Method for complex waveform detection and identification of chemical odors and odor mixtures

Abstract

The method includes, for example in one embodiment, exposing an odorant to a sensor array having a first sensor and a second sensor respectively configured with a first response characteristic and a different second response characteristic. In one embodiment, in response to the odorant, the first sensor outputs a first sensor signal having a signal-time characteristic and the second sensor outputs a second sensor signal having a different signal-time characteristic due to the different second response characteristic. In one embodiment, the method includes generating a signal having a complex waveform shape corresponding to the odorant, and optionally to a concentration of the odorant, using the first sensor signal and the second sensor signal. The generating includes, for example in one embodiment, converting the first sensor signal and the second sensor signal into respective sensor signal modulated oscillatory signals, and combining the sensor signal modulated oscillatory signals.

Description

Cross-references to related applications

[0001] This application claims the benefit of U.S. Provisional Application 63 / 545,388, filed October 24, 2023, the entire contents of which are incorporated herein by reference. background Technical Field

[0002] The present invention generally relates to the detection and identification of chemical odors and odor mixtures, and more specifically, to the detection and identification of different odors and / or odor mixtures based on an electronic nose. Background Technology

[0003] Devices commonly referred to as "electronic noses" or "e-nose" use gas sensors that output electrical signals whose levels indicate the concentration of certain chemical vapors. These signals are then used to detect and identify specific odors. However, current electronic odor detection and identification technologies have limitations. Part of this limitation stems from the fact that, while current gas sensors can generate signals in response to millions of different chemical substances, another limitation remains: unlike the signal output of optical sensors (which can be characterized by spectral bands of color such as orange, yellow, green, blue, indigo, and violet), there is currently no known "odor spectrum" for characterizing or classifying the output of gas sensors.

[0004] One example of these shortcomings is that current odor recognition and classification technologies may lack selectivity for certain applications, which could be a problem for odor recognition in a broader sense.

[0005] Another drawback of current odor classification technology is its insufficient precision and resolution when detecting certain odor mixtures and aromas (such as those emitted by certain natural substances like coffee beans and other foods and beverages). Another drawback is its insufficient precision in identifying or classifying certain qualities of odors, where the nature of those qualities may change over time. This drawback may occur, for example, in relation to food freshness. Yet another drawback of current odor sensing and classification technology is the lack of a unique correspondence between sensor output levels and odor concentration; that is, a specific output level of a sensor does not necessarily indicate a specific concentration of a particular odorant.

[0006] Therefore, there is a need for improved electronic odor detection and identification methods and systems. Summary of the Invention

[0007] This "Summary" identifies exemplary features and aspects, but is not an exclusive or exhaustive description of the disclosed subject matter. It should be understood that the inclusion or omission of a feature or aspect in this "Summary" is not intended to indicate its relative importance. Other features and aspects will be described in the following detailed description and the accompanying drawings, which form part of this document.

[0008] The systems and methods according to various embodiments offer numerous features and advantages, including the novel generation of complex waveform electrical characteristics in response to and corresponding to different unique odors and odor mixtures. According to one or more embodiments, this novel generation can produce complex waveform electrical characteristics that are unique to both odor and odor concentration.

[0009] An example system according to one or more embodiments may include a first odor sensor and a second odor sensor, which are respectively configured to convert the process of exposure to an odorant into an electrical signal, and the electrical signals respectively exhibit different electrical response characteristics.

[0010] An example system according to one or more embodiments may also include a complex waveform generation resource (e.g., circuitry or processing logic or a combination of both), which is configured to generate a complex waveform using both a first oscillation signal modulated by a first sensor and a second oscillation signal modulated by a second sensor.

[0011] The method according to one or more embodiments has the following novel features: generating complex waveform features in response to different odorants; providing complexity through the combination of features, which include: exposing the odorant to two or more sensors that produce different electrical responses to the odorant, then converting these different electrical responses into corresponding oscillating signals of different morphologies, and then forming complex features by combining these oscillating signals of different morphologies.

[0012] The system according to one or more embodiments may further include conversion or translating resources (e.g., circuitry or processing logic, or a combination of both) configured to convert a first sensor signal into a first oscillation signal modulated by the first sensor, and to convert or translate a second sensor signal into a second oscillation signal modulated by the second sensor. According to one or more embodiments, the conversion or translating may include: generating a first frequency carrier signal and a second frequency carrier signal, modulating the first frequency carrier signal using the first sensor signal, and modulating the second frequency carrier signal using the sensor signal. In one or more embodiments, the modulation may be, for example, but not limited to, amplitude modulation.

[0013] The steps in an example method according to one or more embodiments may include: a sensor array including at least a first sensor and a second sensor, the sensor array being configured to have different electrical response characteristics, receiving an odorant at an increased concentration, and the sensors respectively responding to output a first sensor signal and output a second sensor signal. Further according to one or more embodiments, the first sensor signal may exhibit a first signal-time characteristic and is at least partially based on a difference between the first and second electrical response characteristics, which may differ from each other. The shape may differ from the first signal-time shape, at least partially based on the odorant type combined with the difference between the second and first electrical response characteristics. The steps in the method process may also include generating a complex waveform signal, which may be at least partially based on both the first and second sensor signals and may have a complex waveform shape, which is at least partially based on both the first and second signal-time shapes, thereby serving as a complex waveform feature of the odorant.

[0014] An example system according to one or more embodiments is capable of generating complex waveforms corresponding to odors, characterized by comprising: a sensor array having at least two sensors, wherein a first sensor of the at least two sensors is configured with a first electrical response characteristic relative to the sensing response of the first sensor to at least one target odorant, and the first sensor is configured to output a first sensor output signal in response to exposure to the target odorant, the first sensor output signal having a first change in a time-dependent characteristic, the first change in a time-dependent characteristic being at least partially based on the target odorant and the first electrical response characteristic. The system may further comprise: a second sensor of the at least two sensors configured with a second electrical response characteristic relative to the sensing response to at least one target odorant, and the second sensor is configured to output a second sensor output signal in response to exposure to the target odorant, the second sensor output signal having a second change in a time-dependent characteristic, the second change in a time-dependent characteristic differing from the first change in a time-dependent characteristic by a difference at least partially based on the target odorant and a difference between the first and second electrical response characteristics. The system may further include: a processor programmed to: modulate a first oscillation signal using a first sensor output signal to generate a first oscillation signal modulated by the first sensor signal, modulate a second oscillation signal using a second sensor output signal to generate a second oscillation signal modulated by the second sensor signal, and combine the first oscillation signal modulated by the first sensor signal and the second oscillation signal modulated by the second sensor signal to form a complex waveform corresponding to the odorant.

[0015] Further features and benefits may include, but are not limited to: a processing block or step configured to compare a complex waveform signal generated in response to an unknown odorant or odorant mixture with a stored reference database of complex waveform features for “best match” identification of the odor or odor mixture.

[0016] Furthermore, according to one or more embodiments, the step or processing block for generating complex waveform features that are unique to different odors and odor mixtures can be configured to place these features within a bandwidth that is audible to humans. Attached Figure Description

[0017] The nature and advantages of the embodiments can be further understood by referring to the following figures. It should be understood that these figures show illustrative rather than limiting examples. It should also be understood that the graphics in the figures have been scaled for readability, and the graphical representations of functions and features need not be drawn at a scale consistent with their physical implementation. Furthermore, similar components or features may have the same reference numerals in the figures.

[0018] Figure 1 A functional block diagram of an example system according to one or more embodiments is shown. The system is used to generate corresponding complex waveform features in real time in response to different odors and / or odor mixtures by using novel generation and combination of oscillating signals modulated by multiple sensor signals, each feature being unique to the sensed odor and / or odor mixture.

[0019] Figure 2 A functional block diagram of another example system according to one or more embodiments is shown, which uses an exemplary number of sensors to modulate a greater number of fundamental frequencies to generate complex waveform features in real time that correspond to and are unique to different odorants and / or odorant mixtures.

[0020] Figure 3 A graphical illustration of the operation of generating and combining multiple oscillating signals is shown, and according to various embodiments, these operations can be used to provide complex waveform characteristics that are unique to different odorants and / or odorant mixtures.

[0021] Figure 4 A functional block diagram of another example system according to one or more embodiments is shown, which uses novel generation and combination of oscillating signals modulated by multiple sensors to provide real-time generation of different complex waveform features that are unique to different odorants and / or odorant mixtures, and is further characterized by configuring a reference complex waveform database for odorant identification and classification.

[0022] Figure 5A functional block diagram of another example system according to one or more embodiments is shown, which provides the generation of oscillating signal frequencies modulated by multiple sensors with complex waveform characteristics, and further features complex feature-based audio notifications or alarms in response to one or more specific odorants and / or odorant mixtures.

[0023] Figure 6 A schematic diagram of a functional block for an example of a multi-gas sensor amplitude modulation (AM) frequency configuration for system or method operation according to one or more embodiments is shown. This multi-gas sensor AM frequency configuration is used to generate complex waveform features that are unique to different odorants and / or odor mixtures in real time.

[0024] Figure 7 A schematic diagram of the functional modules of an example computer system configured to provide system logic and perform processing steps according to one or more of the disclosed embodiments is shown.

[0025] Figure 8 It shows that according to Figure 6 A circuit schematic diagram of the hardware implementation of one or more systems of a functional module.

[0026] Figure 9 A photograph is shown of a hardware prototype implementation of an example system according to one or more embodiments, which has been built and tested by the inventors, for generating different complex waveform features that correspond to and are unique to different odors and / or odor mixtures.

[0027] Figure 10 The graph shows the source Figure 9 The observation signals of the prototype system tested by the inventors are in response to presenting the same odor to the first and second sensors of the system. The signals include: (i) amplitude modulation of the first sensor signal at a first channel frequency, (ii) amplitude modulation of the second sensor signal at a second channel frequency, and (iii) complex waveform features generated by combining the two amplitude modulation channel frequencies.

[0028] Figure 11 Three independent signal level-time curves are graphically displayed on a two-dimensional (2D) signal level-time graph, showing the inventors' measurements of the output from a commercial off-the-shelf (COTS) NH3 sensor, a COTS CO(RED) sensor, and a COTS NO2 (oxygen or "OX") sensor in response to exposure to different concentrations of ethanol vapor.

[0029] Figure 12The signal level-time curves are graphically displayed on a two-dimensional (2D) signal level-time graph, showing the outputs measured by the inventors from the COTS NH3 sensor, COTS CO(RED) sensor, and COTS NO2(OX) sensor in response to sequential exposure of the sensors to ethanol, citral (C10H16O), Windex™ glass cleaner, and phenylethanol (PEA).

[0030] Figure 13 The diagram graphically illustrates some of the generated signal operations and amplitude-time plots during the process of generating complex waveform characteristics that are unique to a selected concentration of Listerine™ vapor according to one or more embodiments. The operations include: exposing the vapor to NO2 (OX), CO (RED), and NH3 sensors; using the resulting sensor outputs to amplitude modulate the corresponding frequencies to generate AM modulation frequencies; and combining these AM modulation frequencies to generate complex waveform characteristics.

[0031] Figure 14 It is illustrated graphically as similar to Figure 13 The signal operation and amplitude-time curves generated in the process are shown. According to one or more embodiments, the process uses multiple generated AM modulation frequencies to generate corresponding complex waveform characteristics that are unique to a selected concentration of ethanol.

[0032] Figure 15 It shows Figure 14 The graph is overlaid with a representation of the test equipment, and a magnified view of the complex waveform features is also shown.

[0033] Figure 16 The complex waveform characteristics of Listerine™ vapor and ethanol vapor at specific concentrations generated by a prototype constructed according to one or more embodiments are illustrated graphically.

[0034] Figure 17 Illustrative examples are shown of how a complex waveform feature is generated by a multi-sensor frequency-modulated oscillation signal based on one or more embodiments. Detailed Implementation

[0035] This disclosure provides novel and improved techniques for detecting, identifying, classifying, and quantifying odors. Systems and methods according to various embodiments, combined with other elements and aspects, are characterized by novel processes comprising: exposing an odorant or a mixture thereof to multiple gas sensors of different configurations; generating multiple sensor-modulated oscillations based on the outputs of the multiple sensors; and then combining these sensor-modulated oscillations to create a corresponding complex waveform feature that can be unique for each odor or odor mixture.

[0036] As used in this disclosure, the terms “sensor,” “gas sensor,” and “odor sensor” have the same meaning and can be used interchangeably without changing their meaning.

[0037] The term “electrical response characteristics” and its abbreviation “ER characteristics” as used in the context of describing or referring to the sensor shall be understood to refer to: a specific change in the electrical output signal of the sensor relative to time characteristics in response to the sensor receiving an increase in the concentration of an odorant to which the sensor is sensitive, and it should be understood that “characteristics” include transient signal-time characteristics and steady-state signal-time characteristics.

[0038] As used in this disclosure, "odor" includes smells or aromas caused by the vapor or gaseous state of a physical substance (e.g., a compound) carried by the surrounding atmosphere.

[0039] As used herein, “odorant” refers to molecules or particles in the air that produce or exhibit a corresponding odor at least at a threshold concentration.

[0040] As used in this article, “volatility” refers to the tendency to evaporate at room temperature, where “evaporation” refers to a phase transition from a liquid or solid state to a gaseous state without any substantial change in the molecules themselves.

[0041] An example system according to one or more embodiments may include at least two different sensors, where "different" means having different ER characteristics relative to at least one odor or combination of odors. One example configuration of "at least two different sensors" includes, but is not limited to, a combination of at least one first sensor (having a first ER characteristic relative to a first target odorant) and a second sensor (having a second ER characteristic relative to the first target odorant). Another example configuration of "at least two different sensors" may include, but is not limited to, a combination of at least one first sensor (having a first ER characteristic relative to a first target odorant), a second sensor (having a second ER characteristic relative to the first target odorant), and further, a third sensor, which, for example, has a third ER characteristic relative to the first target odorant, or is, for example, a replica of the first sensor in terms of sensor functionality.

[0042] It should be understood that, as used in this disclosure, "sensor array" refers to a plurality of sensors arranged in a spatially distributed manner, and unless expressly described or otherwise stated to the contrary, such arrangement is not intended to, nor implies, any limitation on a spatial pattern or mode, nor does it limit any spatial pattern or mode or any arrangement.

[0043] According to one or more embodiments, the sensor array can be supported within a structure configured to enclose a volume, which may be referred to as the "internal volume" for the purposes of description. In one or more embodiments, the housing may be configured to have, for example, an inlet for entering the internal volume and an outlet for exiting the internal volume for flow purposes.

[0044] According to one or more embodiments, the spatial distribution and arrangement of sensors in the sampling space can ensure that when an odor is to be analyzed, all sensors can be exposed to the odor simultaneously, and the concentration of the odorant remains constant throughout the sampling space.

[0045] In one or more implementation schemes, a single sensor may be used, for example, to establish a single corresponding waveform as a reference.

[0046] In some implementations of systems and methods according to one or more embodiments, it is preferable to configure two or more sensors in a plurality of sensor arrays to have different respective detection characteristics. For example, one sensor in the array is configured to detect NH3, another sensor is configured to detect CO2, and so on. Alternatively or additionally, multiple identical sensors may exist in the array for purposes including, but not limited to, operating as controls, for example, by comparing the signals of nominally identical sensors. Another purpose or benefit of including multiple identical filters in the array is to correspondingly obtain the option to selectively apply different modifications to different identical sensors, for example, by connecting different filters, as described in more detail in later paragraphs.

[0047] Each sensor can be configured to detect and respond to at least one molecule or group of molecules (one or more odor stimuli) sharing certain chemical properties in vapor form, which may be referred to herein as “target vapor,” “target molecule,” “target odor molecule,” “target vapor molecule,” etc. Therefore, it should be understood that the term “non-target vapor” as used herein can be any collection of airborne molecules or particles that do not significantly affect the response or behavior of the sensor array. Thus, a “target vapor” can be a pure vapor containing multiple molecules all having the same chemical formula, or a mixed vapor containing multiple molecules with different chemical formulas, the combination of which produces a sensor array response different from that produced by a sensor array response to one or more chemical formulas presented individually. A group of target molecules may share, for example, similar binding / ligand properties or diffusion rates through filters. When target molecules interact with the sensor surface, they alter the sensor’s conductivity and change the amount of current detected.

[0048] Each sensor or group of sensors in the sensor array can be configured to be sensitive only to a specific target vapor. In one embodiment, the sensor array may include multiple groups of one or more sensors, each group being configured to detect a different vapor. Alternatively, each sensor may be sensitive to multiple or a range of vapors.

[0049] In implementations according to various embodiments, one or more sensors can be configured to be selective for a specific target vapor by, for example, placing a target-selective pass-through filter (e.g.) above the sensor's detection layer. This target-selective pass-through filter can operate, for example, by preventing vapors of chemical components other than the target vapor from reaching the sensor's detection layer. Installing and removing such filters can be used to modify the sensor's selectivity. For example, all sensors in an array, or a section or portion of sensors in an array, can include identical sensors that can be selectively or optionally modified to each include different filters to distinguish different vapors. In such implementations, each filter can differentially affect the passage or flow of molecules through the filter, for example, by active regulation or alternatively by passive regulation (e.g., absorption or diffusion of different vapor molecules at different rates). Therefore, each sensor can have different responses / sensitivities to the same vapor molecules. Consequently, one or more originally identical sensors can produce different response profiles for a given vapor. These different response profiles can correspondingly be associated with a unique odor fingerprint.

[0050] According to one or more embodiments, multiple sensors can be configured to output analog signals. Thus, an array of sensors with different sensitivity characteristics can output multiple different analog signals in response to receiving a specific odorant or odorant mixture, each sensor's analog signal having its own amplitude and exhibiting a change in its amplitude relative to time, which is related to or corresponds to the sensor's sensitivity to that odorant or odorant mixture. According to one or more embodiments, the respective analog output signal of each of two or more sensors can be converted into its own domain waveform before being combined with n, thereby generating multiple initial waveforms. The multiple initial waveforms are then combined to generate a domain complex waveform feature corresponding to the detected odor or odor mixture.

[0051] Figure 1 A schematic diagram of functional modules of an example system 100 according to one or more embodiments is shown. The system 100 can provide complex waveform characteristics for a variety of different odors and / or odor mixtures or both by means of functional modules configured to convert multiple gas sensor signals into corresponding sensor modulated oscillation signals and functional modules configured to combine these sensor modulated oscillation signals.

[0052] refer to Figure 1 System 100 may include a first sensor 102-1 and a second sensor 102-2. According to one or more embodiments, the first sensor 102-1 may be configured to be sensitive to gaseous or vapor molecules of substances (e.g., compounds) within a first group or list, while the second sensor 102-2 may be configured to be sensitive to gaseous or vapor molecules of substances within a second group or list. For illustrative purposes, the molecules within the first group or list will be alternatively referred to as "first target molecules," and the molecules within the second group or list will be alternatively referred to as "second target molecules." According to various embodiments, the first sensor 102-1 and the second sensor 102-2 may be disposed within a housing 103, within a closed internal volume 103-V. According to one or more embodiments, the housing 103 may be provided with a first opening or first air passage 103-A and a second opening or second air passage 103-B to allow, for example, odorant vapor to flow from outside the housing 103 into the internal volume 103-V and outwards. Optionally, according to one or more embodiments, the first air passage 103-1 and the second air passage 103-2 may be provided with selectively actuated open-closed channel covers or louvers, which may be controlled, for example, but not limited to, via computer-generated commands, user interface actuated buttons, or equivalents. It should be understood that, according to one or more embodiments and in various applications, the housing 103 may be omitted.

[0053] According to one or more embodiments, the first sensor 102-1 may be configured with a first electrical response characteristic, and the second sensor 102-2 may be configured with a second electrical response characteristic different from the first electrical response characteristic.

[0054] Figure 1 The amplitude-time form of an example signal of the first sensor signal "GS1(t)" and an example signal of the second sensor signal "GS2(t)" are illustrated graphically. According to one or more embodiments, system 100 may include a first oscillation signal generator 104-1 modulated by the first sensor signal, which may be configured to receive the first sensor signal and, in response thereto, generate a first oscillation signal or a first frequency modulated by the first sensor signal according to the following formula (1), for example... Figure 1 Instance MB1(t) in:

[0055] MB1 (t) = GS1 (t) • SG(ω1(t)) Formula (1)

[0056] in,

[0057] SG can be, for example, a sine function or a cosine function, and

[0058] ω1 can be, for example, radians per second.

[0059] System 100 may further include a second oscillation signal generator 104-2 modulated by a second sensor signal, which may be configured to receive the second sensor signal and, in response thereto, generate a second oscillation signal or frequency modulated by the second sensor signal. According to one or more embodiments, the second oscillation signal generator 104-2 may be configured to generate a second oscillation signal modulated by the second sensor signal as a second oscillation signal modulated by the amplitude of the second sensor signal, according to formula (2), for example... Figure 1 Instance MB2 (t) :

[0060] MB2 (t) = GS2 (t) • SG(ω2 (t) ) Formula (2)

[0061] Where ω2 can be, for example, radians per second.

[0062] According to each implementation scheme, the SG function of formula (2) can be the same as the SG function of formula (1). For example, both can be sine functions.

[0063] System 100 may also include combiner 106, which can combine MB1 (t) and MB2 (t)To generate complex waveforms, such as the instance CSS(t) shown in the figure, for example, by summing using the following formula (3):

[0064] CSS (t) = MB1 (t) + MB2 (t) Formula (3)

[0065] Figure 2 A functional block diagram of another example system 200 according to one or more embodiments is shown, which uses a greater number of gas sensors to modulate a greater number of oscillation signals or frequencies to generate complex waveform features in real time that correspond to and are unique to different odorants and / or odorant mixtures. Figure 2 The system 200 achieves a greater number of gas sensors by adding a third sensor 202-1 and up to the Nth sensor 202-N (collectively referred to as “sensor 202” for descriptive purposes).

[0066] The third sensor 202-1 can be configured with a third electrical response characteristic, up to the Nth sensor 102-N being configured with an Nth electrical response characteristic.

[0067] Based on the electrical response characteristics of sensor 202, in response to exposure to one or more odorants of a group or series of odorant types, each sensor outputs a corresponding sensor signal, as detailed below for the third sensor signal MB3(t):

[0068] MB3 (t) = GS3(t) • SG(ω3t) Formula (3)

[0069] MBN (t) = GSN(t) • SG(ω N Formula (4)

[0070] Among them, ω3 and ω N Each can be, for example, radians per second.

[0071] As described above for formulas (1) and (2), according to each implementation scheme, the SG functions of formulas (4) and (3) can be the same as each other and can be the same as the SG functions of formulas (1) and (2).

[0072] Figure 3The illustration schematically depicts some aspects and operations of one or more embodiments of generating complex waveforms in response to different odorants and their mixtures by generating multiple different frequencies (e.g., in the example shown, multiple frequencies include a first frequency carrier 302-1, a second frequency carrier 302-2, and a third frequency carrier 302-3, collectively referred to herein as "carrier 302"). The operation also includes 304 combining these different frequency carriers to generate a sum of multiple different frequencies, in this example, an integer three. Figure 3 The examples are simplified because the combination (e.g., summation) is performed on an unmodulated oscillating signal. Figure 3 The example configures the carrier 302 as an unmodulated sine wave according to, for example, formulas (5), (6) and (7).

[0073] F1 (t) = M1·sin(ω4 t ) Formula (5)

[0074] F2 (t) = M2·sin(ω5 t ) Formula (6)

[0075] F3 (t) = M3·sin(ω6 t ) Formula (7)

[0076] in,

[0077] M1, M2, and M3 can be scalar weights; they can be equal to each other but are not necessarily equal.

[0078] ω4, ω5, and ω6 can be, for example, radians per second.

[0079] The 304 combination that forms the complex waveform FC(t) can be used to convert F1 according to the following formula (8). (t) F2 (t) and F3 (t) through Pass Combine the summation operations.

[0080] FC (t) = F1 (t) + F2 (t) + F3 (t) Formula (8)

[0081] refer to Figure 1 and Figure 2The generation of the described complex waveform features varies depending on the odor or the chemical substance. Therefore, these complex waveform features can be used to identify an unknown odor sample based on, for example, comparing a unique feature with existing known (control) features in a database. Thus, systems such as System 100 or System 200 may include a database of previously acquired digital images of complex waveforms corresponding to known vapors and vapor mixtures, and methods for identifying unknown odor agents include the step of performing a best-match comparison between existing, predetermined complex waveforms of known vapors to identify the sample (e.g., unknown) vapor.

[0082] Various embodiments may further include processing resources and procedures for establishing and storing a database of complex waveform features. The complex waveform database may be generated, for example, by performing the steps of one or more of the methods described above, but using samples of known odorants. Optionally, according to various embodiments, various “blank” or other control waveforms may be stored together with or separately from instances of known odorants.

[0083] Building the database can further include performing data acquisition using the same odorant but at different concentrations. In this way, unique, complex waveforms can be generated for each of the many different concentrations of the odorant and included in the database.

[0084] Figure 4 A schematic diagram of the functional modules of an example system 400 according to one or more embodiments is shown. The system 400 is used to generate different complex waveform features in real time using novel generation and combination of multiple sensor modulation frequencies in response to different odorants and / or odorant mixtures, and further provides the generated complex waveform features for identification and classification with reference to the "closest match" odorant based on a complex waveform database.

[0085] Figure 4 The configuration of the system 400 shown includes... Figure 2 System 200 is adapted to avoid confusing the concepts and operations of these features in System 400 with details unrelated to the identification and classification features of the reference complex waveform database. As shown in the figure, instance system 400 may include systems such as system 200, which are combined in various configurations with A / D converter resources (e.g., A / D 402) to process complex waveforms ( Figure 4 The complex waveform features output by the CPXW (abbreviated as "CPXW") generation module 208 are digitized, and the CPXW feature recognizer-classifier database 404 is operatively (e.g., logically) coupled to the CPXW feature recognizer-classifier logic 406 and the CPXW feature recognizer-classifier database management logic 408.

[0086] As those skilled in the art will understand upon a full reading of this disclosure, a system providing functional capabilities such as those described for system 400 can, for various applications, be implemented using computer resources for generating complex waveforms and for creating and managing a complex waveform database. These computer resources reside in a server connected to sensors (e.g., sensors 102 and 202 of system 400) via a server interface. The hardware implementation of the resources used to create and / or maintain the CPXW recognizer-classifier database 404 may include, but is not limited to, storage resources of a computer system, as described later in this disclosure (e.g., references to…). Figure 7 (More detailed description)

[0087] Similarly, according to various embodiments, the CPXW feature recognizer-classifier database management logic 408 can be implemented by specific computer processing instructions stored, for example, in non-volatile, non-transitory memory, communicatively connected to programmable processing resources, and in conjunction with the available processing power of the computer resources, as described later herein (e.g., see references). Figure 7 (More detailed description)

[0088] Figure 5 A schematic diagram of the functional modules of a system 500 configured according to one or more embodiments is shown. The system 500 is used to generate complex waveform features that are unique to one or more specific odorants and / or odorant mixtures based on multi-sensor modulation frequencies, and also includes complex waveform features that trigger audio notifications or alarms. Figure 5 The instance system 500 is shown as configured. Figure 2 The system 200 is modified to avoid obscuring these features of the system by describing details unrelated to the characteristics of the system's audio notification implementation. The modification of system 200 may include, for example, adding an acoustic speaker 504, and optionally (at least in part depending on the specifications of the acoustic speaker 504 and the desired audio level) adding an audio amplifier 502. The modification may also include, due to the audible nature of the alarm, configuring a first oscillation signal generator 104-1 modulated by a first sensor signal, a second oscillation signal generator 104-2 modulated by a second sensor signal, a third oscillation signal generator 204-1 modulated by a third sensor signal, ... and an Nth oscillation signal generator 204-N modulated by an Nth sensor signal such that ω1, ω2, ω, ... and ω N Therefore, ω6 is within the audible frequency band. Adaptations may also include, for example, adding a digital-to-analog converter (DAC) to a configuration in which the combiner or combinational operation 206 outputs a complex waveform in the form of discrete digital data.

[0089] Figure 6A schematic diagram of the functional modules of a system 600 for multi-sensor signal amplitude modulation (AM) baseband generation according to one or more embodiments is shown. The system 600 is used to generate complex waveform features that are unique to different odorants and / or odor mixtures.

[0090] The setup of system 600 may include a first sensor 602-1, a second sensor 602-2, a third sensor 602-3, and a fourth sensor 602-4, which will be collectively referred to as "sensor 602" in the following description. According to various embodiments, each sensor 602 may be configured with specific ER characteristics to output a respective sensor signal having a respective signal variation with respect to time in response to exposure to target vapor. Figure 6 An example of such generation is shown: a first sensor signal GN1(t) output from a first sensor 602-1, a second sensor signal GN2(t) output from a second sensor 602-2, a third sensor signal GN3(t) output from a third sensor 602-3, and a fourth sensor signal GN4(t) output from a fourth sensor 602-4, which may be collectively referred to as "sensor signal 602" in the following description.

[0091] According to one or more embodiments, system 600 may further include a first fundamental frequency oscillation signal / frequency generator 604-1, a second fundamental frequency oscillation signal / frequency generator 604-2, a third fundamental frequency oscillation signal / frequency generator 604-3, and a fourth fundamental frequency oscillation signal / frequency generator 604-4. These may be collectively referred to as "fundamental frequency oscillation frequency generator 604" in the following description.

[0092] The fundamental frequency oscillator 604 can be configured to generate, for example, a respective unmodulated oscillating carrier, such as a first sinusoidal carrier signal SF(ω1). t ), the second sinusoidal carrier signal SF(ω2) t ), the third sinusoidal carrier signal SF(ω3) t ) and the fourth sinusoidal carrier signal SF(ω4) t ). “SF” can be, for example, a sine function, while ω1, ω2, ω3, and ω4 can be, for example, values ​​in radians per second. It should be understood that, in Figure 6 The ω1, ω2, ω3 and ω4 in the context may be different from the ω1, ω2, ω3 and ω4 that appear in formulas (1) to (7).

[0093] System 600 may also include a first AM mixer 606-1, which can be configured to receive SF(ω1) tThe first sensor signal GN1(t) is used as the amplitude modulator of the first sinusoidal carrier signal SF(ω1t), and the amplitude modulated first sinusoidal carrier signal SF(ω1t) of the first sensor signal GN1(t) is output on line 608-1. Similarly, the second AM mixer 606-2 can receive SF(ω2t) and GN2(t), and output the amplitude modulated second sinusoidal carrier signal SF(ω2t) of the second sensor signal GN2(t) on line 608-2. t The third AM mixer 606-3 and the fourth AM mixer 606-4 can also output the third sensor signal GN3(t) amplitude-modulated third sinusoidal carrier signal SF(ω3) on lines 608-3 and 608-4 respectively. t The fourth sinusoidal carrier signal SF(ω4t) is modulated by the amplitude of the fourth sensor signal GN4(t).

[0094] In the following description, the outputs of the first AM mixer 606-1, the second AM mixer 606-2, the third AM mixer 606-3, and the fourth AM mixer 606-4 can be collectively referred to as the "sensor signal GNX". (t) Amplitude-modulated sinusoidal carrier signal SF(ω) X t According to various implementation schemes, instances of system 600 may further include a combiner or summing device 610, which combines a sinusoidal carrier signal SF(ω) modulated by the amplitude of the sensor signal GNX(t). X t It can generate complex waveform features CSWS(t).

[0095] The analog signals generated or produced from each sensor can be provided as analog sensor output signals. In one aspect, the analog sensor output signals from multiple sensors can be processed individually to generate a modulation amplitude-frequency waveform for each output. This can produce multiple modulation amplitude-frequency waveforms. The initial waveforms acquired during a single exposure of the array to the odor are combined, for example, by a voltage summing device to generate a unique complex waveform. The processing of the sensor analog output signals may include the step of detecting a first electrical characteristic curve from the sensor. The electrical characteristic curve may be, for example, a time-varying current, resistance, voltage, or impedance.

[0096] Due to factors such as sensor aging, fluctuations or deviations in signal readings (i.e., "sensor drift") may occur during the device lifespan of certain implementations of a system according to one or more embodiments. Therefore, systems according to various embodiments may include specific monitoring features that can identify fluctuations or gradual changes in sensor behavior / signal output over time. These monitoring features may be configured to compare, for a target vapor, one or more analog sensor output signals, digital sensor output signals stored in a sensor input buffer, and / or any other response parameter values ​​stored in a response parameter buffer with odor data of the target vapor stored in memory. The system's processor may also include calibrator logic that can correct or compensate for certain fluctuations or gradual changes in the electrical characteristics and / or sensitivity of the sensors in the sensor array.

[0097] Those skilled in the art will understand upon fully reading this disclosure that implementations of the system according to the appended claims may include known sensors and / or known sensor arrays, and may even utilize processing of existing sensor arrays. In alternative embodiments, commercially available sensor arrays for detecting vapor molecules may be adapted for use with the present invention. For illustrative purposes, one example of such a commercially available sensor array may be, for example, but not limited to, the Cyranose electronic nose manufactured and sold by Intelligent Optical Solutions (California, USA). The Cyranose® electronic nose is a handheld device that can be configured with a variety of different types of sensors, such as, but not limited to, CO2, H2S, O2, or VOC (volatile organic compound) sensors.

[0098] According to one or more embodiments, processing resources for performing the process steps described herein may be implemented at least in part as processor-executable instructions embodied in a non-transitory computer-readable medium communicatively connected to processor logic, the instructions being configured to cause the processor logic to perform the described operations. The computer-readable medium may include any non-transitory medium, such as, but not limited to, non-volatile media. Processing resources also include volatile media. Non-volatile media may include, for example, optical discs or magnetic disks, and other persistent storage. Volatile media may include, for example, dynamic random access memory (“DRAM”), which typically constitutes main memory. Common forms of computer-readable media include, for example, magnetic disks, hard disks, magnetic tapes, any other magnetic media, optical disc read-only memory (“CD-ROM”), digital video discs (“DVD”), any other optical media, random access memory (“RAM”), programmable read-only memory (“PROM”), electrically erasable programmable read-only memory (“EPROM”), FLASH-EEPROM, any other memory chip or memory cartridge, or any other non-transitory tangible computer-readable medium.

[0099] Figure 7 A functional block diagram of an example computing resource 700 is shown. The computing resource 700 may include one or more programmable processors 702, general-purpose memory 704, and instruction memory 706. These components are communicatively connected to the one or more processing resources 702 via a communication infrastructure (e.g., bus 708).

[0100] The processor 702 may be provided as a type or form of processing unit, for example, capable of processing data or interpreting, executing, and / or supervising the execution of one or more instructions, procedures, and / or operations stored in the instruction memory 706. The processor 702 may also direct or manage operations performed by external processing resources.

[0101] The general-purpose storage device 704 may include one or more data storage media, devices, or configurations, and may take any type, form, and combination of data storage media and / or devices. For example, the general-purpose storage device 704 may include, but is not limited to, hard disk drives, network drives, flash drives, magnetic disks, optical disks, RAM, dynamic RAM, other non-volatile and / or volatile data storage units, or combinations or sub-combinations thereof. Electronic data (including the data described herein) may be temporarily and / or permanently stored in the general-purpose storage device 704.

[0102] The instruction memory 706 may (e.g., on a non-transitory storage medium) store processor-executable instructions, such as a baseband modulation control module, a sensor selection module, a sensor configuration module, a sensor monitoring module, a sensor calibration module, a complex waveform feature and reference database matching module, and an alarm configuration module.

[0103] The computer system may include a sensor interface 710, which can be connected to a sensor 712, and for the purpose of receiving sensor output signals, the system 700 may include an analog-to-digital converter (A / D) 714. The sensor interface 710 may also provide a sensor control configuration connection 715 to the sensor 712. According to one or more embodiments, the computer system 700 may include a reference complex feature database 716 and a user interface 718.

[0104] The user interface 718 may be implemented in ways that include, but are not limited to, hardware and / or software for capturing user input, including but not limited to a keyboard or keypad, a touchscreen component (e.g., a touchscreen display), a receiver (e.g., an RF or infrared receiver), a motion sensor, and / or one or more input buttons.

[0105] The user interface device 718 may include one or more devices for presenting output to a user, including but not limited to a graphics engine, a display (e.g., a screen), one or more output drivers (e.g., a display driver), one or more audio speakers, and one or more audio drivers. According to one or more embodiments, the computer system 700 may also include an alarm audio device 720, which, for example, uses a means such as… Figure 5 The audio speaker 504 or audio speaker 504 with an audio amplifier 502 in the instance system 500 is implemented by the processor 702, which can activate the alarm audio device 720 through the alarm interface 722 and the D / A converter 204.

[0106] According to one or more embodiments, computer system 700 may include, for example, a cloud interface 728 for connecting to cloud resource 730.

[0107] Exemplary uses and applications

[0108] The unique sound characteristics can be used in many different applications to alert and inform users. Electronic nose devices are used by consumers (e.g., in homes or vehicles), R&D laboratories, quality control laboratories, and process and production departments for a variety of purposes, including but not limited to:

[0109] At home, for example, the use of one or more applications and / or adapted systems and methods can include not only detecting spoilage of perishable foods in refrigerators, but also further detecting and quantifying characteristic changes indicative of the degree of spoilage of food in refrigerators and / or on shelves through novel generation of complex waveforms according to one or more implementations. Acoustic features can alert users to gas leaks, high concentrations of CO, CO2, or smoke (e.g., from food burning in an oven or stove, or from a fire inside a building).

[0110] Applications in quality control laboratories include, but are not limited to: monitoring the conformity of raw materials, intermediate products, and final products; batch-to-batch consistency; detecting certain types of contamination, spoilage, and / or adulteration; origin or supplier selection; monitoring storage conditions; rapid food classification; and quality monitoring of meat, fish, and poultry.

[0111] In the process and production departments, applications may include, but are not limited to: managing the variability of raw materials; comparing with reference products; measuring and comparing the impact of manufacturing processes on products; tracking the efficiency of in-situ cleaning processes; and scale-up monitoring.

[0112] During the product development phase, applications may include, but are not limited to: sensory analysis and comparison of various formulations or recipes; benchmarking against competing products; and evaluating the impact of process or ingredient changes on sensory characteristics.

[0113] In the health and safety field, applications may include, but are not limited to: detecting the odor of dangerous and harmful bacteria, such as MRSA (methicillin-resistant Staphylococcus aureus) and MSSA (methicillin-sensitive Staphylococcus aureus), for example by placing them in the ventilation systems of hospitals (or airplanes, buses, etc.) to detect and thus prevent many highly infectious pathogens from contaminating other patients or equipment; detecting medical conditions, including cancer, by detecting VOCs (volatile organic compounds) that indicate medical conditions; detecting viral and bacterial infections during acute exacerbations of COPD (chronic obstructive pulmonary disease); and food quality control, such as indicating when food begins to spoil or detecting bacterial or insect contamination during on-site use.

[0114] In the fields of crime prevention and security, applications may include, but are not limited to: detecting “odorless” odors to detect the smell of bombs, explosives, and bullet residues, even in the presence of other airborne odors that could confuse police dogs; and drug detection, etc.

[0115] In environmental monitoring, its applications may include, but are not limited to, identifying volatile organic compounds in air, water, and soil samples.

[0116] In manufacturing, applications include, but are not limited to: monitoring the flavor and / or aroma of food and beverages; packaging materials (e.g., leak detection); pharmaceuticals; cosmetics and perfumes; and chemical manufacturing, such as monitoring the type and level of volatile chemicals.

[0117] Odor recognition based on the complex waveform features of odor fingerprints, according to various implementation schemes, can also be helpful in many personal and commercial applications. At the personal level, individuals who are either insensitive or accustomed to hygiene-related odors can signal in a unique way through audio output. The complex waveform will have a fundamental frequency and overtones, which can be recognized through training. Individuals with anosmia, olfactory dysfunction, or complete olfactory adaptation can be alerted to environmental hazards such as smoke, ammonia, or natural gas leaks through immediately identifiable audio alarms. Other less threatening events, such as the use of perfume by a significant other, will also trigger a signal.

[0118] In a commercial quality control environment, product deterioration can be signaled by unique sound waveforms. Environmental hazards, such as smoke, natural gas leaks, and refrigerant leaks, can be identified through unique auditory patterns.

[0119] The normal components of odorous seasonings, condiments, and the degree of charring in meat can be recorded and compared with standards.

[0120] Environmental hazards involving gases that are, for example, odorless or easily overlooked by people can be detected and optionally signaled with identifiable specificity.

[0121] Another feature and advantage provided by one or more embodiments is the ability to co-present a mixture of odor components. In response, multiple sensors generate their respective outputs, which are converted into oscillating carriers modulated (e.g., amplitude modulated) by multiple sensors according to the processes of one or more disclosed embodiments. These processes then combine the oscillating carriers modulated by multiple sensors to produce a complex waveform in which the complexity incorporates the presence of these components. This provides complexity by bypassing odor recognition, via, for example (but in practice), a identifiable complex waveform. This can be generalized from odor recognition to odor mixtures, allowing for the co-presentation of the mixture components.

[0122] Example

[0123] Various embodiments and aspects thereof are further described through the following non-limiting examples, and will be further understood from these examples. These examples should be understood as illustrating the concepts and aspects of the embodiments and are not intended to constitute any limitation on the scope of the invention.

[0124] Running hardware prototype

[0125] Figure 8 This paper presents the circuit schematic of one of several operational hardware prototypes built and tested by the inventors, which implements... Figure 6 One or more systems of functional modules.

[0126] Figure 9 A photograph is shown of a constructed, operational, and inventor-tested hardware prototype that implements an instance system according to one or more embodiments for generating complex waveform features that correspond to and are unique to different odors and odor mixtures, generally following... Figure 8 The circuit schematic configuration.

[0127] Figure 9 The prototype device shown includes two gas sensors, each with different ER characteristics, and each sensor is connected to its own channel. These channels are referred to as "Channel 1" and "Channel 3". The prototype is powered via a Universal Serial Bus (USB) connection (visible in the lower right corner of the photo) and outputs complex waveforms or odor characteristics (telephone jack in the upper right corner) when an odor or odor mixture is presented to the gas sensors.

[0128] Sensor characteristics

[0129] As mentioned above, Figure 9The operational prototype shown uses multiple independent, physically separate hardware volatile organic compound (VOC) sensors.

[0130] Figure 10 Showing from Figure 9 The prototype sensor outputs amplitude-modulated carrier frequencies and complex waveform signals. When an odor is presented to the first of three VOC sensors, the output signal of the first VOC sensor modulates the amplitude of the channel 1 frequency, producing the channel 1 frequency modulated by the first sensor, as shown in item number 1002 in the figure, and displayed in more detail in magnified view area "A". When the same odor is presented to the second sensor, the output of the second VOC sensor modulates the amplitude of the channel 2 frequency, producing the channel 2 frequency modulated by the second sensor, as shown in item number 1004 in the figure, and displayed in more detail in magnified view area "B". When both sensors are exposed to the odor, the amplitude of the channel 1 frequency is modulated by the output of the first sensor, while the amplitude of the channel 2 frequency is modulated by the output of the second sensor. The combination of the first sensor amplitude modulation of the channel 1 frequency and the third sensor amplitude modulation of the channel 2 frequency is a complex mixture of the two channels, forming a complex waveform sound characteristic, such as... Figure 10 As shown in item 1006, the complex waveform sound characteristics are unique to this odor and are visible in more detail in the magnified view area "C".

[0131] Experimental methods

[0132] In the inventors' experimental implementation, the odorant is presented to the sensor element via headspace diffusion from a solution of water or other odorless carrier. Products such as glass cleaner Windex™ and other common products are presented in a similar manner. Solid or semi-solid products (e.g., peanut butter) are presented close to the sensor surface. The sensor is placed at a distance from the processing unit and connected via a cable. The cable is a printed ribbon cable containing conductive traces for the sensor and ground. The sensor is connected between ground and its respective load resistor on the processor board. The load resistor is in turn connected to a regulated power supply. The changing resistance of the sensor in response to the odorant causes a corresponding voltage change.

[0133] In the later-built, operational hardware prototypes incorporating the microcontroller, the device typically includes analog-to-digital converter (ADC) resources. For example, one microcontroller is the ESP32, which includes an ADC device that converts signals into digital signals, which are then recorded and processed within the microcontroller (ESP32). The stimulus waveform is recorded in memory, where it is retrieved for subsequent processing. Alternatively, processing is performed directly on the microcontroller, which uses a neural network to analyze the waveform and principal component analysis to identify stimulus dimensions and assign amplitude and frequency components, which are then output via an onboard digital-to-analog converter.

[0134] The operational prototypes subsequently built under license by the inventors and / or applicants used a multi-sensor setup package that included multiple sensors and a programmable microcontroller. An example of such a sensor package is the MICS6814 sensor, a microelectromechanical sensor consisting of three sensor elements, each specified by the supplier to have a different chemical response characteristic than the other two. These differences include: one of the three sensor elements is specified by the supplier as a RED sensor element, another as an OX sensor element, and the third as an NH3 sensor element.

[0135] This sensor prototype comprises a structure that encapsulates all three sensor elements together in a single housing. The housing measures 5 mm × 7 mm. Each of the three sensor elements is specified by the supplier to be coated with its own sensing layer, and these sensing layers differ from each other corresponding to the sensor's distinct chemical response characteristics. The specific composition of the sensing layers is not specified in the SGX-Sensortech™ datasheet. n-type (WO3, SnO2, ZnO, TiO2, V2O5) and p-type (NiO, CuO, Co3O4) metal oxide semiconductors are commonly used. They have different chemical sensitivity spectra and are typically commercially available for detecting the chemicals with the highest sensitivity in sensors. In the description of the operating prototype herein, responses to non-target chemicals are alternatively referred to as "interference."

[0136] The RED sensor in the MICS6814 sensor package, according to its supplier documentation, is specified to be sensitive to CO, H2S, ethanol, hydrogen, ammonia, methane, propane, and isobutane; the OX sensor is specified to be sensitive to NO, NO2, and hydrogen; and the NH3 sensor is specified to be sensitive to ammonia, ethanol, hydrogen, propane, and isobutane. Differences in concentration ranges are common where sensitivities overlap. In practice, we have found that each sensor can detect many other different chemicals and odorants.

[0137] Figure 11Three independent signal level-time curves are graphically presented on a two-dimensional (2D) signal level-time plot, showing the sensor outputs measured by the inventors from a commercial off-the-shelf (COTS) NH3 sensor, a COTS RED sensor, and a COTSOX sensor in response to exposure to different concentrations of ethanol vapor.

[0138] Figure 12 The signal level-time curve is graphically displayed on a two-dimensional (2D) signal level-time graph, showing the signal level-time curve measured by the inventor from... Figure 11 The same COTS sensor used in the figure responds to the output of sequentially exposing the sensor to ethanol, citral (C10H16O), Windex™ glass cleaner, PEA, and ethanol.

[0139] Figure 13 The example operation of a process 1300 according to one or more embodiments is illustrated graphically. This process 100 is used to generate complex waveform characteristics that are unique to and responsive to a specific concentration of Listerine™ vapor. The operation in process 1300 includes: [The text abruptly ends here, so the translation stops as well.] t0 Listerine vapor is initially exposed to NH3, CO, and NO2 sensors 1302; the sensors responsively output their respective sensor signals 1304 within a sensing interval, which are shown in the figure as the NH3 sensor output, CO sensor output, and NO2 sensor output. The operation of process 1300 further includes amplitude modulation 1306 of the first response to the concentration of listerine vapor, generating a first frequency 1308A modulated by the NH3 sensor, a second frequency 1308B modulated by the CO sensor, and a third frequency 1308C modulated by the NH3 sensor, collectively referred to as item 1308 in the figure. Process 1300 further includes 1310 combining the frequencies of the amplitude modulation of the three sensor outputs to form a complex waveform characteristic 1312 unique to a specific concentration of listerine vapor.

[0140] Figure 14 The operation of an example process according to one or more embodiments is illustrated graphically, which responds to a specific concentration of ethanol vapor and uniquely provides complex waveform characteristics to it. Figure 14 In the example, process 1400 used the same as Figure 13 Sensors with the same process.

[0141] Figure 15 It shows Figure 14 The graph is overlaid with representations of the sensor test module and equipment, while also showing a magnified view "D" of complex waveform features.

[0142] Figure 16The complex waveform characteristics of Listerine™ vapor and ethanol vapor at specific concentrations generated by a prototype constructed according to one or more embodiments are illustrated graphically.

[0143] Figure 17 An illustrative example setup 1700 is shown for a process of generating complex waveform features based on multi-sensor, multi-frequency modulated carrier signals according to one or more embodiments. The example setup of process 1700 differs from processes 1300 and 1400 in that it uses sensor outputs to frequency modulate the carrier frequency 1702, generating a first carrier signal 1704A modulated by a first sensor frequency, a second carrier signal 1704B modulated by a second sensor frequency, and a third carrier signal 1704C modulated by a third sensor frequency (collectively referred to as "sensor signal frequency modulated carrier signal 1704"), and then combines these signals to generate a corresponding FM-based complex waveform signal 1706.

[0144] It should be understood that the present invention is not limited to the specific embodiments described herein, as the embodiments described herein are susceptible to various modifications and alternatives. Embodiments have been shown by way of example in the accompanying drawings and will be described in detail herein. However, the exemplary embodiments described are not limited to the specific forms disclosed. Rather, this disclosure covers all modifications, equivalents, and alternatives falling within the scope of the appended claims.

[0145] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting, as the scope of the invention will be limited only by the appended claims.

[0146] When a numerical range is provided, it should be understood that, unless the context explicitly specifies otherwise, every intermediate value (to one-tenth of the lower limit unit) between the upper and lower limits of the range, as well as any other value or intermediate value within the range, is included in this invention. The upper and lower limits of these smaller ranges may be independently included within the smaller ranges and also within this invention, but are subject to any express exclusions within the ranges. Where the range includes one or two limits, the range excluding any one or both of these included limits is also included in this invention.

[0147] When ordinal terms such as “first,” “second,” and “third” are used in this specification and the appended claims to modify, for example, steps, functional modules, signals, instructions, or elements, they should be understood as marks used to individually refer to different steps, functional modules, signals, instructions, and / or elements, and unless otherwise stated, they should not be construed as any indication of temporal order, spatial order, or priority.

[0148] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Representative and illustrative methods and materials are described herein. Similar or equivalent methods and materials may also be used in the practice or testing of this invention.

[0149] All publications and patents referenced in this specification are incorporated herein by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference, and are incorporated herein by reference to disclose and describe the methods and / or materials associated with the referenced publications. Reference to any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present invention has no right to claim prior invention rights to that publication. Furthermore, the publication dates provided may differ from the actual publication dates and may require independent verification.

[0150] It should be understood that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly specifies otherwise. It should also be noted that claims can be drafted to exclude any optional elements. Therefore, this statement is intended to support the use of exclusive terms such as “only,” “unique,” ​​or “negative” restrictions in the claims in relation to the cited claim element, or the use of such restrictions as “where [specific feature or element] is absent,” or “other than [specific feature or element],” or “where [specific feature or element] is absent (excluding, etc.)…”.

[0151] As will be apparent to those skilled in the art upon a full reading of this disclosure, each individual embodiment described and illustrated herein has discrete components and features that can be readily separated from or combined with features of any other plurality of embodiments without departing from the scope or spirit of the invention.

[0152] It should be understood that various methods and operations are described as multiple independent actions, steps or operations, but it should be understood that such descriptions may be intended to further assist the reader in understanding, for example, concepts and / or logical relationships, and should not be construed as limiting the order in which these actions, steps or operations can be performed, and these actions, steps or operations may be performed in the chronological or spatial order described or in any other logically possible order or arrangement.

[0153] While the invention has been described with reference to several exemplary embodiments thereof, those skilled in the art will recognize that the invention can be practiced with modifications within the spirit and scope of the appended claims. Therefore, the invention should not be limited to the above-described embodiments, but should further include all modifications and equivalents thereof within the spirit and scope of the description provided herein.

Claims

1. A method for generating corresponding complex waveform features in response to an odorant, the method comprising the following steps: The odorant in a vapor state at a new concentration is distributed to a sensor array including a first sensor and a second sensor, wherein each sensor is sensitive to the odorant, the first sensor has a first electrical response characteristic, the second sensor has a second electrical response characteristic different from the first electrical response characteristic, and the new concentration is greater than the concentration of the odorant at the sensor array at the start of distribution; The first sensor, in response to receiving the new concentration of odorant, generates a first sensor signal having a first signal-time characteristic, the first signal-time characteristic being at least partially based on the odorant, the new concentration, and the first electrical response characteristic; The second sensor, in response to the first sensor receiving the new concentration of odorant, generates a second sensor signal having a second signal-time characteristic that differs from the first signal-time characteristic by a difference that is at least partially based on the odorant, the new concentration, and a second electrical response characteristic that differs from the first electrical characteristic; A complex waveform signal is generated at least in part based on both the first sensor signal and the second sensor signal, wherein the generation is configured to generate the complex waveform signal having a complex waveform shape corresponding to the odorant, and the generation configuration includes: The first sensor signal is converted into a first oscillation signal modulated by the first sensor signal, and the second sensor signal is converted into a second oscillation signal modulated by the sensor signal. The complex waveform signal is formed by combining at least a first oscillation signal modulated by the first sensor signal and a second oscillation signal modulated by the second sensor signal.

2. The method according to claim 1, wherein: The first sensor and the second sensor are disposed inside the housing, which includes a switchable fluid path from the outside of the housing to the inside of the housing. The distribution of the new concentration includes switching the switchable fluid path from a closed state to an open state at the switching time. The first sensor receives the new concentration at a first start time relative to the switching time, and the second sensor receives the new concentration at a second start time relative to the switching time. The complex waveform shape is also based, at least in part, on the time sequence and time interval between the first start time and the second start time.

3. The method of claim 1, wherein the configuration for generating the complex waveform signal further comprises the following step: Generate the first oscillating carrier signal; Generate a second oscillating carrier signal. in, Generating a first oscillation signal modulated by a first sensor signal includes amplitude modulation of the first oscillation carrier signal using the first sensor signal. Generating a second oscillation signal that modulates the amplitude of the second sensor signal includes using the second sensor signal to modulate the amplitude of the second oscillation carrier signal.

4. The method according to claim 3, wherein the first oscillating carrier signal oscillates at a first frequency, the first frequency being a first audio frequency, and the second oscillating carrier signal oscillates at a second frequency, the second frequency being a second audio frequency.

5. The method of claim 4, wherein the method further comprises outputting to a user, at least in part, an audible odor indication sound based on the complex waveform signal via an audio speaker.

6. The method according to claim 5, wherein: The first frequency, the second frequency, amplitude modulation of the first oscillating carrier signal using the first sensor signal, and amplitude modulation of the second oscillating carrier signal using the second sensor signal are configured to each other such that: In response to the odorant being a target substance at a first concentration level, the audible odor indication sound output to the user has a first audible characteristic. In response to the odorant being a target substance at a second concentration level higher than the first concentration level, the audible odor indicator sound has a second audible characteristic, which differs from the first audible characteristic by quality and / or character that can be discerned by the user.

7. The method of claim 1, further comprising identifying odors by matching the complex waveform of the complex waveform signal with a database containing a plurality of different reference complex waveforms, wherein each reference complex waveform corresponds to a corresponding reference odor or odor mixture.

8. The method according to claim 1, wherein The first sensor is a member of a first group of one or more sensors of a first type, and the second sensor is a member of a second group of one or more sensors of a second type, wherein... Each of the one or more first-type sensors is configured to have a first sensitivity to odors. Each of the one or more second-type sensors is configured to have a second sensitivity to odors. The first sensitivity is different from the second sensitivity.

9. The method according to claim 1, The first sensor includes a first sensor device, which includes a first sensor sensing layer and a first filter disposed on the first sensor sensing layer. The second sensor includes a second sensor device, which includes a second sensor sensing layer and a second filter disposed on the second sensor sensing layer. The first filter influences the passage or flow of molecules through the sensing layer of the first sensor in a manner that provides the first electrical response characteristic.

10. The method according to claim 1, wherein the first sensor signal includes a first sensor digital signal, and the second sensor signal includes a second sensor digital signal.

11. The method according to claim 1, wherein the first sensor signal includes a first sensor analog signal, and the second sensor signal includes a second sensor analog signal.

12. A system for generating complex waveforms corresponding to odors, comprising: A sensor array, comprising at least two sensors, wherein The first sensor of the at least two sensors is configured with a first electrical response characteristic relative to the sensing response to at least one target odorant, and the first sensor is configured to output a first sensor output signal in response to exposure to the target odorant. The first sensor output signal has a first change in a time-dependent characteristic, the first change in the time-dependent characteristic being at least partially based on the target odorant and the first electrical response characteristic. The second sensor of the at least two sensors is configured with a second electrical response characteristic relative to the sensing response to the at least one target odorant, and the second sensor is configured to output a second sensor output signal in response to exposure to the target odorant. The second sensor output signal has a second change in its time-dependent characteristics, which differs from the first change in its time-dependent characteristics by a difference at least in part based on the target odorant and the difference between the first and second electrical response characteristics. Processor, the processor being programmed to: The first sensor output signal is used to modulate the first oscillation signal to generate the first oscillation signal modulated by the first sensor signal. The second sensor output signal is used to modulate the second oscillation signal to generate the second sensor signal modulated second, and The first oscillation signal modulated by the first sensor signal and the second oscillation signal modulated by the second sensor signal are combined to form a complex waveform corresponding to the odorant.

13. The system of claim 12, wherein the sensor array comprises a plurality of groups of one or more sensors, each group being configured to detect a different odor.

14. The system of claim 12, wherein the sensor array comprises at least two identical sensors, wherein each of the at least two identical sensors is associated with a different filter to differentially influence the passage or flow of different molecules through the filter.

15. The system of claim 12, wherein the processor is programmed to: By modulating the amplitude of the first oscillation signal using the first sensor signal, the first oscillation signal is modulated using the output signal of the first sensor, thereby outputting a first oscillation signal modulated by the amplitude of the first sensor signal. By modulating the amplitude of the second oscillation signal using the second sensor signal, the second oscillation signal is modulated using the output signal of the second sensor, thereby outputting a second oscillation signal modulated by the amplitude of the second sensor signal. The first oscillation signal modulated by the amplitude of at least the first sensor signal and the second oscillation signal modulated by the amplitude of the second sensor signal are summed to form the complex waveform corresponding to the odorant.

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