Devices, systems, and methods for saliva-based lactate threshold assessment

Abstract

Various implementations of devices, systems, and methods for determining an individual's lactate threshold, a physical performance indicator, using saliva-based lactate measurements are described. A lactate threshold determination protocol can be established, measurements logged, and measurements interpreted to allow individuals without specific training and expertise to perform lactate threshold assessments and to access guidance on training and timing of re-assessment of lactate thresholds. A test strip including: a biosensor with an enzyme test can provide an enhancement layer on an electrode to control for osmolarity and / or pH variability of saliva samples.

Description

DEVICES, SYSTEMS, AND METHODS FOR SALIVA-BASED LACTATE THRESHOLD ASSESSMENTINCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

[0001] This application claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 63 / 634,277, filed April 15, 2024, which is hereby incorporated by reference herein in its entirety.BACKGROUNDField of the Invention

[0002] The present application describes various implementations of devices, systems, and methods for determining an individual’s lactate threshold, a physical performance indicator, using saliva-based lactate measurements.Background

[0003] During periods of increased energy demand, such as intense exercise, the human body switches from aerobic to anaerobic metabolism. During anaerobic metabolism various tissues, primarily muscle cells and red blood cells, produce lactate. The rate at which this lactate is cleared from these tissues primarily depends on the body’s ability to oxidize the lactate via mitochondria and secondarily through conversion of lactate back to glucose / glycogen.

[0004] The lactate threshold (or lactate inflection point) is the maximum intensity at which physical exertion can be sustained where lactate production is equal to or below the rate of lactate clearance. Above this threshold, lactate levels in the blood and other body fluids will increase. Regular physical training is associated with physiological changes in lactate metabolism which increase the intensity of physical activity which can be maintained before blood lactate levels will increase. As such, assessment of lactate threshold is a useful measure of physical fitness and is a common tool used by athletes to assess changes in performance, forexample to improve performance over time or to assess return to physical fitness following injury or reduction in activity.

[0005] Determination of lactate threshold is most commonly achieved through direct measurement of blood lactate levels. A standard assessment will involve serial measurement of finger-prick or ear-prick capillary blood samples with a handheld blood lactate measurement device following running, cycling, or swimming at increasing intensity. Once all measurements have been collected a lactate threshold can be established using one of a range of approaches that seek to mathematically determine the threshold, including Log-log, Onset of Blood Lactate Accumulation (OBLA), Baseline plus (Bsln+), Dmax, Lactate Turning Point (LTP), and Lactate / Intensity ratio (LTratio).

[0006] This current approach for determination of lactate threshold is effective but has three key disadvantages. Firstly, blood sampling is unpleasant and invasive, which reduces participant willingness to conduct routine lactate threshold assessments. Secondly, protocol planning, measurement logging, and interpretation is largely performed manually, limiting the ability for untrained individuals to perform lactate threshold assessments and increasing the risk of error. Thirdly, blood-based meters do not provide training guidance in relation to improving fitness levels and / or timing for re-assessment, further limiting the utility of lactate threshold assessments for untrained individuals.

[0007] Therefore it would be beneficial to have systems and methods whereby a less invasive bodily fluid, such as saliva, could be used to determine an individual’s lactate threshold. Furthermore, it would be beneficial to automate the process by which a lactate threshold determination protocol is established, measurements logged, and measurements interpreted to allow individuals without specific training and expertise to perform lactate threshold assessments and to access guidance on training and timing of re-assessment of lactate thresholds.SUMMARY

[0008] Determination of lactate threshold through assessment of lactate levels in saliva is an attractive alternative to conventional blood-based approaches due to the less invasive nature of saliva sampling. As with blood lactate, saliva lactate has been shown to bea performance indicator, with delayed onset of saliva lactate increase associated with improved exercise capacity and physical fitness.

[0009] The present application describes systems and methods by which a user may use saliva lactate measurements to determine their aerobic capacity. The method may involve the use of a smart computing device that guides the user through the saliva sample collection and analysis process and the use of a handheld lactate measurement device to determine the concentration of lactate in each saliva sample. Various other data and parameters may also be collected or incorporated into the analysis to improve the ease-of-use, accuracy and / or utility of the proposed method.

[0010] In some implementations, a smart computing device is used to establish an exertion and saliva sampling protocol. This protocol can be designed to conduct physical exertion over a suitable range of intensities while minimizing the number of samples that need to be collected to accurately determine a lactate threshold value.

[0011] Factors that may be considered by the smart computing device to establish this protocol include: survey data, biometric data, demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and / or prior lactate threshold assessment data. In some implementations, these data may be manually entered by the user into the smart computing device. In some implementations, data may be automatically input from various data sources or connected devices. In some implementations the protocol may include guidance on how to prepare for the exertion and sampling protocols, such as guidance around pre-hydration or nutrition.

[0012] In some implementations, a smart computing device may be used to guide the end user through an established exertion and saliva sampling protocol. Real time prompts and guidance can assist non-technical users to enhance compliance with the protocol and improve the accuracy of lactate threshold assessment results. In some implementations, guidance and prompt(s) may take the form of notifications, timers, and / or other visual or audio cues displayed on a smart computing device, a lactate measurement device, or another companion device such a display, speaker, phone, tablet, smart-watch or similar device.

[0013] In some implementations, additional companion measures are conducted prior to or during the exertion and saliva sampling protocol to improve the accuracy of the lactate threshold assessment. For example, some implementations may include an assessmentof the user’s hydration status to ensure that they are suitably hydrated to conduct the assessment. A hydration status assessment may be conducted through a salivary osmolarity assessment using the same measurement device used to determine the saliva lactate concentration, or using an alternative assessment method and / or device. Other measures that may be conducted to improve the accuracy of the assessment include heart rate, VO2 max, salivary pH, salivary ketone levels, saliva electrolyte levels, and salivary cortisol levels.

[0014] In some implementations, saliva sample analysis is conducted during the exertion protocol. In some implementations, the results of the measurements may be used to modify the protocol. In some implementations, sample analysis is conducted following the collection of all saliva samples. In some implementations, saliva samples may be collected directly from the mouth or tongue for analysis. In some implementations, saliva samples may be collected into tubes for later analysis.

[0015] In some implementations, a smart computing device may automate the analysis and interpretation of the saliva lactate measurements to determine the lactate threshold. This may include providing information which contextualizes results or estimates and / or provides guidance on training to improve fitness and the timing of future lactate threshold assessments to track fitness progression. In some implementations, a smart computing device may use other data sources such as sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, or environmental data to establish this training protocol.

[0016] In some aspects, the techniques described herein relate to a method for determining an individual's lactate threshold including: establishing an exertion and saliva sampling protocol to collect one or more saliva samples; guiding completion of the exertion and saliva sampling protocol; measuring a lactate concentration of each of the one or more saliva samples using a portable measurement device; analyzing the lactate concentration measurements and estimating the individual's lactate threshold; and establishing a training protocol intended to improve an individual's exertion intensity capacity using the estimated lactate threshold.

[0017] In some aspects, the saliva sampling protocol is established using a smart computing device, the smart computing device is used to guide the completion of the protocol, and the smart computing device is used to analyze the lactate concentration measurements andestimate the individual's lactate threshold. In some aspects, the smart computing device provides real-time guidance and alerts throughout the exertion and saliva sampling protocol.

[0018] In some aspects, another device connected to the smart computing device provides real-time guidance and / or alert. In some aspects, the real-time guidance and / or alert is configured to assist completion of the exertion and saliva sampling protocol.

[0019] In some aspects, the portable measurement device is integrated into the smart computing device.

[0020] In some aspects, the exertion and saliva sampling protocol is established using a dataset composed of at least one of survey data, biometric data, demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and prior lactate threshold data.

[0021] In some aspects, the method further includes conducting a hydration assessment using the portable measurement device prior to guiding completion of the exertion protocol. In some aspects, the method further includes instructing the individual to follow a hydration protocol prior to guiding completion of the exertion and saliva sampling protocol.

[0022] In some aspects, all saliva samples are collected before measuring the lactate concentration of each sample. In some aspects, each saliva sample is analyzed in realtime during completion of the exertion and saliva sampling protocol.

[0023] In some aspects, the method further includes modifying the exertion protocol and / or the saliva sampling protocol using results of the real-time analyses.

[0024] In some aspects, saliva samples are collected directly from the tongue for analysis.

[0025] In some aspects, the estimated lactate threshold is combined with a dataset including at least one of sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, environmental data to establish the training protocol.

[0026] In some aspects, the techniques described herein relate to a system for determining an individual's lactate threshold, wherein the system is configured to: establish an exertion and saliva sampling protocol to collect one or more saliva samples; guide completion of the exertion and saliva sampling protocol; measure a lactate concentration of each of the one or more saliva samples using a portable measurement device; analyze the lactate concentration measurements and estimating the individual's lactate threshold; and establish atraining protocol intended to improve an individual's exertion intensity capacity using the estimated lactate threshold.

[0027] In some aspects, the system further includes a smart computing device, wherein the saliva sampling protocol is established using the smart computing device, the smart computing device is used to guide the completion of the protocol, and the smart computing device is used to analyze the lactate concentration measurements and estimate the individual's lactate threshold. In some aspects, the smart computing device provides real-time guidance and alerts throughout the exertion and saliva sampling protocol.

[0028] In some aspects, the system further includes another device, wherein the another device connected to the smart computing device and provides a real-time guidance and / or an alert. In some aspects, the real-time guidance and / or alert is configured to assist completion of the exertion and saliva sampling protocol. In some aspects, the portable measurement device is integrated into the smart computing device.

[0029] In some aspects, the exertion and saliva sampling protocol is established using a dataset composed of at least one of: survey data, biometric data, demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and prior lactate threshold data.

[0030] In some aspects, the system is further configured to conduct a hydration assessment using the portable measurement device prior to guiding completion of the exertion protocol. In some aspects, the system is further configured to instruct the individual to follow a hydration protocol prior to guiding completion of the exertion and saliva sampling protocol.

[0031] In some aspects, all saliva samples are collected before measuring the lactate concentration of each sample. In some aspects, each saliva sample is analyzed in realtime during completion of the exertion and saliva sampling protocol.

[0032] In some aspects, the system is further configured to modify the exertion protocol and / or the saliva sampling protocol using results of the real-time analyses.

[0033] In some aspects, the saliva samples are collected directly from the tongue for analysis.

[0034] In some aspects, the estimated lactate threshold is combined with a dataset including at least one of: sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, environmental data to establish the training protocol.

[0035] In some aspects, the techniques described herein relate to a test strip for determining an estimated lactate threshold, the test strip including: a biosensor with an enzyme test; an electrode; and an enhancement layer.

[0036] In some aspects, the enhancement layer includes a salt deposition on a surface of the electrode. In some aspects, the salt deposition is a salt-polysaccharide deposition. In some aspects, the test strip further includes a second electrode including an enzyme on a surface of the second electrode. In some aspects, the enzyme comprises a polysaccharide solution. In some aspects, the salt deposition is configured to be maintained in a region around the electrode for 10-30 seconds.

[0037] In some aspects, the enhancement layer includes an acid or base deposited on the biosensor surface. In some aspects, the acid or base includes a pH-buffering polysaccharide deposition. In some aspects, the test strip further includes a second electrode including an enzyme on a surface of the second electrode. In some aspects, the enzyme comprises a polysaccharide solution.

[0038] In some aspects, the enhancement layer includes a polysaccharide and / or a polymer membrane deposited between a surface of the electrode and an enzyme layer. In some aspects, the enhancement layer includes the polysaccharide, wherein the polysaccharide includes Chitosan. In some aspects, the enhancement layer includes the polymer membrane, wherein the polymer membrane includes Nafion.

[0039] In some aspects, the enhancement layer is configured to mitigate any variations in the electrode consistency or roughness.

[0040] In some aspects, the enhancement layer includes both the polysaccharide and the polymer membrane.

[0041] In some aspects, the techniques described herein relate to a method of controlling a salivary osmolarity and / or pH of a saliva sample to improve accuracy of an enzyme test, the methods including applying the collected saliva sample to a testing region of a biosensor used to perform the enzyme test, wherein the testing region includes an electrode and an enhancement layer on a surface of the electrode.

[0042] In some aspects, the enhancement layer is a salt deposition on the surface of the electrode. In some aspects, the salt deposition is a salt-polysaccharide deposition. In some aspects, the testing region further includes a second electrode including an enzyme on asurface of the second electrode. In some aspects, the enzyme comprises a polysaccharide solution. In some aspects, the electrode is a counter electrode and the second electrode is a working electrode.

[0043] In some aspects, the enhancement layer includes an acid or base deposited on the surface of the electrode. In some aspects, the acid or base includes a pH-buffering polysaccharide deposition. In some aspects, the testing region further includes a second electrode including an enzyme on a surface of the second electrode. In some aspects, the enzyme comprises a polysaccharide solution.

[0044] In some aspects, the enhancement layer includes a polysaccharide and / or a polymer membrane deposited between a surface of the electrode and an enzyme layer. In some aspects, the enhancement layer includes the polysaccharide, wherein the polysaccharide includes Chitosan. In some aspects, the enhancement layer includes the polymer membrane, wherein the polymer membrane includes Nafion.

[0045] In some aspects, the enhancement layer is configured to mitigate any variations in the electrode consistency or roughness.

[0046] In some aspects, the enhancement layer includes both the polysaccharide and the polymer membrane.

[0047] In some aspects, the techniques described herein relate to a computing device for a saliva-based lactate assessment including one or more features of the foregoing description.

[0048] In some aspects, the techniques described herein relate to a measurement device for a saliva-based lactate assessment including one or more features of the foregoing description.

[0049] In some aspects, the techniques described herein relate to a system for a saliva-based lactate assessment including a computing device and a measurement device, including one or more features of the foregoing description.

[0050] In some aspects, the techniques described herein relate to a test strip for a saliva-based lactate assessment including one or more features of the foregoing description.

[0051] In some aspects, the techniques described herein relate to a method for performing a saliva-based lactate assessment including one or more features of the foregoing description.

[0052] These and other aspects and embodiments are described in greater detail below, in relation to the drawing figures.BRIEF DESCRIPTION OF THE DRAWINGS

[0053] For purposes of summarizing the disclosure, certain aspects, advantages, and novel features are discussed herein. It is to be understood that not necessarily all such aspects, advantages, or features will be embodied in any particular embodiment of the disclosure, and an artisan would recognize from the disclosure herein a myriad of combinations of such aspects, advantages, or features.

[0054] FIG. 1A illustrates an implementation a system used to determine salivary lactate.

[0055] FIG. IB illustrates an implementation of a test strip that can be used with the system of FIG. 1A.

[0056] FIG. 1C illustrates a side view of the test strip shown in FIG. IB.

[0057] FIG. 2 illustrates an implementation of an exertion and testing protocol.

[0058] FIG. 3A illustrates a post-analysis workflow for collecting and analyzing saliva samples.

[0059] FIG. 3B illustrates a real-time analysis workflow for collecting and analyzing saliva samples.

[0060] FIG. 4 illustrates a method of providing real time guidance to assist with completing a saliva lactate threshold assessment according to FIB 3A.

[0061] FIG. 5 illustrates a method of providing real time guidance to assist with completing a saliva lactate threshold assessment according to FIB 3B.

[0062] FIG. 6 illustrates a training guidance for running.

[0063] FIG. 7 illustrates a training guidance for cycling.DETAILED DESCRIPTION

[0064] The present application describes various implementations of systems and methods for determining an individual’s lactate threshold, a physical performance indicator, using saliva-based lactate measurements.

[0065] FIG. 1A is a diagrammatic illustration of an implementation of the various components of a system 100 that may be used to determine salivary lactate. For example, asillustrated in FIG 1 A, a system 100 may include a computing device 110, sample tubes 140 that may be used to collect saliva samples for analysis, and a measurement device 120 which can be used to determine salivary lactate using test strips 130. In some implementations, a computing device 110 may be a smart phone, tablet, notebook computer, laptop computer, or similar device.

[0066] Smart computing device

[0067] In some implementations, a smart computing device 110 may be used to establish an exertion and saliva sampling protocol. In some implementations, a smart computing device 110 may be used to guide the user through a saliva sample collection and analysis process and the use of a computing device 110, for example a handheld lactate measurement device to determine the concentration of lactate in each saliva sample. In some implementations, a smart computing device 110 may process lactate concentration data to establish a lactate threshold estimate and report this back to the user. In some implementations, various other data and parameters may also be collected or incorporated into the analysis to improve the ease-of-use, accuracy, and / or utility of the lactate assessment, lactate threshold determination, and / or use of the system 100.

[0068] In some implementations, a smart computing device 110 may be a mobile phone with an application installed on it and a connection to the measurement device 120. In some implementations, the connection may be a wireless connection. For example, a user can interact with the mobile phone to establish the measurement protocol and then instructive information can be displayed or conveyed to the user on the mobile phone screen 112 or other display and on the measurement device screen 122 or other display to guide the user through the protocol. In some implementations, the smart computing device 110 or measurement device 120 may provide instructions via other feedback, such as sounds, lights, haptics, or other alerts. Following the completion of the exertion and sampling protocols and the measurement protocols, the results of the analysis can be displayed on the mobile phone screen 112 or other display.

[0069] In some implementations, a smart computing device 110 may be a mobile phone that can communicate with one or more additional smart computing devices 110, such as a second phone, a tablet, a television, and / or a smart watch, that may be used to convey instructive guidance to the user.

[0070] In some implementations, a smart computing device 110 may be the same device as the measurement device 120, and the user interacts directly with this device to establish the measurement protocol, be guided through the measurement protocol, and analyze the saliva samples with this device.

[0071] Portable measurement device

[0072] In some implementations, a lactate threshold estimate can be determined using saliva by establishing the lactate concentration of multiple saliva samples collected under different exertion intensity conditions. This concentration data can be processed alongside exertion intensity data to determine the intensity at which saliva lactate begins to exponentially increase.

[0073] In some implementations, lactate concentration of a biological sample may be determined using a wide range of methods, including liquid chromatography tandem mass spectrometry and enzymatic-based methods. In some implementations, electrochemical enzyme-based assays may be used, which enables rapid quantification of lactate concentration in a handheld and easy to use format.

[0074] In some implementations, a portable measurement device 120 may be a handheld device that uses a single-use lateral flow assay, for example as described in U.S. Pat. No. 11,701,036 (Attorney Docket No. MX3D 005A) titled “Saliva test strip and method” filed July 9, 2020 and issued July 18, 2023, which is hereby incorporated by reference in its entirety. In some implementations, portable measurement device 120 may use single-use enzymatic biosensors to determine the concentration of lactate in the saliva samples. For example, to determine the concentration of saliva lactate, a test strip 130 may be inserted in a measurement device 120, then a small amount of saliva can be collected using a single-use enzymatic test strip 130. The measurement device 120 can measure the electrochemical signal generated by the enzymatic reaction of the saliva on the strip 130, and can then use this information to establish the concentration of lactate in the sample. In some implementations, this information can be communicated wirelessly to a smart measurement device 120.

[0075] In some implementations, a portable measurement device 120 may analyze saliva directly from an individual's tongue using a single-use test strip 130. In some implementations, a saliva sample may be first collected into a sample tube 140 and then sampled from this tube 140 using a single use test strip 130. In some implementations, a salivasample may be processed using a filtration device, for example to remove contaminants or modify physical properties of the sample prior to analysis by the portable measurement device. In some implementations, saliva samples may be pre-filtered prior to analysis using a test strip 130. In this approach a saliva sample is spit into a small collection receptacle, for example, sample tube 140. A lid can be attached to this receptacle or sample tube 140. The lid can contain a hole covered by a filtering element. When the receptacle or sample tube 140 is inverted and squeezed, the sample will pass through the filter and the hole and can be deposited onto a sampling tray or test strip 130 for analysis. In some implementations, the filtering element can be configured to remove a particular contaminant. For example, by using a specific filtering element, one or more various physical contaminants (e.g. mucins, bubbles, and / or food debris) can be removed from the sample prior to analysis. Removal of one or more physical contaminants can allow for more consistent measurement of the sample. For example, in some implementations, removing contaminants can lower viscosity of a sample and provide more consistent filling of microfluidics on a test strip 130. In some implementations, removing contaminants, for example bubbles or debris, can reduce analysis errors caused by voids in the collected sample. Any same tube 140 discussed herein may include a filtering element.

[0076] In some implementations, a portable measurement device 120 may be used to only determine saliva lactate concentration. In some implementations, a measurement device 120 may further determine other relevant parameters, such as saliva osmolality (a measure of hydration), saliva pH (a measure of saliva acidity), or sweat sodium (a measure of electrolyte replacement needs). In some implementations, a portable measurement device 120 may use a separate test strip 130 to determine each parameter. In some implementations, a single test strip 130 may be used to determine multiple parameters.

[0077] In some implementations, additional measurement parameters may be used to assist in generation of the exertion and saliva sampling protocol. For example, in some implementations, an individual who is dehydrated may be advised to actively rehydrate prior to initiating an exertion protocol. In some implementations, additional measurement parameters may be used to assist in the interpretation of the saliva lactate measurements. For example, in some implementations, if an individual has highly acidic saliva a correction coefficient may be applied to the saliva lactate value estimated. For example, in some implementations, a correction coefficient for a pH, osmolarity, temperature, ionicconcentration, or other auxiliary measurement (as discussed in U.S. Pat. No. 12,123,865 [Attorney Docket No. MX3D 006A] titled “Assessment of biomarker concentration in a fluid” filed January 14, 2021 and issued October 22, 2024, and U.S. App. No. 18 / 688,580 [Attorney Docket No. MX3D.009NP] titled “Integrated lateral flow bioassay and biosensor” filed March 1, 2024, both of which are hereby incorporated by reference in their entireties) may be applied to an estimated saliva lactate value. In some implementations, an auxiliary measurement may be used to identify or optimize a particular lactate estimation algorithm, for example to select an estimation procedure that is stable in the presence of an ionic concentration identified as highly variable in a set of samples, or to select an estimation model that easily accounts for a highly variable pH or other auxiliary measure. In some implementations, additional measurement parameters may be used to assist in construction of guidance to be provided alongside the lactate threshold estimate. For example, in some implementations, sweat sodium values may be used to modify provided guidance to include electrolyte replacement in a suggested training protocol.

[0078] Test Strip

[0079] In some implementations, a saliva-based lactate testing system 100 uses a test strip, for example test strip 130 as shown in FIG. 1A. In some implementations, test strip 130 may include a single-use lateral flow assay as described above. In some implementations, a test strip, for example test strip 150 shown in FIG. IB, may include an electrochemical biosensor, for example a biosensor including working electrode 154 and counter electrode 156. Test strip 150 may be optimized for testing lactate from a saliva sample. Some test strip features described herein may be suitable for testing a wide range of other salivary biosensors / biomarkers, for example for parameters that may have salt- or pH-dependent electrochemistry. In some implementations, a test strip 130, 150 may include an enzyme test. In some implementations, stabilization reagents may be used to stabilize a testing compound, for example an enzyme within a polysaccharide solution.

[0080] In some implementations, an electrochemical biosensor may be impacted by one or more properties of the sample body fluid itself. For example, a salt concentration of a saliva sample can impact the electrochemical response for a given concentration of a given analyte, impacting test accuracy. As discussed above, blood-based biosensors can be used to determine a biomarker concentration, for example lactate, from a collected blood sample. Suchblood-based biosensors do not typically need to control for the salt concentration of blood, as blood salt concentration is highly controlled and predictable, for example blood osmolarity is typically in a known range of about 275 to 295 mOsm / kg. In contrast, saliva has a much more variable salinity range (25 to 250 mOsm / kg). Therefore, it can be advantageous in some implementations to mitigate the impact of a salt content in a sample on the performance of the biosensor. In some implementations, direct measurement of osmolarity and algorithmic correction of this variable may be used. Similarly, in some implementations a correction coefficient or algorithmic correction may be used to adjust the estimated lactate threshold and / or saliva lactate value for other auxiliary measures, including pH, osmolarity, temperature, ionic concentration, and others as discussed in incorporated U.S. Pat. No. 12,123,865, and U.S. App. No. 18 / 688,580.

[0081] In some implementations, chemistry of the strip, for example test strip 150 shown in FIG. IB, may be modified, for example with an enhancement layer, to mitigate the need for salt measurement and / or algorithmic correction. Test strip 150 can include multiple layers, as shown in FIGS. IB-1 to IB-6. In some implementations, a test strip 150 may include a substrate 160 supporting a working electrode 154 and a counter electrode 156. A working electrode 154 and counter electrode 156 can be patterned on a substrate 160 using a layer of conductive material 164, as illustrated in FIG. IB-1. As shown in FIG. IB-2, a second layer 166 may be provided over the conducive layer 164. In some implementations, working electrode 154 and counter electrode 156 may include a conductive layer 164 of silver and second layer 166 of carbon. In some implementations, alternate or additional materials may be used, for example noble metals such as silver, gold, titanium, or platinum, conductive alloys, carbon, conductive polymers, conductive inks, and combinations of appropriate conductive materials may be used for conductive material 164 and second layer 166. As shown in FIG. IB-2, in some implementations counter electrode 156 may include an exposed portion 164a of conductive material 164 that does not include second layer 166. As illustrated in FIG. IB-3, a microfluidics layer 170 can be provided over the second layer 166. As illustrated in FIGS. 1B- 3 and FIG. 1C, microfluidics layer 170 can be shaped to create a test region 172. In some implementations, an enzyme 182 can be provided on working electrode 154 in the test region 172 as illustrated in FIG. IB-4. In some implementations, a deposition 184, for example a salt- polysaccharide deposition, can be provided on a surface of counter electrode 156 in the testregion 172, as shown in FIG. IB-5. A cover 190 can be placed over the test strip 150, as shown in FIG. IB-6. Cover 190 can include a hole 192, which can allow air to escape during fdling of test region 172 with fluid, for example saliva. The sample enters the test region 172 at a first end 194. The positioning of the hole 192 at the end of the test region 172 opposite from the first end 194 (as shown in FIG. IB-6) can also facilitate filling of the test region 172 so that the sample fills the test region 172 and contacts the electrodes within the test region 172.

[0082] In some implementations, when a saliva sample fills the test region 172, the saliva dissolves some or all of the enzyme 182. This allows the enzyme 182 to function by being dissolved in a liquid. The enzyme 182, for example lactate oxidase, dissolves over several seconds and begins reacting with lactate in the saliva sample to produce hydrogen peroxide or other chemical that reacts with a carbon ink 166 on the working electrode 154 to produce an output signal when an excitation voltage is applied across two electrodes in the test region 172, for example working electrode 154 and counter electrode 156. In some implementations, the test region 172 holds the sample in place, which can create a region on / near the working electrode 154 that has a high concentration of enzyme 182. In some implementations, the enzyme 182 is allowed to dissolve in the sample and react with the lactate in the saliva sample for a fixed amount of time. For example, in some implementations, the enzyme 182 is allowed to dissolve for 10, 12, 15, 20, 25, 30, 45, or 60 seconds, or other appropriate time to allow the enzyme 182 to sufficiently dissolve and react with the sample. Then the measurement can be conducted and the output used to estimate lactate concentration, for example using a reference calibration curve and / or a temperature correction coefficient as described herein.

[0083] In some implementations, a saliva sample in test region 172 also dissolves some or all of the deposition 184, for example a salt solution as described herein. By positioning the deposition 184, for example a salt-cellulose solution, on the counter electrode 156, salt levels can be saturated in this area of test region 172.

[0084] As discussed above, some bodily fluids, for example saliva, have a highly variably osmolarity. As noted, osmolarity of a sample can be directly measured and an appropriate correction factor can be applied to final result, for example to an estimate of lactate threshold. In some implementations, osmolarity impact on the measurement can be minimized by controlling the osmolarity of the sample during the measurement. For example, a highconcentration of salt can be applied to the sample, making the variability in the sample osmolarity no longer relevant. While a high salt concentration on a counter electrode 156 is desirable (to control for osmolarity), a high salt concentration on a working electrode 154 is less desirable because very high salt concentrations can impact the enzyme 182. In some implementations, an enhancement layer including a deposition 184, for example a salt- polysaccharide matrix, can be used to highly localise the region where salt is deposited and slow the undesirable diffusion of salts to the working electrode 154.

[0085] For example, in some implementations, an enhancement layer can be used on the counter electrode. In some implementations, an enhancement layer may include a deposition 184, which may be a salt deposition such as a salt-polysaccharide deposition, on a surface of counter electrode 156 that can be used to control for the highly variable salt concentration of saliva. In some implementations, a deposition 184, for example a salt deposition or salt-polysaccharide deposition, can be used on a counter electrode 156 of a biosensor or test strip 150. In some implementations, a deposition 184, for example a salt deposition, can create a localized region of high-salt concentration, for example within test region 172. In some implementations, a region of high salt concentration may be localized to a counter electrode, for example counter electrode 156, and the salt concentration can be configured and arranged to be maintained throughout the duration of the measurement. For example, a deposition 184 can be configured to be maintained in a region around a counter electrode 156 for 10-30 seconds. In some implementations deposition 184, for example a salt deposition or salt-polysaccharide deposition, may include one or more stabilization reagents that can act to stabilize the compounds within the deposition 184, for example to stabilize a polysaccharide solution. For example, in some implementations, deposition 184, for example a salt deposition or salt-polysaccharide deposition, may include one or more enzymes.

[0086] Appropriate selection of viscosity of deposition 184, for example a salt deposition, may enable highly precise salt deposition. In some implementations, deposition 184, for example a salt deposition or a salt-polysaccharide solution, may have a viscosity high enough to allow for deposition on the desired electrode surface, for example counter electrode 156, and low enough to allow for deposition using typical automated fluid dispensing equipment. In some implementations, after a solution of deposition 184 dries, a highly precise region may be left on the desired region of the biosensor, for example a precise region of salton a counter electrode 156 of a biosensor on a test strip 150. This precision in application can allow for the deposition 184 to be repeatably applied to a test strip and allow for predicable dissolution and interaction of the contents of the deposition 184 with the testing solution and the other components in the testing region.

[0087] In some implementations, a solution of a deposition 184, for example a salt solution or a salt polysaccharide solution as discussed herein, may also be used on a test strip 150 to slow the rate at which a deposited salt dissolves and spreads after a sensor on the test strip 150 is wetted. For example, in some implementations, a solution of a salt deposition 184 may be used to create a region of deposited salt on a test strip 150, for example on a counter electrode 156 as described above. In some implementations, further modification of the solution of the deposition 184, and therefore the deposited salt in the region, may be used to maintain a high salt concentration in the region after a sample, for example a body fluid such as saliva, is added to the biosensor test strip 150. For example, a high salt concentration deposit in a region on a counter electrode 164 of a test strip 150 can maintain a high salt concentration throughout the duration of the electrochemical measurement by slowing the rate at which a deposited salt diffuses after a sample (for example saliva or other body fluid) is added to the biosensor (for example test strip 150). This approach can prevent or minimize the spread of the very high salt concentration to the working electrode 154, where it may interfere with other aspects of the test strip chemistry (e.g. enzyme function), or to other regions of the test strip 150.

[0088] By using one or more of these approaches, impact of the salt concentration in the saliva sample on the strip electrochemical response may be mitigated, while reducing impact on other aspects of the test strip chemistry. This can allow for a more accurate assessment of salivary biomarkers such as salivary lactic acid concentration as described herein.

[0089] Electrochemical biosensors can also be impacted by the pH of the sample being measured. For example, a pH concentration of a sample may impact the function of enzymes that react with a compound of interest to generate an electrochemical signal. Bloodbased biosensors do not typically need to control for the pH of blood, as blood pH is highly controlled and known to be within a typical range of 7.35 - 7.45. However, the pH of other body fluid samples may be variable and may affect a measured biomarker result. For example,saliva has a much more variable pH, within a typical range of 5.5 - 8.5. In some implementations, direct measurement of pH and algorithmic correction of this variable can be used to account for the affects of variable pH. In some implementations, it can be advantageous to take alternate or additional steps to mitigate the impact of sample pH on the performance of the biosensor. In some implementations, pH impact on the measurement can be minimized by controlling the pH of the sample during the measurement. For example, in some implementations, an enhancement layer may include deposition 184, which may include a pH- buffering polysaccharide deposition on a surface of an electrode, for example counter electrode 156 on a test strip 150 can be used to control for variable pH of the body fluid, for example, to control for variable pH of saliva.

[0090] In some implementations, chemistry of a test strip 150 may be modified to mitigate the need for pH measurement and / or algorithmic correction. For example, in some implementations, strategic deposition of an acid or base on the biosensor surface may be used. Deposition of an appropriate acid or base can create a localized region of optimized pH. In some implementations, an enhancement layer may include a localized region of optimized pH that may be targeted to a pH of an enzyme's optimal pH or an expected pH of a body fluid sample. In some implementations, an enhancement layer may include a deposition 184, which may include a high concentration of known pH, for example an acid or a base, that can be applied to the sample, making the variability in the sample pH no longer relevant. While a region of acid or a region of base on a counter electrode 156 is desirable (to control for pH), an altered or extreme pH on a working electrode 154 is less desirable because pH may impact the enzyme 182. In some implementations a deposition 184, for example a pH deposition or a pH-buffering polysaccharide deposition, may include one or more stabilization reagents that can act to stabilize the compounds within the polysaccharide solution. For example, in some implementations, a pH-buffering polysaccharide deposition may include one or more enzymes.

[0091] In some implementations, deposition 184 may allow an acid or base to be deposited in a highly precise location on a test strip 150. For example, in some implementations, deposition 184 may include an acid-polysaccharide or base-polysaccharide solution that may be used to deposit an acid or a base and control the pH of a region of a test strip 150. In some implementations, deposition 184 for example an acid or base solution, may have a viscosity high enough to allow for deposition and retention in a desired region, forexample counter electrode 156, of a test strip 150 or biosensor, and also have a viscosity low enough to allow for deposition using typical automated fluid dispensing equipment. In some implementations, after an acid or base solution dries, a highly precise region of acid or base can be left on the desired region of the biosensor or test strip 150. This precision in application can allow for the deposition 184 to be repeatably applied to the test strip and allow for predicable dissolution and interaction of the contents of the deposition 184 with the testing solution and the other components in the testing region.

[0092] In some implementations deposition 184, for example an acid solution or a base solution, and / or a polysaccharide solution, may be further modified to slow the rate at which a deposited acid or base diffuses once a sample, for example a body fluid, is added to the biosensor, for example on a test strip 150. This approach may further maintain an optimized pH on the test strip 150 or biosensor throughout the duration of the electrochemical measurement, and may help prevent the spread of acid or base to other regions of the biosensor, where it may interfere with other aspects of the test strip chemistry.

[0093] In some implementations, this approach may mitigate the impact of pH of a body fluid sample, for example saliva pH, on a biosensor or test strip 150 electrochemical response while avoiding impact on other aspects of the test strip chemistry. For example, deposition 184 of an acid or base may allow for a more accurate assessment of body fluid biomarkers, for example salivary lactic acid concentration as described herein.

[0094] In some implementations, deposition 184 may include a solution containing a polysaccharide and an acid or base that may also contain one or more enzymes to be deposited on the test strip 150. For example, in some implementations, an enzyme solution and a polysaccharide solution may be mixed together and deposited in a single step onto the working electrode of a test strip 130.

[0095] In some implementations, strategic positioning of working electrode 154 and counter electrode 156 can enable a biosensor on a test strip 150 to self-correct for features of a body sample, for example to create salt-corrective or pH-corrective biosensors. For example, saliva samples can be quite viscous, which may cause biosensors to fdl non- uniformly over several seconds. In some cases, non-uniform fdling may cause one electrode to be wetted by the sample fluid several seconds before wetting of one or more additional electrodes or other biosensor features on the same test strip 150. In some implementations,features of a test strip 150 or biosensor, for example sensor dimensions, materials, and microfluidics 170 may be altered to increase uniform wetting or mitigate confounding effects of non-uniform wetting. In some implementations, test strip 150 or biosensor features may be configured to help control a timing between wetting of portions of a sensor, for example a timing between wetting of a first electrode such as counter electrode 156 and a second electrode such as working electrode 154.

[0096] In some implementations, an electrochemical output may be sensitive to an amount of time these surfaces have been wetted. For example, a reaction may start as soon as a working electrode is wet, a chemical on an electrode may diffuse and alter a concentration over time, and / or a chemical on a wetted electrode may spread to undesired regions of the biosensor surface. In some implementations, it may be advantageous to deliberately and strategically design one or more features of the test strip 130, 150 or biosensor. For example, in some implementations, a position of the working electrode 154 and / or counter electrode 156 or a space between a working electrode 154 and a counter electrode 156 may be designed to consider and / or influence the flow of a sample. In some implementations, a feature of the test strip 150 may be designed to consider the type of sample on a test strip 150, for example to account for a flow characteristic, viscosity, density, compressibility, susceptibility to shear, expected speed, turbulence, contaminants, debris, bubbles, or other property of saliva, sweat, tears, urine, or target body fluid.

[0097] In some implementations, a solution of a deposition 184 may be configured based on a salt or a pH concentration of one or more desired deposition regions to maintain a desired amount for a duration of a reaction. For example, a biosensor may be configured such that a salt-doped counter electrode is positioned at the far end of the biosensor testing region, which may reduce the likelihood that the salt will have dissolved and diffused throughout the biosensor prior to the conclusion of the measurement. This approach may reduce or minimize a time between when a body fluid sample reaches a counter electrode and when the measurement is initiated. For example, a body fluid sample reaching a counter electrode may also be used to trigger measurement initiation. In some implementations, a large spacing between a working electrode and a counter electrode may further reduce the likelihood of undesirable diffusion of salt from the counter electrode to the working electrode.

[0098] In some implementations, a similar approach may be used to assist control of diffusion, for example diffusion of salt or pH, across an electrode surface. For example, in some implementations, positioning a working electrode at a far end of the biosensor testing region can minimize diffusion of pH from the working electrode region.

[0099] In some implementations a test strip 130 or biosensor, for example an enzymatic test strip such as test strip 150, may benefit from or require a temperature-based correction. In some implementations, an ambient temperature can be measured and used to perform an algorithmic correction of the sample temperature. In some implementations, a sample temperature can be measured and used to perform an algorithmic correction.

[0100] In some implementations, a test strip 130, 150 or a biosensor can include one or more further chemistry modifications, which can improve the accuracy and precision of lactate assessments. In some implementations, a test strip 130 can include an enhancement layer on a working electrode. For example, in some implementations, an enhancement layer of a polysaccharide (e.g. Chitosan) and / or a polymer membrane (e.g Nafion) may be deposited between the electrode surface and the enzyme layer. Once dried, this enhancement layer can better define the region for enzyme deposition due to its highly hydrophilic properties. The enhancement layer can improve consistency in enzyme droplet size and position, thereby increasing accuracy of test strip 130, 150. One or more enhancement layers can also mitigate any variations in the electrode consistency or roughness, which may induce small changes in the output of test strip 130.

[0101] In some implementations, a polymer membrane (e.g. Nafion) can be deposited on top of and / or below the enzyme layer. Once dried, the polymer membrane can protect the enzyme layer, for example physically and / or from undesirable interactions with the atmosphere, both of which may result in degradation of the test strip 130, 150. The polymer membrane may also act to improve the selectivity of the test strip 130, improving the precision and accuracy of measurements. In some implementations, a test strip 130, 150 may include an enhancement layer, a polymer membrane, or both on an electrode, for example a working electrode 154. As described herein, a test strip 130, 150 may include an electrode, for example a counter electrode 156, with an enhancement layer. For example, the enhancement layer can include one or more of a salt deposition, a salt-polysaccharide deposition, a pH deposition, a pH buffering deposition, an acid deposition, a base deposition, an acid-polysaccharidedeposition, a base-polysaccharide deposition, and a pH buffering-poly saccharide deposition. In some implementations, an enzyme 182 and deposition 184 may be drop cast on the surface of an electrode, for example working electrode 154 and / or counter electrode 156. For example, a drop of a solution of enzyme 182 or deposition 184 can dispensed on an electrode surface and allowed to dry. In some implementations, enzyme 182 and / or deposition 184 may be screen printed, sprayed, or placed in the desired location of test region 172. In some implementations, cellulose and / or polysaccharide in the solution of enzyme 182 and / or deposition 184 can allow the enzyme 182 and / or deposition 184 to be specifically positioned. This technique can increase consistency and reliability of measurements taken across multiple test strips 130.

[0102] In some embodiments, a test strip 130, 150 includes a counter electrode 156 with a deposition 184 of salt and a working electrode 154 with an enzyme 182. In some embodiments, a test strip 130, 150 includes a counter electrode 156 with a deposition 184 of pH (an acid, a base, or a pH buffer) and a working electrode 154 with an enzyme 182. In some embodiments, a test strip 130, 150 includes a counter electrode 156 with a deposition 184 of salt and a deposition 184 of pH (an acid, a base, or a pH buffer), and the test strip 130, 150 includes a working electrode 154 with an enzyme 182. In some embodiments, a test strip 130, 150 includes a first counter electrode 156 with a deposition 184 of pH (an acid, abase, or a pH buffer), a second counter electrode 156 with a deposition of salt, and a working electrode 154 with an enzyme 182.

[0103] While a working electrode 154 and a counter electrode 156 are described having particular locations, materials, layers, and arrangements, each of working electrode 154 and counter electrode 156 can be any conductive electrode and any number or electrodes that can have any of these components interchangeable.

[0104] Exertion and saliva sampling protocol

[0105] In some implementations, a smart computing device 110 can be used to establish a testing protocol, for example an exertion and saliva sampling protocol 200 illustrated in FIG. 2, and guide a user through this protocol 200. The goal of the derived protocol 200 is to direct the individual being measured to perform physical activity (e.g. running / cycling / swimming / physical labor) at intervals (e.g. pace / power) of increasing intensity, generally an exertion protocol 210, such that the range of exertion intensity will crossthe individual’s lactate threshold, while minimizing the number of exertion intervals 212 and the length of the exertion intervals 212 required to identify this threshold. The exertion and saliva sampling protocol 200 also includes a sampling protocol 220, to direct the individual being measured to collect samples at sampling intervals 222.

[0106] To establish this protocol 200 the smart computing device 110 may use several data sources, including but not limited to, survey data, biometric data, demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and prior lactate threshold testing data.

[0107] In some implementations, a data source may include a short survey completed by the individual being measured detailing the desired activity mode and a subjective estimated sustainable pace. In some implementations, the data sources can include the desired exertion mode, a log of previous lactate threshold testing data, weather information, and hydration status data.

[0108] Alongside each increasing intensity interval 212a, 212b, etc., to 212n (generally, exertion interval 212) during exertion protocol 210, body fluid, for example saliva samples, can be collected and / or analyzed at testing intervals 222a, 222b, etc. to 222n, (generally, sampling interval 222) according to sampling protocol 220, as per the established exertion and saliva sampling protocol 200. In some implementations, a first saliva sample B may be collected and / or analyzed prior to physical activity to establish a baseline. In some implementations, the first saliva sample B may be collected following a preliminary step 205, for example the preliminary step of rinsing with water and waiting, for example for 5 minutes, (as shown in FIG. 2) to eliminate residual accumulated lactate in the mouth. In some implementations, subsequent saliva samples, for example samples T1-T5, may be collected following each activity interval 212. For example, in some implementations, each subsequent saliva sample T1-T5 may be collected immediately following each activity interval 212.

[0109] FIG. 2 illustrates an implementation of an exertion and testing protocol 200, including preliminary step 205, collection of a pre-exertion baseline sample B, and exertion (running) at 3-minute exertion intervals 212a-n between 10 and 14 km / h. Following each exertion interval 212a-n there is a corresponding testing interval 222a-n (generally testing interval 222). For example, testing interval 222 can comprise a 1-minute break, during which the user is prompted to collect a saliva sample Tl, for example into a sample tube 140.Following the last exertion interval (e g., 212n), the user is prompted to collect a final sample, for example T5, and initiate the sample measurement workflow 240.

[0110] In some implementations, the exertion mode may be running, swimming, cycling, working, or other activity. In some implementations, the exertion interval 212 may be 1 min, 2 min, 5 min, 10 min, 12 min, 15 min, or other appropriate time. In some implementations, the duration of each exertion interval 212a-n may increase over a range and decrease over another range. In some implementations, the testing / break interval 222 may be 15 sec, 30 sec, 45 sec, 60 sec, 90 sec, 120 sec, or other appropriate time sufficient to collect the sample. In some implementations, testing interval 222 may be shorter or dynamically adjusted, for example to maintain an exertion or lactate level. In some implementations, testing interval 222 may be longer or dynamically adjusted, for example to allow for more time to collect the sample. In some implementations, each exertion interval 212 and / or testing interval 222 may be the same duration as other respective exertion 212 and testing 222 intervals. In some implementations, the exertion intervals 212a-n and / or testing intervals 222a-n may be different. For example, in some implementations, the exertion intervals 212a-n may increase or decrease, and the testing intervals 222a-n may independently increase or decrease. In some implementations, the exertion intervals 212a-n and / or testing intervals 222a-n may be dynamically adjusted to reach, but not exceed or saturate, the user’s lactate threshold. As shown in FIG. 2, five exertion intervals 212 and corresponding testing intervals 222 may be indicated by exertion and saliva sampling protocol 200. In some implementations, the number of exertion intervals 212 and testing intervals 222 may be another appropriate number, such as 3, 4, 5, 6, 7, 8, 9, 10, 12, or more exertion intervals 212 and testing intervals 222. The number of exertion intervals 212 and testing intervals 222 may be set to achieve a test subject’s lactate threshold, to determine a lactate threshold after a total period of exertion, or dynamically adjusted to optimize exertion and saliva sampling protocol 200.[OlH] In some implementations, an exertion and saliva sampling protocol 200 may further consist of a series of preliminary steps 205 which should be conducted prior to the protocol to ensure an individual is appropriately prepared to complete the lactate threshold assessment. For example, in some implementations, preliminary steps 205 may instruct the user to ingest a specific volume of fluid over the course of 24 hours to ensure they are well hydrated prior to the test. In some implementations, the user may be instructed to rest andrefrain from food and drink intake for a period of time, for example 1 hour, prior to the test to help ensure baseline lactate levels (e.g., sample B) are representative and to reduce any confounding impact of food or drink on salivary lactate estimates.

[0112] In some implementations, an exertion and saliva sampling protocol 200 may include periodic uploading and / or downloading of data to a remote device, for example a remote database, remote analysis unit, medical record, employment record, training history, or other device. In some implementations, periodic data transfer may allow capture of interim analysis and / or protocol adjustment as described herein. In some implementations, periodic data transfer may allow an exertion and saliva sampling protocol to be interrupted, paused, adjusted, and / or resumed with minimal data loss. In some implementations, an exertion and sampling protocol may include an initial step of downloading a user’s previous testing protocol parameters and / or test results, which then may be used to establish or modify a current testing protocol.

[0113] Saliva measurement protocol

[0114] As discussed above, in some implementations, the lactate concentration of saliva may be determined with the measurement device in parallel with the exertion protocol. In some implementations, the lactate concentration of saliva may be determined following the completion of the exertion protocol. FIGS. 3A-B illustrate two workflows in which saliva samples are collected and analyzed.

[0115] As shown in FIG. 3A, an implementation of a post-analysis workflow 300 can include administration of a survey 302 used to establish an exertion and saliva sampling protocol 304. The steps of this protocol 304 are followed, and several saliva samples are collected 306 at intervals during the course of the protocol 304. After all samples have been collected 306, they are analyzed in series 308, and the results are used to generate a report 310 detailing the individual’s lactate threshold. In some implementations, report generation 310 includes providing information regarding one or more of the type of workflow used, the information obtained during survey 302, details of protocol 304, intermediate or preliminary results of particular samples collected during sample collection 306 (e.g. volume and timing data), and intermediate or preliminary results of particular analyses performed during sample analysis 308 (e.g., raw results and / or trends).

[0116] As shown in FIG. 3B, an implementation of a real-time analysis workflow 300’ includes similar steps of conducting a survey 302’ used to establish an exertion and saliva sampling protocol 304’. In some implementations, survey 302’ may be identical to survey 302 in some or all respects. In some implementations, survey 302 and / or survey 302’ may include questions or database queries as described elsewhere herein. In some implementations, survey 302 or 302’ may be used to establish use of a post-analysis workflow 300 or real-time analysis workflow 300’. Similarly, in some implementations, exertion and saliva sampling protocol 304’ may be identical to protocol 304 in some or all respects. In some implementations, exertion and saliva sampling protocol 304’ may differ to allow more time between samples to conduct collection and / or analysis. In some implementations, exertion and saliva sampling protocol 304’ may differ from protocol 304 to increase or otherwise adjust exertion levels and / or duration to account for increased processing time and / or to incorporate processing results to the next phase of exertion. As further illustrated in FIG. 3B, saliva samples are collected 306a-306n, (generally sample collection 306’) and immediately analyzed 308a-308n (generally analysis 308’) during the protocol 300’. Once sufficient data has been collected, a report is generated 310’ detailing the individual’s lactate threshold. In some implementations, report generation 310’ may be identical to report generation 310 in some or all respects. In some implementations, report generation 310’ may account for a different number of samples collected in sample collection 306’, altered duration of real-time analysis workflow 300’, and / or report changes dynamically made to exertion and saliva sampling protocol 304’. As shown in FIG. 3B, three sample collections 306’ and corresponding analysis 308’ may be indicated by exertion and saliva sampling protocol 300’. In some implementations, the number of sample collections 306’ and analysis steps 308’ may be another appropriate number, such as 4, 5, 6, 7, 8, 9, 10, 12, or more. As discussed above, the number of sample collections 306’ and analysis steps 308’ may be set to achieve a test subject’s lactate threshold, to determine a lactate threshold after a total period of exertion, or dynamically adjusted to optimize exertion and saliva sampling protocol 300’. Similarly, the post-analysis workflow 300 illustrated in FIG. 3A may include an appropriate number of samples collected during sample collection 306, all batch analyzed at analysis 308.

[0117] In some implementations, the post-analysis workflow 300 may be more suitable due to the convenience of decoupling sample collection 306 and analysis 308. Forexample, when an individual is conducting their own lactate threshold test, it may be impractical to analyze samples while performing the next exertion interval. Similarly, when a person (e.g., a coach or trainer) is conducting several lactate threshold tests 300 with different users at the same time (e.g., a team or class), it may be easier to collect all samples 306 from all users for analysis 308 at a later time. In some implementations, the real-time workflow 300’ may be more suitable due to the convenience of a dynamic analysis. For example, when an individual (e.g., a coach or clinician) is conducting analysis of a single user, it may be more efficient to analyze 308a-308n each sample 306a-306n as it is collected (or during the next exertion interval). In this example additional exertion intervals past the lactate threshold may be avoided, and the report generation 310’ may be performed faster. In some implementations, the real-time workflow 300’ may be used to generate preliminary results that can be used to dynamically adjust the exertion portion of exertion and saliva sampling protocol 304’ as described below. In some implementations, the real-time workflow 300’ may be used to generate interim results that can indicate a level of compliance with the exertion and saliva sampling protocol 304’. For example, in some implementations, the system may generate an error message or a corrective action suggestion if an interim analysis indicated the exertion and saliva sampling protocol 304’ is not being followed. For example, an error may be generated if a sample size obtained during sample collection 306’ is insufficient compared to the current exertion and saliva sampling protocol 304’ instructions, if an exertion time does not match the prescribed exertion time (see, e.g. FIG. 2), or if an individual becomes too dehydrated to continue the exertion and saliva sampling protocol 304’. Similarly, a corrective action, for example to collect a larger sample during sample collection 306’, to perform the exertion period for the correct duration as set forth in the exertion and saliva sampling protocol 304’, or to pause testing to hydrate, may be provided.

[0118] FIG. 4 illustrates an implementation 400 whereby a smart computing device, for example smart computing device 110 provides real time guidance to assist with completing a post-analysis saliva lactate threshold assessment, for example post-analysis workflow 300. A smart computing device 110 may provide direction 402 the user to collect a sample 404, perform an exertion 450, and collect additional samples 414 at repeated intervals, for example according to post-analysis workflow 300. A smart computing device 110 may direct 402 the user to collect samples 404 into specific tubes 140. Each tube, for examplesample tube 140, may be labeled to indicate the measurement time point and a performed activity at a specific exertion intensity for a specific duration. In some implementations, the user can be instructed to drop, squeeze, or otherwise deposit a collected saliva sample from a sample tube 140 onto a test strip 130. In some implementations, each sample 404, 414 is collected directly onto a test strip 130. In some implementations, each sample 404, 414 is collected from the mouth or a test tube 140 with a new test strip 130. In some implementations, two or more samples 404, 414 are collected with the same test strip 130, for example with different sections and / or biosensors on a single test strip 130.

[0119] Once all samples prescribed by directed protocol 402 have been collected, the smart computing device 110 prompts the user to insert the lactate test strip(s) into the measurement device 406, analyzes the samples 408, for example with the portable measurement device, and reports a lactate threshold estimate 480. As illustrated in FIG. 4, smart computing device 110 may further direct the user to eject the test strip(s) 460. For example, in some implementations, each sample 404, 414 is collected with a new test strip 130. Smart computing device 110 provides direction 406 to insert a first test strip to be analyzed during measurement 408 before providing instructions 460 to eject the first test strip. Further instructions can be provided to insert the next test strip 406 for analysis 408 and ejection 460 until all test strips 130 have been inserted 406 and analyzed 408 to generate report 480. In some implementations, the report may be generated 480 before the last strip is ejected 460.

[0120] As noted above, in some implementations, the real-time workflow 300’ will be more suitable, for example due to the advantages of real-time sample analysis. For example, when the measurement device 110 is used to collect and analyze saliva samples directly from the tongue, real-time analysis 300’ simplifies the sample analysis process. Real-time analysis 300’ may also be beneficial because the interim results of the analysis 300’ for example 308’, may be used to modify the exertion and sample collection protocol 304’ in real time. This may be useful when, for example, an additional datapoint is necessary because the initial protocol has not resulted in sufficient exertion intensity. Similarly, the initial protocol may “overshoot” the target exertion intensity and quickly exceed the lactate threshold. In both cases, the exertion protocol 304’ may be modified to adjust the exertion intensity and more easily identify the lactate threshold.

[0121] FIG. 5 illustrates an implementation 500 whereby a smart computing device, for example smart computing device 110, provides real time guidance 502 to assist with completing a real time analysis saliva lactate threshold assessment, for example as shown in real-time analysis workflow 300’. For example, the smart computing device 110 can direct a user to collect samples into specific tubes 504, 514. In some implementations the initial sample 504 may be used as a baseline sample B, as shown in FIG. 2. Smart computing device 110 can further direct the user to insert test strip 130, with the loaded saliva sample, into a measurement device, for example measurement device 120, at step 506. The saliva sample can be analyzed at measurement step 508, and the smart computing device 110 can instruct the user to eject the test strip 130 at step 510. Smart computing device 110 can further direct the user to perform an exertion 550, for example a step of an exertion protocol 210 described herein. Smart computing device 110 can instruct the user to take breaks and collect additional saliva samples 514 during, for example exertion and saliva sampling protocol 304’. Smart computing device 110 can provide prompts to collect saliva samples 514, insert test strips 516, and resume exertion. In some implementations, the user is instructed to resume exertion while the previous sample is measured 518. In this way, the protocol 300’ can be streamlined to measure each sample with the measurement device 120 in parallel with the next step of the exertion protocol 300’.

[0122] After testing, smart computing device 110 can provide instructions to eject the test strip 560. In some implementations, the measurement 518 and ejection 560 steps may be performed during the next exertion phase 550. In some implementations, the smart computing device 110 can continue to provide instructions to perform exertion 550, collect a sample 514, insert a test strip 516, measure the sample 518, and eject the strip 560 until all samples are collected and tested. In some implementations, the number of cycles of exertion 550, collecting a sample 514, inserting a test strip 516, measuring the sample 518, and ejecting the strip 560 may be any appropriate number, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, or more, or dynamically adjusted, for example as described herein. Once all samples have been analyzed in parallel with exertion, the smart computing device can prompt the user to analyze the samples with the portable measurement device 120 and report a lactate threshold estimate 580. In some implementations, smart computing device 110 can direct the user to insert a test strip 130 into each tube 140 to collect a specific sample onto atest strip 130. In some embodiments,the user can be instructed to drop, squeeze, or otherwise deposit a collected saliva sample from a sample tube 140 onto a test strip 130. In some implementations, each sample 504, 514 is collected from the mouth or a test tube 140 with a new test strip 130. In some implementations, two or more samples 404, 414 are collected with the same test strip 130, for example with different sections and / or biosensors on a single test strip 130.

[0123] In some implementations, additional parameters may be determined using a measurement device 120 to improve the accuracy and / or utility of the lactate threshold estimate. For example, in some implementations, salivary osmolarity or other hydration biomarker can be measured using the portable measurement device 120 prior to the collection of a baseline saliva sample B. If the saliva osmolality value indicates that the subject is dehydrated, the user will be instructed to postpone the threshold assessment until the subject has an opportunity to rest and hydrate, for example as part of preliminary step 205.

[0124] In some implementations, saliva pH of one or more collected samples Tl- Tn can be measured, for example using a single-use pH test strip and the portable measurement device 120. This coordinated analysis can result in the generation of a dataset of matched saliva pH, lactate, and exertion intensity data. Because enzymatic biosensor activity can be impacted by the pH of the sample being measured, the pH of the sample may be used to apply a correction coefficient to the lactate concentration to improve the accuracy of the measurement.

[0125] Lactate Threshold Estimate and Training Suggestions

[0126] In some implementations, after the completion of the exertion and sampling protocol 300, 300’ and the measurement of all samples, the paired saliva measurements and exertion intensity data can then be used to calculate a lactate threshold estimate.

[0127] A range of approaches have been reported that can mathematically determine a lactate threshold value from a dataset of paired lactate and exertion intensity measurements. These include, but are not-limited to, Log-log, Onset of Blood Lactate Accumulation (OBLA), Baseline plus (Bsln+), Dmax, Lactate Turning Point (LTP), and Lactate / Intensity ratio (LTratio). By applying at least one of these approaches to the saliva measurement and exertion intensity dataset, a smart computing device can determine a lactate threshold estimate.

[0128] In some implementations, multiple samples are collected following increasingly intense exercise as described above. The change in the concentration of salivarylactate is used to calculate a lactate threshold value using at least one of a range of mathematical approaches discussed above. Using this approach the output is a “threshold value”. In some implementations, the methods and systems described herein can be used to collect only two salivary lactate samples. In some implementations, a sample can be collected before and after a period of exertion at “maximal effort,” as determined for example by the user, a clinician or trainer, or based on historical data. The change in salivary lactate before exertion and after intense or maximal exertion (based on two points) can be indicative of the degree of lactate clearance during this period of intense exertion, and therefore can provide data indicative of physical fitness.

[0129] This assessment can be compared with populational reference data, and / or compared against multiple maximal effort tests from the same individual to determine change over time. For example, reduced increase in salivary lactate during maximal effort following training can indicate improved fitness or performance over time. In some implementations, guidance, sample collection, analysis, and timing of two-point assessments may be similar or identical to those discussed herein in some or all respects. In some implementations, a change in lactate and an interpretation of this change may be reported as an alternative or addition to the reports, for example report generation 310, report generation 310’, lactate threshold estimate 480, and / or lactate threshold estimate 580.

[0130] In some implementations, only a single lactate measurement is collected. This single-point assessment may be collected at any time, rather than specifically before or after a period of exertion. For example, a single-point assessment may be useful when monitoring fitness or recovery from exertion to evaluate if an individual has returned to their pre-exertion salivary lactate levels after a suitable rest period. Single-point assessment may also be useful for monitoring fatigue, for example to assess if an individual presenting to a worksite for a physically intense shift is appropriately rested and recovered from prior work. This value can also be useful when compared with populational reference data. It may be of further value by comparing multiple discrete single-point measurements from the same individual to observe day-to-day changes or trends in salivary lactate and correct for interindividual variation. In some implementations, guidance, sample collection, analysis, and timing of single-point assessments may be similar or identical to those discussed herein in some or all respects. In some implementations, a single lactate value and / or an interpretationof this single value may be reported as an alternative or addition to the reports, for example report generation 310, report generation 310’, lactate threshold estimate 480, and / or lactate threshold estimate 580.

[0131] In some implementations, a single-point assessment may be used to provide guidance following a single-point assessment conducted before exertion. For example, alternatively or in addition to the other guidance and recommendations discussed herein, a single-point assessment may be used to provide a recommendation to reduce exercise intensity and focus on recovery, for example in response to an elevated single-point lactate measurement. In some implementations, a recommendation to proceed with high-intensity training may be provided in response to a low or normal single-point lactate measurement.

[0132] In some implementations, a threshold value may be accompanied by training guidance intended to improve a user’s lactate threshold in future assessments. For example, this guidance can be customized based on a determined threshold estimate. In some implementations training guidance, for example including an exercise, training, rest, hydration, and / or diet recommendation, may be provided. In some implementations, guidance may be designed to improve a user’s lactate threshold, for example to increase a user’s ability to perform an exertion activity at a higher intensity and / or for a longer duration. In some implementations, guidance may be designed to assist a user in changing an exertion type, for example from running to swimming, at similar or improved intensity and / or duration between activities. In some implementations, guidance may be provided to reduce the likelihood of injury. In some implementations, guidance may be provided to achieve and / or maintain a longterm fitness goal, for example to train for a marathon or triathlon, to improve on performance in a prior sport season, and / or to efficiently exercise to maintain a level of performance.

[0133] An implementation of a training guidance for running, for example as shown in FIG. 6, may include one or more suggestions 600 to increase a weekly running distance, add a periodic long run at a metabolic threshold, include interval runs, or conduct mock lactate threshold test(s). Similarly, an implementation of a training guidance for cycling, for example as shown in FIG. 7, may include one or more suggestions 700 to increase a weekly cycling distance or duration, add long duration ride(s) at a portion of metabolic threshold, include fasted rides that may be at a portion of a metabolic threshold, or conduct mock lactate threshold test(s). In some implementations, training guidance suggestions may be similarlyprovided as described herein, for example for additional sports or exertion activities. In some implementations, training guidance may combine activities, for example a training guidance regimen may include running and cycling suggestions.

[0134] In some implementations, at a time following a user’s lactate threshold assessment, a re-assessment of an individual’s lactate threshold may be performed. In some implementations, a prompt may be given, for example via an app, on a computing device, and / or a measuring device, to undertake a re-assessment to assess progression. In some implementations, advice on maintaining or increasing training paces or power may be provided to the user. For example, advice may be used to help with improving a user’s lactate threshold, sustainable pace, and / or resultant aerobic capacity.

[0135] In some implementations, an initial lactate threshold can be designated as the baseline, for example for an individual or pre-season measurement. A baseline can be used as a reference point for initial assessment with pre-determined timelines for further lactate threshold assessments to be undertaken in-line with a desired training period (weeks or months). In some implementations, a previous target lactate threshold data for fitness may be used, for example, to set training schedules and / or frequency of re-assessment.

[0136] In some implementations, a lactate threshold assessment can be carried out following recovery from an injury. Previous target lactate threshold data related to fitness will be utilized to set training schedules frequency of re-assessment.

[0137] In some implementations, accessory data may also be used to provide further customized training guidance. Accessory data may include of at least one of: sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, and environmental data. In some implementations, the exertion and measurement protocol can be based on either a subjectively estimated threshold value or historical measurement data, for example to determine the range of exercise intensities and / or durations. In some implementations, the range of exercise intensities and / or durations can be established based on additional data, such as heart rate, speed, and age, as compared to a subjective estimate. Use of this dataset can allow for a more accurate estimate of an individual's sustainable pace. For example, a maximal heart rate can be estimated from an individual’s age compared through extrapolation of logged measurement data. This in turn allows for a truncated or optimized exertion and saliva sampling protocol 200. For example, a standardexertion and saliva sampling protocol 200 may require 6 exercise intervals 212 and corresponding sample intervals 222, where an optimized exertion and saliva sampling protocol 200 may adjust each activity interval 212 (via intensity and / or duration) and / or each sampling interval 222 to reduce the total number of intervals or samples to 3 or 4. As described elsewhere herein, the total number of samples may be 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more. In some implementations, the number of intervals and samples can be reduced while encompassing the user’s lactate threshold within the range of exercise intensities.

[0138] Additional Considerations and Terminology

[0139] Features, materials, characteristics, or groups described in conjunction with a particular aspect, implementation, or example are to be understood to be applicable to any other aspect, implementation or example described herein unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features or steps are mutually exclusive. The protection is not restricted to the details of any foregoing implementations. The protection extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed.

[0140] While certain implementations have been described, these implementations have been presented by way of example only and are not intended to limit the scope of protection. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms. Furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made. Those skilled in the art will appreciate that in some implementations, the actual steps taken in the processes illustrated or disclosed may differ from those shown in the figures. Depending on the implementation, certain of the steps described above may be removed, others may be added. For example, the actual steps or order of steps taken in the disclosed processes may differ from those shown in the figure. Depending on the implementation, certain of the steps described above may be removed, others may be added. Furthermore, the features and attributes of the specific implementations disclosed above may be combined in different ways to form additional implementations, all of which fall within the scope of the present disclosure.

[0141] Although the present disclosure includes certain implementations, examples and applications, it will be understood by those skilled in the art that the present disclosure extends beyond the specifically disclosed implementations to other alternative implementations or uses and obvious modifications and equivalents thereof, including implementations which do not provide all of the features and advantages set forth herein. Accordingly, the scope of the present disclosure is not intended to be limited by the described implementations, and may be defined by claims as presented herein or as presented in the future.

[0142] Conditional language, such as “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain implementations include, while other implementations do not include, certain features, elements, or steps. Thus, such conditional language is not generally intended to imply that features, elements, or steps are in any way required for one or more implementations or that one or more implementations necessarily include logic for deciding, with or without user input or prompting, whether these features, elements, or steps are included or are to be performed in any particular implementation. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list. Likewise, the term “and / or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list. Further, the term “each,” as used herein, in addition to having its ordinary meaning, can mean any subset of a set of elements to which the term “each” is applied. Additionally, the words “herein,” “above,” "below," and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application.

[0143] Conjunctive language such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to convey that an item, term, etc. may be either X, Y, or Z. Thus, such conjunctive language isnot generally intended to imply that certain implementations require the presence of at least one of X, at least one of Y, and at least one of Z.

[0144] Language of degree used herein, such as the terms “approximately,” “about,” “generally,” and “substantially” as used herein represent a value, amount, or characteristic close to the stated value, amount, or characteristic that still performs a desired function or achieves a desired result. For example, the terms “approximately”, “about”, “generally,” and “substantially” may refer to an amount that is within less than 10% of, within less than 5% of, within less than 1% of, within less than 0.1% of, and within less than 0.01% of the stated amount. As another example, in certain implementations, the terms “generally parallel” and “substantially parallel” refer to a value, amount, or characteristic that departs from exactly parallel by less than or equal to 15 degrees, 10 degrees, 5 degrees, 3 degrees, 1 degree, or 0.1 degree.

Claims

WHAT IS CLAIMED IS:

1. A method for determining an individual's lactate threshold comprising: establishing an exertion and saliva sampling protocol to collect one or more saliva samples; guiding completion of the exertion and saliva sampling protocol; measuring a lactate concentration of each of the one or more saliva samples using a portable measurement device; analyzing the lactate concentration measurements and estimating the individual’s lactate threshold; and establishing a training protocol intended to improve an individual’s exertion intensity capacity using the estimated lactate threshold.

2. The method of claim 1, wherein the saliva sampling protocol is established using a smart computing device, the smart computing device is used to guide the completion of the protocol, and the smart computing device is used to analyze the lactate concentration measurements and estimate the individual’s lactate threshold.

3. The method of claim 2, wherein the smart computing device provides real-time guidance and alerts throughout the exertion and saliva sampling protocol.

4. The method of any of claims 2-3, wherein another device connected to the smart computing device provides real-time guidance and / or alert.

5. The method of claim 4, wherein the real-time guidance and / or alert is configured to assist completion of the exertion and saliva sampling protocol.

6. The method of any of claims 2-5, wherein the portable measurement device is integrated into the smart computing device.

7. The method of any of claims 1-6, wherein the exertion and saliva sampling protocol is established using a dataset composed of at least one of: survey data, biometric data,demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and prior lactate threshold data.

8. The method of any of claims 1-7, further comprising conducting a hydration assessment using the portable measurement device prior to guiding completion of the exertion protocol.

9. The method of any of claims 1-8, further comprising instructing the individual to follow a hydration protocol prior to guiding completion of the exertion and saliva sampling protocol.

10. The method of any of claims 1-9, wherein all saliva samples are collected before measuring the lactate concentration of each sample.

11. The method of any of claims 1-10, wherein each saliva sample is analyzed in real-time during completion of the exertion and saliva sampling protocol.

12. The method of claim 11 , further comprising modifying the exertion protocol and / or the saliva sampling protocol using results of the real-time analyses.

13. The method of any of claims 1-12, wherein saliva samples are collected directly from the tongue for analysis.

14. The method of any of claims 1-13, wherein the estimated lactate threshold is combined with a dataset comprising at least one of sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, environmental data to establish the training protocol.

15. A system for determining an individual's lactate threshold, wherein the system is configured to: establish an exertion and saliva sampling protocol to collect one or more saliva samples; guide completion of the exertion and saliva sampling protocol;measure a lactate concentration of each of the one or more saliva samples using a portable measurement device; analyze the lactate concentration measurements and estimating the individual’s lactate threshold; and establish a training protocol intended to improve an individual’s exertion intensity capacity using the estimated lactate threshold.

16. The system of claim 15, further comprising a smart computing device, wherein the saliva sampling protocol is established using the smart computing device, the smart computing device is used to guide the completion of the protocol, and the smart computing device is used to analyze the lactate concentration measurements and estimate the individual’s lactate threshold.

17. The system of claim 16, wherein the smart computing device provides real-time guidance and alerts throughout the exertion and saliva sampling protocol.

18. The system of any of claims 16-17, further comprising another device, wherein the another device connected to the smart computing device and provides a real-time guidance and / or an alert.

19. The system of claim 18, wherein the real-time guidance and / or alert is configured to assist completion of the exertion and saliva sampling protocol.

20. The system of any of claims 16-19, wherein the portable measurement device is integrated into the smart computing device.

21. The system of any of claims 15-20, wherein the exertion and saliva sampling protocol is established using a dataset composed of at least one of: survey data, biometric data, demographic data, environmental data, physiological assessment data, sweat sodium concentration data, hydration status data, and prior lactate threshold data.

22. The system of any of claims 15-21 , wherein the system is further configured to conduct a hydration assessment using the portable measurement device prior to guiding completion of the exertion protocol.

23. The system of any of claims 15-22, wherein the system is further configured to instruct the individual to follow a hydration protocol prior to guiding completion of the exertion and saliva sampling protocol.

24. The system of any of claims 15-23, wherein all saliva samples are collected before measuring the lactate concentration of each sample.

25. The system of any of claims 15-24, wherein each saliva sample is analyzed in real-time during completion of the exertion and saliva sampling protocol.

26. The system of claim 25, wherein the system is further configured to modify the exertion protocol and / or the saliva sampling protocol using results of the real-time analyses.

27. The system of any of claims 15-26, wherein saliva samples are collected directly from the tongue for analysis.

28. The system of any of claims 15-27, wherein the estimated lactate threshold is combined with a dataset comprising at least one of sweat sodium composition, salivary osmolarity, heart rate, VO2 max, biometric data, demographic data, environmental data to establish the training protocol.

29. A test strip for determining an estimated lactate threshold, the test strip comprising: a biosensor with an enzyme test; an electrode; and an enhancement layer.

30. The test strip of claim 29, wherein the enhancement layer comprises a salt deposition on a surface of the electrode.

31. The test strip of claim 30, wherein the salt deposition is a salt-polysaccharide deposition.

32. The test strip of any of claims 30-31, further comprising a second electrode comprising an enzyme on a surface of the second electrode.

33. The test strip of claim 32, wherein the enzyme comprises a polysaccharide solution.

34. The test strip of any of claims 30-33, wherein the salt deposition is configured to be maintained in a region around the electrode for 10-30 seconds.

35. The test strip of any of claims 29-34, wherein the enhancement layer comprises an acid or base deposited on the biosensor surface.

36. The test strip of claim 35, wherein the acid or base comprises a pH-buffering polysaccharide deposition.

37. The test strip of claim 36, further comprising a second electrode comprising an enzyme on a surface of the second electrode.

38. The test strip of claim 37, wherein the enzyme comprises a polysaccharide solution.

39. The test strip of any of claims 29-38, wherein the enhancement layer comprises a polysaccharide and / or a polymer membrane deposited between a surface of the electrode and an enzyme layer.

40. The test strip of claim 39, wherein the enhancement layer comprises the polysaccharide, wherein the polysaccharide comprises Chitosan.

41. The test strip of any of claims 39-40, wherein the enhancement layer comprises the polymer membrane, wherein the polymer membrane comprises Nafion.

42. The test strip of any of claims 39-41, wherein the enhancement layer is configured to mitigate any variations in the electrode consistency or roughness.

43. The test strip of any of claims 39-42, wherein the enhancement layer comprises both the polysaccharide and the polymer membrane.

44. A method of controlling a salivary osmolarity and / or a pH of a saliva sample to improve accuracy of an enzyme test, the method comprising: applying the collected saliva sample to a testing region of a biosensor used to perform the enzyme test, wherein the testing region comprises an electrode and an enhancement layer on a surface of the electrode.

45. The method of claim 44, wherein the enhancement layer comprises a salt deposition on the surface of the electrode.

46. The method of claim 45, wherein the salt deposition is a salt-polysaccharide deposition.

47. The method of claim 46, wherein the testing region further comprises a second electrode comprising an enzyme on a surface of the second electrode.

48. The method of claim 47, wherein the enzyme comprises a polysaccharide solution.

49. The method of any of claims 47-48, wherein the electrode is a counter electrode and the second electrode is a working electrode.

50. The method of any of claims 44-49, wherein the enhancement layer comprises an acid or base deposited on the surface of the electrode.

51. The method of claim 50, wherein the acid or base comprises a pH-buffering polysaccharide deposition.

52. The method of claim 51, further comprising a second electrode comprising an enzyme on a surface of the second electrode.

53. The method of claim 52, wherein the enzyme comprises a polysaccharide solution.

54. The method of any of claims 52-53, wherein the electrode is a counter electrode and the second electrode is a working electrode.

55. The method of any of claims 44-54, wherein the enhancement layer comprises a polysaccharide and / or a polymer membrane deposited between the surface of the electrode and an enzyme layer.

56. The method of claim 55, wherein the enhancement layer comprises the polysaccharide, wherein the polysaccharide comprises Chitosan.

57. The method of any of claims 55-56, wherein the enhancement layer comprises the polymer membrane, wherein the polymer membrane comprises Nafion.

58. The method of claim 55, wherein the enhancement layer is configured to mitigate any variations in the electrode consistency or roughness.

59. The method of any of claims 55-58, wherein the enhancement layer comprises both the polysaccharide and the polymer membrane.

60. A computing device for a saliva-based lactate assessment comprising one or more features of the foregoing description.

61. A measurement device for a saliva-based lactate assessment comprising one or more features of the foregoing description.

62. A system for a saliva-based lactate assessment comprising a computing device and a measurement device, comprising one or more features of the foregoing description.

63. A test strip for a saliva-based lactate assessment comprising one or more features of the foregoing description.

64. A method for performing a saliva-based lactate assessment comprising one or more features of the foregoing description.

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