Multidimensional signal detection using optical sensors.

Abstract

Described herein are systems and methods for detecting multiple physical characteristics. The methods may include receiving a sensor signal from a single optical sensor proximate a measurement region, determining multiple sensor responses from the sensor signal, and generating multiple measurement signals from the multiple sensor responses. Each of the measurement signals may correspond to a different respective physical characteristic of the measurement region.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 62,236,610, filed August 24, 2021, the contents of which are incorporated herein by reference in their entirety.

[0002] The devices, systems, and methods described herein relate to optical sensors. [Background technology]

[0003] In many applications, it is desirable to detect multiple types of physical parameters. For example, in the field of medical technology, it may be advantageous to have a medical device equipped with a sensor that can sense multiple different physical parameters (e.g., simultaneously in real time or near real time). For example, an ablation catheter for cardiovascular treatment may include a temperature sensor for measuring the temperature of the treated tissue and a force sensor for measuring the force applied to the arterial wall during cardiac ablation. It may be possible to incorporate multiple types of sensors together in a single device to monitor multiple different types of parameters. However, it may be more difficult to include additional sensors, for example, because it may be more difficult to fit multiple sensors into the desired form factor of the device. Additionally or alternatively, including more sensors may result in more difficulties in accommodating additional components (e.g., mechanical, electrical, power) and connections to enable proper functioning of each of the different sensors. Therefore, it may be desirable to provide an optical sensor configured to sense multiple physical parameters. Summary of the Invention

[0004] Methods and systems for multi-dimensional sensing using optical sensors are described herein. In some variations, a method for multi-dimensional sensing may include receiving a sensor signal from a single optical sensor proximate a measurement region, determining a plurality of sensor responses from the sensor signal, and generating a plurality of measurement signals from the plurality of sensor responses. Each of the measurement signals may correspond to a different respective physical signal of the measurement region.

[0005] In some variations, the sensor response of the plurality of sensor responses may be selected from the group consisting of mode shift, baseline drift, mode splitting, mode broadening, and any combination thereof. In some variations, the sensor response may be a mode shift including one or more changes in resonant frequency, depth change, shape change, or any combination thereof. In some variations, the physical signal of the environment may be at least two of a temperature, a pressure, and an acoustic wave of the environment.

[0006] In some variations, generating the plurality of measurement signals may further include isolating at least a portion of the physical signal. Isolating at least a portion of the physical signal may include analyzing a first sensor response of the plurality of sensor responses for a first time period. The first measurement signal for the first time period may be generated based on the first sensor response. A second sensor response of the plurality of sensor responses may be analyzed over a second time period. The second measurement signal for the second time period may be generated based on the second sensor response. In some variations, the method may further include analyzing a third sensor response for a third time period and generating a third measurement signal for the third time period based on the third sensor response. In some variations, the first response may include a mode shift and the first measurement signal may correspond to temperature. The second sensor response may include a baseline shift and the second measurement signal may correspond to pressure.

[0007] In some variations, isolating at least a portion of the physical signals may include selectively modifying the environment based on the target physical signal. In some variations, isolating at least a portion of the physical signals may include suppressing one or more of the physical signals that are different from the target physical signal. In some variations, suppressing one or more of the physical signals may include adjusting the environment such that the one or more physical signals that are different from the target physical signal are within a first sensitivity signal region of the optical sensor. In some variations, suppressing one or more physical signals may include modifying at least one of a temperature, a pressure, and an acoustic characteristic of the environment.

[0008] In some variations, isolating at least a portion of the physical signal may include increasing the sensitivity of the optical sensor to the target physical signal. In some variations, increasing the sensitivity of the optical sensor may include adjusting an environment of the sensor such that the target physical signal is within a second sensitivity signal range of the optical sensor that is different from the first sensitivity signal range. For example, the second sensitivity signal range may be higher than the first sensitivity signal range. In some variations, increasing the sensitivity may include analyzing a first sensor response of the plurality of sensor responses for a first time period associated with the first sensitivity signal range and generating a first measurement signal corresponding to the target physical signal.

[0009] In some variations, generating the plurality of measurement signals may include associating a first sensor response of the plurality of sensor responses to a first physical signal and associating a second sensor response of the plurality of sensor responses to a second physical signal. In some variations, generating the plurality of measurement signals may include applying a signal transformation function to the plurality of sensor responses. The signal transformation function may include a signal transformation matrix.

[0010] In some variations, the optical sensor may comprise a first optical sensor in an array of optical sensors. In some variations, the sensor signal may include a first sensor signal, the plurality of sensor responses may include a first plurality of sensor responses, and the method may further include receiving a second sensor signal from a second optical sensor in the array of optical sensors, determining a second plurality of sensor responses from the second optical sensor, and generating a first measurement signal indicative of the first physical signal. The first measurement signal may be based on the first plurality of sensor responses to the first optical sensor, the second plurality of sensor responses to the second optical sensor, and sensitivities of the first and second optical sensors to the first and second physical signals.

[0011] In some variations, the plurality of measurement signals may be generated based at least in part on a reference signal from a reference sensor. In some variations, the optical sensor may comprise an interference-based optical sensor. In some variations, the optical sensor may comprise an optical resonator or an optical interferometer. In some variations, the optical sensor may comprise a whispering gallery mode (WGM) resonator. In some variations, the optical sensor may comprise one or more of a microbubble optical resonator, a microsphere resonator, a microtoroid resonator, a microring resonator, and a microdisk optical resonator.

[0012] Also described herein is a system for multi-dimensional sensing of a measurement region. The system may include an optical sensor and a signal processor. The signal processor may be configured to receive a sensor signal from the optical sensor, determine a plurality of sensor responses from the sensor signal, and generate a plurality of measurement signals from the plurality of sensor responses. Each measurement signal may correspond to a different respective physical signal of the measurement region.

[0013] In some variations, the sensor response of the plurality of sensor responses may be selected from the group consisting of a mode shift, a baseline drift, a mode splitting, a mode broadening, and any combination thereof. In some variations, the sensor response may be a mode shift including one or more of a change in resonant frequency, a change in depth, a change in shape, or any combination thereof.

[0014] In some variations, the physical signal of the environment may include two or more of a temperature, a pressure, and an acoustic wave of the environment. In some variations, the optical sensor may comprise an interference-based optical sensor. In some variations, the optical sensor may comprise an optical resonator or an optical interferometer. In some variations, the optical sensor may comprise a whispering gallery mode (WGM) resonator. In some variations, the optical sensor may comprise one or more of a microbubble resonator, a microsphere resonator, a microtoroid resonator, a microring resonator, a microbottle resonator, a microcylinder, or a microdisk optical resonator. In some variations, the optical sensor may comprise a microring resonator including one or more of a circular, a racetrack, and an elliptical cross-sectional shape.

[0015] In some variations, the optical sensor may comprise a first optical sensor of an array of optical sensors, and the system may further comprise the array of optical sensors. In some variations, the array of optical sensors may comprise a second optical sensor. The first optical sensor may have a higher sensitivity to the first physical signal than the second optical sensor, and the second optical sensor may have a higher sensitivity to the second physical signal than the first optical sensor. The first and second physical signals may be different.

[0016] In some variations, the environment of the first optical sensor may be configured to enhance the first physical signal, or the environment of the second optical sensor may be configured to suppress the first physical signal, or both. In some variations, the environment of the first optical sensor may be configured to suppress the second physical signal, or the environment of the second optical sensor may be configured to enhance the second physical signal, or both. In some variations, the system may further comprise a reference sensor configured to provide a reference signal corresponding to one or more of the physical signals of the measurement region. In some variations, the reference sensor may comprise an optical sensor. In some variations, the reference sensor may comprise a non-optical sensor. [Brief description of the drawings]

[0017] [Figure 1] 1 illustrates an exemplary variation of a whispering gallery mode (WGM) microsphere resonator. [Diagram 2] FIG. 2 is a schematic block diagram of an example variation of a system including an optical sensor configured to measure physical signals such as temperature and pressure. [Diagram 3] FIG. 2 is a schematic block diagram of an exemplary variation of a system for sensing multiple physical signals. [Figure 4] 11 is a flowchart of an exemplary variation of a method for sensing multiple physical signals using a single optical sensor. [Diagram 5] 1 is a schematic diagram of an exemplary variation of an optical sensor for sensing multiple physical signals. [Figure 6A-6C] Illustrated are exemplary optical sensor signals in response to nominal conditions, pressure changes, and temperature changes, respectively, in a measurement region proximate the optical sensor. [Figure 7A] 1 is an exemplary plot illustrating a sensor response curve having a sensitivity region. [Figure 7B] 1 is an exemplary plot illustrating a sensor response curve having a dead region. [Figure 8]FIG. 1 is a schematic block diagram of an exemplary variation of a system for performing multi-dimensional sensing by separating individual physical signals detected by sensors. [Figure 9] FIG. 1 is a schematic block diagram of an exemplary variation of a system for performing multi-dimensional sensing by isolating individual physical signals detected by an optical sensor by modifying the optical sensor's environment. [Figure 10] 1 shows a schematic block diagram of an example variation of a system configured to modify a sensor's environment to adjust the sensor's sensitivity. [Figure 11] FIG. 1 is a schematic diagram of an example variation of a system for performing multi-dimensional sensing by distinguishing between multiple physical signals detected by a sensor. [Figure 12] FIG. 1 is a schematic diagram of an exemplary variation of a system for performing multi-dimensional sensing by combining multiple sensor responses of sensors. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Non-limiting examples of various aspects and variations of the present invention are described herein and illustrated in the accompanying drawings.

[0019] Described herein are systems and methods for sensing (e.g., detecting, measuring, determining) multiple physical signals (e.g., temperature, pressure). For example, a single optical sensor may be configured to detect multiple physical signals, which may enable, for example, accurate measurement of multiple physical signals substantially simultaneously using a single sensor. The physical signals may correspond to physical characteristics or features associated with a state of a physical system.

[0020] Sensors configured to measure multiple physical signals can be useful for a variety of applications. For example, some medical devices, such as cardiovascular therapy, cardiovascular monitoring and diagnostics, patient monitoring and diagnostics, surgical procedures, etc., may require detection of more than one physical signal. Similarly, Internet of Things (IoT) devices with applications in consumer (e.g., smart homes), organizational (e.g., healthcare, transportation), and industrial (e.g., manufacturing) applications often require measurement of more than one physical signal.

[0021] Traditionally, devices and systems incorporate multiple different sensors to detect various physical signals, with each sensor configured to detect a separate respective physical signal. For example, a device may incorporate a temperature sensor to measure temperature and a separate pressure sensor to measure pressure. However, having separate sensors to detect different physical signals can make the device bulkier and / or pose design challenges, as the separate sensors require more physical volume for packaging and may require separate electronics and connections. Having separate sensors can also reduce the reliability of the device, due to additional components that are susceptible to damage and failure.

[0022] It may therefore be advantageous for a device or system to have a single sensor capable of performing multi-dimensional sensing (e.g., measuring multiple different physical signals substantially simultaneously in real-time or near real-time). Described herein are systems and methods for such multi-dimensional sensing. This may reduce one or more of the size, energy requirements, signal interference, and cost of the device and / or system.

[0023] Optical Sensor System An optical sensor system configured to measure multiple physical signals may generally include one or more optical sensors that may detect multiple physical signals, such as temperature, pressure, acoustic waves, etc., using an optical sensor (e.g., a single sensor) by analyzing the sensor response for mode shifts (e.g., changes in frequency, depth, shape of response), baseline drift, mode splitting, and mode broadening. The optical sensors described herein may advantageously have high sensitivity and wide bandwidth compared to conventional sensors.

[0024] In some variations, the optical sensor may include an interference-based optical sensor such as an optical interferometer, an optical resonator, etc. Examples of optical interferometers may include a Mach-Zehnder interferometer, a Michelson interferometer, a Fabry-Perot interferometer, a Sagnac interferometer, etc. For example, a Mach-Zehnder interferometer may include two nearly identical optical paths (e.g., fiber, on-chip silicon waveguides). The two optical paths may include fine-tuned acoustic waves (e.g., by acoustic wave induced physical motion, acoustic wave induced refractive index adjustment) configured to distribute optical power at the output of the Mach-Zehnder interferometer to detect the presence or magnitude of acoustic waves.

[0025] In general, the optical resonator may include a closed-loop transparent medium that allows light of a predetermined frequency to propagate continuously within the closed loop and may allow light energy of the predetermined frequency of light to be stored within the closed loop. For example, the optical resonator may include a whispering gallery mode (WGM) resonator that may be configured to allow propagation of whispering gallery modes (WGMs) (e.g., waves) traveling through a concave surface of the optical resonator that correspond to a predetermined frequency circulating around the circumference of the resonator. Each mode of the WGM resonator may correspond to the propagation of a frequency of light from the predetermined frequency of light. The predetermined frequency of light and the Q value of the optical resonator may be based at least in part on a set of geometric parameters of the optical resonator, a refractive index of the transparent medium, and a set of refractive indexes of an environment surrounding the optical resonator.

[0026] In some variations, the WGM resonator may include a substantially curved portion (e.g., a spherical portion, a toroid-shaped portion, a ring-shaped portion). The substantially curved portion may be supported by a stem portion (e.g., coupled, attached, integral). The shape of the WGM resonator (e.g., the shape of the substantially curved portion of the WGM resonator) may be any suitable shape. For example, the shape of the WGM resonator may be spherical (i.e., a solid sphere), bubble-shaped (i.e., a sphere with a cavity), cylindrical, elliptical, ring, disk, toroid, etc. Some non-limiting examples of WGM resonators include microring resonators (e.g., circular microring resonators, non-circular microring resonators such as resonators having a shape of a racetrack, ellipse), microbottle resonators, microbubble resonators, microsphere resonators, microcylinder resonators, microdisk resonators, microtoroid resonators, combinations thereof, etc.

[0027] 1 is an exemplary variation of a WGM microsphere resonator 102. The WGM microsphere resonator 102 can include a substantially curved portion 102a (e.g., a spherical portion). The substantially curved portion 102a can be supported by a stem portion 102b. In some variations, the substantially curved portion 102a of the WGM microsphere resonator 102 can be coupled to or integral with the end of the stem portion 102b of the WGM microsphere resonator 102.

[0028] As discussed above, the WGM microsphere resonator 102 can be configured to capture (e.g., hold, capture, retain) a predetermined set of frequencies of light. The predetermined set of frequencies of light can be configured to cycle within the substantially curved portion 102a of the WGM microsphere resonator 102, thereby enabling propagation of whispering gallery modes along the surface of the WGM microsphere resonator 102 (e.g., along the circumference of the substantially curved portion 102a). In some variations, each set of WGMs propagated by the WGM microsphere resonator 102 can be confined to one or more planes within the WGM microsphere resonator 102.

[0029] Although the WGM microsphere resonator shown in FIG. 1 has a spherical shape, the substantially curved portion 102a may be any suitable shape. In general, one or more of the performance characteristics of the WGM resonator 102 may depend on its shape. For example, generally, a more spherical microsphere may be more effective at confining the WGM within the WGM resonator. Some suitable variations of the WGM microsphere resonator 102 are elliptical (e.g., having some degree of eccentricity, such as about 0 to about 0.9) and may be described herein.

[0030] To efficiently sense light using an optical sensor, phase matching between the incident light and the resonating light may be required. In some variations, an optical waveguide configured to provide phase matching may be used to couple the light to the optical sensor. The optical waveguide may be configured to provide controllable and robust light that can efficiently utilize the sensing capabilities of the optical sensor. Thus, in some variations, a sensor system may include at least one optical waveguide and one or more optical sensors.

[0031] In some variations, at least a portion of the optical waveguide and optical sensor can be embedded within a polymer structure, thereby encapsulating the optical waveguide and optical sensor. The polymer structure can protect the optical sensor and optical waveguide from physical damage, where the optical sensor may be particularly fragile and susceptible to physical damage. In some variations, the refractive index of the polymer coating can be lower than the effective refractive index of the optical sensor. This can allow the packaged optical sensor to respond to a wide range of frequencies.

[0032] Further examples of optical systems that can be used for multidimensional sensing (e.g., types of optical sensors, manufacturing and packaging of optical sensors) are described in International Patent Application No. PCT / US2020 / 064094, International Patent Application No. PCT / US2021 / 022412, and International Patent Application No. PCT / US2021 / 039551, each of which is incorporated by reference herein.

[0033] FIG. 2 is a schematic diagram of an example variation of a system 200 for sensing multiple physical signals. The system 200 may include an optical sensor 202, an optical waveguide 204, a light source 206, a light detector 208, a temperature processor 210, a pressure processor 212, and an optional display 214. In some variations, the optical sensor 202 may be configured to measure multiple physical signals, such as temperature and pressure, within or proximate to a measurement region. As seen in FIG. 2, the optical sensor 202 (e.g., an optical resonator such as a WGM resonator) may be configured to be optically coupled (e.g., optically communicated) to a light source 206 (e.g., a laser) and a light detector 208 (e.g., a photodetector, light emission) via one or more optical waveguides 204 (e.g., optical fiber, slab waveguide). For example, the light source 206 may be configured to transmit light to the optical sensor 202 via the optical waveguide 204. The optical detector 208 may be configured to receive modulated optical signals from the optical sensor 202 via the optical waveguide 204 and convert the optical signals (e.g., sensor signals) received from the optical sensor 202 into electrical signals. As described in further detail below, the optical detector 208 may be communicatively coupled to one or more processors (e.g., a temperature processor 210 for determining temperature data, a pressure processor 212 for determining pressure data) configured to determine a plurality of sensor responses (e.g., measurement data) from the electrical signals from the optical detector 208. The processors may be communicatively coupled to components for processing data (e.g., input / output devices), such as a display 214, a memory device (not shown), etc.

[0034] In some variations, the optical sensor 202 may comprise any suitable optical sensor as described above (e.g., a WGM resonator configured to propagate a WGM). In some variations, the optical sensor 202 may include, for example, a diameter of less than about 200 μm.

[0035] 2, it should be understood that in some variations, the system 200 may include an array of optical sensors, where at least one of the optical sensors 202 may be configured to generate a sensor signal that is used to generate multiple measurement signals corresponding to multiple physical signals. Thus, while the array may include multiple optical sensors, each (or at least one) optical sensor in the array may function as a multi-dimensional sensor capable of measuring multiple physical signals, independently and alone from other optical sensors in the array.

[0036] As described above, the light source 206 may be configured to transmit light to the optical sensor. The light source 206 may include, for example, a laser that radiates continuous wave or pulsed laser energy to the sensor via an optical waveguide, such as an optical fiber. In variations where the optical sensor is a WGM resonator, the light from the light source 206 may propagate a first set of WGMs around a surface (e.g., a wall) surrounding the WGM resonator. The propagation of the first set of WGMs may generate a first set of optical signals corresponding to the resonant frequencies of the first set of WGMs. Changes in temperature and / or pressure in the measurement volume proximate to the WGM resonator may induce a set of changes to the radius and / or refractive index of the WGM resonator and / or the refractive index of the environment proximate to the WGM resonator. In some variations, these sets of changes may propagate a second set of WGMs around a wall surrounding the WGM resonator. The propagation of the second set of WGMs may generate a second set of optical signals corresponding to the resonant frequencies of the second set of WGMs. In some variations, the first set of optical signals and the second set of optical signals may be configured to propagate within the optical waveguide 204 to the optical detector 208, which then processes the optical signals into a sensor response (e.g., converting the first set of optical signals into a first set of electrical signals and converting the second set of optical signals into a second set of electrical signals).

[0037] In some variations, the optical detector 208 may be coupled to one or more processors configured to generate measurement signals corresponding to a plurality of physical signals based on a plurality of sensor responses determined from the sensor signal (e.g., an electrical signal from the optical detector 208). In some variations, one or more of the processors may be part of a signal processor, such as that described below with respect to FIG.

[0038] For example, as shown in FIG. 2, the optical detector 208 may be coupled to a temperature processor 210 and a pressure processor 212. The temperature processor 210 may be configured to characterize one or more sensor responses determined from the first set of electrical signals and / or the second set of electrical signals (e.g., sensor signals) and generate a measurement signal(s) corresponding to a temperature. In some variations, the temperature processor 210 may generate a measurement signal(s) indicative of a change in temperature and / or an absolute value of the temperature based on the sensor response between the first and second sets of electrical signals. For example, a mode shift (e.g., a change from a first set of resonant frequencies of the WGMs of the first set of optical signals to a second set of resonant frequencies of the WGMs of the second set of optical signals) may correspond to or be indicative of a temperature of the measurement region. Thus, the temperature processor 210 may be configured to generate temperature information of the measurement region by analyzing the mode shift. Similarly, a baseline drift (e.g., a change in baseline signal value(s) of the first set of optical signals relative to the second set of optical signals) may correspond to or be indicative of a pressure of the measurement region. Thus, the pressure processor 212 may be configured to generate pressure information of the measurement region by analyzing the baseline drift. In some variations, the mode shift may include a shift in resonant frequency. However, it should be understood that the mode shift may include one or more of a shift in frequency, a shift in wave height (e.g., a change in depth), and a shift in wave shape (e.g., a change in shape).

[0039] In some variations, the measurement signals corresponding to the physical signals (e.g., temperature information and pressure information) may be transmitted to the display 214, for example, for real-time monitoring of the measurement area. In some variations, the display 214 may include an interactive user interface (e.g., a touch screen) and may be configured to transmit a set of commands (e.g., pause, resume, etc.) to the light source 206. In some variations, the imaging system 200 may further include a set of auxiliary devices (not shown) used to input information to the imaging system 200 or output information from the imaging system 200. In some variations, the set of auxiliary devices may include, for example, one or more of a keyboard, a mouse, a monitor, a webcam, a microphone, a touch screen, a printer, a scanner, a virtual reality (VR) head mounted display, a joystick, a biometric reader, etc. Additionally or alternatively, in some variations, the system 200 may include or be communicatively coupled to one or more storage devices (e.g., local or remote memory device(s)).

[0040] 2 shows two separate processors (i.e., temperature processor 210 for measuring temperature and pressure processor 212 for measuring pressure), it should be readily understood that in some variations, a single processor may be used to extract temperature and pressure information. Furthermore, in some variations, multiple processors may be used to extract temperature information and / or multiple processors may be used to extract pressure information (e.g., for purposes of averaging different measurement signals). In other words, there may be an n:m ratio of processors for a measured physical signal, where n is equal to m, or n is less than m, or n is greater than m. Furthermore, the processor(s) may be configured to determine other types of measurement data corresponding to different physical signals. For example, in some variations, a third processor (not shown) may be configured to determine measurement data from a sensor response corresponding to an acoustic wave (e.g., ultrasound imaging).

[0041] 3 is a schematic diagram of an example variation of a system 300 for sensing multiple physical signals. In some variations, the system 300 may include an optical sensor 302 (e.g., a WGM resonator) with a measurement region 316 proximate the optical sensor 302 and a signal processor 312. The optical sensor 302 may be communicatively coupled to the signal processor 312 via a photodetector (not shown in FIG. 3 ) similar to that described with respect to FIG. 2 . For example, the optical sensor 302 may be optically coupled to the optical detector, similar to that described above. The photodetector may then be communicatively coupled to the signal processor 312 via a network.

[0042] The optical sensor 302 may be any suitable optical sensor and may include any of the optical resonators (e.g., WGM resonators) described herein. The measurement region 316 may include a polymer structure that packages the WGM resonator.

[0043] In some variations, the signal processor 312 may include one or more processors (e.g., CPUs) (e.g., similar to the processors described above with respect to FIG. 2). The processor(s) may be any suitable processing device configured to operate and / or execute a set of instructions or code and may include one or more data processors, image processors, graphic processing units, digital signal processors, and / or central processing units. The processor(s) may be, for example, a general-purpose processor, a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), etc. The processor(s) may be configured to operate and / or execute application processes and / or other modules, processes and / or functions associated with the system 300.

[0044] In some variations, the signal processor 312 may run and / or execute application processes and / or other modules. When executed by the processor, these processes and / or modules may be configured to perform specific tasks. Collectively, these specific tasks may enable the signal processor 312 to analyze the sensor response to generate multiple measurement signals, each of which may be indicative of a physical signal. For example, these specific tasks may enable the signal processor 312 to accurately detect multiple physical signals based on the sensor response of the optical sensor 302 caused by changes in temperature, pressure, acoustic waves, etc. within the measurement region 316.

[0045] In some variations, the application processes and / or other modules may be software modules. The software modules (which execute on the hardware) may be expressed in a variety of software languages ​​(e.g., computer code), including C, C++, Java, Python, Ruby, Visual Basic, and / or other object-oriented, procedural, or other programming languages ​​and development tools. Examples of computer code include, but are not limited to, microcode or microinstructions, machine instructions such as those generated by a compiler, code used to generate web services, and files containing high-level instructions that are executed by a computer using an interpreter. Additional examples of computer code include, but are not limited to, control signals, encrypted code, and compressed code.

[0046] In some variations, the signal processor 312 may comprise a memory configured to store data and / or information. In some variations, the memory may comprise one or more of random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), memory buffer, erasable programmable read-only memory (EPROM), electrically erasable read-only memory (EEPROM), read-only memory (ROM), flash memory, volatile memory, non-volatile memory, combinations thereof, and the like. Some variations described herein may relate to a computer storage product having a non-transitory computer-readable medium (which may also be referred to as a non-transitory processor-readable medium) having thereon instructions or computer code for performing various computer-implemented operations. The computer-readable medium (or processor-readable medium) is non-transitory in the sense that it does not itself include a transient propagating signal (e.g., a propagating electromagnetic wave that propagates information over a transmission medium such as space or cable). The media and computer code (which may also be referred to as code or algorithms) may be designed and constructed for a particular purpose or for multiple purposes.

[0047] In response to changes in the measurement area 316, the optical sensor 302 may be configured to transmit one or more sensor signals (e.g., mode shift, baseline drift, mode splitting, mode broadening) as optical signals to the optical detector. The optical detector may be configured to convert the optical signals into a number of sensor responses (e.g., electrical signals). The electrical signals indicative of the sensor responses may be transmitted to the signal processor 312. In some variations, the optical detector (not shown in FIG. 3) may be communicatively coupled to the signal processor 312 via a computing device and / or a network (not shown in FIG. 3).

[0048] In some variations, the signal processor 312 may be configured to analyze the sensor responses using methods such as those described below (e.g., by isolating or otherwise distinguishing individual physical signals and / or by collectively analyzing multiple sensor responses to determine individual physical signals). The signal processor 312 may be further configured to generate measurement signals that may correspond to (e.g., be indicative of) individual physical signals. In this manner, the signal processor 312 may be configured to detect multiple physical signals.

[0049] How to detect multiple physical signals In some variations, a method of detecting multiple physical signals may include receiving a sensor signal from a single optical sensor proximate to a measurement area. Multiple sensor responses may be determined from the sensor signal. Multiple measurement signals may be generated from the multiple sensor responses, each measurement signal may be indicative of a different physical signal of the measurement area. These multiple measurement signals may be generated by various techniques, such as isolating individual physical signals and / or collectively analyzing the multiple sensor responses to determine individual physical signals, as described further below.

[0050] 4 is a flow chart of an example variation of a method 400 for detecting multiple physical signals using a single optical sensor. The method 400 may include receiving a sensor signal from a single optical sensor proximate a measurement area (402), determining multiple sensor responses from the sensor signal (404), and generating multiple measurement signals from the multiple sensor responses (406). Each measurement signal may be indicative of a different respective physical signal of the measurement area. The method may be performed, for example, by a signal processor (e.g., structurally and / or functionally similar to signal processor 312 of FIG. 3) that may receive a sensor signal from a single optical sensor proximate a measurement area (e.g., structurally and / or functionally similar to optical sensor 102 of FIG. 1, optical sensor 202 of FIG. 2, or optical sensor 302 of FIG. 3).

[0051] FIG. 5 shows a schematic diagram of an exemplary variation of an optical sensor 502 for detecting multiple physical signals. Physical characteristics of a measurement area proximate to the optical sensor 502 may be reflected in the sensor response of the optical sensor 502. For example, the optical sensor 502 may be configured to detect physical characteristics (e.g., physical signals) of the measurement area, such as acoustic waves (e.g., reflected acoustic waves), temperature, and pressure. These characteristics are shown as physical signals 521a, 521b, 521n, etc. (commonly referred to as physical signals 521). In response to the physical signals, the optical sensor 502 may generate a sensor signal 525 including one or more sensor responses, such as mode shift, baseline drift, mode splitting, mode broadening, etc. These sensor responses are shown as sensor responses 523a, 523b, 523m, etc. (commonly referred to as sensor responses 523). The sensor signal 525 may include all sensor responses 523a, 523b, 523m, etc. output by the optical sensor 502.

[0052] The detection of multiple physical signals by the optical sensor 502 is noted as follows: y i =T i (x1,x2,…x n ), i=1,2,…m(1) In the formula, {x i} represents a physical signal, and {y i} represents the sensor response, and {T i} represents a system transformation. In general, x i Or y i Either of these can be a function of time, but can also be a simple variable. i can be either linear or non-linear.

[0053] In some variations, each sensor response 523 may be associated with (e.g., may be more sensitive to or responsive to) a given physical signal 521. For example, sensor response 523a may be more sensitive to physical signal 521a, while sensor response 523b may be more sensitive to (e.g., more closely associated with) physical signal 521b. In some variations, multiple sensor responses may be associated with a given physical signal.

[0054] As an illustrative example of how different sensor responses can be related to different physical signals, Figures 6A-6C show plots illustrating three exemplary sensor signals generated by an exemplary WGM resonator in response to different physical signals (temperature and pressure) in a measurement region. The horizontal axis of each plot represents wavelength in nm, and the vertical axis represents the amplitude of the WGM resonator optical output.

[0055] 6A shows a sensor signal under conditions of temperature T=t0 and pressure P=p0 in the measurement region. As can be seen in this plot, the sensor signal may have two sensor responses, one for the resonant frequency and one for the baseline value. For example, the sensor signal may have a first sensor response representing four resonant frequencies at approximately 932 nm, approximately 935.3 nm, approximately 938.7 nm, and approximately 942 nm, and a second sensor response representing a baseline of approximately 590 units of amplitude.

[0056] FIG. 6B shows the sensor signal in response to a pressure change in the measurement region: P=p0+Δp. As can be seen in this plot, the baseline (e.g., sensor response) is significantly shifted to an amplitude of about 540 units relative to the baseline amplitude shown in FIG. 6A. However, the resonant frequency is hardly reduced compared to that shown in FIG. 6A. Thus, FIG. 6B shows that the baseline shift is a sensor response that is more sensitive to pressure than the mode shift. In other words, the baseline of the WGM resonator response may be more suitable for detecting pressure variations. In some variations, the sensor response (e.g., baseline) may be expressed as a percentage of the change in the sensor response as the pressure changes. For example, the baseline may be expressed as a percentage of the change in the baseline from P=p0 to P=p0+Δp.

[0057] FIG. 6C represents a sensor signal in response to a temperature change in the measurement region: T=t0+Δt. In FIG. 6C, the resonant frequencies are each significantly decreased by more than 0.7 nm (e.g., at least about 0.007%) compared to those shown in FIG. 6A, while the baseline is only very slightly increased to an amplitude of about 600 units compared to those shown in FIG. 6A. Thus, FIG. 6C shows that the mode shift is a sensor response that is more sensitive to temperature than the baseline shift. In other words, the resonant frequency shift may be more suitable for detecting temperature variations. In some variations, the sensor response (e.g., frequency shift) may be expressed as a percentage of the change in the sensor response when the pressure changes. For example, the mode shift may be expressed as a percentage of the change in the mode shift from T=t0 to T=t0+Δt.

[0058] In addition to being more sensitive to a particular physical signal, the sensor response may have at least one sensitivity region for that physical signal in that it may have a region where the sensor response changes particularly rapidly (for a given slope threshold) in response to a change in the physical signal. FIG. 7A is an example plot showing an example sensor response curve with sensitivity regions. As can be seen in FIG. 7A, at lower values ​​of the physical signal below value A, the sensor response increases slowly with increasing physical signal. However, at the sensitivity region of the optical sensor (the segment of the sensor response curve indicated by the two vertical bars corresponding to parameter values ​​A and B of the physical signal), the slope of the sensor response curve becomes steeper, indicating a more rapid increase in the sensor response for each unit increase in the physical signal between values ​​A and B of the physical signal. At higher values ​​of the physical signal above value B, the sensor response again increases slowly with increasing physical signal.

[0059] Additionally or alternatively, the sensor response may have at least one dead zone for the physical signal in that it may have a region where the sensor response changes relatively slowly in response to a change in the physical signal. FIG. 7B is an example plot showing an example sensor response curve with a dead zone. As seen in FIG. 7B, at lower values ​​of the physical signal below value C, the sensor response increases rapidly with an increase in the physical signal. However, in the dead zone of the optical sensor (a segment of the sensor response curve is shown by two vertical bars corresponding to parameter values ​​C and D of the physical signal), the slope of the sensor response curve is about zero, indicating that the sensor response changes little or not at all per unit increase in the physical signal. At higher values ​​of the physical signal above value D, the sensor response again increases more rapidly with an increase in the physical signal.

[0060] Thus, as described above, a method for multi-dimensional sensing may include generating measurement signals from the sensor responses, each of which may be indicative of a respective physical signal. For example, the signal processor may generate a temperature measurement signal based at least in part on the resonant frequency shift (e.g., mode shift) and a pressure measurement signal based at least in part on the baseline drift. Described in further detail below are exemplary variations of generating measurement signals from the sensor responses, including isolating individual physical signals and / or collectively analyzing multiple sensor responses to determine individual physical signals.

[0061] Separation of individual physical signals As discussed above, each sensor response may be relatively sensitive to a given physical signal. Thus, in some variations, measurement signals of different physical signals may be generated by separating out the individual physical signals, which may include analyzing each sensor response over a predetermined period of time and generating a measurement signal of the physical signal that is most correlated to that sensor response. In this manner, the separated physical signals may be distinguished from one another and analyzed separately by analyzing the separated (e.g., separated) sensor responses.

[0062] Additionally, as discussed above, a sensor response may be relatively sensitive to a particular physical signal (e.g., mode shift may be sensitive to temperature, while baseline drift may be more sensitive to pressure). Thus, a method of sensing multiple physical signals may include correlating one sensor response to one physical signal. For example, the method may include correlating mode shift to a temperature measurement and baseline drift to a pressure measurement. Following this correlation, a sensor response (output of an optical sensor) may be selected for processing such that the analyzed sensor response is correlated to a target physical signal (e.g., input to a photodetector).

[0063] For example, Figure 8 is an example schematic diagram of a system 800 for separating individual physical signals. System 800 may include an optical sensor 802 (e.g., structurally and / or functionally similar to optical sensor 102 of Figure 1, optical sensor 202 of Figure 2, or optical sensor 302 of Figure 3) communicatively coupled to a signal processor 812 (e.g., structurally and / or functionally similar to signal processor 312 of Figure 3).

[0064] The system may also include a multiplexer 828 configured to control the selection and output of one or more sensor responses from a set of sensor responses (e.g., collectively referred to as sensor responses) to the signal processor 812. In some variations, the multiplexer 828 may comprise a time division multiplexer. Thus, the multiplexer 828 may be configured to selectively connect individual sensor response channels to the signal processor 812 for each time period. For example, the multiplexer 828 and the signal processor 812 may be configured to output a first sensor response during a first time period and a second sensor response during a second time period. The signal processor 812 may additionally be configured to output a third sensor response during a third time period.

[0065] Thus, although the optical sensor 802 may be configured to generate multiple sensor responses, due to the multiplexer 828, the signal processor 812 may be configured to process only one sensor response at any given time. For example, in FIG. 8, the signal processor 812 may process a sensor response 823a from time t0 to t1, a sensor response 823b from time t1 to t2, and a sensor response 823c from time t1 to t2. m-1 ~t m Sensor response of 823 mConsidering that sensor response 823a may be most sensitive to physical signal 821a, sensor response 823b may be most sensitive to physical signal 821b, and sensor response 823m may be most sensitive to physical signal 821n. Thus, the signal processor 812 may be configured to process the measurement signal of physical signal 821a over time t0-t1, the measurement signal of physical signal 821b over time t1-t2, and the measurement signal of physical signal 821b over time tm. -1 ~t m Over 823 m In some variations, after each of the sensor responses has been processed at least once for a predetermined period of time, the signal processor 812 may be configured to process the first sensor response 823a again and continue to analyze the responses until the separation process is completed. In some variations, the signal processor 812 may be configured to process the sensor responses in one of at least two modes: a continuous / endless mode or a finite duration mode. In the continuous mode, each of the sensor responses may be processed at least once and repeatedly (e.g., a series of repeated sensor responses 823a-823m, either continuously or in any suitable series) until the signal processor 812, the optical sensor 802, and / or the system 800 are shut down (e.g., by a user). In the finite duration mode, the signal processor 812 may be configured to analyze the sensor responses for a predetermined amount of time. For example, all of the sensor responses may be processed at least once, and the signal processor 812 may be configured to process the first response 823a again and continue to analyze the responses until a predetermined amount of time has passed (e.g., two hours or other suitable period, which may additionally or alternatively be expressed as the predetermined number of times each sensor response is processed). In this manner, the signal processor 812 may be configured to separate the individual physical signals using time division multiplexing. Given a sufficiently high switching speed of the multiplexer, it may be possible to detect multiple physical signals in real time or near real time without losing information.

[0066] In some variations, the sequence of selecting individual sensor responses for processing by the signal processor may be pre-determined. For example, the signal processor may alternate between two sensor responses or may repeatedly process three or more sensor responses in the same sequential order. As another example, certain physical signals known to have an inherently slower rate of change may be sampled at a lower rate for processing (e.g., in some applications of a certain type of measurement area, it may be known that the temperature of the measurement area changes may not vary as fast as the pressure). As another example, in some applications, certain physical signals whose values ​​are more important to measure in real time may be sampled at a higher rate for processing compared to less important physical signals in order to prioritize the more important physical signals for measurement.

[0067] Additionally or alternatively, the time period (e.g., duration of analysis) for which each sensor response is processed by the signal processor may be pre-determined. For example, it may be pre-determined that all sensor responses may be processed for equal time periods. As another example, certain physical signals that are known to have an inherently slower rate of change or are less critical (at least in some applications) may be processed for shorter time periods.

[0068] Additionally or alternatively, the sequence in which individual sensor responses are selected for processing by the signal processor and / or the amount of time each sensor response may be processed may be determined, at least from time to time, in real time by the signal processor 812. In some variations, the sequence in which the sensor responses are processed and / or the amount of time each sensor response is processed may be based, at least in part, on a closed-loop algorithm. For example, a rate of change of a physical signal over a particular period of time may be fed into a closed-loop algorithm to dynamically adjust the frequency with which the signal processor processes the sensor responses corresponding to that physical signal and / or the overall amount of time the signal processor processes the sensor responses corresponding to that physical signal. For example, in response to a physical signal that recently began to change rapidly, the signal processor may process the sensor responses corresponding to that physical signal more frequently and / or for a longer period of time in order to more closely monitor the physical signal in real time.

[0069] 11 is another example variation of a system 1100 for distinguishing between physical signals. System 1100 may include an optical sensor 1102 (e.g., structurally and / or functionally similar to optical sensor 102 of FIG. 1, optical sensor 202 of FIG. 2, or optical sensor 302 of FIG. 3) communicatively coupled to a signal processor 1112 (e.g., structurally and / or functionally similar to signal processor 312 of FIG. 3).

[0070] The system may also include multiple multiplexers, for example, a first multiplexer 1128 (e.g., structurally and / or functionally similar to multiplexer 828) and a second multiplexer 1130. In some variations, the multiplexers may be synchronized. For example, if the physical signal of interest to be measured is temperature, then the second multiplexer 1130 may be switched to detect temperature, and the first multiplexer 1128 may be synchronized with the second multiplexer 1130 to select the sensor response mode shift for processing / analysis. However, if the target physical signal is measured in pressure, then the second multiplexer 1130 may be switched to detect pressure, and the first multiplexer 1128 may be synchronized with the second multiplexer 1130 to select the sensor response baseline drift for processing / analysis. In this manner, correlating the sensor response to the physical signal and using a multiplexer to select a target physical signal and a target sensor response may reduce and / or minimize interference from other physical signals and enable the system 1100 to accurately measure the target physical signal.

[0071] In some variations, the sensor response may be correlated to a physical signal based at least in part on other known information. For example, in some variations, multiple possible physical signals may contribute to a particular sensor response, but the relative sensitivity of the optical sensor to those physical signals may be known and may be used to help distinguish or differentiate between different physical signals. For example, an optical sensor may inherently have a sensor response (e.g., mode shift) to both temperature and acoustic waves, but with different known sensitivities to each of these physical signals due to the nature of the environment around the sensor. A temperature signal may be differentiated from an acoustic wave signal, for example, based on the rate of change of the sensor response and the relative sensitivity of the sensor to temperature and pressure. For example, if the optical sensor is placed in a thermally insulating environment and is thereby somewhat insensitive to temperature changes, then a rapid change to mode shift may be more indicative of an acoustic wave signal than a temperature signal. In contrast, if the optical sensor is adjacent to or embedded in a damping material, a rapid change to mode shift may be more indicative of a temperature signal than an acoustic wave signal.

[0072] Additionally or alternatively, in some variations, other known information used to help distinguish between different physical signals may include a typical frequency range of the sensor response. For example, one or more predefined thresholds of the frequency of the sensor response may be used to help distinguish between different physical signals. As an illustrative example, as described above, an optical sensor may inherently have a sensor response (e.g., mode shift) to both temperature and acoustic waves. Thus, in some variations, a mode shift (e.g., frequency shift, depth change, shape change) with a frequency above a predefined threshold (e.g., above about 500 kHz) may be more indicative of an acoustic wave signal than a temperature signal. In contrast, a mode shift with a frequency below a predefined threshold (e.g., below about 500 kHz) may be more indicative of a temperature signal than an acoustic wave signal. In some variations, a single predefined threshold may be used to distinguish between physical signals (e.g., a sensor response with a characteristic above a threshold corresponds to or is indicative of a first physical signal, and a sensor response with a characteristic below the same threshold corresponds to or is indicative of a second physical signal). Alternatively, in some variations, multiple predefined thresholds can be used to distinguish between physical signals. For example, a sensor response having characteristics above a first threshold may correspond to (e.g., indicate) a first physical signal, and a sensor response having characteristics below a second threshold that is lower than the first threshold may indicate a second physical signal. However, a sensor response having characteristics between the first and second thresholds may be treated as indicating either the first or second physical signal, and further analysis (e.g., one of the other methods described herein) may be used to further distinguish between the first and second physical signals.

[0073] In some variations, isolating the individual physical signals may additionally or alternatively include modifying an environment proximate the optical sensor to selectively increase the salience of a sensor response associated with a target physical signal, either by making the environment more sensitive to the target physical signal or by making the environment less sensitive to all physical signals other than the target physical signal. FIG. 9 is an exemplary variation of a system 900 for isolating individual physical signals by modifying the optical sensor's environment. System 900 may include an optical sensor 902 (e.g., structurally and / or functionally similar to optical sensor 102 of FIG. 1, optical sensor 202 of FIG. 2, or optical sensor 302 of FIG. 3) located within an environment 916 (e.g., polymeric packaging, other surrounding packaging) and communicatively coupled to a signal processor 912 (e.g., including a signal processor structurally and / or functionally similar to signal processor 312 of FIG. 3). The optical sensor 902 may be proximate to an environment 916 (eg, may be structurally and / or functionally similar to the measurement area 316 of FIG. 3).

[0074] In FIG. 9, the signal processor of signal processor 912 may first process all sensor responses corresponding to physical signals, analyze these sensor responses, and generate an environmental control signal to modify one or more physical characteristics of the environment based on the identity of at least one targeted physical signal. For example, signal processor 912 may provide instructions to the system to modify environment 916 such that one or more physical signals different from the targeted physical signal are suppressed. For example, suppression of a physical signal may include adjusting the environment such that physical signals (not targeted for measurement) are within a relatively low sensitivity signal region of the optical sensor. The signal processor may then process the sensor responses from the modified environment to generate a measurement signal of the targeted physical signal(s) that is more prominent given the suppression of the non-targeted physical signal(s).

[0075] For example, to make the temperature-related physical signal more prominent to enable more accurate temperature measurements, it may be advantageous to suppress the pressure-related physical signal by reducing or eliminating undesired pressure fluctuations in the sensor environment 916. Reducing or eliminating the environmental pressure change may be performed, for example, by detecting the current pressure and then adjusting the environmental pressure accordingly in a feedback manner using the signal processor 912 (e.g., moving the environmental pressure level into the dead zone of the optical sensor's baseline sensor response). When the environmental pressure is in the dead zone, the signal processor may generate a measurement signal based on the sensor response associated with temperature (e.g., mode shift). The method of modulation of the environmental pressure may depend on the structure of the sensor package. For example, in some variations, the optical sensor may be disposed in a cavity (or between two plates), and a fluid (gas, liquid) may be selectively introduced and / or withdrawn from the cavity using one or more controllable fluid valves and / or one or more pressurized sources (e.g., positive pump, vacuum pump). In this example, the environmental pressure may be increased by introducing additional fluid into the cavity and / or reduced by withdrawing fluid from the cavity. As another example, in some variations, the optical sensor may be disposed within the cavity (or between two plates) and surrounded by a fluid (gas, liquid), with the cavity volume being adjustable by one or more actuators. In this example, the environmental pressure may be increased by reducing the cavity volume (e.g., moving the cavity walls inward, compressing the deformable cavity) and / or reduced by increasing the cavity volume (e.g., moving the cavity walls outward).

[0076] As another example, it may be advantageous to suppress the temperature-related physical signal by reducing or eliminating undesired temperature fluctuations in the sensor environment to make the pressure-related physical signal more prominent to enable more accurate pressure measurements. Undesired temperature fluctuations may be eliminated and / or reduced, for example, by adjusting the environment 916 to move its temperature level into a dead zone of the mode-shifting sensor response of the optical sensor with the signal processor 912. For example, the signal processor 912 may provide feedback / instructions to modify the environment such that the temperature level may be moved into the dead zone. Once the temperature level reaches the dead zone, the signal processor may measure the pressure and / or extract information related to the pressure from the sensor response (e.g., baseline drift) that correlates to the pressure. The method of modulation of the environment temperature may depend on the structure of the sensor package. For example, in some variations, the temperature of the environment surrounding the sensor may be reduced by insulating the environment (e.g., by using insulating materials such as fiberglass, mineral wool, polyurethane, etc., or by passing a fluid with thermal insulating properties in contact with or near the sensor). As another example, in some variations, the temperature of the surrounding environment may be increased by using a thermally conductive material for the surrounding environment (e.g., copper, graphite, or by passing a fluid with thermally conductive properties in contact with or near the sensor).

[0077] As another example, in some variations it may be advantageous to modify the acoustic properties of the sensor's environment such that physical signals associated with acoustic waves (e.g., acoustic waves reflected from a measurement region) are suppressed, which may allow another target physical signal (e.g., temperature, pressure) to be measured more accurately. For example, a suitable actuator may move a damping material towards or near an optical sensor such that incident acoustic waves that would otherwise be detected are instead attenuated (e.g., suppressed).

[0078] Additionally or alternatively, it may be possible to increase the sensitivity of an optical sensor to a particular input physical signal (e.g., to "tune" the optical sensor to a target physical signal). For example, the sensitivity of an optical sensor to a target physical signal may be increased, at least in part, by adjusting the sensor's environment such that the target physical signal is in a relatively high sensitivity signal region of the optical sensor.

[0079] For example, the sensitivity of pressure detection may be increased by adjusting the environment 916 such that the pressure level of the environment 916 falls within the sensitivity region of the baseline drift curve. As discussed above, in some variations, the baseline drift is the sensor response that is most sensitive to changes in pressure. Thus, the signal processor 912 may provide feedback / instructions such that the pressure level in the environment is altered to fall within the sensitivity region of the sensor's response curve. The method of modulation of the environmental pressure may depend on the structure of the sensor package. For example, any of the techniques described above (e.g., control of fluid in and / or outside the cavity containing the sensor, control of the volume of the fluid-filled cavity containing the sensor) may be implemented to modulate the environmental pressure such that the environmental pressure is within the sensitivity region of the optical sensor, and the optical sensor is tuned to measure the pressure of the measurement region with higher sensitivity. Thus, when the pressure level falls within the sensitivity region, the signal processor may measure the pressure and / or extract information (e.g., related to pressure from the baseline drift).

[0080] FIG. 10 illustrates an exemplary variation of a system 1000 for modifying an environment by adjusting the pressure of the environment. In some variations, the system 1000 may include an optical sensor 1002, a signal processor 1012, a digital-to-analog converter 1037, and a voltage-to-pressure converter 1033. The optical sensor 1002 (e.g., structurally and / or functionally similar to the optical sensor 102 of FIG. 1, the optical sensor 202 of FIG. 2, or the optical sensor 302 of FIG. 3) may be communicatively coupled to the signal processor 1012 (e.g., structurally and / or functionally similar to the signal processor 312 of FIG. 3). The optical sensor 1002 may be configured to generate a sensor signal after detecting a pressure change in the environment and may transmit the sensor signal to the signal processor 1012. In some variations, the signal processor 1012 may be configured to process the sensor signal to generate digital control instructions. In some variations, the digital control instructions may include instructions to modify the environment by adjusting pressure levels to increase or decrease the sensitivity of the optical sensor 1002 for accurate pressure or temperature measurements. The digital-to-analog converter 1037 may be configured to convert the digital control instructions into an analog voltage signal. The analog voltage signal may be transmitted to the voltage-to-pressure converter 1033. In some variations, the voltage-to-pressure converter 1033 may be configured to generate a desired pressure (e.g., a target pressure included in the digital control instructions) to increase or decrease the sensitivity of the optical sensor 1002 for accurate pressure or temperature measurements.

[0081] As discussed above, if the system 1000 is incorporated into an application requiring accurate sensing of temperature, it may be advantageous to adjust the pressure within the dead zone. However, if the system 1000 is incorporated into an application requiring accurate sensing of pressure, it may be advantageous to adjust the pressure within the sensitive zone. For example, to increase sensitivity and adjust the pressure within the sensitive zone, the pressure may be increased in the same direction as the pressure change. For example, if the pressure within the environment increases from 100 KPa to 101 KPa, an additional 2 KPa of pressure may be added to the pressure within the sensitive zone to create a pressure of 103 KPa, so that the pressure falls within the sensitive zone. However, if the sensitivity changes such that the pressure is within the dead zone, the pressure may be reduced to follow the direction of the pressure change. For example, if the pressure in the environment decreases from 100 KPa to 98 KPa, an additional 1 KPa of pressure may be added to the pressure in the environment to create a pressure of 99 KPa. In some variations, the pressure in the environment may be kept constant at 100 KPa.

[0082] Similarly, as another example, referring again to FIG. 9, the sensitivity of temperature detection may be increased by adjusting the environment 916 so that the temperature of the environment is within the sensitivity region of the mode shift curve. As discussed above, in some variations, the mode shift is the sensor response that is most sensitive to changes in temperature. Thus, the signal processor 912 may be configured to provide feedback / instructions so that the temperature of the environment is altered to be within the sensitivity region of the sensor's response curve. The manner of temperature modulation may depend on the structure of the sensor package. For example, any of the above systems or techniques may be used to heat or cool the sensor environment (e.g., using insulating or thermally conductive materials) toward the sensitivity region of the sensor.

[0083] Additionally or alternatively, in some variations, detection of acoustic waves may be selectively enhanced by conditioning the environment such that one or more acoustic properties of the environment are improved or optimized. For example, in some variations, a suitable actuator may be configured to move an acoustic matching material toward or near the optical sensor to improve transmission and / or reduce attenuation of incident acoustic waves that may otherwise be difficult to detect.

[0084] Thus, the separation may include selectively modifying the environment based on the target physical signal being measured. As discussed above, modifying the environment may include suppressing physical signals that are not the target physical signal by adjusting the physical signals that are suppressed within the blind zone. Alternatively, modifying the environment may include increasing the sensitivity of the target physical signal. In other words, the environment may be adjusted such that the target physical signal may be within the sensitivity zone.

[0085] Collective analysis of multiple sensor responses In some variations, multiple sensor responses may be collectively analyzed to determine a measurement signal of an individual physical signal. FIG. 12 is a schematic block diagram of an example variation of a system 1200 for collectively analyzing multiple sensor responses to determine an individual physical signal. The system may include an optical sensor 1202 (e.g., structurally and / or functionally similar to the optical sensor 102 of FIG. 1, the optical sensor 202 of FIG. 2, or the optical sensor 302 of FIG. 3) communicatively coupled to a signal processor 1212 (e.g., structurally and / or functionally similar to the signal processor 312 of FIG. 3). The signal processor 1212 may be coupled to the parameter estimator 1250 or may be included in the signal processor 1212.

[0086] In some variations, the optical sensor 1202 may convert n input physical signals into m distinct output response signals, as described above. The signal processor 1212 may be configured to perform a series of signal processing steps, including amplification, analog-to-digital conversion, and filtering of the sensor signals. The parameter estimator 1250 may be configured to estimate a set of target physical signal parameters using either a theoretical model or an empirical model.

[0087] For example, the sensor response y i Using the physical signal x i Solve the equation: i and y i are related by Equation 1 and may represent the process of combining multiple responses. Alternatively, the physical signal x i can be solved as follows: x i =T i -1 (y1,y2,…y m ), i=1,2,…n(2) In the formula, T i -1 represents the inverse system transformation.

[0088] In some variations, x i and i It can be assumed that both are simple variables, but can be real or complex variables. Additionally, it can be assumed that the system described by Equation 1 in FIG.

[0089] The first assumption is based on all signals being constant or slowly varying functions. However, for fast varying functions, the assumption is still valid if the time interval is short enough. The second assumption is based on the system 1200 being stable and the range of all signals being small enough to ensure linearity. For a wide range of signals, the wide nonlinear range can be divided into several small linear regions.

[0090] Using the above two assumptions, Equation 1 can be rewritten as: [Number] (3) wherein ij is a coefficient determined by a multi-dimensional sensor. Equation 3 can be further simplified by using the following elegant determinant: y = Ax (4) where x is an n-dimensional vector, y is an m-dimensional vector, and A is an m×n matrix.

[0091] To solve Equation 4, there are three different scenarios depending on the values of m and n. Each scenario requires a different approach and leads to different results.

[0092] Scenario 1: Under-determined system. In this case, n > m, or there are more unknowns than equations. An under-determined system either has no solution or has infinitely many solutions. Therefore, this scenario may not be further considered as it cannot yield useful results for practical applications.

[0093] Scenario 2: Critical system. In this case, n = m, or there are the same number of equations as the number of unknowns. Mathematically, it can be proven that a critical system always has a unique solution if all the equations are completely independent of each other. The solution to an important system can be obtained as follows: x = A -1 y (5) where A -1 is the reciprocal of A. However, if there are at least two dependent equations, the critical system is reduced to an under-determined system.

[0094] Scenario 3: Over-determined system. In this case, n < m, or there are more equations than unknowns. According to linear system theory, an over-determined system generally has no solution, but may have a solution in some cases, for example, some of the equations are not completely independent. An over-determined system can become either a critical system or an under-determined system depending on the number of dependent equations it contains.

[0095] For most real overdetermined systems, exact solutions do not exist, but approximate solutions can be obtained in a number of different ways. For example, using least squares methods, an approximate solution can be obtained by: x=(A T A) -1 A T y(6) In the formula, A T is the transpose of A.

[0096] Based on the above considerations, the detection of a physical signal or parameter essentially involves the use of matrices A, A -1 , A T , and (A T A) -1 A T The matrix can be calculated either theoretically or empirically.

[0097] The theoretical approach may include three steps: First, a physical or theoretical model may be developed. Second, a set of equations may be derived using the model. Third, these equations may be linearized.

[0098] The empirical approach may also include three steps. First, a general linear system model may be constructed. Second, experiments may be conducted to generate data. Third, the coefficients of the system equation may be estimated using the experimental data.

[0099] Optical Sensor Array As mentioned above, in some variations, a system for multidimensional sensing may include an array of two or more multidimensional optical sensors, each of which is capable of performing multidimensional sensing as described herein. The methods disclosed herein can be extended from a single optical sensor to an array of optical sensors.

[0100] In some variations, each sensor in an array of optical sensors may be the same type of optical sensor. For example, each sensor in the array may be an optical sensor that may be more sensitive to one type of physical signal (e.g., temperature, pressure, acoustic waves) than other types of physical signals. In such a scenario, the entire array of sensors may be configured to measure one physical signal with higher precision or accuracy. For example, the entire array of sensors may be configured to measure temperature with higher precision, or the entire array of sensors may be configured to measure pressure with higher precision. In some variations, having two or more optical sensors configured to target measurements of the same physical signal may be advantageous to combine similar sensor signals together to "boost" the sensor signals and / or system redundancy (e.g., fault tolerance in the event of a sensor failure).

[0101] Alternatively, some sensors in the array of sensors may be configured to target measurement of a different physical signal than the remaining sensors in the array of sensors (e.g., to have different sensitivities to various physical signals, such as by configuring the environment surrounding such sensors, as described above). For example, a first portion of the optical sensors may be configured to be more sensitive to a first physical signal (e.g., temperature), while a second portion of the optical sensors may be configured to be more sensitive to a second physical signal (e.g., pressure). Furthermore, any suitable number of portions of the array may be configured to be more sensitive to any suitable physical signal (e.g., additionally, a third portion of the optical array may be more sensitive to a third physical signal).

[0102] At least some of the optical sensors that are sensitive to the same physical signal may be grouped together (e.g., one line or cluster of sensors in the array may be sensitive to a first physical signal, and a second line or cluster of sensors in the array may be sensitive to a second physical signal). Additionally or alternatively, at least some of the optical sensors that are sensitive to the same physical signal may be distributed equally or unevenly (e.g., sparse or staggered, or randomly distributed), which may allow, for example, a larger area of ​​sensing coverage for each physical signal.

[0103] The sensitivity of the optical sensors can be modulated in any suitable manner, including those described herein, such as by the configuration of the environment surrounding each optical sensor to tune the sensitivity of that optical sensor to one or various physical signals (e.g., to be more or less sensitive to a physical signal). Such configuration of the environment may be dynamic (e.g., dynamically adjusted in real time according to a desired measurement or sensing function) or may be permanently built into the design of the array (e.g., a first portion of the optical sensors may always be configured to be more sensitive to a first physical signal, and a second portion of the optical sensors may always be configured to be more sensitive to a second physical signal).

[0104] In some variations, at least some of the optical sensors may be adjacent (e.g., embedded or otherwise proximate) to a surrounding environment that enhances the physical signal measured by the optical sensors. For example, the surrounding environment of at least some of the sensors may be made thermally insulating and / or thermally conductive such that the temperature of the surrounding environment falls within the sensitivity region of the sensors such that they are more sensitive to temperature.

[0105] In some variations, some sensors in an array (e.g., arrays of the same type of sensors or different types of sensors) may have an ambient environment that suppresses one or more physical signals other than those measured by their optical sensors. For example, some sensors may be shielded with a rigid barrier so that they may be shielded from pressure changes, and such sensors may be more sensitive to, for example, temperature signals. As another example, some sensors may be shielded with an attenuating barrier to shield the sensors from acoustic waves, and such sensors may be more sensitive to, for example, pressure signals.

[0106] In some variations, the system may include one or more reference sensors configured to provide a reference sensor signal. For example, the reference sensor may be an optical sensor in the optical array (e.g., an array of sensors of the same type or different types) or may be a non-optical sensor (e.g., a thermocouple, a force transducer, a piezoelectric element). The reference sensor may help differentiate between different physical signals. For example, the reference sensor may have a predetermined or known sensitivity to a particular physical signal of interest (e.g., pressure, temperature, acoustic waves, combinations thereof, etc.). Thus, the reference sensor may be used to calibrate one or more optical sensors in the optical array and / or to verify the sensitivity of other optical sensors in the optical array. For example, if the reference sensor is more sensitive to temperature in a predetermined frequency range, the output of the reference sensor may be analyzed to evaluate the sensor response in that predetermined frequency range. A sensor that may be similar to the reference sensor may be calibrated based on the sensor response of the reference sensor.

[0107] In some variations, using more than one sensor may help differentiate between two physical signals. For example, an optical array having a first optical sensor may be configured to provide a first sensor signal (and a first plurality of sensor responses), and a second optical sensor may be configured to provide a second sensor signal (and a second plurality of sensor responses). In some variations, the first optical sensor and the second optical sensor may have different sensitivities to different physical signals. Using such an optical array, a method of multidimensional sensing may further include generating a first measurement signal indicative of a first physical signal (e.g., a target physical signal), the first measurement signal being based on (i) the first plurality of sensor responses to the first optical sensor, (ii) the second plurality of sensor responses to the second optical sensor, and (iii) the sensitivities of the first and second optical sensors to the first and second physical signals. Additionally, the method may include generating a second measurement signal indicative of the second physical signal using (i), (ii), and (iii).

[0108] As an illustrative example, consider a first optical sensor that may respond to both pressure and temperature signals. The sensor signal of the first sensor is proportional to the change in temperature by one unit (temperature sensitivity S 1T =1), and may change by one unit in response to a one unit pressure change (pressure sensitivity S 1P =1), it may change by one unit in response to a temperature sensitivity S of the first sensor. In such a scenario, if the sensor signal of the first sensor changes by two units, it may be difficult to distinguish whether the change is caused entirely by a two unit change in temperature, a two unit change in pressure, or a one unit change each in temperature and pressure. However, the response of the first sensor to twice the temperature (temperature sensitivity S 2T = 2), but in conjunction with the first sensor, has the same response to pressure (pressure sensitivity S 2P By using a second sensor with a temperature sensor having a capacitance of 1.0 μm / s, the temperature and pressure can be deconvoluted, as further shown in the table below. [Table 1]

[0109] As can be seen in the table above, in response to a one unit temperature change and a one unit pressure change, the total output of the first sensor is different from the total output of the second sensor. The change in temperature may be determined, for example, by the following sequence of equations: First, the outputs of the first and second sensors may be expressed as equations (7) and (8), respectively. O1=S 1T *ΔT+S 1P *ΔP(7) O2=S 2T *ΔT+S 2P *ΔP(8) From equations (7) and (8): ΔP = (O1-S 1T *ΔT) / S 1P (9) ΔP = (O2-S 2T *ΔT) / S 2P (10) By equating equations (9) and (10), the change in temperature can be derived as follows: (O2-S 2T *ΔT) / S 2P =(O1-S 1T *ΔT) / S 1P (11) S 1P (O2-S 2T *ΔT)=S 2P (O1-S 1T *ΔT)(12) S 1P O2-S 1P S 2T *ΔT=S 2P O1-S 2P S 1T *ΔT(13) S 1P O2-S 2P O1=S 1P S 2T *ΔT-S 2P S 1T *ΔT=(S 1P S 2T -S 2P S 1T )*ΔT(14) ΔT = (S 1P O2-S2P O1) / (S 1P S 2T -S 2P S 1T )(15)

[0110] Similarly, the change in pressure can be determined by the following sequence of equations: From equations (7) and (8) above: ΔT = (O1-S 1P *ΔP) / S 1T (16) ΔT = (O2-S 2P *ΔP) / S 2T (17) By equating equations (15) and (16), the change in pressure can be derived as follows: (O2-S 2P *ΔP) / S 2T =(O1-S 1P *ΔP) / S 1T (18) S 1T (O2-S 2P *ΔP)=S 2T (O1-S 1P *ΔP)(19) S 1T O2-S 1T S 2P *ΔP=S 2T O1-S 2T S 1P *ΔP(20) S 1T O2-S 2T O1=S 1T S 2P *ΔP-S 2T S 1P *ΔP=(S 1T S 2P -S 2T S 1P )*ΔP(21) ΔP = (S 1T O2-S 2T O1) / (S 1T S 2P -S 2T S 1P )(twenty two)

[0111] Equations (15) and (22) are solvable when the first optical sensor and the second optical sensor have different sensitivities such that the denominators of equations (15) and (22) are nonzero (S 1T S 2P ≠S 2T S 1P ). In other words, differential detection using multiple sensors with different sensitivities may be possible, for example, when (i) the product of the sensitivity of a first sensor to a first physical signal and the sensitivity of a second sensor to a second physical signal, and (ii) the product of the sensitivity of the second sensor to the first physical signal and the product of the sensitivity of the second sensor to the first physical signal, such that (i) and (ii) are not equal to each other. Thus, if equation (15) is solvable, a measurement signal of ΔT may be generated from the sensor response, and if equation (22) is solvable, a measurement signal of ΔP may be generated from the sensor response. Similar approaches may be used to differentiate other physical signals.

[0112] In the above equation, S 1T represents the sensitivity of the first sensor to temperature, and S 1P represents the sensitivity of the first sensor to pressure, and S 2P represents the sensitivity of the second sensor to pressure, and S 2T where O represents the sensitivity of the second sensor to temperature, O1 represents the output of the first sensor, and O2 represents the output of the second sensor. ΔT represents the change in temperature. ΔP, which represents the change in pressure, can be calculated in a similar manner as ΔT.

[0113] In this manner, the systems and methods described herein allow for accurate measurement of multiple physical signals using a single optical sensor. The techniques described herein may be used, for example, in devices during surgery or other medical procedures. For example, the techniques described herein may be used in applications that require simultaneous detection of temperature and pressure changes, such as monitoring multiple vital signs of a patient in real time during cardiac surgery to ensure patient safety.

[0114] In the foregoing description, for purposes of explanation, specific nomenclature was used to provide a thorough understanding of the invention. However, it will be apparent to one skilled in the art that specific details are not required to practice the present invention. Thus, the foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed, and obviously, many modifications and variations are possible in light of the above teachings. The embodiments were chosen and described in order to explain the principles of the invention and its practical application, thereby enabling those skilled in the art to utilize the invention and various embodiments with various modifications as suited to the particular use contemplated. It is intended that the following claims and their equivalents define the scope of the invention.

Claims

1. 1. A method for multidimensional sensing, comprising: receiving a sensor signal from a single optical sensor proximate to a measurement region; determining a plurality of sensor responses from the sensor signals; generating a plurality of measurement signals from the plurality of sensor responses, each of the measurement signals corresponding to a different respective physical signal of the measurement region.

2. a sensor response of the plurality of sensor responses: Mode shifting, including one or more of a change in resonant frequency, a change in depth, and a change in shape; Baseline drift, Mode division, Mode expansion, and 10. The method of claim 1, selected from the group consisting of one or more of any combination thereof.

3. The method of claim 1 , wherein the physical signals of the environment include two or more of a temperature, a pressure, and an acoustic wave of the environment.

4. The method of claim 1 , wherein generating the plurality of measurement signals further comprises isolating at least a portion of the physical signal.

5. Separating at least a portion of the physical signal analyzing a first sensor response of the plurality of sensor responses for a first time period; generating a first measurement signal for the first time period based on the first sensor response; analyzing a second sensor response of the plurality of sensor responses for a second time period; The method of claim 4 , further comprising: generating a second measurement signal for the second time period based on the second sensor response.

6. analyzing a third sensor response of the plurality of sensor responses for a third time period; The method of claim 5 , further comprising: generating a third measurement signal for the third time period based on the third sensor response.

7. 6. The method of claim 5, wherein the first sensor response includes a mode shift and the first measurement signal corresponds to a temperature, and the second sensor response includes a baseline shift and the second measurement signal corresponds to a pressure.

8. The method of claim 4 , wherein isolating at least a portion of the physical signals comprises selectively modifying the environment based on a target physical signal.

9. The method of claim 8 , wherein isolating at least a portion of the physical signals comprises suppressing one or more of the physical signals that are different from the target physical signal.

10. 10. The method of claim 9, wherein suppressing one or more of the physical signals comprises adjusting the environment such that the one or more physical signals different from the target physical signal are within a first sensitivity signal region of the optical sensor.

11. The method of claim 9 , wherein suppressing the one or more physical signals comprises modifying one or more of a temperature, a pressure, and an acoustic property of the environment.

12. The method of claim 8 , wherein isolating at least a portion of the physical signal comprises increasing the sensitivity of the optical sensor to the target physical signal.

13. 13. The method of claim 12, wherein increasing the sensitivity of the optical sensor comprises adjusting an environment of the optical sensor such that the target physical signal is within a second sensitivity signal range of the optical sensor that is different from the first sensitivity signal range.

14. Increasing the sensitivity analyzing a first sensor response of the plurality of sensor responses for a first time period associated with the first sensitivity signal region; and generating a first measurement signal corresponding to the target physical signal.

15. The method of claim 1 , wherein generating the plurality of measurement signals comprises applying a signal transformation function to the plurality of sensor responses.

16. The method of claim 15 , wherein the signal transformation function comprises a signal transformation matrix.

17. the sensor signal comprises a first sensor signal, the plurality of sensor responses comprises a first plurality of sensor responses, and the method further comprises: receiving a second sensor signal from a second optical sensor of the array of optical sensors; determining a second plurality of sensor responses from the second optical sensor; 10. The method of claim 1, further comprising: generating a first measurement signal indicative of a first physical signal, the first measurement signal being based on the first plurality of sensor responses to the first optical sensor, the second plurality of sensor responses to the second optical sensor, and sensitivities of the first and second optical sensors to the first and second physical signals.

18. The method of claim 1 , wherein the plurality of measurement signals are generated based at least in part on a reference signal from a reference sensor.

19. 10. The method of claim 1, wherein the optical sensor comprises one or more of an interference-based optical sensor, an optical resonator, an optical interferometer, a whispering gallery mode (WGM) resonator, a microbubble optical resonator, a microsphere resonator, a microtoroid resonator, a microring resonator, and a microdisk optical resonator.

20. 1. A system for multidimensional sensing of a measurement area, comprising: an optical sensor; A signal processor configured to perform the method of any one of claims 1 to 19.

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