Environmental conditions 356, 384 Online Weather Monitoring Service 360, 380 Exercise Level 362 Heart Rate Monitor 376 Salivary Osmolality 450 Algorithm 460 Water loss 462 Fluid Replacement Protocol 470 Algorithm 472 Environmental and / or athletic data 474 Measured Sweat Sweat data from 476 reference panels 502 users 503 Adhesive absorbent patch, patch 506 Sweat, sweat samples 507 Collection Container 508 Test Strips 510 Handheld Inspection System 520 Sweat Measurement System 521 Sweat Collection Kit 522 Sweat collection patch 524 Alcohol Wipes 526 Sweat collection tray 528 Syringe 530 Sweat collection and storage tube 532 Sweat Test Strips 534 Handheld Measuring Devices 536 Computer Applications 538 Smartphone 562 One-time use patches

Claims

1. 1. A method for measuring an analyte in a body fluid sample and combining measurement data from multiple users, comprising: initiating a wireless connection between the handheld analyzer and a smart computing device having a sample analysis application downloaded thereon; inserting a test strip into the handheld analyzer; collecting a sample of a user's bodily fluid on the test strip; measuring the concentration of an analyte in the sample with the handheld analyzer; wirelessly communicating the measured concentration from the handheld analyzer to the smart computing device; displaying the measured concentration on the smart computing device; transmitting said measured concentrations to a database; compiling data including the measured concentrations and at least one additional measured analyte concentration from at least one additional user on the database; automatically downloading and storing test strip type and batch data on said handheld analyzer; Using the handheld analyzer, determining an ambient temperature; determining the concentration of the analyte using a batch specific calibration factor and the ambient temperature; The method includes:

2. 2. The method of claim 1, further comprising initiating a wireless connection between the smart computing device and an Internet, the database being located on a cloud storage location, and transmitting the measured concentration to the database comprising wirelessly transmitting the measured concentration from the smart computing device to the cloud storage location via the Internet.

3. The method of claim 1 , wherein the data is organized based on groups of users belonging to multiple organizations.

4. The method further includes initiating, via the smart computing device, the measuring step, the initiating step comprising: logging into an operator account on the sample analysis application; selecting a particular source from which the sample will be taken; verifying the wireless connection between the handheld analyzer and the smart computing device; 2. The method of claim 1, comprising:

5. The step of automatically downloading and storing the test strip type and batch data includes: measuring resistively encoded test strip identification information on the test strip; comparing the resistively encoded test strip identification information with data in a memory of the handheld analyzer to determine the test strip type and batch data.

2. The method of claim 1, comprising:

6. communicating the test strip type and batch data to the smart computing device; if the test strip type is an unknown test strip type, alerting a user via an error message on the handheld analyzer and smart computing device.

6. The method of claim 5, further comprising:

7. Do not use used or defective test strips. determining that the test strip has been used or is defective; prompting the user at at least one of the handheld analyzer or the smart computing device to discard the test strip; The method of claim 1 , further comprising the step of preventing by:

8. 10. The method of claim 1, further comprising providing instructions to a user regarding how to collect the sample using at least one of the sample analysis application and the handheld analyzer.

9. The step of: applying a detection technique based on the ambient temperature. The method of claim 1, further comprising:

10. Using the handheld analyzer, measuring signal mismatch; detecting an abnormally high or low signal on the test strip; The method of claim 1 , further comprising determining that the measurement is inaccurate by:

11. 10. The method of claim 1, further comprising: analyzing the measured concentrations to aid in user interpretation using the smart computing device.

12. The method of claim 1 , wherein the smart computing device correlates the raw measured concentrations to previously established individual-specific reference values.

13. The method of claim 12, further comprising the steps of: applying an electrical signal to the test strip; measuring a response of the combination of the test strip and the bodily fluid sample to the applied electrical signal using the handheld analyzer; analyzing the reaction with the handheld analyzer to determine that the bodily fluid sample is a valid sample; The method of claim 1 further comprising:

14. 1. A handheld analyzer for determining a concentration of one or more analytes in a body fluid, comprising: Housing and a test strip port in the housing; a display integral with the housing; a temperature sensor within the housing; and a plurality of electronic components within the housing, the plurality of electronic components comprising: at least one of a direct digital synthesis (DDS) chip or a digital-to-analog converter (DAC) chip; an analog-to-digital converter (ADC) chip; A wireless communication chip; A processing circuit; Computer memory and Equipped with The handheld analyzer comprises: configured to determine test strip type and batch data using resistively encoded identification information on the test strip and data stored in the computer memory; the temperature sensor is configured to measure an ambient temperature, and the processing circuitry is configured to process the measured ambient temperature. Handheld analyzers.

15. 15. The handheld analyzer of claim 14, wherein the test strip port is configured to accept a test strip selected from the group consisting of analyte-specific test strips and test strips capable of measuring multiple analytes.

16. 15. The handheld analyzer of claim 14, wherein the plurality of electronic components are configured to automatically transfer test strip configuration settings to the computer memory when the handheld analyzer is connected to a database via a mobile application.

17. 15. The handheld analyzer of claim 14, wherein the plurality of electronic components are configured to automatically adjust detection methods, excitation waveforms, and gain settings for a plurality of types of test strips.

18. The handheld analyzer of claim 14, wherein the processing circuitry is configured to process the measured ambient temperature using a temperature detection algorithm.

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