Respiratory sensor calibration method and apparatus

Abstract

This document describes a method and apparatus for calibrating a respiratory sensor, wherein the respiratory sensor apparatus typically includes a sampling unit having a housing configured to receive sample breaths from a user and a sensor positioned within the housing. A processor electrically connected to the sensor can be configured to determine the dissipation time as the sensor is exposed to a decrease in CO concentration from near-constant levels detected in the breath sample to ambient levels detected. The processor can also be configured to calculate a time constant based on the dissipation time and the decrease from near-constant levels to ambient levels. Furthermore, the processor can be configured to apply the time constant to the transient response of the sensor to address drift during sensor calibration.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Provisional Application No. 62 / 955,558, filed December 31, 2019, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to apparatus and methods for maintaining the accuracy of devices for receiving and detecting biological parameters from respiratory samples over time. Specifically, this invention relates to apparatus and methods for calibrating respiratory sensors that naturally deteriorate over time. Background Technology

[0004] Health problems associated with smoking are well-known. Cigarette smoke contains nicotine, as well as many other compounds and additives. Tobacco smoke exposes individuals to carbon monoxide (CO) and these other compounds, many of which are carcinogenic and toxic to smokers and those around them. The presence and level of carbon monoxide in a smoker's exhaled breath can provide an indicator of an individual's overall smoking behavior, as well as their overall exposure to other toxic compounds.

[0005] Sampling exhaled breath requires a portable, inconspicuous respiratory sensor that is easy for users to carry. However, the relatively small size of the respiratory sensor also presents several challenges in capturing and accurately measuring exhaled breath samples. Due to its relatively small size, factors such as the moisture content of the breath and the temperature of the breath can affect the accuracy of the sensor used to measure parameters.

[0006] To sample exhaled breaths, a portable, inconspicuous respiratory sensor is needed that is easy for users to carry. While such a portable respiratory sensor can measure the amount of carbon monoxide (eCO) exhaled by a user, how to use this data may not be very intuitive for all users, as it may not be a widely understood metric.

[0007] Electrochemical sensors commonly included in portable respiratory sensors for detecting carbon monoxide levels in exhaled breath can degrade over time, leading to decreased sensor sensitivity. This decrease in sensitivity over time is generally consistent for such sensors, provided they are kept away from extreme environments. However, the sensor's transient response can vary from device to device and may not be predictable by the type of sensor inputs available in the device.

[0008] Therefore, there remains a need for methods and devices that can correct for changes in sensor characteristics and allow for longer sensor lifespan and higher accuracy (especially for short-duration exposures, such as short exhalation cycles from a user). Summary of the Invention

[0009] Between the time a breath sampling device is manufactured and the time it is actually used by the user, there is typically a period of time during which the device is stored before use. During this period, the electrochemical sensor may begin to degrade, leading to a decrease in sensor sensitivity and resulting in inaccurate sensor readings when put into use.

[0010] To increase the lifespan of breath sensors used to detect analytes (such as carbon monoxide (CO)) from users, various methods can be employed to extend the shelf life of breath sampling devices before they are sold to users, and also result in longer usage time for users. This not only increases the accuracy of the breath sensor, but also enhances its ease of use by providing highly accurate readings from breaths with relatively short exhalation durations that are allowed by other means.

[0011] Examples of respiratory sampling devices and methods for determining and quantifying eCO levels from users are described in more detail in various patents, such as U.S. Patents 9,861,126; 10,206,572; 10,306,922; 10,335,032; and U.S. Patent Publication 2019 / 0113501, each of which is incorporated herein by reference in its entirety and is used for any purpose. Any of the devices described can be used in conjunction with the methods and apparatus described herein.

[0012] Portable or personal sampling units can communicate with either a personal electronic device or a computer. Personal electronic devices include, but are not limited to, smartphones, cellular phones, or other personal transmission devices designed or programmed to receive data from the personal sampling unit. Similarly, computers are intended to include personal computers, local servers, remote servers, etc. Data transmission from the personal sampling unit can occur to either the personal electronic device or the computer. Furthermore, synchronization between the personal electronic device and the computer is optional. As described herein, personal electronic devices, computers, and / or personal sampling units can transmit data to a remote server for data analysis. Alternatively, data analysis can be performed entirely or partially via a processor contained in a local device such as a sampling unit (or computer or personal electronic device). In any case, personal electronic devices and / or computers can provide information to individuals, caregivers, or other individuals.

[0013] The personal sampling unit receives an exhaled air sample from an individual via a collection inlet or opening. The hardware within the personal sampling unit may include any commercially available electrochemical gas sensor for detecting CO gas in the breath sample, and commercially available data transmission hardware (e.g., via Bluetooth). (Data transmission is provided via cellular or other radio waves). The transmitted data, along with associated measurements and quantizations, is then displayed on either a computer monitor or a personal electronic device (or both). Alternatively or in combination, any information may be selectively displayed on a portable sampling unit.

[0014] Electrochemical sensors contained within a sampling unit typically respond to exposure to changes in gas concentration, such as when a user initially blows air into the sampling unit. Before the user provides eCO, the electrochemical sensor can maintain a nominal steady-state voltage value, depending on the amount of ambient CO detected by the sensor within the unit. Upon exposure to a breath sample, the electrochemical sensor can exhibit an initial transient response, followed by a steady-state response, due to the change in gas concentration detected from the breath sample.

[0015] The steady-state response component indicates the sensor's sensitivity, for example, as measured in terms of voltage per unit gas concentration (mV / ppm CO). As the sensor deteriorates over time, this steady-state response value may drift, depending on the sensor's sensitivity, resulting in an increase or decrease in the voltage value. The transient response component indicates the sensor's rate of stabilization, and similarly, depending on the sensor's sensitivity, this transient response value may also drift, but may increase or decrease the voltage rate per unit gas concentration, resulting in a flat or steep response curve.

[0016] If the transient characteristics of a gas sensor are known, this transient response can be compensated for. This allows for accurate prediction of the steady-state response before the sensor has stabilized. To calibrate the sensor to address degradation since its initial calibration, the drift during measurement in the transient response and the drift during the steady-state response can be addressed independently. The steady-state response can be calibrated by exposing the sensor to a known gas concentration until a steady-state reading is obtained. Predicting the steady-state response of the sensor in respiratory sensor applications allows the user to provide a relatively short duration of breathing. Typically, the sensor can be initially calibrated for both transient and steady-state responses during manufacturing, and the initial calibration values ​​can be stored within the cell. In one variant, the initial calibration can be determined by collecting data on the sensor sensitivity over time to track the rate of sensitivity reduction. Based on this information, a linear or nonlinear model reflecting the sensitivity drift over time can be developed, and this model can be used to compensate for the time-varying sensitivity drift. For example, if it is known that the sensor sensitivity will decrease by a certain percentage, such as 5% per year, the processor can automatically apply a correction factor for the degradation percentage, for example within unit 20, to adjust the measured steady-state value by 5% to address the sensor degradation.

[0017] During user operation, users may not typically have access to a CO source with a known concentration for steady-state calibration purposes. Therefore, a breathing test can be performed, instructing the user to hold their breath for, for example, 10 seconds or longer, to allow the CO concentration in the bloodstream to equalize with the concentration in the alveoli of their lungs. The gas in their mouth and trachea may have a lower CO concentration, so as the user exhales into the sampling unit, the gas sensor may see a steady increase in CO concentration until the air in the mouth and trachea is depleted, at which point the CO gas concentration seen on the sensor approaches a constant level until breathing ceases. When the user stops exhaling, the CO gas concentration at the electrochemical sensor returns to the concentration in ambient air due to diffusion.

[0018] In some variations, during the breath test, the user can be instructed to inhale through the device after exhaling into it while holding their breath, so that the gas level within the unit returns to ambient levels. The rate of concentration equalization can be adjusted through design aspects of the breath sensor unit, such as device size, flow path constraints, proximity of the sensor to the vent, and the rate at which the sensor consumes CO. These values ​​may be consistent across devices of the same model; however, the user can also influence the rate of gas concentration equalization with the environment. For example, the user can block the vent to reduce the equalization rate, or gently shake or inhale through the device to increase the equalization rate.

[0019] Based on the drop in CO concentration from a near-constant measured value (near the end of the user's exhalation) back to the ambient value, a transient time constant characterizing the response to the measured drop can be calculated, and this calculated time constant value can indicate the degree of sensor degradation. This time constant can then be used to calculate the corrected eCO measurement when the user exhales a breath sample into the unit used for measurement.

[0020] For the various types of electrochemical sensors that can be used with sampling units, different types of sensors may exhibit different stability modes. Each of the various sensor stability modes is described in each of the following sections.

[0021] One type of sensor can have a time-stable sensitivity, but the stabilization rate may drift. During manufacturing, both sensitivity and stabilization rate can be calibrated by exposing the sensor to a step function change in gas concentration. Calibration parameters are stored on the device and used to calculate the CO level corresponding to the sensor voltage output. The sensor within sampling unit 20 can be provided to a user, who can then begin use by providing a breath sample. The stabilization rate parameters can be periodically recalibrated using the user's breath sample. Here, it can be assumed that the gas concentration at the end of the breath sample is in a steady state. When the user stops exhaling, the sensor may see a step response from the user's CO concentration to the carbon monoxide concentration in the ambient air.

[0022] Another type of sensor can have time-stable sensor sensitivity and stabilization speed, with minimal variability within the device. During device development, sensitivity and stabilization speed can be calculated by exposing the respiratory sensor to a step function change in gas concentration. Since calibration is not required on a per-device basis, sensitivity and stabilization speed parameters from device development can be pre-loaded into the device, and calibration parameters can also be stored on the device and used to calculate the CO level corresponding to the sensor's voltage output.

[0023] Another type of sensor can have both time-stable sensor sensitivity and stabilization speed. During manufacturing, both the sensor's sensitivity and stabilization speed can be calibrated by exposing the breath sensor to a step function change in gas concentration. Calibration parameters can be stored on the device and used to calculate the CO level corresponding to the sensor's voltage output. Alternatively, the stabilization speed can be calibrated once using a user's breath sample.

[0024] Another type of sensor may have a sensitivity pre-provided by the supplier, but the stabilization rate may vary from device to device. During manufacturing, the sensitivity parameters can be programmed into the device using values ​​provided by the gas sensor manufacturer. The stabilization rate parameters can be initialized using estimates obtained during device development, and the stabilization rate can be calibrated using user breath samples.

[0025] Another type of sensor can have a sensitivity that is consistent within a manufacturing batch, but the steady-state speed may vary from device to device. During manufacturing, the sensitivity parameters can be programmed into the device using values ​​provided by calibration from one or more sensors from the manufacturing batch. The steady-state speed parameters can be initialized using values ​​calculated by the calibration unit or using estimates obtained during device development, and the steady-state speed can be calibrated using user breath samples.

[0026] Another type of sensor can have sensor sensitivity and / or stabilization rate that vary consistently over time across devices. During manufacturing, sensitivity and / or stabilization rate parameters can be programmed into the sampling device along with a timestamp corresponding to the calibration date. A sensor drift model can also be loaded onto the device. Before using calibration parameters to calculate CO concentration from the sensor output, the parameters can first be adjusted using an aging factor based on the model. The aging factor can be applied to the sensor calibration before determining sensor drift. Optionally, the sensor drift model can be updated and deployed to the user's sensor via wireless options using any number of wireless protocols.

[0027] The aging factor can be applied to situations where a decrease in sensor response is known or experimentally verifiable. For example, it can be generally assumed that sensor sensitivity may decrease, for instance, by 2% to 5% per year, depending on storage conditions. Under typical storage conditions used in warehouse environments, a decrease in sensor sensitivity of, for example, 3% per year can be assumed. For instance, a device calibrated a year ago might have given a 200mV sensor response signal for a CO level of 50 ppm, while a current user providing a breath sample might generate a 100mV response signal associated with a CO level of 25 ppm. However, due to sensor degradation over the past year, the 25 ppm value might have increased by 3% (or some other percentage), thus increasing the CO level to 25.75 ppm, which can be rounded to 26 ppm.

[0028] Aging factors can be empirically determined by setting up a sufficient number of equipment groups under different conditions, conducting periodic tests, and then performing multivariate regression analysis to determine the impact of each component (e.g., temperature, humidity, time). Temperature and humidity can be subdivided into multiple ranges to provide a quick reference for determining the degradation rate. If a sufficient number of data points are available, a continuous distribution can be generated.

[0029] Another type of sensor can have sensor sensitivity and / or stabilization speed based on changes in environmental conditions over time. As mentioned above, during manufacturing, sensitivity and / or stabilization speed parameters can be programmed into the sampling device along with a timestamp corresponding to the calibration date. A sensor drift model can also be loaded onto the device. In this variant, sampling unit 20 can be combined with an environmental sensor package that can independently measure parameters included in the sensor drift model, such as temperature and relative humidity. The environmental sensor package can periodically measure these parameters and instantaneously correct and update calibration parameters and / or record and store parameters for use in calculating calibration parameters during use.

[0030] Before calculating the gas concentration from the sensor output using calibration parameters, the parameters can first be adjusted using an aging factor, as described above. Optionally, the sensor drift model can be updated and deployed to the user's sensor via wireless updates.

[0031] Another variation for calibrating the sensor may include a sampling unit 20 configured to self-calibrate its transient sensor performance. While the sensor may generally be stable, its stabilization rate may vary over time. Therefore, factory calibration of both sensitivity and stabilization rate can be combined with periodic recalibration of sensitivity rate based on a heuristic clearing model to improve the sensor's transient performance.

[0032] In one variant of a respiratory sensor device, the device typically includes a sampling unit having a housing configured to receive sample breaths from a user, a sensor positioned within the housing and in fluid communication with the sample breaths when received within the housing, and a processor in electrical communication with the sensor. The processor can be configured to determine the dissipation time as the sensor is exposed to a decrease in CO concentration from near-constant levels detected in the breath sample to ambient levels. The processor can also be configured to calculate a time constant based on the dissipation time and the decrease from near-constant levels to ambient levels. Furthermore, the processor can be configured to apply the time constant to the sensor's transient response to account for drift during sensor calibration.

[0033] In a method for calibrating a sensor, the method typically includes: receiving a breath sample from a user until the sensor detects CO at a near-constant concentration level from the breath sample; determining the time length during which the near-constant concentration level of CO dissipates to the ambient level of CO; calculating a time constant based on the time length and the reduction from the near-constant concentration level to the ambient level; and calibrating the sensor to address drift by applying the time constant to the sensor's transient response. Attached Figure Description

[0034] Figure 1A A variant of the system is shown that is capable of receiving breaths from a subject and detecting various parameters and is able to communicate with one or more remote devices.

[0035] Figure 1B The internal circuitry and a variant of the sensor contained within the housing of the breathing sensor are shown.

[0036] Figure 2 An example of the voltage response over time of an electrochemical sensor with transient and steady-state responses is shown.

[0037] Figure 3A and Figure 3B An example is shown of how sensor degradation can be effectively compensated by utilizing a dynamic correction algorithm.

[0038] Figure 4 Examples of eCO and eCO exhalation graphs measured from breath samples taken from healthy occasional smokers before and after smoking are shown.

[0039] Figure 5 A flowchart showing how to calculate the time constant for calibrating the sensor is presented.

[0040] Figure 6 A flowchart is shown illustrating how an aging factor is applied for calibration before the calculation of the time constant for calibrating the sensor. Detailed Implementation

[0041] To extend the lifespan of breath sensors used to detect analytes (such as CO) from users, various methods can be employed to increase the shelf life of breath sampling devices before they are sold to users, and also result in longer usage time for users. This not only increases the accuracy of the breath sensor, but also enhances its ease of use by providing highly accurate readings from breaths with relatively short expiratory durations that are allowed by other means.

[0042] When obtaining eCO from a user, certain biometric data can be obtained by non-invasively detecting and quantifying the user's smoking behavior, based on measuring one or more biometric data points; however, other biometric data can also be used. Such measurement or data collection can be performed using portable or fixed measurement units, either of which communicate with one or more electronic devices to perform quantitative analysis. Alternatively, the analysis can be performed in a portable / fixed unit. For example, the portable unit can be coupled to a keychain, an individual's cigarette lighter, a mobile phone, or other items that the individual will regularly carry with them. Alternatively, the portable unit can be a standalone unit or can be worn by the individual.

[0043] Figure 1A A variation of the system and / or method is illustrated, in which multiple samples of biometric data are obtained from a user and analyzed to quantify the user's exposure to cigarette smoke, thereby enabling the quantified information to be communicated to the individual, healthcare professionals, and / or other parties with a stake in the individual's health. The example discussed below employs a portable device 20 that utilizes a generally available sensor to obtain multiple exhaled air samples from an individual, the sensor measuring the amount of eCO in the exhaled air samples. However, quantification and information delivery are not limited to smoking exposure based on exhaled air. As mentioned above, numerous sampling mechanisms can be used to obtain a user's smoking exposure. The methods and devices described in this example can be combined with or supplemented by any number of different sampling mechanisms where possible, while still remaining within the scope of this invention.

[0044] Measurement of eCO levels is known to be a direct, non-invasive method for assessing an individual's smoking status. The eCO levels of non-smokers can range, for example, from 0 ppm to 6 ppm, or more specifically, from, for example, from 3.61 ppm to 5.6 ppm.

[0045] As shown in the figure, the portable or personal sampling unit 20 can communicate with a personal electronic device 10 or a computer 12. The personal electronic device 10 includes, but is not limited to, smartphones, cellular phones, or other personal transmission devices designed or programmed to receive data from the personal sampling unit 20. Similarly, the computer 12 is intended to include a personal computer, a local server, a remote server, etc. Data transmission 14 from the personal sampling unit 20 can occur to either the personal electronic device 10 or the computer 12. Furthermore, synchronization 16 between the personal electronic device 10 and the computer 12 is optional. As described herein, the personal electronic device 10, the computer 12, and / or the personal sampling unit 20 can transmit data to a remote server for data analysis. Alternatively, data analysis can be performed entirely or partially via a processor contained in a local device such as the sampling unit 20 (or the computer 12 or the personal electronic device 10). In any case, the personal electronic device 10 and / or the computer 12 can provide information to individuals, caregivers, or other individuals, such as... Figure 1A As shown.

[0046] The personal sampling unit 20 receives a sample of exhaled air 18 from an individual via a collection inlet or opening 22. The hardware within the personal sampling unit 20 may include any commercially available electrochemical gas sensor for detecting CO gas in the breath sample, and commercially available data transmission hardware 14 (e.g., via Bluetooth). (Data transmission can be provided via cellular or other radio waves). The transmitted data and associated measurements and quantizations are then displayed on either (or both) a computer display 12 or a personal electronic device 10. Alternatively or in combination, any information may be selectively displayed on the portable sampling unit 20.

[0047] The personal sampling unit 20 (or personal breathing unit) may also employ a standard port to allow direct wired communication with the corresponding devices 10 and 12. In some variations, the personal sampling unit 20 may also include removable or built-in memory storage, allowing for data recording and separate data transfer. Alternatively, the personal sampling unit may allow simultaneous data storage and transfer. Other variations of device 20 do not require memory storage. Furthermore, unit 20 may incorporate any number of GPS components, inertial sensors (for motion tracking), and / or other sensors that provide additional information about patient behavior.

[0048] The personal sampling unit 20 may also include any number of input triggers (such as switches or sensors) 24, 26. As described below, the input triggers 24, 26 may allow an individual to activate the device 20 to deliver a breath sample 18 or record other information about the cigarettes, such as the number of cigarettes smoked, their intensity, etc. Furthermore, variations of the personal sampling unit 20 may associate any input timestamp with the device 20. For example, the personal sampling unit 20 may associate the time of sample delivery with the time of measurement or input data delivery when transmitting data 14. Alternatively, the personal sampling device 20 may use alternative mechanisms to identify the time of sample acquisition. For example, given a series of samples, instead of recording a timestamp for each sample, the time intervals between each sample in the series can be recorded. Therefore, identifying the timestamp of any one sample allows the determination of the timestamp for each sample in the series.

[0049] In some variations, the personal sampling unit 20 can be designed to have a minimal profile and be easily carried by an individual with minimal effort. Therefore, the input trigger 24 may include a thin tactile switch, an optical switch, a capacitive touch switch, or any commonly used switch or sensor. The portable sampling unit 20 may also provide feedback or information to the user using any number of known technologies. For example, as shown, the portable sampling unit 20 may include a screen 28 displaying selection information as described below. Alternatively or additionally, feedback may be in the form of vibratory elements, auditory elements, and visual elements (e.g., a light source of one or more colors). Any feedback component can be configured to provide an alarm to the individual, which can serve as a reminder to provide a sample and / or to provide feedback related to smoking behavior measurements. Furthermore, the feedback component may repeatedly provide alarms to the individual in an effort to remind the individual to periodically provide exhaled air samples to extend the time period during which the system captures biometrics (such as eCO, CO levels, H2, etc.) and provide other behavioral data (such as manually entered location or location entered via a GPS component coupled to the unit, number of cigarettes, or other triggering conditions). In some cases, the reminders may be triggered at a higher frequency during the initial procedure or data acquisition. Once enough data is obtained, the frequency of reminders can be reduced.

[0050] When obtaining a breath sample using sampling unit 20, instructions can be provided on personal electronic device 10 or computer display 12 to be displayed to the subject during guided breathing tests for training the subject to use unit 20. Typically, the subject can be instructed, for example, on screen 28 of electronic device 10 to first inhale away from unit 20 and then exhale toward unit 20 for a set period of time. Unit 20 may optionally incorporate one or more pressure sensors fluidly coupled to, for example, a check valve, to detect whether the subject inhales through unit 20.

[0051] Figure 1BA top view of the sampling unit 20 is shown, with a portion of the housing 30 and the collection inlet or opening 22 removed to reveal the electrochemical sensors contained therein. In this variant, a first sensor 38 and a second sensor 42 (either or both of sensors 38 and 42 may include CO and H2 sensors) are shown optionally positioned on corresponding sensor platforms 36 and 40, which in turn may be mounted on a substrate such as a printed circuit board 44. In other variants, one or more sensors may be used depending on the parameter being detected. In other variants, one or more sensors may be mounted directly on the printed circuit board 44. A power port and / or data access port 46 is also seen integrated with the printed circuit board 44 and easily accessible via a remote device such as a computer, server, smartphone, or other device. As shown, multiple sensors 38 and 42 or a single sensor can be used to detect parameters from the sampled breath.

[0052] In other variations, at least one CO sensor or multiple CO sensors may be implemented individually. Alternatively, one or more CO sensors may be used in combination with one or more H2 sensors. If both CO and H2 sensors are used simultaneously, readings from the H2 sensor can be used to interpret or compensate for any H2 signal detected by the CO sensor, as many CO sensors have cross-sensitivity to H2, and H2 is often present in sufficient quantities to potentially interfere with CO measurements in human respiration. If a CO sensor is used without an H2 sensor, various methods can be applied to reduce any H2 measurement interference to a nominally acceptable level. However, directly measuring and compensating for the presence of H2 using an H2 sensor can aid in CO measurements. The sensor may also include any number of different sensor types, including chemical gas sensors, electrochemical gas sensors, etc., for detecting reagents such as carbon monoxide in cases of smoking-related inhalation.

[0053] Other examples of respiratory sampling devices and methods for determining and quantifying eCO levels from users are described in more detail in various patents, such as U.S. Patents 9,861,126; 10,206,572; 10,306,922; 10,335,032; and U.S. Patent Publication 2019 / 0113501, each of which is incorporated herein by reference in its entirety and for any purpose. Any of the devices described can be used in conjunction with the methods and apparatus described herein.

[0054] The electrochemical sensor contained within sampling unit 20 is typically responsive to changes in gas concentration, such as when a user initially blows gas into sampling unit 20. Before the user provides eCO, the electrochemical sensor can maintain a nominal steady-state voltage value 52 based on the amount of ambient CO detected by the sensor within unit 20, such as... Figure 2 An exemplary graph 50 is shown, illustrating the voltage response of the electrochemical sensor over time. When exposed to a breath sample, the electrochemical sensor may exhibit an initial transient response 54, followed by a steady-state response 56, as shown, due to changes in the gas concentration detected from the breath sample.

[0055] The steady-state response component 56 indicates the sensor sensitivity, for example, as measured in terms of voltage per unit gas concentration (mV / ppm CO). As the sensor deteriorates over time, this steady-state response value may drift, depending on the sensor's sensitivity, resulting in an increase or decrease in the voltage value (e.g., a vertical shift in the steady-state response along curve 50). The transient response component 54 indicates the sensor's steady-state rate, and similarly, depending on the sensor's sensitivity, this transient response value may also drift, but may increase or decrease the voltage rate per unit gas concentration, resulting in a flat or steep response curve (e.g., a horizontal contraction or expansion of the transient response along curve 50).

[0056] If the transient characteristics of the gas sensor are known, this transient response 54 can be compensated for. This allows for accurate prediction of the steady-state response 56 before the sensor has stabilized. Figure 3A and Figure 3B An example is shown of how sensor degradation can be effectively compensated by utilizing a dynamic correction algorithm. Figure 3A Graph 60 shows an example of gas supplied at different concentrations C (ppm) over time for measurement purposes. Figure 3B Graph 62 shows the curve obtained via an electrochemical sensor and the curve from... Figure 3A The measurements correspond to changes in the gas concentration level. Curve 64 shows the corresponding uncorrected voltage obtained from the sensor, while curve 66 shows the corresponding corrected voltage obtained from the sensor, the correction resulting in a relatively more accurate voltage reading corresponding to the actual gas concentration value.

[0057] To calibrate the sensor to address degradation since its initial calibration state, the drift during measurement on the transient response 54 and the drift during steady-state response 56 can be addressed independently. The steady-state response 56 can be calibrated by exposing the sensor to a known gas concentration until a steady-state reading is obtained. Predicting the sensor's steady-state response in respiratory sensor applications allows the user to provide a relatively short duration of breathing. Typically, the sensor can be initially calibrated at manufacturing for both transient and steady-state responses, and the initial calibration values ​​can be stored within unit 20. In one variant, the initial calibration can be determined by collecting data on the sensor sensitivity over time to track the rate of sensitivity reduction. Based on this information, a linear or nonlinear model reflecting the sensitivity drift over time can be developed, and this model can be used to compensate for the time-varying sensitivity drift. For example, if it is known that the sensor sensitivity will decrease by a certain percentage, such as 5% per year, the processor can automatically apply a correction factor for the percentage of degradation, for example within unit 20, to adjust the measured steady-state value by 5% to address the sensor degradation.

[0058] The transient response can be calibrated by exposing the sensor to known gas concentration changes, and the parameters in the model that convert the sensor voltage output can be fitted to the shape of the gas concentration curve, such as... Figure 3A and Figure 3B The calibration curve 66 is shown in the figure. The shape of the concentration-time curve (e.g., a step response from one concentration to another) needs to be known in advance; however, the gas concentration value does not need to be known, as the model may be suitable for a steady-state response calibrated separately.

[0059] During user operation, users may not typically have access to a CO source with a known concentration for steady-state calibration purposes. Therefore, the user can be instructed to perform a breathing test, whereby they hold their breath for, for example, 10 seconds or longer, to allow the CO concentration in their bloodstream to equalize with the concentration in the alveoli of their lungs. The gas in their mouth and trachea may have a lower CO concentration, so when the user exhales into sampling unit 20, the gas sensor may see a steady increase in CO concentration until the air in the mouth and trachea is depleted, at which point the CO gas concentration seen on the sensor is nearly constant or almost constant until the breathing ends. When the user stops exhaling, the CO gas concentration at the electrochemical sensor returns to the concentration in ambient air due to diffusion.

[0060] Figure 4Examples of eCO and eCO exhalation graphs measured from breath samples obtained from healthy occasional smokers before smoking (19 hours after their last cigarette) and 15 seconds after smoking are shown in eCO graphs 70 and 72. The corresponding eCO exhalation graph 74 shows the values ​​corresponding to eCO graph 70, and eCO exhalation graph 76 shows the values ​​corresponding to eCO graph 72, illustrating how the measured eCO values ​​begin to reach a steady state some time after the user begins exhaling and then fall back to ambient levels in the transient response.

[0061] In some variations, during the aforementioned breath test, the user can be instructed to inhale through the device after exhaling into it while holding their breath, so that the gas level within unit 20 returns to ambient levels. The rate of concentration equalization can be adjusted through design aspects of the breath sensor unit 20, such as the device's size, flow path constraints, proximity of the sensor to the vent, and the rate at which the sensor consumes CO. These values ​​may be consistent across devices of the same model; however, the user can also influence the rate of gas concentration equalization with the environment. For example, the user can block the vent to reduce the equalization rate, or gently shake or inhale through the device to increase the equalization rate.

[0062] Based on the drop in CO concentration from a near-constant measured value (near the end of the user's exhalation) back to the ambient value, a transient time constant characterizing the response to the measured drop can be calculated, and this calculated time constant value can indicate the degree of sensor degradation. This time constant can then be used to calculate the corrected eCO measurement when the user exhales a breath sample into unit 20 for measurement.

[0063] Figure 5 A flowchart illustrating how a time constant is calculated for sensor calibration is shown, as described above. Initially, (e.g., via sampling unit 20) the user 80 may be instructed to hold their breath for, for example, 10 seconds or longer, to allow the CO concentration in the bloodstream to equalize with the concentration in the alveoli of their lungs. The user 82 may then be instructed to blow a breath sample into the device to allow the CO concentration in the sample to approach a constant concentration until the exhalation ends. When the user stops exhaling, the CO gas concentration at the electrochemical sensor will return to the concentration in ambient air due to diffusion, or the user may be further instructed to facilitate CO diffusion within the device back to ambient levels. In either case, a transient time constant 84 may be determined based on the decrease in CO concentration from near-constant to ambient levels. This time constant is then used to calibrate the sensor 86 to calculate a corrected eCO measurement when the user exhales a breath sample into unit 20 for measurement.

[0064] Since users may influence the response speed, as described (e.g., covering the vent to reduce gas diffusion speed, shaking the sensor to increase diffusion speed, etc.), several transient response times can be stored for evaluation, and the stored response times can be evaluated against certain criteria. For example, the current calibration value for the response speed can be used in a model that assumes a step response of gas concentration from the user's inhalation concentration to the ambient air concentration. If the lowest response speed in the stored data is lower than the value created by the model, the calibration parameter can be reduced to the lowest value in the stored data.

[0065] Another evaluation criterion could be to use the current calibration value for the response speed in the model with the highest response speed, which assumes all sensor vents are blocked. If the highest response speed in the stored data is higher than the value created by the model, the calibration parameters can be changed to the highest value in the stored data.

[0066] Another evaluation criterion could be to create a model for each combination of user actions that might affect the concentration equalization speed. If any model has a unique waveform that matches the concentration equalization waveform, the calibration parameters can be updated based on that model.

[0067] If all responses in the stored data are higher than the calibration value, another evaluation criterion may include slightly increasing the calibration value.

[0068] For assigning initial sensitivity, this may include batch testing that may not allow for evaluation of initial transient response rate parameters. In such batch testing scenarios, a default transient response rate parameter at the population level can be determined through pre-production and continuous testing, and this parameter can then be updated over time.

[0069] Sensor stability mode

[0070] For the various types of electrochemical sensors that can be used with sampling unit 20, different types of sensors may exhibit different stability modes. Each of the various sensor stability modes is described in each of the following sections.

[0071] Example 1

[0072] This type of sensor can have a time-stable sensitivity, but the stabilization rate may drift. During manufacturing, both sensitivity and stabilization rate can be calibrated by exposing the sensor to a step function change in gas concentration. Calibration parameters are stored on the device and used to calculate the CO level corresponding to the sensor voltage output. The sensor within sampling unit 20 can be provided to a user, who can then begin use by providing a breath sample. The stabilization rate parameters can be periodically recalibrated using the user's breath sample. Here, it can be assumed that the gas concentration at the end of the breath sample is in a steady state. When the user stops exhaling, the sensor may see a step response from the user's CO concentration to the carbon monoxide concentration in the ambient air.

[0073] Example 2

[0074] This type of sensor can have time-stable sensor sensitivity and stabilization speed, with minimal variability within the device. During device development, sensitivity and stabilization speed can be calculated by exposing the respiratory sensor to a step function change in gas concentration. Since calibration is not required on a per-device basis, sensitivity and stabilization speed parameters from device development can be pre-loaded into the device, and calibration parameters can also be stored on the device and used to calculate the CO level corresponding to the sensor's voltage output.

[0075] Example 3

[0076] This type of sensor can have time-stable sensor sensitivity and stabilization speed. During manufacturing, both the sensor's sensitivity and stabilization speed can be calibrated by exposing the breath sensor to a step function change in gas concentration. Calibration parameters can be stored on the device and used to calculate the CO level corresponding to the sensor's voltage output. Alternatively, the stabilization speed can be calibrated once using a user's breath sample.

[0077] Example 4

[0078] This type of sensor can have a sensitivity pre-provided by the supplier, but the stabilization rate may vary from device to device. During manufacturing, the sensitivity parameters can be programmed into the device using values ​​provided by the gas sensor manufacturer. The stabilization rate parameters can be initialized using estimates obtained during device development, and the stabilization rate can be calibrated using user breath samples.

[0079] Example 5

[0080] This type of sensor can have a consistent sensitivity within a manufacturing batch, but the steady-state speed may vary from device to device. During manufacturing, the sensitivity parameters can be programmed into the device using values ​​provided by calibration from one or more sensors from the manufacturing batch. The steady-state speed parameters can be initialized using values ​​calculated by the calibration unit or using estimates obtained during device development, and the steady-state speed can be calibrated using user breath samples.

[0081] Example 6

[0082] This type of sensor can have sensor sensitivity and / or stabilization rate that vary consistently over time across devices. During manufacturing, the sensitivity and / or stabilization rate parameters can be programmed into the sampling device along with a timestamp corresponding to the calibration date. A sensor drift model can also be loaded onto the device. Before using the calibration parameters to calculate the CO concentration from the sensor output, the parameters can first be adjusted based on the model using an aging factor, as described in Example 1 above. Figure 6 As shown in the figure. As described above, an aging factor can be applied to the sensor calibration as shown in the figure before determining sensor drift. Optionally, the sensor drift model can be updated and deployed to the user's sensor via wireless options using any number of wireless protocols.

[0083] The aging factor can be applied to situations where a decrease in sensor response is known or experimentally verifiable. For example, it can be generally assumed that sensor sensitivity may decrease, for instance, by 2% to 5% per year, depending on storage conditions. Under typical storage conditions used in warehouse environments, a decrease in sensor sensitivity of, for example, 3% per year can be assumed. For instance, a device calibrated a year ago might have given a 200mV sensor response signal for a CO level of 50 ppm, while a current user providing a breath sample might generate a 100mV response signal associated with a CO level of 25 ppm. However, due to sensor degradation over the past year, the 25 ppm value might have increased by 3% (or some other percentage), thus increasing the CO level to 25.75 ppm, which can be rounded to 26 ppm.

[0084] Aging factors can be empirically determined by setting up a sufficient number of device groups under different conditions, testing them periodically, and then performing multivariate regression analysis to determine the impact of each component (e.g., temperature, humidity, time). Temperature and humidity can be further subdivided into multiple ranges to provide a quick reference for determining the degradation rate. For example, the table below shows examples of sensor degradation rates induced within a given temperature and relative humidity range:

[0085] Table 1. Sensor degradation with temperature and relative humidity (RH) .

[0086] temperature 15% to 35% RH 35% to 85% RH 12℃ to 26℃ 4% per year 2% per year 26℃ to 40℃ 8% per year 3% per year

[0087] Generally, lower storage temperatures (e.g., ≤26°C) and lower relative humidity (e.g., ≤35%RH) lead to a relatively higher rate of degradation, while lower storage temperatures (e.g., ≤26°C) and higher relative humidity (e.g., ≥35%RH) lead to a relatively lower rate of degradation. Similarly, higher storage temperatures (e.g., ≥26°C) and lower relative humidity (e.g., ≤35%RH) lead to a relatively higher rate of degradation, while higher storage temperatures (e.g., ≥26°C) and higher relative humidity (e.g., ≥35%RH) lead to a relatively lower rate of degradation. However, since the effects of temperature and humidity are separable, these effects can also be summarized as relatively higher storage temperatures potentially leading to a relatively higher rate of degradation, while relatively lower storage temperatures potentially leading to a relatively lower rate of degradation. Likewise, relatively lower relative humidity potentially leading to a relatively higher rate of degradation, while relatively higher relative humidity potentially leading to a relatively lower rate of degradation. If a sufficient number of data points are available, a continuous distribution can be generated.

[0088] Example 7

[0089] This type of sensor can have sensor sensitivity and / or stabilization speed based on changes in environmental conditions over time. As mentioned above, during manufacturing, sensitivity and / or stabilization speed parameters can be programmed into the sampling device along with a timestamp corresponding to the calibration date. A sensor drift model can also be loaded onto the device. In this variant, sampling unit 20 can be combined with an environmental sensor package that can independently measure parameters included in the sensor drift model, such as temperature and relative humidity. The environmental sensor package can periodically measure these parameters and instantaneously correct and update calibration parameters and / or record and store parameters for use in calculating calibration parameters during use.

[0090] Before calculating the gas concentration from the sensor output using calibration parameters, the parameters can first be adjusted using an aging factor, as described above. Optionally, the sensor drift model can be updated and deployed to the user's sensor via wireless updates.

[0091] Self-calibration

[0092] Another variation for calibrating the sensor may include a sampling unit 20 configured to self-calibrate its transient sensor performance. While the sensor may generally be stable, its stabilization rate may vary over time. Therefore, factory calibration of both sensitivity and stabilization rate can be combined with periodic recalibration of sensitivity rate based on a heuristic clearing model to improve the sensor's transient performance.

[0093] Although illustrative examples have been described above, it will be apparent to those skilled in the art that various changes and modifications can be made therein. Furthermore, the various devices or procedures described above are also intended to be used in combination with each other, if practically feasible. The appended claims are intended to cover all such changes and modifications that fall within the true spirit and scope of the invention.

Claims

1. A respiratory sensor device, comprising: A sampling unit having a housing configured to receive a breath sample from a user; A sensor, positioned within the housing and in fluid communication with the respiratory sample when received within the housing; The processor is electrically connected to the sensor. The processor is configured to determine the dissipation time when the sensor is exposed to CO levels that decrease from near a constant concentration detected in the breath sample to ambient levels. The processor is further configured to calculate a time constant based on the dissipation time and the decrease from the near-constant concentration level to the environmental level; and The processor is further configured to apply the time constant to the transient response of the sensor to address drift during sensor calibration.

2. The apparatus of claim 1, wherein the processor is further configured to apply an aging factor to the sensor prior to calculating the time constant to address sensor degradation over time.

3. The apparatus of claim 2, wherein the aging factor depends on the sensor being exposed to temperature and humidity over a period of time.

4. The apparatus of claim 3, wherein the aging factor ranges from 2% to 5% per year.

5. The apparatus of claim 1, wherein the processor is configured to calibrate the sensor to address drift during both transient and steady-state responses.

6. The apparatus of claim 1, wherein the processor is further configured to provide instructions to the user to hold their breath for a predetermined period of time before exhaling the breath sample.

7. The apparatus of claim 6, wherein the processor is further configured to provide instructions to the user to dissipate the respiratory sample from the sensor.

8. A method for calibrating a sensor, comprising: Receive breath samples from the user until the sensor detects a near-constant concentration level of CO in the breath sample; Determine the length of time it takes for the near-constant concentration level of CO to dissipate to the ambient level of CO. The time constant is calculated based on the time length and the decrease from the near-constant concentration level to the environmental level; as well as The sensor is calibrated to resolve drift by applying the time constant to the sensor's transient response.

9. The method of claim 8, further comprising applying an aging factor to the sensor before calculating the time constant to address sensor degradation over time.

10. The method of claim 9, wherein the aging factor depends on the sensor being exposed to temperature and humidity over a period of time.

11. The method of claim 10, wherein the aging factor ranges from 2% to 5% per year.

12. The method of claim 8, further comprising calibrating the sensor to address drift in the steady-state response.

13. The method of claim 8, wherein receiving the respiratory sample comprises receiving the respiratory sample into a sampling unit, wherein the sensor is positioned in the sampling unit.

14. The method of claim 8, wherein receiving the breath sample further comprises instructing the user to hold their breath for a predetermined period of time before exhaling the breath sample.

15. The method of claim 14, further comprising instructing the user to dissipate the breath sample from the sensor.

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