Systems and methods for monitoring an analyte or parameter for a patient

Abstract

A sensor system includes a probe and a photon source configured to direct photons at the probe. The probe can emit light in response to receiving the photons. The sensor system can include a photodetector configured to detect light emitted from the probe, and the photon source is configured to emit photons according to a first time-varying intensity profile having a first frequency. A controller can be configured to receive optical data from the photodetector based on an interaction between the light emitted from the probe and the photodetector. The optical data can include a second time-varying intensity profile having a second frequency. The second frequency can be substantially the same as the first frequency. The controller can be configured to determine a phase difference between the first time-varying intensity profile and the second time-varying intensity profile, and generate a report based on the phase difference.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Patent Application No. 63 / 073,426, filed September 1, 2020, entitled "System and Methods for Multi-Dye Frequency Fluorimetry and Phosphorimetry," which is incorporated herein by reference in its entirety.

[0003] Statement on Federally Funded Research

[0004] This invention was developed with government grant FA9550-17-1-0277 granted by the U.S. Department of Defense's Office of Air Force Scientific Research, and specifically by the U.S. Department of Defense's Military Medical Photonics Program. This invention was also developed with government grant HU0001-17-2-009 granted by the Henry M. Jackson Foundation of the Military Medical Translational Technology Collaboration. The government holds specific rights in this invention. Background Technology

[0005] In recent years, wearable devices have been widely used as medical devices and consumer electronics for sports and health tracking. For example, pulse oximetry is currently used to measure the oxygen saturation of hemoglobin in the blood, which can indicate the systemic oxygen level. However, these devices lack the ability to directly measure oxygen in tissues (e.g., transcutaneous oxygen monitoring), and therefore are not particularly helpful in predicting wound healing, determining amputation levels (e.g., the optimal point for amputation), monitoring hyperbaric oxygen therapy, and determining the severity of ischemia. Therefore, improved portable / wearable systems and methods for oxygen sensing are desired. Summary of the Invention

[0006] Some disclosed embodiments provide sensor systems or methods for monitoring patients. These systems or methods may utilize probes to monitor parameters, such as analytes. Probes may be configured to have more than one operating range, or to monitor more than one analyte, or to determine multiple parameters associated with an analyte, etc. A controller may create, select, or determine a time-varying distribution that can excite the probes relative to more than one operating range, more than one analyte, or multiple parameters, etc. Additionally or alternatively, the controller may adjust the time-varying distribution to switch between more than one operating range, more than one analyte, or multiple parameters, etc.

[0007] According to one aspect of this disclosure, a sensor system for monitoring a patient is provided. The system includes: a probe sensitive to at least one analyte and having at least a first and a second operating range for monitoring the patient; a photon source configured to direct photons at the probe; a probe emitting light in response to receiving photons from the photon source; and a photodetector configured to detect the light emitted from the probe. The system also includes a controller in communication with the photon source and the photodetector. The controller is configured to direct photons from the photon source at the probe according to a first time-varying distribution to excite the probe to emit light relative to the first and second operating ranges in response to receiving photons, and to receive optical data from the photodetector based on the interaction between the light emitted from the probe and the photodetector during operation within the first and second operating ranges, wherein the optical data includes a second time-varying distribution. The controller is further configured to determine a difference between the first and second time-varying distributions, and to determine parameters associated with the analyte based on the difference between the first and second time-varying distributions.

[0008] According to another aspect of this disclosure, a sensor system is provided comprising a probe, a photon source, a photodetector, and a controller communicating with the photon source and the photodetector. The controller is configured to generate a first time-varying distribution comprising at least two first sub-signals, the first time-varying distribution being configured to excite the probe relative to both the at least two first sub-signals, and to direct photons from the photon source toward the probe according to the first time-varying distribution, and to excite the probe to emit light in response to receiving photons. The controller is also configured to receive optical data from the photodetector based on the interaction between the light emitted from the probe and the photodetector, determine a second time-varying distribution based on the optical data, extract at least two second sub-signals, and determine conditions of parameters by comparing the at least two first sub-signals with the at least two second sub-signals.

[0009] According to another aspect of this disclosure, a sensor system is provided comprising a probe, a photon source, and a photodetector, the probe being sensitive to changes in parameters associated with a medical patient across a variety of operating ranges. The system further includes a controller communicating with the photon source and the photodetector. The controller is configured to direct photons from the photon source toward the probe according to a first time-varying distribution consisting of a plurality of first sub-signals, the probe emitting light based on the first time-varying distribution simultaneously responsive to both of the plurality of first sub-signals in response to receiving photons directed toward the probe. The controller is further configured to receive optical data from the photodetector based on the interaction between the light emitted from the probe and the photodetector, wherein the optical data includes a second time-varying distribution. The controller is configured to extract response information from the optical data forming the plurality of second sub-signals to determine at least one of the following: a phase difference between the plurality of first sub-signals and the plurality of second sub-signals, a time delay reflected in the plurality of first sub-signals and the plurality of second sub-signals, or a time constant of the plurality of second sub-signals. The controller is further configured to generate a report on conditions for parameters across a variety of operating ranges based on the determination.

[0010] According to another aspect of this disclosure, a method for monitoring a patient's condition is provided. The method includes: positioning a probe close to the patient to monitor an analyte; positioning a photon source to deliver photons to the probe to excite it; and positioning a photodetector to receive light emitted by the probe in response to excitation by the photon source. The method further includes operating a controller in communication with the photon source and the photodetector to generate a first time-varying intensity distribution of at least two first sub-signals configured to excite the probe relative to both the at least two first sub-signals; and directing the photon source to direct photons at the probe according to the first time-varying distribution and exciting the probe to emit light in response to receiving photons. The controller is further operated to receive optical data from the photodetector based on the interaction between the light emitted from the probe and the photodetector; determine a second time-varying distribution based on the optical data; extract at least two second sub-signals; and generate a report on the patient's analyte or the patient's condition by comparing the at least two first sub-signals with the at least two second sub-signals.

[0011] The foregoing and other aspects and advantages of this disclosure will become apparent from the following description. In this description, reference is made to the accompanying drawings, which form a part herein, and one or more exemplary versions are illustrated in the drawings. These versions do not necessarily represent the full scope of this disclosure. Attached Figure Description

[0012] The accompanying drawings are intended to help illustrate various features of the non-limiting examples of this disclosure and are not intended to limit the scope of this disclosure or exclude alternative implementations.

[0013] Figure 1 A schematic diagram of the block diagram of the sensor system is shown.

[0014] Figure 2A A schematic diagram of the probe is shown.

[0015] Figure 2B It shows along Figure 2A The line 2B-2B is cut off Figure 2A A cross-sectional view of the probe.

[0016] Figure 3A A graph showing an example of a Stern-Volmer curve is provided, which corresponds to a single photoluminescent region with a single type of photoluminescent material.

[0017] Figure 3B A graph of multiple Stern-Volmer curves is shown, each of which corresponds to a photoluminescence region with a different diffusion constant.

[0018] Figure 4 A schematic diagram of another sensor system is shown.

[0019] Figure 5 It shows Figure 4 A cross-sectional view of the substrate of the sensor system, in which the sensor head portion of the sensor system has been removed for visual clarity.

[0020] Figure 6 A cross-sectional view of another substrate is shown.

[0021] Figure 7A A schematic diagram of another sensor head is shown.

[0022] Figure 7B It shows along Figure 7A The line 7B-7B cut Figure 7A A cross-sectional view of the sensor head.

[0023] Figure 8 A schematic diagram of another sensor system block diagram is shown.

[0024] Figure 9 A schematic diagram of the block diagram of the sensor system is shown.

[0025] Figure 10 A flowchart of a process for monitoring subjects according to this disclosure is shown.

[0026] Figure 11A prototype of a transdermal optical wireless wearable device based on phosphorescence emission from a highly breathable sensing film is shown. The prototype consists of a sensing film, a sensor head, and control electronics. A block diagram illustrates the control electronics and sensor head circuitry.

[0027] Figure 12 The exponential decay of the phosphorescence of the sensing film in indoor air and pure nitrogen atmosphere is shown, as well as the curves fitted to the double exponential decay.

[0028] Figure 13 shows panels a, b, and c. Panel a shows the optical density map of the excitation and collection optical filters. Panel b shows the spectrum of the pulsed LED, revealing unwanted phosphorescence that overlaps with the emission spectrum of the sensed porphyrin. Panel c shows the optical spectrum demonstrating that the emission filter successfully filters out unwanted light from the LED.

[0029] Figure 14 illustrates the response of the sensing membrane to pO2 and temperature during calibration runs. Specifically, Figure 14 shows panels a, b, c, and d. Panel a shows the changes in temperature (measured by a thermistor in the sensor head) and pO2 (measured by a commercial oxygen sensor) in the sealed chamber during calibration, where the oxygen partial pressure is varied by mixing nitrogen and air at different ratios. Panel b shows the ADC outputs of the photodiode and reference signal channels at different time points throughout the calibration. The photodiode signal reveals the changes in amplitude and phase of the phosphorescence of the oxygen sensing membrane relative to the reference signal during changes in oxygen (and, to a lesser extent, temperature). The reference signal remains stable during the measurement. Panel c shows the phase (minus the initial value at t = 0) of the reference and photodiode signals versus time during the calibration cycle. The relative phase between the photodiode and the reference signal (θ = θ) p - θ r It exhibits high sensitivity to changes in pO2 across the entire physiological range. Panel d shows the amplitude of emission I versus time, exhibiting a similar response to phase. Phase and amplitude were obtained from the data in panel b using a multilinear regression algorithm.

[0030] Figure 15 The graph shows the phase calibration of each harmonic relative to time, divided by its exponent I and taking the offset β0 and the harmonic amplitude I. i The logarithm of .

[0031] Figure 16 The calibration setup and installation of the sensor head on the heating stage inside the sealed chamber are shown.

[0032] Figure 17 illustrates the fitting of the temperature-dependent Stern-Volmer equation. Specifically, Figure 17 shows panels a, b, c, d, e, and f. Panel a shows the Stern-Volmer plot of lifetime data and its fitting of the temperature-dependent Stern-Volmer equation. This model is able to describe the variation in measured lifetime as well as changes in oxygen partial pressure and temperature. Panel b shows supplementary lifetime data with temperature. The lifetime-temperature dependence is explained by modeling the Keff as a temperature-dependent second-order polynomial. Panel c shows a comparison of pO2 measured by the developed device and a commercial reference sensor, along with the 95% confidence interval (CI) of the measurements. The pO2 estimated from the lifetime data reproduces all the features observed in the reference pO2 data, with subtle differences due to mismatches in sensor velocity and temperature compensation. Panels d, e, and f repeat equivalent plots of panels a, b, and c for intensity data to reveal similar features.

[0033] Figure 18 illustrates the in vivo testing of the oxygen-sensing prototype in a pig model. Specifically, Figure 18 shows panels a, b, and c. Panel a shows a diagram of the experimental setup. Blood flow to the forelimb of a Yorkshire pig was blocked by applying a tourniquet to the elbow joint to induce changes in tissue oxygenation. A wearable device was placed on a shaved area of ​​skin on the forelimb. Panel b shows the temperature and pO2 (estimated based on lifetime and intensity) during the experiment. The estimates of pO2 and temperature show that the device is sensitive to physiological changes due to impaired blood flow to the limb during complete occlusion. Panel c shows the time derivatives of two partial oxygen pressure estimates, which reveal a faster rate of change in local oxygenation within minutes after the application and removal of the tourniquet.

[0034] Figure 19 The temperature dependence of LED leakage is shown, which was measured using a photodiode with a blank control film. The left graph shows the temperature reached by the sensor head over time during the measurement. The right graph shows the percentage change in background (β0 in linear regression) and the intensity of the fundamental frequency. Background value vs. I OFF The obtained values ​​matched, and the LED leakage observed in the base mode explained the differences in lifetime measured by the device and the spectrophotometer measurements. Including the linear dependence of the LED amplitude in the Stern-Volmer fit did not improve the quality of the fit, and the obtained coefficients were negligible.

[0035] Figure 20 shows a schematic diagram of an electronic device. For example, Figure 20 shows panels a, b, c, d, and e. Panel a shows a schematic diagram of a reference signal conditioning circuit. Panel b shows the signals at different nodes of panel a measured by an oscilloscope, where the average value of the final reference signal is 3.3V, which drives an LED. Panel c shows a schematic diagram of an ADC circuit. Panel d shows a schematic diagram of a ribbon cable connection. Panel e shows a schematic diagram of a sensor head.

[0036] Figure 21a A graph of the DC transfer function of the transimpedance amplifier circuit is shown, and Figure 21b A graph showing the AC transfer function of a transimpedance amplifier circuit is provided.

[0037] Figure 22 The input signals of the ADC, reference (top curve), and photodiode (bottom curve) are shown as measured by an oscilloscope.

[0038] Figure 23 The diagram shows the output bits of the ADC for the reference and photodiode channels before (left) and after (right) mode operation.

[0039] Figure 24 The thermistor circuit is shown.

[0040] Figure 25 shows panels a, b, and c. Panel a shows the photodiode and reference signal, where f r = 796Hz, sampled at 5kHz. Panel b shows 1000 samples each for the photodiode and the reference signal, where time is plotted as a base of 1 / f. r The modulus (period of the reference signal). Since the signal remains unchanged over this timescale (0.2s), a single oscillation can be constructed from these signals with very high detail. Panel c shows the Fast Fourier Transform of the reference and photodiode signals. The reference signal reveals the presence of odd harmonics that leak from the PWM output through a low-pass filter. The photodiode signal also contains even harmonics, which may originate from the nonlinear nature of the LED.

[0041] Figures 26a-26d The fitting and reference frequencies for a photodiode are shown as linear combinations with a sine wave. The reference frequency is fitted using the fundamental frequency and harmonics 3f, 5f, and 7f, while the photodiode requires an additional 2f harmonic for proper fitting.

[0042] Figure 27 A schematic diagram of an oxygen sensor system is shown.

[0043] Figure 28The molecular structures of Pt(II)-alkyl-porphyrin (left) and Pt(II)-trimethylacetyl-porphyrin (right) for use in formulations are shown.

[0044] Figure 29 A schematic diagram of the prototype device is shown (10×11 cm, weighing 200 grams). Figure 29 Panels a, b, and c are also shown. Panel a shows a needle / conduit containing porphyrin-PPMA coated fibers, panel b shows a needle / conduit recoated with silicone, and panel c shows a thermocouple placed next to the fibers inside the needle. The obtained spectrum is shown on the right, with emission (red) and excitation peaks (blue). The 375 nm excitation light is partially blocked by a 400 nm long-pass filter, where the peak seen in the spectrum is the tail of the excitation light from the LED that is not blocked by the filter.

[0045] Figure 30 The experiment using a pig model is illustrated. In the first experiment, limb oxygenation was measured in Yorkshire pigs after cardiac arrest. Oxygen measurements were taken in the hind limb (biceps femoris). A needle was then inserted into the muscle tissue, subcutaneous tissue, and then back into the muscle tissue. In the second experiment, limb oxygenation was measured in two pigs after tourniquet application. An oxygen sensor was inserted into the flexor carpi ulnaris muscle in the forelimb. The tourniquet was applied above the elbow joint, above the triceps brachii and brachialis muscles. The illustration in the lower right corner shows two different versions of the equipment used in the pig experiments.

[0046] Figure 31 The 2D calibration obtained from Pt(II)-trimethylacetyl in PPMA coated fibers is shown. I is the intensity of phosphorescence (red / blue), I0 is the phosphorescence at zero oxygen, T is the temperature, TC is the calibration temperature for 1D calibration, and k0 and k T These are the temperature-independent and temperature-dependent Stern-Volmer quenching constants, respectively, and f explains the phosphorescence of porphyrin molecules that are inaccessible to the quencher.

[0047] Figure 32 A comparison of Stern-Volmer distributions extracted for different matrices is shown: 50 μM Pt(II)-trimethylacetyl + 1.4 wt% Triton X-100 in TEOS sol-gel; Cavilon TM 50 μM Pt(II)-trimethylacetyl in membrane formulations, 0.025 mg / μL PEMA and 0.025 mg / μL PPMA.

[0048] Figure 33The Stern-Volmer distribution extracted at different time points and during calibration of the same sensor, including after in vivo use with a Pt(II)-trimethylacetyl-PPMA coating cleaned with isopropanol, is shown. The total signal intensity I decreases over time, while the relative sensitivity I0 / I increases.

[0049] Figure 34 This illustrates limb oxygenation in Yorkshire pigs following cardiac failure. Oxygen measurements were initiated 1 minute post-mortem in the hind limb (biceps femoris). The needle was subsequently inserted into the muscle tissue, subcutaneous tissue, and then back into the muscle tissue, as shown. Figure 30 As shown.

[0050] Figure 35 The results show limb oxygenation and needle-based measurements after tourniquet application on pig 1 (Hampshire breed).

[0051] Figure 36 The study shows limb oxygenation and catheter-based measurements after tourniquet application using a pig (Yorkshire breed).

[0052] Figure 37 Typical measurements during clinical trials are shown, where p T It originates from lifetime pO2, and p I From intensity. Detailed Implementation

[0053] Some typical transdermal oxygen monitors rely on the photoluminescence quenching properties of oxygen-sensitive materials. For example, when excitation light is directed at an oxygen-sensitive material used as a probe, the material emits light in response (e.g., at a lower energy). The amount of light emitted by the oxygen-sensitive probe depends on the partial pressure of oxygen surrounding (and thus diffused) the probe. Therefore, the intensity value of the light received by the probe can be used to determine the oxygen partial pressure. However, these strictly intensity-based methods can have drawbacks. First, intensity-based methods rely heavily on the correct orientation (or placement) of the oxygen-sensitive probe. For example, different orientations and positions (compared to a calibrated orientation) can lead to errors in the true oxygen partial pressure (e.g., the probe does not receive the correct amount of excitation light, or the photodetector does not receive the correct amount of emitted light). Second, amplitude-based methods rely on constant environmental conditions. For example, ambient light (or other light sources, including other photoluminescent materials) can undesirably affect the intensity value (and thus the determined oxygen partial pressure). As another example, humidity, temperature, perspiration, etc., undesirably affect the amplitude value (and thus the determined oxygen partial pressure). As yet another example, oxygen-sensitive materials can degrade over time (e.g., they can be photobleached), in which the photoluminescent material loses its ability to emit light in response to excitation light, resulting in a lower partial pressure value than actually emitted (e.g., due to a lower intensity value).

[0054] As described above, this disclosure provides various systems and methods to overcome these drawbacks. For example, a sensor system is provided. The sensor system may include one or more probes, and a photon source configured to direct photons at the one or more probes. The one or more probes may emit light in response to receiving photons from the photon source. The photon source may be excited by a time-varying distribution, which may consist of one or more frequencies, wavelengths, waveforms, periods, amplitudes, etc. Thus, the probes may be driven using a time-varying distribution formed by a combination of parameters (e.g., waveform, wavelength, period, amplitude, and frequency). The combination of parameters may be applied simultaneously or may be adjusted over time (e.g., selecting between different operating ranges of the probes) for different analytes, etc.

[0055] For example, each set of parameters (e.g., waveform, wavelength, period, amplitude, and / or frequency) can be selected specifically for information readings from a particular sensing probe. This can be configured such that each of these probes (e.g., phosphor / phosphorescent region) has different characteristics or configurations (e.g., sensitivity or response profile), so measuring multiple of these probes produces an overall operating range (e.g., sensitivity or accuracy) that is greater than that achievable using only one probe or using one probe at a time or at a given location.

[0056] In other embodiments, the luminescence responses of multiple probes (e.g., phosphors / fluorophores) excited by the same photon source can each respond to different analytes (e.g., oxygen, carbon dioxide, nitric oxide, etc.). In this way, a probe formed by multiple probes is controlled to generate readings for multiple analytes, which can occur simultaneously or by switching between analytes.

[0057] The sensor system may include a photodetector configured to detect light emitted from a probe, and a controller in communication with a photon source and the photodetector. The controller may be configured to direct photons from the photon source toward the probe according to a first time-varying intensity distribution having a first frequency. The probe may emit light in response to receiving photons. The controller may be configured to receive optical data from the photodetector based on the interaction between the light emitted from the probe and the photodetector. The optical data may include a second time-varying intensity distribution having a second frequency. The second frequency may be substantially the same as or identical to the first frequency. Furthermore, the second frequency may differ from the first frequency. The frequency may be time-varying or phase-varying. Additional frequencies may also be used. In this case, analysis may be performed on the first and second time-varying distributions relative to their respective frequencies. The controller may be configured to analyze the optical data to determine predetermined parameters or information of interest. For example, the controller may be configured to determine the phase difference between the first and second time-varying intensity distributions and determine parameters (e.g., oxygen partial pressure) based on the phase difference.

[0058] Some disclosed embodiments offer advantages over existing oxygen monitors with these (and other) problems by providing improved systems and methods for oxygen sensing. For example, some embodiments provide an oxygen sensor system that may include an oxygen sensor, which may include a probe. The oxygen sensor can emit light from the probe and receive the light in the form of optical data. This optical data can be used to determine response information, which may include time delay, phase difference, or time constant. This response information relates to the lifetime of the probe's ternary excitation state, which can be used to determine the oxygen partial pressure. Because the response information is largely independent of the amplitude value of the light received from the probe, this approach eliminates many of the problems described above with strictly amplitude-based methods. Furthermore, because the response information is largely independent of the amplitude value, frequent calibration of the oxygen sensor based on constantly changing conditions that undesirably affect the accuracy of oxygen partial pressure measurements is not required. Instead, initial calibration can be performed for a longer period and can be done by professionals (e.g., at the factory) rather than by the end user.

[0059] Figure 1A schematic block diagram of a sensor system 100 is shown. The sensor system 100 may include a sensor 102 and a controller 104 communicating with the sensor 102. The sensor 102 may include one or more photon sources 106, one or more photodetectors 108, a probe 110, optical filters 112, 114, and one or more temperature sensors 116. The one or more photon sources 106 may include one or more photon sources (e.g., one, two, three, four), and in some cases, the one or more photon sources 106 may include a single photon source. Each photon source 106 may be optically coupled to the probe 110 and may be configured to emit a corresponding light 118 toward the probe 110, causing the probe 110 to emit light 120 in response to the absorption of light 118. For example, light 118 may interact with a photoluminescent material of the probe 110 to emit photoluminescence. As a more specific example, light 118 may interact with a phosphorescent material of the probe 110 to emit phosphorescence.

[0060] In some embodiments, light 118 may be emitted such that the amplitude of light 118 (e.g., the intensity of light 118) changes over time. For example, light 118 may be emitted according to a time-varying intensity distribution. Additionally or alternatively, the time-varying distribution may have a single frequency (e.g., a single fundamental frequency) or may have multiple different frequencies (e.g., multiple harmonics of the fundamental frequency and multiple harmonics including the fundamental frequency). In some cases, the time-varying distribution may consist of a sine wave, a square wave, a pulse function (e.g., an increment function), or a portion of each of these functions. In some configurations, the time-varying distribution may be a periodic wave (e.g., a sine wave), and in other cases, the time-varying distribution may be a non-periodic wave (e.g., a portion of a sine wave, a single square pulse, etc.). Additionally, as will be described, the time-varying distribution, and thus the excitation field created by light 118, may be driven by a combination of these properties (e.g., intensity, frequency, waveform, period, etc.). For example, the excitation field created by the light 118 can be driven by a combination of waveforms and frequencies, where each set of waveforms and / or frequencies is specifically targeted at information read from the operating range of a particular sensing probe or one or more probes forming the probe. This can be configured such that each of these probes (e.g., phosphor / phosphorescent region) has a different sensitivity or response profile, thereby enabling measurements of multiple probes to produce a device with a wider range of sensitivity or accuracy than using only one probe or using one probe at a single time or at a given location. In other embodiments, different types of probes (phosphors / fluorophores) may each be sensitive to different analytes (e.g., oxygen, carbon dioxide, nitric oxide, etc.) but are excited by the same photon source, such that a single measurement of the probe produces a device that provides simultaneous readouts of multiple analytes.

[0061] In some configurations, the controller 104 (or oxygen sensor 102) may include a function generator configured to output an electrical waveform to drive each photon source 106 according to a time-varying intensity distribution. For example, an electrical waveform defining a wave (e.g., a sine wave) may be applied to the photon source 106 to cause it to emit light 118 according to a time-varying intensity distribution (e.g., a sine wave). In some cases, including when one or more photon sources 106 comprise multiple photon sources, the function generator (or multiple function generators) may output corresponding electrical waveforms to the corresponding photon source 106, each of which may be different from the others (e.g., causing each photon source 106 to emit light 118 with a different time-varying intensity distribution). As another example, the oxygen sensor 102 may include an optical modulator (or multiple optical modulators) that may be optically coupled to each photon source 106 (or each optical modulator may be optically coupled to a corresponding photon source 106). In this manner, controller 104 can control the optical modulator such that the amplitude of light 118 changes over time according to the wave set by the optical modulator. Therefore, in some cases, light emitted by photon source 106 having a substantially constant amplitude over time (i.e., deviating from a constant amplitude by less than 10%) (e.g., driven by a substantially constant voltage value) can be modulated by the optical modulator so that the amplitude changes over time according to a time-varying intensity distribution. In some cases, each optical modulator can be an electro-optic modulator (e.g., controllable by controller 104). In some cases, the amplitude of light emitted from the photon source can be directly controlled by a voltage or current applied to the photon source itself or externally. In some embodiments, photon source(s) 106 can be implemented in different ways. For example, photon source 106 can be a laser, a lamp (e.g., a halogen lamp), a light-emitting diode (“LED”), including ultraviolet, visible, near-infrared, and other light sources.

[0062] In some embodiments, the controller 104 (or one or more photon sources 106) may include a power source capable of providing a drive signal to the photon sources 106. This drive source may be an AC power source. In this way, light 118 emitted from the photon source 106 can follow the AC power source. In other words, the shape of the time-varying intensity distribution of the light 118 can substantially correspond to the shape of the AC drive signal.

[0063] In some embodiments, the oxygen sensor 102 may include an optical filter 112 that may be optically coupled to (e.g., located in front of) one or more photon sources 106. The optical filter 112 may block light in a wavelength range including photoluminescence emitted by the probe 110 (e.g., light 120). For example, if the probe 110 emits light in a wavelength range of substantially 620 nm to substantially 750 nm, then the optical filter 112 may block light within that wavelength range from the filter 112 to the probe 110 (e.g., increasing the signal-to-noise ratio by limiting the photodetector 108 to sense the light emitted by the photon source 106). In some cases, the optical filter 112 may be a band-stop filter (e.g., a notch filter) having a stopband defined from substantially 500 nm to substantially 700 nm. In some cases, the photoluminescent material of the probe 110 may have a peak emission wavelength (e.g., 645 nm) that can be located within the stopband of the optical filter 112 (e.g., when the optical filter 112 is a band-stop filter). Although Figure 1 The figure shows that optical filter 112 is a single optical filter. In some cases, optical filter 112 can define multiple optical filters, each with a different optical density response (at various wavelengths). Therefore, multiple optical filters can collectively define the optical density response of optical filter 112.

[0064] Similar to one or more photon sources 106, one or more photodetectors 108 may include one or more photodetectors (e.g., one, two, three, four), and in some cases, photodetectors 108 may include a single photodetector. Each photodetector 108 may be optically coupled to probe 110 and may be configured to receive light 120 emitted by probe 110 (e.g., excitation light in response to interaction with the photoluminescent material of probe 110). For example, probe 110 (e.g., and specifically, the photoluminescent material of probe 110) may interact with light 118, and based on the interaction, may emit light 120 at a lower energy level (e.g., a higher wavelength) than light 118. Light 120 may then be directed to one or more photodetectors 108, and the photodetectors 108 may interact with each other to generate optical data (e.g., light 120 causes a photocurrent to appear in photodetector 108). This optical data may be received and processed accordingly by controller 104. In some embodiments, each photodetector 108 can be implemented in different ways. For example, the photodetector 108 can be an optical spectrometer, a spectrophotometer, a photodiode, an avalanche photodiode, a phototransistor, etc. In some configurations, it may be advantageous for the photodetector 108 to be an avalanche photodiode because avalanche photodiodes are more sensitive to received light than, for example, other photodiodes. For example, an avalanche photodiode can be several orders of magnitude more sensitive to photon detection than some photodiodes.

[0065] In some embodiments, sensor 102 may include an optical filter 114 optically coupled to one or more photodetectors 108, which may be implemented in a manner similar to optical filter 112. For example, optical filter 114 may be a single optical filter or may be multiple optical filters forming optical filter 114. In any case, optical filter 114 may block light received by one or more photodetectors 108 in a wavelength range including light emitted by photon source 106 (e.g., light 118). In some cases, optical filter 114 may be a low-pass filter having a cutoff frequency of substantially 450 nanometers. In some cases, optical filter 114 may be a bandpass filter with a passband defined as substantially from 400 nanometers to 1000 nanometers or more specifically, from substantially 600 nanometers to substantially 850 nanometers. In some cases, the photoluminescent material of probe 110 may have a peak emission wavelength that can be located within the passband of optical filter 114 (e.g., when optical filter 114 is a bandpass filter).

[0066] In some embodiments, probe 110 can respond to changes in parameters, variables, etc. For example, parameters may be the concentration of an analyte, oxygen partial pressure, pH value, temperature, humidity, concentration of a biomarker, concentration of a gas, concentration of molecular oxygen, concentration of carbon dioxide, concentration of nitric oxide, concentration of dissolved analyte in plasma (or tissue), etc. In some embodiments, probe 110 may have different lifetime values ​​for different values ​​of parameters, variables, etc. For example, probe 110 may emit light 120 according to a Stern-Volmer curve, which includes parameters (e.g., on the x-axis) and lifetime values ​​(e.g., on the y-axis). Additionally, the intensity of light 120 can change relative to changes in parameters. Therefore, the intensity of light 120 (e.g., intensity value) can correspond to a parameter value. In other configurations, the time difference or phase difference (e.g., time value or phase value) of the time-varying intensity response can correspond to the parameter value.

[0067] In some specific configurations, probe 110 may be implemented as an oxygen probe (e.g., an oxygen-sensitive probe), which is a non-limiting example of probe 110. In this case, sensor 102 may be an oxygen sensor. Although probe 110 may be implemented in different ways, for example, to respond to different variables, the following example describes probe 110 as an oxygen probe capable of sensing different oxygen concentrations (e.g., oxygen partial pressure). Thus, probe 110 implemented as an oxygen-sensitive probe is related to other probes 110, each of which responds to a different variable. Continuing with this non-limiting example, probe 110 may be configured to sense different molecular oxygen pressures (e.g., different oxygen partial pressure levels). For example, probe 110 may include a photoluminescent material that can provide photoluminescent properties of probe 110 (e.g., a photoluminescent material that can respond differently to different oxygen partial pressure levels). As a more specific example, the photoluminescent material may be a phosphorescent material (e.g., a porphyrin, a metalloporphyrin) that can provide phosphorescent properties of probe 110 (e.g., a phosphorescent material that can respond differently to different oxygen partial pressure levels). In some cases, probe 110 may include multiple different photoluminescent materials, or specifically, multiple different phosphorescent materials. In some cases, each photoluminescent material (or phosphorescent material) may have a different oxygen diffusivity or a different quenching response to levels of molecular oxygen (e.g., O2). For example, each photoluminescent material (or phosphorescent material) may have a different sensing range for oxygen (e.g., different Stern-Volmer curves for different O2 ranges). In some cases, a single material may contain different phosphorescent molecular components, each with a different quenching response to levels of molecular oxygen (e.g., different Stern-Volmer curves for different O2 ranges). As a more specific example, polymeric materials may contain different phosphors, each with a different quenching constant for oxygen in the material. As another specific example, a material may contain multiple formulations of the same phosphor, where each phosphor formulation has a different quenching response (e.g., different Stern-Volmer curves).

[0068] In some embodiments, the oxygen-sensitive probe 110 may emit different amounts of light 120 in response to different percentages of molecular oxygen relative to other gases within the probe 110 (e.g., different oxygen partial pressure levels). For example, a greater amount of oxygen quenching quenches the photoluminescent material, resulting in a reduced amount of received light 120. In some cases, the oxygen partial pressure level within the probe 110 may be based on several factors, including: the amount of oxygen in the surrounding environment (e.g., which subsequently diffuses into the probe 110), the amount of oxygen diffused through the tissue (e.g., assuming the probe 110 is in communication with the tissue) (e.g., in contact with the tissue, in gaseous communication with the tissue, in fluid communication with the tissue, or otherwise acquiring tissue-related information), the amount of photoluminescent material, the temperature of the probe 110, etc. Therefore, while the amount of light 120 can indicate the oxygen partial pressure (e.g., and the amount of oxygen diffused through the tissue), using only amplitude-based measurements may be inaccurate—especially over longer periods (as described above).

[0069] For example, photoluminescent materials can degrade over time (e.g., undergo photobleaching), and some of these photoluminescent materials (e.g., molecules) may cease to be photoluminescent (e.g., no longer emit light in response to received light). This can lead to reduced accuracy in oxygen sensing (e.g., the sensed oxygen partial pressure is higher than expected due to less emitted light than anticipated), or it can result in frequent calibrations to account for these phenomena when using intensity-based detection methods. However, in some embodiments, the oxygen sensor system 100 can advantageously sense parameters, such as oxygen levels (e.g., oxygen partial pressure levels), by relying on information that determines the photoluminescence lifetime of probe 110, or that indicates the photoluminescence lifetime (e.g., the phase of the time-varying intensity distribution of light 120, the time delay between the emission of emitted light 118 and the reception of light 120 from photodetector 108, the time constant of the time-varying intensity distribution of light 120, etc.). In some configurations, this approach, rather than a strictly intensity-based approach, may be advantageous because this information can be relatively independent of the degradation of the photoluminescent material over time (e.g., some atoms of the photoluminescent material are undergoing photobleaching).

[0070] In some cases, limiting the size of probe 110 may be important because the physical size of probe 110 can affect the measurement of the desired analyte or parameter (e.g., oxygen tension), allowing the probe to respond rapidly to changes in the analyte or parameter (e.g., oxygen partial pressure). Continuing the example, an oxygen-sensing material senses oxygen in tissue by equilibrating its oxygen level with the oxygen level of the tissue it contacts or is near. The larger the physical size of the oxygen-sensing material, the longer the equilibration process takes. Additionally, the oxygen-sensing material may contain (or retain) molecular oxygen, whose release kinetics can be rapid or slow. The larger the physical size of the oxygen sensor, the more oxygen in the material must diffuse or be kept in equilibration. In other words, the larger probe 110 is, the longer its equilibration time, and therefore the slower it measures oxygen. Therefore, by reducing the size of probe 110, it can respond more quickly to changes in oxygen partial pressure levels, which can increase the speed of oxygen sensing. For example, the volume of probe 110 can be less than 2 mm. 3 As another example, probe 110 has a width of less than 6 mm, a height of less than 0.05 mm, a length of less than 6 mm, etc.

[0071] like Figure 1 As shown, probe 110 may be positioned partially (or entirely) (or in different configurations) within region 122 of sensor 102, or external to region 122 (e.g., but in contact with, gaseously connected to, fluidly connected to, or otherwise able to obtain information related to the region). The subject's tissue 124 to be monitored may be positioned such that region 122 surrounds the tissue 124. For example, sensor 102 may include a substrate that defines region 122. This substrate may be coupled to the subject (e.g., using an adhesive) such that tissue 124 is positioned within the boundaries of the substrate. Ideally, the substrate covers the skin so that no trapped air remains between the skin and sensor 102 in the region. In some cases, the material defining region 122 may be semi-permeable to oxygen, allowing oxygen to diffuse from the surrounding environment into region 122 (and vice versa). In this way, tissue 124 is not completely blocked from oxygen diffusion from the air (e.g., this could damage tissue 124), while region 122 is partially sealed from the surrounding environment (e.g., so that sensor 102 does not simply measure the oxygen partial pressure of the surrounding environment). Therefore, as described below, sensor 102 can be calibrated to the oxygen permeability of the material defining region 122, and the oxygen partial pressure in the atmosphere. In other cases, the material defining the region may be oxygen-impermeable.

[0072] In some embodiments, the sensor system 100 can be used as a transcutaneous oxygen monitor, thus sensing the partial pressure of oxygen from tissue 124 (which may be skin). However, in other cases, the sensor system 100 can sense the oxygen level of other tissues. For example, region 122 may be omitted, and probe 110 may be inserted into tissue 124, which may be muscle, blood, subcutaneous tissue (e.g., subcutaneous fat), etc. In some cases, probe 110 may be inserted into a subject's orifice, a subject's blood vessel, etc. In other cases, the oxygen sensor system may be inserted into or implanted within a region of tissue.

[0073] In some embodiments, the sensor system 100 may include one or more temperature sensors 116 (e.g., one, two, three, four, etc.). In some cases, the first temperature sensor 116 may be in thermal communication with the tissue 124. For example, the temperature sensor 116 may be positioned within region 122, may contact the tissue 124, may be coupled to (and in contact with) a material defining region 122, may be coupled to (and in contact with) an optical fiber, etc. In any case, the first temperature sensor 116 may sense (or indicate) the temperature of the tissue 124, which can be used to compensate for temperature changes that may affect the oxygen partial pressure level sensed by sensor 102. For example, as the temperature increases, oxygen diffusion also increases, so the sensed oxygen partial pressure may be higher (or lower) than the expected oxygen partial pressure (e.g., based on the temperature of calibrating sensor 102).

[0074] In some embodiments, the sensor system 100 may include a second temperature sensor that is thermally connected to the photon source 106. In some cases, the photon source 106 (e.g., when implemented as an LED) may experience a change in the amplitude of its emitted light based on changes in the LED temperature. For example, at higher operating temperatures, the photon source 106 may have reduced light output (e.g., the opposite of a photon source 106 operating at lower temperatures).

[0075] In some embodiments, sensor system 100 may include another temperature sensor that is thermally connected to the oxygen sensing material in probe 110. This sensor can measure the temperature at which the molecular oxygen sensor is located, and thus can be used to calculate the oxygen diffusivity, and therefore the temperature-dependent phosphorescence quenching rate. Therefore, temperature sensing from the temperature sensor can be used to compensate for optical data received at photodetector 108. For example, each amplitude of each intensity value of the optical data, or each lifetime of each lifetime value, can be adjusted based on the temperature value received by the temperature sensor. In an alternative configuration, sensor 102 may include a first photodetector 108 configured to receive light emitted by probe 110, and a second photodetector 108 configured to receive light emitted by photon source 106 to compensate for changes in temperature (or other conditions). In this configuration, since the light emitted by the photon source 106 is directly measured (e.g., rather than estimated based on the electrical waveform applied to the photon source 106), the optical data generated by the photodetector 108, which is configured to receive light from the probe 110, does not need to be compensated for the photon source (e.g., since the light input that excites the probe 110 is directly known).

[0076] In some embodiments, the controller 104 may suitably communicate (e.g., bidirectional communication) with some or all of the components of the oxygen sensor system 100, as well as with the computing device 126 (e.g., a server, a wireless communication device including a smartphone, tablet, computer, etc.) and other computing devices. For example, the controller 104 may communicate with one or more photon sources 106, one or more photodetectors 108, one or more temperature sensors 116, etc. In this way, the controller 104 may transmit data (e.g., instructions) to each of the components communicating with the controller 104 and receive data from each of the components communicating with the controller 104. For example, the controller 104 may cause each photon source 106 to emit light, receive optical data from each photodetector 108, and receive temperature data from each temperature sensor 116.

[0077] In some embodiments, controller 104 may transmit data to computing device 126, which may be a wireless communication device (e.g., a smartphone). For example, controller 104 may communicate with computing device 126 according to the Bluetooth® wireless communication protocol, for example, to transmit data to (or receive data from) computing device 126.

[0078] Controller 104 (e.g., an electronic controller) can be implemented in various ways. For example, controller 104 may include typical components used, such as a processor, memory, display, inputs (e.g., a keyboard, mouse, graphical user interface, touchscreen display, etc.), communication devices, etc. In some cases, controller 104 may simply be implemented as a processor (e.g., a processor device). In other cases, controller 104 may be a microcontroller, a system-on-a-chip (SoC), or a field-programmable gate array (FPGA) based system. In some specific cases, controller 104 may be a laptop, desktop computer, tablet computer, smartphone, standalone computer system, server, microcontroller, etc. Regardless of configuration, controller 104 may appropriately implement some or all of the processes described below.

[0079] In some embodiments, the controller 104 may include a display, while in others, the display may be separate from the controller 104 (e.g., the controller 104 communicates with the display). However, regardless, the controller 104 may present information on the display, which may include oxygen partial pressure levels, temperature data, optical data (e.g., intensity values ​​changing over time, frequency information from the optical data, the spectrum of the optical data, etc.), phase information, results, etc. In some embodiments, the controller 104 may process, analyze, etc., the received data, including optical data, temperature data, etc. For example, the controller 104 may determine frequency information from the optical data (e.g., by fitting a function in the time domain, by applying a Fourier transform to the optical data, by applying a fast Fourier transform to the optical data, etc.). As another example, the controller 104 may digitally filter the optical data, for example, to isolate desired frequencies of interest.

[0080] In some embodiments, controller 104 (or each photodetector 108) may include amplifiers (e.g., transimpedance amplifiers), voltage regulators, etc., with appropriate gain to facilitate proper reception, modification, etc., of various data sources. Additionally, controller 104 (or each photodetector 108) may include fixed or programmable electronic filters to isolate specific desired frequencies. In other embodiments, controller 104 may include an analog-to-digital converter for digitizing signals received from elements of the oxygen sensing system. In this way, controller 104 can utilize algorithmic methods or techniques to process data and determine oxygen levels.

[0081] Figure 2A A schematic diagram of probe 130 is shown, while Figure 2B It shows along Figure 2A The image shows a cross-sectional view of probe 130 taken from line 2B-2B. Probe 130 can be a specific implementation of probe 110, therefore probe 130 is related to probe 110 (and vice versa). Figure 2A As shown, the probe 130 is shaped as a cylinder with a radius and thickness; however, the probe 130 can be shaped in different ways, including, for example, a cube, a prism, etc.

[0082] In some embodiments, probe 130 may include a body 132 and photoluminescent regions 134, 136, 138, 140 coupled to or disposed within (e.g., integrated within) the body 132. Each photoluminescent region 134, 136, 138, 140 may include one or more photoluminescent materials, each of which may be a phosphorescent material. In some cases, each photoluminescent material (e.g., porphyrin) may be quenched in response to the presence of an analyte (e.g., oxygen) and light that excites the photoluminescent material (e.g., light 118). Thus, each photoluminescent material responds differently to different concentrations of analytes (such as oxygen). In some cases, each photoluminescent region 134, 136, 138, 140 may be tuned to different analyte sensing ranges. For example, each photoluminescent region 134, 136, 138, 140 may include different photoluminescent materials, each of which has a different Stern-Volmer profile. In some configurations, each photoluminescent region 134, 136, 138, 140 may have different peak emission wavelengths (e.g., thus, the optical data corresponding to the light emitted from each photoluminescent region 134, 136, 138, 140 can be separated from each other).

[0083] In other cases, each photoluminescent region 134, 136, 138, 140 can have substantially the same type and amount of photoluminescent material (e.g., the same porphyrin), and each region can have a different diffusion constant “K” relative to the Stern-Volmer equation. Therefore, although each photoluminescent region 134, 136, 138, 140 can have the same type and amount of photoluminescent material, each photoluminescent region 134, 136, 138, 140 can have different lifetimes relative to different concentrations of the analyte or parameter (such as oxygen). In this way, the combined response curve of the combination of Stern-Volmer curves from photoluminescent regions 134, 136, 138, 140 can have greater sensitivity and span a larger oxygen partial pressure range compared to a single region. Therefore, changes in phase difference (e.g., between two time-varying intensity curves) can be equally sensitive to oxygen partial pressures than a single region (e.g., compared to a single photoluminescent region). In some cases, to generate different diffusion constants for each photoluminescent region 134, 136, 138, 140, each photoluminescent region 134, 136, 138, 140 can be encapsulated by layers of semi-transparent material (e.g., polymers) of varying thicknesses, which can act as diffusion resistors (e.g., thicker layers produce larger diffusion constants). For example, each photoluminescent region 134, 136, 138, 140 can have substantially the same volume (and concentration) of photoluminescent material (e.g., it can be integrated within a material such as a polymer). This volume of photoluminescent material can be encapsulated by layers of semi-transparent material, where the thickness of the layer can indicate the diffusion constant (e.g., a larger thickness increases the diffusion constant, and vice versa). This can subsequently result in each photoluminescent region 134, 136, 138, 140 having different Stern-Volmer profiles.

[0084] In some embodiments, each photoluminescent region 134, 136, 138, 140, and specifically the photoluminescent material within each region, can be excited by light of different wavelengths. For example, in this manner, each photon source can selectively excite one of the photoluminescent regions 134, 136, 138, 140, thereby selecting from which photoluminescent region 134, 136, 138, 140 to receive optical data. In other configurations, each photoluminescent region 134, 136, 138, 140, and specifically the photoluminescent material within each region, can be excited by the same wavelength (or can be excited by light 118, which may include multiple wavelengths), and each light can emit corresponding light of different wavelengths. In this manner, the controller can receive optical data from a photodetector configured to receive light emitted from the corresponding region 134, 136, 138, 140, as well as minimal (to zero) light emitted from different regions. In other words, each photodetector may include a corresponding optical filter configured to allow light to be emitted from one region 134, 136, 138, 140 while blocking light from other regions 134, 136, 138, 140 (e.g., the other three regions) from passing through the detector. In other configurations, photoluminescent materials in different regions excited by the same wavelength can emit corresponding light of the same wavelength, where each photoluminescent material has a different response lifetime, as shown in Figure 3. In this way, the controller can receive optical data from a photodetector configured to receive light from all regions, but can distinguish the signals and parameters encoded from each region by the unique lifetime of these regions.

[0085] In some configurations, each photoluminescent region 134, 136, 138, 140, and specifically each photoluminescent material, can be configured to respond to changes in different analytes. For example, photoluminescent region 134 can respond to changes in partial oxygen levels, photoluminescent region 136 can respond to changes in pH, and photoluminescent region 138 can respond to changes in analytes (e.g., different analytes), etc.

[0086] In another embodiment, body 132 comprises several phosphors with different molecular properties to produce sufficiently different lifetimes or quenching constants in response to an analyte, such as oxygen. As a non-limiting example, oxygen will be described as the analyte. Unlike the above, in this embodiment, phosphorescent molecules can diffuse uniformly through body 132; it is their respective molecular properties that provide the range of lifetimes or quenching constants to produce oxygenation data corresponding to a greater oxygen partial pressure than a single phosphor alone. Molecular properties defining the phosphor quenching constant can include the phosphor's structure and composition (e.g., different molecular structures), different inserted metals (e.g., platinum versus palladium), and different peripheral or modifying groups (e.g., naked porphyrin versus porphyrin dendritic molecules). These different properties are listed as examples and do not constitute all possible molecular properties that can be used to create different lifetimes, quenching rates, and constant quenching responses to oxygen. Photoluminescent materials configured in this way can be excited by the same wavelength, and each phosphor can emit corresponding light with the same wavelength; these materials each have different response lifetimes, analyte diffusion rates, or quenching constants. In this way, the controller can receive optical data from a photodetector configured to receive light from all phosphors, but can distinguish the signals and parameters encoded from each phosphor by the unique lifetime of these phosphors.

[0087] Figure 3A A graph illustrating an example of a Stern-Volmer curve is shown, which corresponds to a single photoluminescent region with a single type of photoluminescent material. For example... Figure 3A As shown, there is a single curve. Figure 3B The diagram shows multiple Stern-Volmer curves, each corresponding to a photoluminescence region with different diffusion constants or quenching constants, or to different photoclusters with different diffusion constants or quenching constants. Figure 3B As shown, each of the Stern-Volmer curves moves along the vertical axis (e.g., the lifetime axis). Although Figure 3B It is not shown in the text, but Figure 3B Each interception in the Stern-Volmer curve represents the oxygen partial pressure axis at a different location (e.g., each in the Stern-Volmer curve has a different x-interception). The sensitivity to changes in oxygen concentration is highest when lifetime changes most with increasing oxygen concentration. Therefore, in Figure 3A In the example system, when the exponential curve is flat, and the curvature changes to high and low, the sensitivity is greatest at low oxygen levels. For example... Figure 3BAs shown, by having multiple Stern-Volmer responses in a single sensor, the sensitivity of the oxygen sensing system is improved over a wider range, which is generated by analyzing each individual response curve together.

[0088] In some embodiments, since lifetime is related to the time constant of phosphorescence decay (e.g., after an incremental or square pulse of excitation) and the phase difference (e.g., after a sinusoidal pulse of excitation), the oxygen partial pressure can be determined (e.g., via a Stern-Volmer curve) if the time constant or phase difference is determined.

[0089] In other embodiments, the measured lifetime response of the oxygen sensing system can be measured as a function of oxygen concentration. Since the measured lifetime of a single or multiple phosphors or phosphorescent regions depends on the oxygen concentration, these oxygen lifetime responses can be recorded as a lookup table. This lookup table can then be used such that the set of lifetimes measured by the oxygen sensing system gives a measurement of oxygen concentration. In yet another embodiment, the measured lifetime response of the oxygen sensing system can be measured as a function of oxygen concentration to generate an empirical equation. This empirical equation can then be used such that the set of lifetimes measured by the oxygen sensing system gives a measurement of oxygen concentration. In still yet another embodiment, the measured lifetime response of the oxygen sensing system can be measured as a function of oxygen concentration to train a machine learning model. This machine learning model can then be used such that the set of lifetimes measured by the oxygen sensing system gives a measurement of oxygen concentration.

[0090] Figure 4 A schematic diagram of an oxygen sensor system 150 is shown. The oxygen sensor system 150 can be a specific implementation of the oxygen sensor system 100, and therefore the oxygen sensor system 100 is related to the oxygen sensor system 150 (and vice versa). Figure 4 As shown, the oxygen sensor system 150 may include an oxygen sensor 152 and a controller 154. The oxygen sensor 152 may include a sensor head 156, which may include photon sources 158 and 160, photodetectors 162 and 164, and a temperature sensor 166. In some configurations, the photodetector 162 may be positioned between the photon sources 158 and 160, which can be advantageous because the photodetector 162 can shield ambient light (e.g., ambient light reduces the signal-to-noise ratio). In some configurations, the photodetector 164 may be positioned above (or below) the photon sources 158 and 160. In some cases, the photodetector 162 may be configured to sense light emitted from a probe, while the photodetector 164 may be configured to sense light emitted from each of the photon sources 158 and 160.

[0091] In some embodiments, the oxygen sensor system 150 may include a cable 168 electrically connecting components of the sensor head 156 to a controller 154. For example, one end of the cable 168 may be electrically connected to photon sources 158, 160, photodetectors 162, 164, and a temperature sensor 166, while the other end of the cable 168 may be electrically connected to the controller 154. In some cases, the cable 168 may include one or more wires, each configured to be electrically connected at one end to a corresponding one of the photon sources 158, 160, photodetectors 162, 164, or temperature sensor 166, and at the other end (e.g., via pins of the controller 154) to the controller 154. In other cases, the cable 168 may communicate via a serial interface between the sensor and the controller. In some cases, the cable 168 allows the sensor head 156 (and the resulting oxygen sensing capability) to be positioned at a different location relative to the controller 154, which may be larger than the sensor head (e.g., more difficult to anchor to a subject). For example, the sensor head 156 can be oriented to different locations and orientations relative to the controller 154 via the cable 168 (e.g., because the cable 168 is flexible), such as to the subject's back, the subject's shoulder, etc. In some specific cases, the cable may be a ribbon cable. In other embodiments, the entire oxygen sensor 150 may be contained in a single housing, where the sensor head 156 and the controller 154 are part of the same physical device. In such embodiments, the sensor head 156 and the controller 154 may share physical components (e.g., both the sensor head 156 and the controller 154 may be constructed from the same circuit board 169), such that the cable 168 is merely a trace on the circuit board 169.

[0092] Or, refer to Figure 5 In some embodiments, the oxygen sensor system 100 may include a housing 170 and a substrate 172. The housing 170 may be coupled to a controller 154, and the housing 170 may support the controller 154. In some cases, although... Figure 4 or Figure 5 Not shown, but the oxygen sensor system 100 may include straps, bands, etc., coupled to the housing 170 to secure the housing 170 relative to an accessory (e.g., arm, leg, wrist, etc.) or other part of the subject's body. In some cases, the straps, bands, etc., may be adjustable to accommodate different sizes of the subject. For example, the housing 170 may include clips, clamps, etc., to be detachably coupled to the straps, bands, etc., to accommodate different sizes. In some cases, the housing 170 may then be secured in a manner similar to a watch (or other wearable electronic device). In some cases, the housing may be made of a flexible material (e.g., silicone) and adhered to the subject as an adhesive patch. In other cases, the housing 170 may also surround the substrate 172 to form part of the same unit, such as... Figure 5 As shown.

[0093] In some embodiments, substrate 172 may be coupled to sensor head 156 and may engage with a subject to provide a seal between substrate 172 and the subject's tissue. The substrate may include multiple layers. For example, substrate 172 may include layers 174, 176, 178, 180, which... Figure 5 The cross-sectional view of the intermediate substrate 172 is shown. Layer 174 is semi-permeable to oxygen diffusion through it and can be a sheet of material, which allows layer 174 to be flexible to adapt to different surfaces of the subject. Although Figure 4 The diagram shows layer 174 as square, but layer 174 may have other shapes, including, for example, circular and elliptical. In some configurations, layer 174 may include an adhesive layer positioned on the outer surface of layer 174 (e.g., the tissue-facing surface when substrate 172 is bonded to a subject). In some cases, the adhesive layer may partially or completely span the outer surface of layer 174. For example, the adhesive layer may span a region near the peripheral edge of layer 174. In some cases, layer 174 may have a scattering, reflecting, or absorbing layer coupled to the inner surface (or outer surface) of layer 174, which may face the surrounding environment. In this way, the reflective layer may reflect or absorb ambient light that would otherwise interact undesirably with the probe.

[0094] Layer 176, located between layers 174 and 178, can be the probe described previously. In some cases, the positioning of layer 176 (e.g., a sandwich of layer 176) can isolate layer 176, thus preventing the probe from directly contacting the patient. In this way, unwanted material leaching from the probe is advantageously blocked from contact with the patient. Layer 178 can be positioned above and to the sides of layer 176 such that layer 178 blocks the atmosphere above and to the sides of layer 176, and most of the sensed O2 passes through layer 174 from the skin. Layer 178 can be formed of a material with lower oxygen permeability than layer 174. In this way, oxygen from the surrounding environment passing through layer 178 and entering the probe (e.g., layer 176) remains at a low level to allow for more accurate oxygen partial pressure measurements of zone 182 (e.g., preventing external oxygen not originating from zone 182 from diffusing into the probe). Layer 178 can allow light to pass through, including light from each of the photon sources 158 and 160 and light emitted by the probe. Therefore, layer 178 can be transparent.

[0095] In some embodiments, layer 180 may be positioned below layer 174 (e.g., coupled to layer 174) and configured to scatter light directed at layer 180 while blocking light from passing through layer 180. Thus, layer 180 may be defined, for example, as a light scattering or light reflecting layer. In some cases, layer 180 may be aligned with photodetector 162, which can be advantageous when any ambient light (e.g., originating from region 182) is blocked from passing directly through layer 180 and reaching photodetector 162. Instead, ambient light is scattered or reflected after being directed at layer 180. The oxygen sensing layer 176 emits light in all directions, such that light directed toward the tissue (region 182) may enter the tissue and become undetectable. The scattering or reflecting properties of layer 180 serve to redirect a portion of the emitted light that would otherwise be lost back to photodetector 162 for detection. In one non-limiting example, layer 180 may comprise a reflective polyester film (Mylar). In another non-limiting example, layer 180 may comprise white (e.g., silicone) to provide functional scattering. Therefore, compared to the case without layer 180, a higher proportion of the light emitted by the probe can be directed to photodetector 162, and ambient light is blocked, thereby improving the total collected signal and signal-to-noise ratio. In some cases, the width of layer 180 can be greater than the width of photodetector 162 to ensure that ambient light near the periphery of layer 180 is not directed to photodetector 162. In some cases, photon sources 158, 160 and photodetectors 162, 164 can be aligned with layer 180. In some configurations, layer 180 can block light from region 182 from reaching each photodetector 162, 164, and can block light from each photon source 158, 160 from reaching region 182. In some configurations, layer 180 can be configured to specifically reflect or scatter the light emitted by the oxygen sensing layer.

[0096] In some embodiments, each layer 174, 176, 178, 180 of the substrate 172 is coupled together, such as Figure 5 As shown. In other configurations, layers 174, 176, 178, and 180 can be constructed differently. For example, layer 176 can be integrated within layer 174, or it can be integrated within layer 178. Additionally, layer 176 can be partially (or completely) encapsulated by layers 174 and 176.

[0097] like Figure 5As shown, substrate 172 (and specifically layer 174) may define region 182, which may communicate with (e.g., with tissue of a subject to which substrate 172 is attached), including direct contact or fluid communication. Region 182 is at least partially sealed from the surrounding environment (e.g., the area surrounding substrate 172), and oxygen may diffuse through layer 174 and into region 182 (and vice versa) depending on the diffusion properties of layer 174. Additionally, oxygen from tissue may diffuse into (or diffuse out of) region 182. Therefore, oxygen diffused into (and sensed by) the probe may be partially derived from tissue and can then be used to determine the oxygen partial pressure of the tissue. In some embodiments, temperature sensor 166 may be thermally connected to substrate 172 and specifically layer 174. In this way, temperature data from temperature sensor 166 can indicate the temperature of region 182 (and thus the oxygen therein), and can then be used to compensate for temperature changes.

[0098] Figure 6 A cross-sectional view of substrate 200 is shown, which may be similar to substrate 172. Therefore, substrate 200 can be implemented together with oxygen sensor system 150. Substrate 200 may include layers 202, 204, and 206. Figure 6 As shown, layer 202 can be a probe that can be integrated within layer 204. In other cases, layer 202 can be nested within layer 204. For example, layer 204 may include a cavity, and layer 202 can be inserted into the cavity. In some cases, the outer surface of layer 202 can be flush with the outer surface of layer 204, which is... Figure 6 The diagram is shown in the figure. In some cases, layer 204 may be semi-permeable to oxygen diffusion through it, or substantially impermeable to oxygen diffusion through it. Regardless of the configuration, layer 202 may be surrounded by layer 204, thereby reducing oxygen diffusion from the surrounding environment through layer 204 and into layer 202. In some cases, similar to layer 178, light from the photon source and light from the probe can pass through layer 204. Therefore, layer 204 may be transparent.

[0099] In some embodiments, layer 206 may be positioned below layer 202 (and may be coupled to layer 206). Layer 206 may be semi-permeable to oxygen diffusion through it, and may be more permeable to oxygen diffusion through it. In this way, layer 202 receives a greater amount of oxygen from side 208, unlike side 210. In some configurations, layer 206 may scatter or reflect ambient light directed at layer 206, which may prevent ambient light from reaching the photodetector (e.g., this would reduce the signal-to-noise ratio). In some configurations, substrate 200 may include layer 212 positioned below layer 206 (and coupled to layer 206), which may reflect or scatter light directed at layer 212.

[0100] Figure 7A A schematic diagram of sensor head 220 is shown, which may be similar to sensor head 156 of oxygen sensor system 150. Therefore, sensor head 156 may be replaced by sensor head 220, or it may be integrated into different oxygen sensor systems described herein. Figure 7A As shown, the sensor head 220 may include a housing 222 configured to engage with the tissue 224 of the subject.

[0101] Figure 7B It shows along Figure 7A The image shows a cross-sectional view of the sensor head 220 taken from line 7B-7B. (See image for reference.) Figure 7B As shown, the housing 222 may define a region 226 that may contact, be in gas communication with, be in fluid communication with, or otherwise approach the tissue 224. Additionally, the housing 222 may engage the tissue 224 such that the housing 222 is (temporarily) sealed to the tissue 224, thereby (partially) isolating the region 226 from the surrounding environment. In some cases, the housing 222 may be semi-permeable to oxygen diffusion through it. For example, although not shown, the housing 222 may include one or more channels (e.g., microchannels) oriented through the housing 222. In some embodiments, the sensor head 220 may include a probe 228 that may contact, be in gas communication with, or be in fluid communication with the region 226, which is designed to receive the tissue 224, preferably to avoid forming voids. For this purpose, the region 226 may present a probe 228 without any grooves. For example, the probe 228 may be positioned within the region 226 and may be coupled to the housing 222.

[0102] In some cases, sensor head 220 may include photon sources 230, 232 and photodetector 234 optically coupled to probe 228. For example, as Figure 7B As shown, each photon source 230, 232 and photodetector 234 can be positioned within a recess 236 of a housing 222 that is in contact with probe 228 and is in gas or fluid communication with it. In this way, photodetector 234 can be shielded from ambient light by housing 222. In addition, housing 222 can block light from entering area 226 from the surrounding environment.

[0103] Figure 8 A schematic block diagram of an oxygen sensor system 250 is shown, which can be a specific implementation of the oxygen sensor system 100. Therefore, the oxygen sensor system 100 is related to the oxygen sensor system 250 (and vice versa). Figure 8As shown, the oxygen sensor system 250 may include one or more photon sources 252, one or more photodetectors 254, one or more temperature sensors 256, optical fibers 258, 260, and 262, a tree coupler 264, and a probe 266. The probe 266 may be optically coupled to the optical fiber 258. For example, the probe 266 may be coupled to an end of the optical fiber 258. In some cases, the probe 266 may be a coating disposed on the optical fiber 258.

[0104] In some embodiments, opposite ends of optical fiber 258 may be coupled to the output of tree coupler 264. Correspondingly, one end of optical fiber 260 may be coupled to a first input of tree coupler 264, and opposite ends of optical fiber 260 may be optically coupled to one or more photon sources 252. Additionally, one end of optical fiber 262 may be coupled to a second input of tree coupler 264, and opposite ends of optical fiber 262 may be optically coupled to one or more photodetectors 254. In this manner, light from photon source 252 can be emitted into optical fiber 260, which can then pass through optical fiber 260, through tree coupler 264, through optical fiber 258, and can be directed at probe 266 (e.g., excitation probe 266). Correspondingly, light emitted from probe 266 (e.g., in response to photon source 252) can return to photodetector 254 via optical fiber 258, tree coupler 264, and optical fiber 262.

[0105] In some embodiments, temperature sensor 256 may be in thermal communication with probe 266, so that temperature data from temperature sensor 256 can indicate the temperature of the environment in which probe 266 is positioned. For example, the temperature sensor may be in thermal communication with probe 266 at the distal tip of an optical fiber. In another example, temperature sensor 256 may be in thermal communication with optical fiber 258. In other cases, temperature sensor 256 may be in thermal communication with tissue adjacent to probe 266. For example, temperature sensor 256 may be placed within a subject close to tissue.

[0106] In some embodiments, the optical fiber 258 is configured for insertion into the channel 270 of the medical device 268. For example, the diameter (or width) of the channel 270 of the medical device 268 may be less than 500 micrometers, and the optical fiber 258 may be smaller than the diameter of the channel 270 (e.g., the diameter of the optical fiber 258 is less than or equal to 200 micrometers). In some cases, the optical fiber 258 can be advanced through the channel 270 until part (or all) of the probe 266 is outside the channel 270 (e.g., the distal end of the channel 270). In some configurations, the medical device may be a syringe with a needle, catheter, etc. In other cases, the medical device may be an endoscope, and the channel 270 may be the working channel of the endoscope.

[0107] Although the oxygen sensor system 250 is illustrated as having a single probe 266, in other configurations, the oxygen sensor system 250 may include multiple probes, each positioned at a different longitudinal location along the optical fiber 258. In some cases, the optical fiber 258 may include slits, scores, etc., at each longitudinal location of the probe 266 to ensure light is emitted to and received from the corresponding probe 266.

[0108] In some configurations, probe 266 can be formed from multiple layers. For example, a first layer can be coupled to optical fiber 258, a second layer can be coupled to the first layer, and so on, to form probe 266. Each layer may include a photoluminescent material. This structure can produce a thin film for probe 266, which can significantly reduce the size of probe 266, thereby significantly increasing the oxygen sensing speed (e.g., the probe responds quickly to changes in oxygen partial pressure).

[0109] In some configurations, probe 266 can be coupled to medical device 268. For example, probe 266 and optical fiber 258 can be inserted into channel 270 of medical device 268 and coupled to medical device 268 within channel 270 (e.g., via the use of epoxy resin, adhesive, etc.). In this way, when medical device 268 is a needle, the needle can be directly inserted into the subject (e.g., in a muscle area) without needing to redeploy probe 266 into medical device 268, thus saving time. In another example, after the medical device has been inserted into the patient, the optical fiber can be repeatedly inserted into or reinserted into medical device 268. In this way, the probe can be used at specific times or as needed.

[0110] Although the oxygen sensor system 250 has been illustrated with two optical fibers 260, 262, in other configurations, the oxygen sensor system 205 may include additional optical fibers, each coupled to a corresponding input of the tree coupler 264. The opposite ends of each fiber can then be optically coupled to either the photon source 252 or the photodetector 254.

[0111] Figure 9 A schematic block diagram of an oxygen sensor system 280 is shown, which can be a specific implementation of oxygen sensor system 100. Therefore, oxygen sensor system 100 is related to oxygen sensor system 280 (and vice versa). Figure 9 As shown, the oxygen sensor system 280 may include one or more photon sources 282, one or more photodetectors 284, one or more temperature sensors 286, an optical fiber 288, a probe 290, and a beam splitter 292. Figure 9As shown, light emitted from one or more photon sources 282 enters optical fiber 288 through beam splitter 292, passes through optical fiber 288, and is directed to probe 290 (e.g., to excite probe 290). Correspondingly, light emitted from probe 290 is reflected back into optical fiber 288, passes through optical fiber 288, and is directed by beam splitter 292 to one or more photodetectors 284.

[0112] Figure 10 A flowchart of a process 300 for monitoring a patient according to this disclosure is shown. At 302, process 300 may include placing a probe to communicate with the subject's tissue. As used herein, communication may include making contact, in gas communication, in fluid communication, or otherwise positioning to obtain information related to the subject's tissue. For example, this may include coupling a substrate including the probe to the subject's skin. As another example, the medical device may be inserted into the subject (e.g., into the subject's muscle, orifice, cavity, etc.) when the probe is coupled to an optical fiber and the optical fiber (including the probe) is inserted into the medical device (e.g., catheter, needle, etc.). As described above, the probe may include a plurality of probes having corresponding operating ranges and configured for excitation based on corresponding signals.

[0113] At 304, process 300 optionally includes calibrating the sensor system or receiving (e.g., from the memory of a computing device) calibration values(s). In some cases, this may include a computing device receiving a calibration curve based on, for example, temperature data (e.g., a temperature response curve versus analyte concentration). In some cases, the calibration curve may be a Stern-Volmer curve. The calibration steps will be described in more detail below.

[0114] At 306, process 300 may include an analog or computational device that causes one or more photon sources to emit photons. This can be achieved by creating a time-varying distribution that is generally designed to excite probes. As described above, probes may include multiple probes or probe components or regions having corresponding operating characteristics or operating ranges and configured to be excited based on corresponding signals. For this purpose, the time-varying distribution may be formed by combining two or more sub-signals, wherein each sub-signal is designed to excite a corresponding probe component or region of the multiple probe components or regions.

[0115] For example, the corresponding time-varying distribution may have time-varying intensity (e.g., the total intensity of light emitted by a photon source may change over time) and consist of corresponding sub-signals with different frequencies, each frequency being designed for one of a plurality of probe components or regions. In a non-limiting example, the computing device may cause a first photon source to emit photons according to a first sub-signal and a second photon source to emit photons according to a second sub-signal, thereby exciting two of the plurality of probe components or regions. Thus, in some cases, each time-varying intensity distribution may be periodic and may include multiple frequencies. For example, the time-varying intensity curve may be a sum of sine waves (e.g., multiple different sine waves, each corresponding to a different sub-signal configured to excite a corresponding probe component or region), and therefore, the time-varying intensity curve may have multiple different frequencies.

[0116] Creating a time-varying distribution based on sub-signals with different corresponding frequencies is just one non-limiting example. In some cases, the time-varying distribution can be non-periodic. For example, the time-varying distribution can be an impulse function (or in other words, an increment function), a pulse (e.g., a square pulse, a rectangular pulse, etc.), etc.

[0117] Furthermore, the time-varying distribution and / or sub-signals can change over time. For example, the time-varying distribution can change over time (e.g., in response to a change in the measured oxygen concentration). Such changes can include alterations to the waveform, such as modifying the fundamental frequency, or adding or subtracting a sine wave that can be used to dynamically change (e.g., the sensitivity, accuracy, precision, operating range, or functionality of multiple probe components or regions), thereby adjusting the overall sensitivity, accuracy, precision, operating range, or functionality of the entire sensing system. This feedback control approach can be used to optimize the overall functionality of the sensor within a given range, such as the oxygen concentration range.

[0118] At 308, the probe is excited once the photon source(s) emits light based on a time-varying distribution (and thus the sub-signals used to form the time-varying distribution). In a non-limiting example of a probe designed for monitoring an analyte and in a non-limiting example of oxygen as an analyte, the interaction between the oxygen-sensitive probe and photons from one or more photon sources will cause the probe to emit light. In this case, the light emitted from the probe will have a time-varying distribution, which may correspond to the time-varying distribution of photons emitted from one or more photon sources (e.g., at 306), at least because the photons from the probe excite the probe, thus causing the probe to emit light. In this way, the source operates according to a first time-varying distribution, and the probe emits light according to a second time-varying distribution. In some cases, the wavelength of the light emitted by the probe may be greater than the wavelength of the photons emitted from one or more photon sources. For example, the wavelength of the light emitted from the probe may be in the red visible range, while the wavelength of the light emitted from one or more photon sources may be in the blue visible range (or the ultraviolet range).

[0119] At 310, process 300 may include a computing device receiving optical data from one or more photodetectors based on the interaction between light emitted from the probe and one or more photodetectors. In some cases, the optical data may include first optical data from a first photodetector based on the interaction between light emitted from the probe and the first photodetector. Additionally, the optical data may include second optical data from a second photodetector based on the interaction between light emitted from the probe and the second photodetector. In some cases, the optical data may include a time-varying intensity distribution (e.g., represented by intensity values ​​of the optical data) that may correspond to the time-varying intensity distribution of photons emitted from one or more photon sources. For example, the shape of a portion (or the entirety) of the second time-varying distribution of the optical data may correspond to the shape of a portion (or the entirety) of the first time-varying distribution of electrons emitted from one or more photon sources (e.g., it may be substantially the same as the shape of a portion (or the entirety) of the first time-varying distribution of electrons emitted from one or more photon sources).

[0120] At 312, process 300 may include a computing device using optical data (e.g., more than one optical dataset) to determine response information. For example, the computing device or controller may compare or analyze a first time-varying distribution and a second time-varying distribution. Similarly or additionally, the computing device or controller may analyze or compare sub-signals used to create the first time-varying distribution and extract components of the sub-signals from the second time-varying distribution. In some cases, such comparison or analysis may consider one or more time delays, one or more phases, or one or more time constants (e.g., a lifetime). For example, when the time-varying distribution emitted from one or more photon sources is a pulse, the computing device may determine a first time when photons are emitted from one or more photon sources (e.g., using a timestamp). The computing device may then determine a second time when one or more intensity values ​​from the optical data exceed (e.g., are greater than) a threshold (e.g., corresponding to background light, which may be noise). Therefore, the computing device can then determine a time delay by subtracting the first time from the second time. In some cases, the computing device may determine multiple time delays using the process described above (using different start times for the first time and different thresholds to determine the second time). This can be done using time-varying distributions and / or sub-signals.

[0121] As another example, a computing device can determine the phase difference between two time-varying distributions or sub-signals. For instance, the computing device can determine a first time-varying amplitude wave with a frequency based on a first time-varying amplitude distribution corresponding to photons emitted from one or more photon sources, and determine a second time-varying amplitude wave with a second frequency based on a second time-varying amplitude distribution of optical data. In some cases, the time-varying amplitude distribution corresponding to photons emitted from one or more photon sources can be data of an electrical waveform used to drive one or more photons, or it can be optical data received by one or more photodetectors based on the direct interaction of photons (e.g., UV light) from one or more photon sources with one or more photodetectors (e.g., photodetectors receiving UV light). In some cases, the first frequency may be substantially similar to (or the same as) the second frequency. The computing device can then determine the phase difference between the first and second time-varying amplitude waves.

[0122] In some cases, including when a first time-varying distribution includes a first plurality of frequencies and a second time-varying amplitude distribution includes a second plurality of frequencies, the computing device can determine a first reference time-varying amplitude wave having a first reference frequency and a second reference time-varying amplitude wave having a second reference frequency. For example, the computing device can (e.g., by using a multiple regression method) combine the first plurality of frequencies (e.g., a fundamental frequency, one or more harmonics of the fundamental frequency, etc.) into a first reference time-varying amplitude wave. In other words, the computing device can (e.g., using statistical methods such as multilinear regression) combine multiple frequencies (e.g., the fundamental frequency and higher harmonics) with their amplitudes and phases into a signature. Similarly, the computing device can (e.g., by using a multiple regression method) combine the second plurality of frequencies (e.g., the fundamental frequency, one or more harmonics of the fundamental frequency, etc.) into a second reference time-varying amplitude wave. In some cases, the first reference frequency may be substantially similar to (or identical to) the second reference frequency. The computing device can then determine the difference (e.g., phase difference) between the frequencies contained in the first reference time-varying amplitude wave and the second reference time-varying amplitude wave. In some configurations, by using a first reference time-varying amplitude wave with multiple frequency components, the detection of luminescence can be more robust (e.g., more accurate) or within a larger operating or dynamic range than using only a single frequency (e.g., in the case of measuring multiple luminescent dyes with different lifetimes, or when the lifetime of a single dye may undergo increases or decreases requiring different measurement frequencies).

[0123] In some embodiments, the computing device (or electronic filter) can filter each time-varying amplitude distribution to isolate one or more of the aforementioned frequencies. In some cases, this may include digital filtering of the time-varying amplitude distribution in the time or frequency domain (e.g., using Fourier Transform (FT), Fast Fourier Transform (FFT), etc.). In some cases, if filtering is performed in the frequency domain, the resulting frequency information can be converted back to the time domain so that the phase difference can be subsequently determined.

[0124] As another example, when the time-varying intensity distribution of photons emitted from one or more photon sources is pulsed, a computing device can determine one or more time constants from the time-varying intensity distribution of optical data received by one or more photodetectors. For example, the computing device can fit an exponential decay function to the optical data to determine the time constant. In some cases, the exponential decay function can be a single exponential decay with a single time constant, or it can be multiple exponential decays with multiple time constants. In the latter case, the computing device can determine each time constant from multiple exponential decays and can utilize one or more time constants, or can combine each time constant, to determine the resulting time constant. For example, a computing device can extract the different lifetimes of oxygen-sensing dyes embedded in different regions with different diffusion constants.

[0125] In some embodiments, the computing device can determine a time constant from the spectrum of a time-varying intensity distribution. For example, using sufficiently fast data sampling, the computing device can (e.g., using FT or FFT of the time-varying intensity distribution in the frequency domain) perform spectral analysis of the time-varying intensity distribution to determine the amplitude and phase of a first reference time-varying intensity distribution and a second reference time-varying intensity distribution at a given frequency (e.g., at the fundamental frequency or higher harmonics). The relative phase between the first and second reference time-varying intensity distributions at the given frequency can then be obtained from the phase difference, which can be used (e.g., in the case of sinusoidal modulation, via the relationship tan(θ) = 2πτ). f (where θ is the relative phase, f The lifetime is determined by a given frequency and τ is the lifetime.

[0126] At 314, process 300 optionally includes a computing device receiving temperature data from one or more temperature sensors. In some cases, the temperature data may include at least one of the following: first temperature data from a first temperature sensor in thermal communication with the tissue, second temperature data from a second temperature sensor in thermal communication with an oxygen sensor, and third temperature data from a second temperature sensor in thermal communication with one or more photon sources.

[0127] At point 316, parameters can be determined from the analysis described above. As an example only, monitoring may include sensing the analyte, and therefore, parameters may be related to the analyte. As a non-limiting example, the analyte may be oxygen, and monitoring may be, for example, oxygen levels via oxygen partial pressure (e.g., in the subject's tissue), which can be achieved using the oxygen sensor system described herein. Therefore, process 300 may include a computing device determining oxygen partial pressure based on response information. For example, this may include determining oxygen partial pressure based on at least one of phase difference, time delay, or time constant. Specifically, phase difference may be compared to a calibration curve (e.g., a Stern-Volmer curve) that correlates phase difference with oxygen partial pressure to determine oxygen partial pressure. Similarly, time delay may be compared to a calibration curve (e.g., a Stern-Volmer curve) or at least one predetermined lookup table that correlates time delay with oxygen partial pressure to determine oxygen partial pressure. Additionally, time constant (or in other words, lifetime) may be compared to a calibration curve (e.g., a Stern-Volmer curve) that correlates time constant or phase difference with oxygen partial pressure.

[0128] In some cases, in addition to response information, temperature data (e.g., received at box 314) can be used to determine the oxygen partial pressure. For example, a calibration curve (e.g., a Stern-Volmer curve) may include temperature dependence, so the computing device can use temperature data from a temperature sensor in thermal communication with the tissue, along with the response information, to determine the oxygen partial pressure.

[0129] At point 318, process 300 may generate and / or transmit a report. In this case, the computing device may be a controller and / or a separate computing device. In one non-limiting example embodiment, the device measures a waveform and embeds an algorithm into the controller for onboard processing, simply informing a connected mobile phone or computer of the pO2 it measures. In another non-limiting example embodiment, the device sends the waveform to a mobile phone or computer, where the signal is analyzed to obtain the pO2 value. In some cases, if the computing device determines that the oxygen partial pressure exceeds a threshold, the computing device may notify the user (e.g., a practitioner) by activating an alarm, displaying a graphic on a monitor, or otherwise. For example, the computing device may determine the presence of tissue ischemia based on an oxygen partial pressure below a threshold, and subsequently notify the user accordingly. As another example, the computing device may determine the presence of oxygen toxicity based on an oxygen partial pressure above a threshold, and subsequently notify the user accordingly. Therefore, in another non-limiting example, process 300 can be used to determine the presence of local ischemia (e.g., lack of blood) in a tissue (e.g., in conjunction with an oxygen sensor) or to determine the presence of oxygen concentration in the superior ganglion (e.g., when the tissue is being treated with high pressure).

[0130] In some cases, regardless of the reporting in box 318, process 300 may include a computing device (e.g., in the form of a report) to display the results of one or more boxes of process 300. For example, the computing device may display response information, one or more time-varying intensity distributions, oxygen partial pressure, etc. In some cases, process 300 may return to box 306 to continuously monitor the subject's oxygen partial pressure value. This may be done in real time, for example.

[0131] As described above, process 300 can be implemented using one or more computing devices (e.g., a controller). In a non-limiting example of monitoring partial oxygen pressure, partial oxygen pressure can be determined by estimating the lifetime and intensity of luminescence, for example, algorithmically (multilinear regression, nonlinear regression, lock detection, FFT, etc.). In other non-limiting examples, lifetime and intensity can be obtained through machine learning. In yet another non-limiting example, partial oxygen pressure can be calculated based on lifetime and intensity (e.g., by calibrating a lookup table, using a model based on empirical equations, or machine learning).

[0132] As described above, process 300 may include determining a calibration curve (e.g., a Stern-Volmer curve) or one or more calibration values. In some cases, the probe may be placed under known conditions of multiple oxygen partial pressures (and temperatures) rather than in contact with the subject's tissue, gas communication, fluid communication, or otherwise obtaining information related to the subject's tissue. Boxes 306-314 may then be completed for each oxygen partial pressure value (and each temperature value). The computing device may then construct a calibration curve based on the known oxygen partial pressure values ​​(and known temperature values) and corresponding response information (e.g., time delay, phase difference, time constant, etc.) and corresponding temperature data (appropriately). In some embodiments, the computing device may determine one or more calibration values ​​based on comparing the constructed calibration curve with another calibration curve (e.g., an ideal calibration curve, such as an ideal Stern-Volmer curve). For example, the difference between each corresponding point in these curves may be determined and used to refine the determined oxygen partial pressure (e.g., at box 316). For example, the computing device may use the corresponding calibration value to increase (or decrease) the determined oxygen partial pressure to the refined partial pressure.

[0133] Example

[0134] The following examples are intended to further illustrate various aspects of the disclosure and are not intended to limit the scope of this disclosure in any way. The following examples are intended as illustrations of this disclosure, and these (and other aspects of this disclosure) are not theoretically limited.

[0135] Example 1

[0136] In recent years, wearable devices have been widely used as medical devices and consumer electronics for sports and health tracking. One health indicator often overlooked in existing technologies is the direct measurement of molecular oxygen in living tissue, a key component of cellular energy production. This disclosure reports the development of a wireless wearable prototype for transdermal oxygenation monitoring based on oxygen-dependent phosphorescence of metalloporphyrins embedded in a highly permeable oxygen sensing membrane. The device is fully self-contained, weighs less than 30 grams, performs onboard signal analysis, and can communicate with a computer or smartphone. The wearable device measures tissue oxygenation at the skin surface by detecting the lifetime and intensity of phosphorescence, which undergoes quenching in the presence of oxygen. Besides being insensitive to motion artifacts, it provides robust and reliable measurements even under variable atmospheric conditions related to temperature and humidity. Preliminary in vivo testing in a porcine ischemia model demonstrates that the wearable device is highly sensitive to physiologically significant changes in tissue oxygenation after inducing limb perfusion reduction.

[0137] In recent years, wearable devices that provide continuous monitoring of physiological variables have been widely used as medical devices and consumer electronics for exercise and health tracking. Commercially available devices can measure a large number of variables, such as heart rate or respiratory rate, blood oxygen saturation, exercise, force, temperature, and muscle activation. However, commercial wearable devices still lack the basic ability to measure several important physiological parameters.

[0138] Oxygen concentration is a crucial parameter that is often impossible to measure, despite being a key component of the cellular energy production machinery. Understanding tissue oxygen tension, or partial pressure of oxygen (pO2), at the skin surface is critical for diagnostic applications in burns, limb injuries, and surgical interventions. For this purpose, blood oxygen saturation (stO2) measurements are frequently used. However, these saturation measurements are indirect measurements of tissue oxygen content and cannot provide accurate readings when blood flow is impaired. In contrast, transcutaneous oxygen tension (TCOM) measurement is a direct measurement of available oxygen in tissue ready for cellular metabolism and is not entirely dependent on blood oxygen delivery or the condition of the underlying tissue capillary bed. TCOM devices measure local tissue oxygenation and can be advantageous in situations such as the application of a tourniquet or high-pressure therapy, as pO2 measurements may indicate the occurrence of local tissue ischemia or oxygen toxicity, respectively. On the other hand, blood oxygen saturation loses its ability to measure further changes in these situations when it reaches 0% or 100% in each case.

[0139] Despite its advantages over devices used to measure oxygen saturation, the measurement of pO2 and oxygen tension has not been widely adopted, primarily because traditional TCOM techniques involve bulky equipment, time-consuming and frequent bedside calibrations, precise placement, and highly trained operators. This paper describes a method for realizing a portable technique for tissue oxygenation monitoring by creating an optical tool based on metalloporphyrin molecules that undergo phosphorescence quenching upon contact with oxygen. This principle can be used to create a sensor for transdermal oxygen measurement that responds to changes in the lifetime of an oxygen-sensing phosphor incorporated into a transparent membrane. However, the ability to detect phosphorescence lifetime often comes at a cost, as it typically requires cumbersome experimental techniques and large benchtop instruments. Early attempts to improve the portability, ease of use, and data aggregation capabilities of TCOM techniques involved using oxygen-sensing molecules in research, where 2D maps of localized tissue oxygenation and oxygen depletion are generated by collecting images of luminescence intensity using a modified digital camera. Intensity-based methods can demonstrate excellent performance in specific scenarios with controlled experimental conditions or setups. For example, some work using topical oxygen-sensing bandages has found that percutaneous oxygenation monitoring can detect limb ischemia when arterial ligation is performed in mouse models, demonstrating that percutaneous oxygenation can be a non-invasive alternative for measuring tissue health. On the other hand, the phosphorescence lifetime-sensitive techniques described in this paper exhibit significant advantages because they generally do not experience signal variability due to changes in sensor geometry, excitation source intensity, photobleaching, etc., which can plague intensity-based methods. Current advances in low-power electronics, communications, and materials engineering have facilitated the development of TCOM wearable devices; however, these wearable devices are often bulky (e.g., relying on large external reading electronics) or involve invasive components or processes.

[0140] In this example, a wireless and non-invasive wearable prototype has been developed to continuously monitor tissue oxygenation based on an internally developed metalloporphyrin that can be easily embedded in a polymer membrane, thereby providing a material that exhibits bright emission across the entire physiological pO2 range.

[0141] Figure 11 An optical wireless wearable prototype for transdermal oxygen monitoring based on phosphorescence emission using a highly oxygen-permeable sensing membrane is shown. The prototype consists of an oxygen sensing membrane, a sensor head, and control electronics. The block diagram illustrates the control electronics and sensor head circuitry.

[0142] Response and Calibration. The wearable device measures tissue oxygenation at the skin surface by detecting changes in the lifetime τ and fluorescence emission intensity I of a highly permeable multilayer oxygen sensing membrane. The membrane exhibits bright luminescence in the pO2 range of 0–160 mmHg, with a peak emission at 650 nm. It produces a lifetime of approximately 15 μs in indoor air (pO2 = 160 mmHg) and approximately 96 μs in zero oxygen (see [link to relevant documentation]). Figure 12 The oxygen sensing membrane consists of the following layers (see membrane orientation). Figure 11 The study utilizes a semi-permeable transparent membrane that partially isolates the skin from atmospheric oxygen, a poly(propylene methacrylate) (PPMA) membrane with embedded metalloporphyrins, a transparent and breathable membrane, and a spin-coated white breathable layer that increases collected emission through backscattering and also serves as optical insulation against external light sources. These membranes are unaffected by changes in relative humidity, addressing one of the key challenges in applying these oxygen-sensing materials to wearable devices that monitor human performance, as sweat can vary significantly depending on climatic conditions or body position.

[0143] like Figure 11 As shown, the device is built around a wireless-enabled microcontroller and includes a small sensor head and main control electronics. A viscous oxygen-sensing membrane is attached to the sensor head, which is 14 mm in diameter and 3 mm thick, and consists of a flexible printed circuit board (PCB) within a 3D-printed housing. The PCB is the host for several small surface-mount electronics: two high-power UVA LEDs (Lumileds Amsterdam, Netherlands) with a peak wavelength of 385 nm, used to excite phosphor molecules and generate emission from the oxygen-sensing membrane; a PIN photodiode (Osram Munich, Germany) for detecting the emission; and a thermistor (TDK Tokyo, Japan) for measuring temperature. The LED excitation is filtered by stacking two ultrathin flexible optical notch filters (Edmund Optics Barrington, New Jersey, USA), which serve as short-pass filters at 400 nm within the range of interest (see Figure 13). A 500 nm long-pass collecting filter, capable of blocking LED emission, is fabricated by combining a flexible 405 nm long-pass filter (Edmund Optics, Barrington, NJ) and a polyamide film (DuPont, Wilmington, USA). The sensor head is attached to the control electronics via a thin, flexible ribbon cable. By folding the flexible connector and sensor head under the control electronics housing, the sensor head and oxygen sensing membrane are protected from mechanical stress. This design helps protect the sensor head and provides adhesion, as well as an airtight and stable seal for the pO2 sensing membrane on the skin (see Figure 13). Figure 11 This device is a true wearable device because it is completely self-contained, performs signal analysis on the board, and weighs only about 30 grams.

[0144] like Figure 11 The block diagram and the analog-to-digital converter (ADC) output waveform shown in Figure 14 (e.g., panel b) demonstrate how this device utilizes a sinusoidal reference signal (f) rThe change in the fluorescence lifetime of an oxygen-sensing phosphor is detected by driving an excited LED with a frequency of 796 Hz and measuring the microsecond delay or phase (θ) between a reference signal and the emitted signal (also a sinusoidal signal). In the case of a single lifetime during emission, this phase can be expressed by the formula tan(θ) = 2πτf. r This is correlated with lifetime. Because the membrane contains a single fluorescent dye, 97% of the molecules exhibit the same lifetime (see [link to relevant documentation]). Figure 12 A sinusoidal reference signal is sufficient to characterize fluorescence lifetime. As described below, this allows for a simple signal analysis method that can be executed onboard on devices with limited computing power, such as microcontrollers. Changes in lifetime τ are reflected by the emission intensity I, and are obtained from the amplitude of the signal measured at the driving frequency, which responds to changes in pO2. An algorithm based on multilinear regression in matrix form is developed to extract emission lifetime and intensity.

[0145] The dependence of the measured variable X (i.e., τ or I) on pO2 is governed by this equation, which is modified by the Stern-Volmer relation:

[0146] X = X0 / (1 + K eff pO2) + X OFF (1)

[0147] Where X0 is the value of X under hypoxia, and X OFF This is the non-oxygen-related offset generated by the measurement system. In the case of dynamic quenching and diffusion-controlled processes, the Stern-Volmer quenching constant, K... eff K is a measure of the oxygen diffusion coefficient of multilayer films. eff It is temperature-dependent, primarily due to the collisional quenching rate of porphyrins, and to a lesser extent, due to changes in the oxygen diffusion parameters of the polymer layer, which may also change with aging, as shown below. K was discovered. eff Secondary dependence on temperature (K) eff =K0+K1 (T-32)+K2 (T-32) 2 This illustrates the use of Figure 11 The trends observed in the data measured from the final designed and manufactured prototype are shown. Early iterations of the device using different 3D printing materials produced negligible quadratic terms, as can be seen from the data shown in Table 1 (below), which can be explained by slight differences in sensor geometry, LED leakage to photodiode signal, and thermal properties of the sensor head.

[0148] Figure 15The plot shows the intensity versus time curve for phase calibration for each harmonic, divided by its exponent I and taking the offset β0 and the harmonic amplitude I. i The logarithm of the harmonics. For example, the left graph shows the phase change of each harmonic with time, the middle graph shows the logarithm of the harmonic amplitude of each harmonic with time, and the right graph shows the emission intensity with time.

[0149] Table 1

[0150] Lifetime and intensity calibration parameters for the same oxygen sensing membrane at three different calibrations: initial calibration, calibration performed after removing and repositioning the membrane on the sensor head, and final calibration after storing the device with the attached membrane for three months. The percentage change for each parameter is relative to previously measured values. The K2 value is not shown because the fitted value is close to zero.

[0151]

[0152] To evaluate the prototype's performance, the sensor head was equipped with an oxygen-sensing membrane, and the device was inserted into a sealed calibration chamber (see [link]). Figure 16 The changes in temperature and oxygen partial pressure during calibration are shown in Figure 14 (e.g., panel a). During calibration, the first scan of pO2 was performed at a high body-like temperature, and the second scan was performed at room temperature. As shown in panels b and c of Figure 14, θ increased as pO2 was gradually scanned between atmospheric values ​​(160 mmHg) and pure nitrogen atmosphere (0 mmHg). p Monotonically increasing. Throughout the measurement, the temperature varied between indoor conditions (24°C) and skin temperature (32°C). θ p and θ r Both exhibit similar fluctuations, stemming from subtle differences in pO2 measurements between the time elapsed from when the PWM output is "on" to when ADC sampling begins. θ p The fluctuations can be eliminated by calculating the relative phase change between the photodiode and the reference signal, for example, θ = θ p -θ r This is referred to as the phase from here. As shown in panel d of Figure 14, the emission intensity exhibits a very similar response. Both lifetime and intensity signals demonstrate high signal-to-noise ratios (29 dB and 31 dB, respectively) and require no smoothing or filtering to achieve good signal contrast across the entire physiological range. These results are consistent across multiple prototypes and O2 sensing films.

[0153] Panels a and b (and panels d and e) of Figure 17 show that the characteristics of the lifetime and intensity data, due to variations in pO2 and temperature, are well described by the temperature-dependent Stern-Volmer equation. Panels c and d of Figure 17 show estimates of pO2 obtained from the lifetime and intensity data, which closely match measurements from a reference commercial pO2 sensor, where the differences may stem from variations in the response times of the two devices and from the different temperature gradients experienced by each sensor due to its location within the chamber.

[0154] To test the reproducibility of calibration parameters related to the positioning of the sensing membrane, the calibrated oxygen sensing membrane was removed from the device and reattached to the sensor head. Subsequent calibration showed that the fitted parameters for all lifetimes (see Table 1) differed only slightly from the previous values. However, the fitted parameters for intensity were observed to differ from the earlier position of the oxygen sensing membrane. The invariance of lifetime parameters with sensor placement highlights a key advantage of lifetime-based measurements compared to intensity-based methods, which are highly dependent on orientation.

[0155] Membrane aging was also tested over time (see Table 1). Devices with attached membranes were stored for three months, protected from indoor lighting but subjected to changes in environmental conditions. Membrane calibration showed that θ0 and θ... OFF The parameters remained unchanged compared to the previous calibration, while K0 and K1 experienced significant decreases, indicating that the oxygen diffusion properties of the membrane change over time. The intensity parameters did not show a clear trend.

[0156] Tissue oxygenation was sensed in an in vivo porcine model. To evaluate the device's response to monitoring tissue oxygenation during physiological changes, in vivo experiments were conducted on a porcine model (Yorkshire pig). The anatomy of pigs, particularly their skin (structure, thickness, etc.), is very similar to that of humans, making porcine models suitable for monitoring transcutaneous physiological oxygenation changes. Changes in tissue oxygenation were induced by applying a tourniquet above the elbow joint (above the triceps, biceps, and brachialis muscles), obstructing blood flow to the forelimbs of the porcine model, as shown in panel a of Figure 18, for 30 minutes. The 30-minute waiting period was selected under guidance from previous work to allow the device to reach pO2 equilibrium with the skin. The animal surgical protocol was reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of Massachusetts General Hospital.

[0157] To prepare the area of ​​interest, a 10x10 cm area of ​​the pig's foreleg was cleaned with soapy water and shaved until all hair was removed. After shaving, the skin was wiped with isopropyl alcohol. An oxygen sensing membrane was pre-attached to the sensor head, and atmospheric pO2 was sampled for several minutes as a reference before applying the device to the skin, as shown in panel b of Figure 18. Since the initial temperature (19°C) was outside the temperature range (23–32°C) considered during calibration, the reference reading differed from 160 mmHg. As the data shows, when the temperature was within the calibration range (T 23°C), the lifetime pO2 indicated an indoor air value close to 160 mmHg. This issue was easily resolved by expanding the calibration temperature range. After the device was applied to the pig skin, the sensor head rapidly reached thermal equilibrium within approximately 3 minutes due to its small mass. The estimates of pO2 obtained from phosphorescence lifetime and intensity exhibit an exponential decay trend due to a number of factors, such as initial oxygen between the membrane and tissue, tissue oxygenation (i.e., the balance between oxygen supplied by the blood and oxygen consumed by muscles and skin), atmospheric oxygen uptake by the skin, oxygen permeability of the skin, and atmospheric oxygen permeability through the medical adhesive layer.

[0158] After a 30-minute equilibrium period, the tourniquet was applied, and both lifespan and intensity pO2 indices were observed to respond immediately to impaired blood flow by decreasing at a faster rate (see panel b of Figure 18). This is clearly seen by plotting the time derivative of pO2 in panel c of Figure 18, which indicates the oxygen consumption rate in the tourniquet scenario. The data show an increasingly negative pO2 slope, reaching its maximum approximately 5 minutes after tourniquet application (occlusion). Due to the lack of blood flow, the limb temperature decreased by 2.5°C from its original baseline temperature. The tourniquet was released after 30 minutes, and the limb temperature was observed to return to baseline, while pO2 again exhibited an increased decay rate of approximately 5 minutes. This further decay, occurring simultaneously with intense bleaching of the limb's skin, indicates irreversible tissue damage due to the tourniquet's location.

[0159] These preliminary results demonstrate the device's significant potential for applications involving the monitoring of oxygenation in living tissue. While their capabilities have been enhanced as diagnostic or monitoring tools for predicting wound healing, determining amputation levels, hyperbaric oxygen therapy, ischemia severity, etc., devices for directly measuring tissue oxygenation have not been widely adopted due to issues such as the need for bulky tools, complex calibration procedures, and extensive user training. Developed wearable devices overcome these problems by using readily available, low-power electronics that can easily interface with multiple devices such as computers or smartphones. These devices require very few components and their size can be significantly reduced for commercial applications. Therefore, the techniques described herein can certainly find applications in consumer devices, thus allowing for the assessment of tissue oxygenation at the point of care, and accessibility to people in low-resource environments. Furthermore, the process developed for extracting lifetime and intensity from time series is suitable for implementation in embedded devices with low computational power, as it involves simple matrix operations with minimal memory requirements.

[0160] The measurements are always reproducible between the device and calibration, and are robust to changes in temperature and humidity. Since pO2 measurements are based on lifetime detection, this device offers a significant advantage over purely intensity-based measurements, which can exhibit instability due to factors such as background noise, excitation source fluctuations, and photobleaching. These claims are supported by lifetime calibration parameters that remain constant regardless of film repositioning, making lifetime-based measurements more motion-tolerant. Additionally, because lifetime is unaffected by parameters including film placement and LED intensity, the developed device can achieve K... eff Constantly tracking changes in permeability is used to detect and compensate for the effects associated with polymer membrane aging. On the other hand, as shown in Table 1, such information cannot be obtained from the intensity calibration parameters because the overall intensity-oxygen response changes with membrane aging, which affects factors such as membrane drying and aggregation. Furthermore, the lifetime estimate from the developed inexpensive and miniaturized device is in excellent agreement with lifetime characterization performed on the oxygen-sensing membrane using a state-of-the-art spectrometer (FLS1000 steady-state and phosphorescent lifetime spectrometer from Livingston Edinburgh Instruments, UK); the device yielded values ​​of 10 µs and 80 µs at 24°C in atmospheric and zero oxygen conditions, while the values ​​obtained using the spectrometer were 15 µs and 96 µs. This discrepancy may be due to excitation light leakage into the detector (see Table 1). Figure 19 ) or there may be more than one lifetime material (see Figure 12 This can lead to a lower detected average lifetime. These contributions can be accounted for by appropriate models to better estimate lifetime; however, we were able to obtain a reproducible relationship between phase and pO2, which was the main objective of this project.

[0161] This example also demonstrates the feasibility of applying the device to in vivo measurements in a porcine occlusion model. Following induced physiological changes, the device is able to monitor changes in tissue pO2 on the skin surface, responding rapidly to changes in local oxygenation. Changes in variables such as temperature, humidity, and skin bleaching can confound phosphorescent oxygen quenching-based pO2 measurements and are often overlooked or ignored in the literature, or overcome by adding heating elements that prohibit the application of such tools (e.g., in neonatal care). The device presented here is able to track changes in tissue oxygenation during in vivo experiments without being affected by these variables. For non-temperature-compensated systems, increases in temperature can be misinterpreted as increases in pO2. During in vivo testing, a faster decrease in pO2 was observed after the application and removal of tourniquets, which cannot be explained solely by changes in limb temperature. During the calibration of the membrane used for in vivo studies, colder temperatures were not considered; instead, a focus was placed on warmer, body-like temperatures. To address this issue in future studies, the sensor can be easily recalibrated by scanning a wider temperature range, which can be accomplished using calibration chambers, hot plates, and ice / water mixtures, among other methods.

[0162] This device demonstrates an ideal response time for detecting physiological changes that typically occur within a few minutes. The fact that each component of this wearable tool is designed to be biocompatible (or skin-friendly) will accelerate the transition as it is brought into the first human clinical trials. Because measurements are performed on the skin surface, both skin and muscle contribute to the signal, and because transcutaneous measurements used to assess limb ischemia are largely homogeneous, the interpretation of transcutaneous oxygen measurements is complex and challenging, with many physiological factors contributing to the signal that are not well understood today.

[0163] Oxygen sensing membrane. Chemicals and adhesives: Trimethylacetyl-terminated platinum porphyrin embedded in the oxygen sensing membrane was prepared according to a previous protocol. Poly(propyl methacrylate) (PPMA) was purchased from Scientific Polymer Products. For use in semipermeable membranes (3M... TM Medical tape 1513 (double-sided transparent polyester, 80# inner lining, configurable) and breathable membrane (3M). TM Medical transfer adhesive 1524 (fiber-filled polyester, 60# liner, configurable) was purchased from 3M. i O2 white pigment concentrate and (45-55% methylhydrosiloxane)-dimethylsiloxane copolymer (HMS) were purchased from Gelest. Platinum (0)-1,3-divinyl-1,1,3,3-tetramethyldisiloxane complex solution (platinum catalyst) was purchased from Sigma-Aldrich.

[0164] Oxygen-sensing PPMA layer: 0.5 mg / μl PPMA in dichloromethane was prepared in small, clean microcentrifuge tubes. An aliquot from a stock solution of trimethylacetylplatinum porphyrin (resulting in a final metalloporphyrin concentration of 30 µM) was added to the PPMA solution and thoroughly mixed by vortexing. 20 µl of the porphyrin / PPMA solution was deposited onto a glass slide into an 8 mm diameter circular mold made of PDMS. The PPMA oxygen-sensing membrane was removed from the glass slide after drying in a hood for 30 minutes.

[0165] White scattering layer: 1 g of white pigment concentrate was thoroughly mixed with 3 µl of platinum catalyst on a weighing boat. The mixture was added to a glass slide and spun at 1500 rpm for 1 minute. 0.1 g of HMS copolymer was added to the white pigment film and spun at 750 rpm for 1 minute. The white scattering layer was completely cured overnight.

[0166] Sensor Head: The flexible PCB was designed using KiCad software and fabricated using a polyimide flexible substrate (OSH Park, Portland, Oregon, USA). The housing was manufactured at a resolution of 25µm using a Formlabs Form 3B 3D printer employing a biocompatible photopolymer resin suitable for medical applications. The fabricated part was then washed in a 90-100% isopropanol (IPA) bath for 20 minutes, stirred by a magnetically coupled impeller, and cured at 60°C for 30 minutes with LED / thermal at a wavelength of 405nm. After curing, the fabricated part can be chemically sterilized or autoclaved. This assembly serves as an optical cover for mounting excitation and emission filters. It also serves to optically isolate the LED from the photodiode and as a skin-friendly, flat surface on which the oxygen sensing membrane is placed. The optimal geometry was found to be a planar configuration of the LED and photodiode, with the parts as close as possible to each other. The housing is attached to the PCB using UV-cured epoxy resin (Thorlabs, New Jersey, USA), which provides mechanical stability and optical transparency for the propagation of excitation and emission light signals. Additionally, the epoxy resin acts as a thermal link between the O2 sensing film and electronic devices (LEDs, photodiodes, and temperature sensors). Due to the small size and mass of the sensor head, rapid thermal equilibrium is allowed, resulting in accurate localized temperature readings of the skin surface, film, and LED with a short response time.

[0167] Control electronics: The PCB was designed using KiCad software and fabricated on a standard glass fiber substrate (OSH Park, Portland, Oregon, USA). Flexible ribbon cables (Molex, Lyle, Illinois, USA) connect the sensor heads to the control electronics, which includes a custom-designed PCB whose electronics are built around a Particle Photonics or Argon microcontroller board with Bluetooth Low Energy (BLE) and / or WiFi connectivity (Particle, San Francisco, California, USA), powered by a rechargeable lithium polymer battery (see [link to documentation]). Figure 11 The microcontroller communicates via I2C with a 12-bit analog-to-digital converter (ADC) (Texas Instruments, Dallas, Texas Instruments, Inc.), which samples the reference signal, photodiode signal, and thermistor voltage through three differential voltage channels. Using a provided 5V reference, the ADC achieves a resolution of 1.2mV / bit. The LED is controlled by a programmable frequency (f... r The signal is modulated by a sinusoidal voltage signal (reference signal). This study uses f... r =796Hz reference frequency. The reference signal is filtered by a low-pass (LP) filter (4 poles, corner frequency or roll-off frequency f). c =f r The square wave (PWM) output provided by the microcontroller and amplified (gain x2) was obtained (see panels a and b in Figure 20). The filter and gain were chosen to achieve optimal depth modulation of the LED, producing a high-contrast, sinusoidal emission with a very low minimum output and a high maximum brightness. The LP filter method was chosen as a simple method to obtain a sinusoidal reference signal using only passive components. Using a function generator, it was found that the LED produces a brighter emission at frequencies below 1 kHz. Additionally, as shown in panel c in Figure 13, the LED also exhibits broad phosphorescence in the spectral region of oxygen-sensing dye emission, and for slower frequencies, the ratio of blue emission to phosphorescence is highest. A value of 796 Hz was obtained by using R = 5 kΩ and C = 0.1 μF, therefore f c =12πRC.

[0168] The photodiode signal is amplified by a transimpedance amplifier circuit (e.g., a transimpedance amplifier or TIA). Once the sensor head geometry, porphyrin concentration, and reference signal frequency are fixed, the TIA gain is selected to maximize the utilization of the ADC's dynamic range (e.g., a high ADC count, but without saturation at the maximum phosphorescence signal). A bandwidth of 636 kHz is achieved using a resistor fixed at 2.5 MΩ and a feedback capacitor of C = 0.1 pF. More information regarding the DC and AC characterization of the TIA and the ADC input and output can be found in Figure 20- Figure 23 Found it.

[0169] Temperature is measured by a thermistor with R1 = 10kΩ and a B value of 3650 (see [reference]). Figure 24 A dual-resistor circuit consisting of a reference resistor (R2 = 5kΩ) and a standard resistor (R2 = 5kΩ) was used for measurement using the Steinhart-Hart thermistor equation. A 3D-printed housing (see...) Figure 11 It is designed to house electronic devices and allows the devices to be securely fastened to the limbs via elastic bands or straps.

[0170] Calibration: Calibration is performed in a sealed calibration chamber, where temperature and pO2 can be controlled via a hot plate and by altering the mixture of nitrogen and air gases fed into a gas mixer, such as... Figure 16 As shown. A commercial oxygen sensor (PreSens GmbH, Regensburg, Germany) was used to measure a portion of the oxygen pressure in the chamber.

[0171] Data Collection: To obtain a single measurement of pO2, a modulated LED was blinked for approximately 0.2 seconds. During this time, 1000 time-voltage pairs were recorded against the reference and photodiode signals, with time measured in microseconds per unit. The LED blink duration was determined by the ADC sampling rate and the desired number of data points to acquire. The number of data points (1000) was chosen because it provides the amount of detail needed to accurately extract the phase and intensity values. By using a modulo operator, we used a value with T = 1 / f. r The time variable t' = mod(t, T) allows us to reconstruct a single oscillation of the reference signal and the photodiode signal with efficient high time resolution (see [reference]). Figure 22 , Figure 23 (See Figure 25). Data was collected via a Python script on a PC through a USB serial port or Bluetooth.

[0172] Data Analysis: Phase and Intensity Extraction. The reference signal is dominated by a sine wave at the fundamental frequency, but higher-order odd harmonics (3f, 5f, 7f, ...) contribute to the signal. These higher-order odd harmonics are not fully filtered out from the square-wave PWM source. Plotting the Fast Fourier Transform (FFT) of the reference signal (see Figure 25 panel c) shows that the amplitudes of harmonics 3f, 5f, and 7f are only 2.3%, 0.8%, and 0.3% of the fundamental frequency, respectively. It was found that including terms up to 7f improves the accuracy of the fit and allows phase determination with high precision and reproducibility. As can be seen (see Figure 25 panel c), the photodiode signal also needs to include even harmonics (2f, 4f, ...) because they are present in phosphorescence due to the nonlinear nature of LEDs.

[0173] The reference and photodiode signals were fitted to the following function using matrix-form multilinear regression:

[0174] (2)

[0175] Where cos2πft + θ = cosθcos2πft - sinθsin2πft. The least squares coefficient βi allows for the calculation of the intensity (I) and phase (θ) of the fundamental frequency:

[0176] (3)

[0177] (4)

[0178] See the fitting results. Figures 26a-26d Data analysis is performed using GNU Octave and rewritten in C++ so that the device can perform calculations onboard.

[0179] Error calculation: The standard error of the least squares coefficients is derived from the variance-covariance matrix of the fitted parameters. The standard errors of θ and I are calculated through error propagation. The 95% confidence interval (95% CI) of the pO2 values ​​obtained from both phase and intensity measurements is calculated by estimating the standard error of pO2 using the Stern-Volmer equation and error propagation.

[0180] The lifetime of our oxygen sensing membrane was measured under deoxygenated conditions using an Edinburgh Instruments spectrometer at room temperature and indoor air (pO2 = 160 mmHg). 97% of the phosphors exhibited a lifetime of τ = 14.92 μs, while the remaining 3% produced a lifetime of τ = 57 μs. The 3% was shielded from oxygen alterations, as given by fitting a double exponential decay in the deoxygenation measurements. We obtained two distinct lifetimes for the emitter at 100% room temperature with a lifetime of τ = 95.73 μs.

[0181] Circuit design and characterization. Schematic diagram. Figure 20 shows a schematic diagram of the reference signal conditioning circuit in panel a (and the node signal measured by the oscilloscope in panel b), the ADC connection in panel b, and the ribbon cable connection between the control electronics PCB in panel d and the sensor head in panel e.

[0182] Regarding the signal conditioning circuit, the capacitor of the 4-pole low-pass filter is fixed at 0.1μF, and the resistor is selected such that the cutoff frequency of the LP filter is centered around the fundamental frequency of the PWM signal. Therefore, f c =1 / (2πRC) and R=2πf c C, for a modulation frequency of 796Hz, produces 5kΩ.

[0183] Ground and VIN are provided by a microcontroller, which is either Particle Photon (USB and Wi-Fi) or Particle Argon (USB, Wi-Fi, BLE, and sufficient RAM to perform onboard signal analysis). The microcontroller is powered by a USB or Li-Po battery connected to the appropriate power pin on the microcontroller board.

[0184] Transimpedance amplifier circuit. The TIA application specification specifies a fixed amplification range of 1MHz. The gain resistor is chosen to maximize the use of the ADC range, such that the maximum phosphorescent signal (at 0mmHg) will result in a high bit count without saturating the ADC channel. This resistor is fixed at 2.5MΩ, and with a desired amplification range of 1MHz, the required capacitor is obtained from C≤2π¹, resulting in C≤0.06pF. We are able to find C=0.1pF, which translates to a bandwidth of 636.6kHz, three orders of magnitude higher than the modulation frequency (796Hz). The DC and AC transfer functions of the TIA are further shown below, illustrating the circuit's gain and bandwidth.

[0185] TIA Characterization: The following measurements were performed on a prototype board of the circuit first built before designing the device's PCB. To characterize the DC transfer function, a constant illumination source was moved across a photodiode at increasingly shorter distances. The current generated by the photodiode was measured by connecting an ammeter in series with the photodiode, and the TIA output was measured by a voltmeter.

[0186] Figure 21a and Figure 21b A graph of the TIA experiment is shown, illustrating the expected linear dependence of the output voltage on the photocurrent. The linear fit reveals a voltage offset of 0.130V for the TIA (100mV for each design) and a V / A gain of 2.4MΩ, which is close to the value of resistor R6 in the circuit schematic.

[0187] Regarding bandwidth, the previous design was followed to reproduce the 1MHz photodiode amplifier characteristics of the device. To this end, once the sensor head was constructed with optimal geometry (LED as close to the photodiode as possible), the gain resistor was adjusted on the circuit to detect the light signal from the oxygen sensing membrane at a gain resistor of RG = 2.5MΩ (instead of the 53.6kΩ in the reference), which amplifies the 1.92μA current to 4.9V. To maintain the -3dB bandwidth at f p =1MHz, requires indoor air (low signal) to prevent amplifier saturation under low oxygen (high signal) conditions. Capacitor C = 1 / (2πRGf) p=0.06pF. 0.01pF was purchased, which makes fp = 636.6kHz. To characterize the AC transfer function, the schematic diagram on page 14 of the Texas Instruments application note was followed, and a Tektronix oscilloscope with a built-in function generator was used, and a photodiode simulator with a 2MΩ resistor was selected to generate a 0.25μA current at a drive frequency with a peak-to-peak amplitude of 1V. The amplitude of the TIA's output signal was measured with the oscilloscope and shown in dB. Figure 21b In this context, the equation dB = 20log10(VOUT / IIN) is used, where IIN = 0.25µA. It can be seen that for values ​​higher than f... p At a frequency of 636.6 kHz (marked with a red dot), the transfer function amplitude drops sharply.

[0188] ADC input and output. The ADC input signal, measured by an oscilloscope, can be... Figure 22 As seen in the image, the reference signal is shown in yellow and the photodiode signal is shown in blue.

[0189] Regarding the output, if the analysis is not performed on-board, the following JSON string can be read via the serial port (in our case, this is done in Python):

[0190] {"temp":,"time":[1,282,564,845,1127,1412,1694,1975,2256,2544,2826,3107,...,281619] "voltage":[821,61,1061,2284,1607,118,379,2005,2200,634,71,1247,2307,1435,86,...,979] "tclk":[142,423,705,986,1267,1553,1834,2116,2397,2685,2966,3247,3529,3810,...,281759] "clk":[3072,3192,3756,3843,3321,3034,3492,3873,3579,3040,3245,3815,3803,3258,...,3]}

[0191] Parse the JSON string to extract the temperature value, as well as tREF and V. ADC and tPIN, V ADC array

[0192] parsed_json = json.loads(line) temp = parsed_json['temp'];

[0193] t = parsed_json['time'];

[0194] tclk = parsed_json['tclk'];

[0195] pin = parsed_json['voltage'];

[0196] clk = parsed_json;

[0197] exist Figure 23 The signals shown as bits in the Y scale are plotted in (left and right).

[0198] To measure power consumption, the USB power cable was modified to interrupt the current path and included an ammeter for measuring current. If the device is powered by USB (a constant voltage source of V=5.17V), the current measured when the LED is off is I. OFF =38mA, and I when the LED is turned on ON =108mA, therefore P OFF =VI OFF =196μW and P ON =VI ON =558μW. If each t S The measurement is performed over 5 seconds, and the light flashes t during each measurement. LED For an LED with a t = 0.2s time, the average power is P = {(t)} S -t LED ) P OFF +t LED P ON} / t S =211mW.

[0199] The device has not yet been optimized for power consumption, as the circuitry was designed to prove the principle, but it is more energy efficient than commercial wearable or portable devices such as the Garmin Edge 800 GPS bike computer (1200mAh and 15h battery life, P=296mW) or the Polar V800 triathlon watch (350mAh and 13h battery life, P=100mW).

[0200] Figure 25 panel a shows the photodiode and reference signal, where f r =796Hz, sampling frequency is 5kHz. Panel b of Figure 25 shows 1000 samples each for the photodiode and the reference signal, where time is plotted as radix 1 / f. rThe modulus of (the period of the reference signal). Since the signal does not change in this timescale (0.2s), it is possible to reconstruct a single oscillation for the signal with very high detail. Panel c of Figure 25 shows the Fast Fourier Transform of the reference and photodiode signals. The reference signal reveals the presence of odd harmonics that leak from the PWM output through a low-pass filter. The photodiode signal also contains even harmonics, which may originate from the nonlinear nature of the LED.

[0201] Regarding signal processing, the conditioning of the reference signal (e.g., a 4-pole low-pass filter and a x2 gain amplification stage) and the circuit diagram described above are presented. The photodiode signal is fed directly into the TIA input without hardware filtering. The signal plotted in Figure 14 corresponds to the ADC output channels of the photodiode and reference signal, and this numerical data undergoes no filtering via software. The process for extracting lifetime and intensity (linear regression in matrix form) and predicting pO2 from lifetime and intensity is described, and this simplicity is the advantage (or promise) of the method.

[0202] The Octave or C++ code used to perform signal analysis uses no other components. The original waveform, the reconstruction of a single cycle using the modulo operator, and the harmonic content of the signal are shown in Figure 25. The fitting results are shown in Figure 26.

[0203] The following is a snippet of Octave code used to extract phase and amplitude from a photodiode signal:

[0204] t = mod(t, T); time modulo period T = 1 / f_ref; [t, I] ​​= sort(t); sort time ascending order.

[0205] x = x(I); sort the photodiode voltage relative to time multilinear regression in matrix form y = x; ones = zeros(1, length(x)) + 1;

[0206] w=2 pi ref_freq;

[0207] x1=cos(w t-0.0 pi);

[0208] x2=sin(w t-0.0 pi);

[0209] x3=cos(3 w t);

[0210] x4=sin(3 w t);

[0211] x5=cos(5 w t);

[0212] x6=sin(5 w t);

[0213] x7=cos(2 w t);

[0214] x8=sin(2 w t); M=[ones;x1;x2;x3;x4;x5;x6;x7;x8]';

[0215] p = inv(M' M) M' y'; Fitting coefficients

[0216] b0=[sqrt(p(2)^2+p(3)^2),sqrt(p(4)^2+p(5)^2),sqrt(p(6)^2+p(7)^2),sqrt(p(8)^2+p(9)^2)];

[0217] The amplitude of each harmonic

[0218] phase=[acos(p(2) / b0(1)),acos(p(4) / b0(2)),acos(p(6) / b0(3)),acos(p(8) / b0(4))]; phase of each harmonic fitting function.

[0219] fit = p(1) + p(2) x1+p(3) x² + p(4) x3+p(5) x4+p(6) x5+p(7) x6+p(8) x7+p(9) x8;

[0220] The B value or β value of a thermistor indicates the shape of the curve representing the relationship between the resistance and temperature of a negative temperature coefficient (NTC) thermistor.

[0221] The thermistor is defined by a constant B between two temperatures, as specified by the manufacturer, given by the Steinhart-Hart equation. In this case, B = 3650, T1 = 25°C + 273.15 K = 298.15 K, and R(T1) = 10 kΩ. Therefore, by measuring the resistance, we can determine the temperature by measuring the resistance at T2.

[0222] The resistance of a thermistor is measured by supplying power to a circuit with two resistors (reference resistor R1 and thermistor R2) and measuring the voltage drop across the thermistor. These two resistors are connected in series with a constant voltage, such as... Figure 24 As shown. Since the voltage is known and one resistor is fixed, the resistance of the thermistor can be calculated using Ohm's law. Knowing T1 = 25.0 + 273.15, R1 = 5kΩ (reference resistor), and R25... C = 10kΩ; V = 5V, therefore, by measuring V2 on a thermistor, we can replace T2 with R2(T2) = VV2 in the Steinhart-Hart equation to calculate the temperature.

[0223] BLE communication. As mentioned above, the multilinear regression algorithm is implemented in the microcontroller. This allows for the calculation of the phase and amplitude of signals on the device's board. The code uses the MatrixMath.h Arduino library to perform the same calculations as described above for Octave.

[0224] Then, each time pO2 is sampled, a custom BLE GATT protocol is used to transmit three quantities to the PC: {TEMPERATURE, PHASE, AMPLITUDE (temperature, phase, amplitude)}. This is done via a Python script that uses the Bleak library and inserts the device's Bluetooth MAC address and the UUID of the custom BLE service. From these three variables, after previously performing calibration on the oxygen sensing membrane in use, pO2 in mmHg is calculated using the temperature-dependent Stern-Volmer equation.

[0225] This technique could be further refined by implementing the Stern-Volmer equation in the device's firmware, allowing the device to directly output temperature and pO2 values, but it would be desirable to preserve phase and amplitude values ​​during these experiments. However, in most applications, USB is used for measurement because the "raw" waveform can be preserved.

[0226] Example 2

[0227] Portable oxygen sensing devices for improving the assessment of inter-absence syndrome and other hypoxia-related conditions.

[0228] Muscle oxygen measurement plays a crucial role in the early diagnosis of acute compartment syndrome (ACS), a common condition following severe trauma that leads to ischemia and long-term consequences including rhabdomyolysis, limb detachment, and death. However, to date, no oxygen sensors have been approved for this purpose. To address the need for improved ACS assessment, a portable fiber optic device for measuring intramuscular oxygen has been developed. This device is based on phosphorescence quenching, where the tip of the optical fiber is coated with a poly(propyl methacrylate) (PPMA) matrix containing brightly emitting Pt(II)-nucleoporphyrin. The optoelectronic circuitry is highly portable and relies on a microspectrometer and a microcontroller utilizing a smartphone for readings. Results from an in vivo tourniquet-equipped pig model demonstrate that the sensor is sensitive within the physiological oxygen partial pressure range of 0–80 mmHg and exhibits an appropriate and reproducible response to changes in intramuscular oxygen. Commercial laboratory oxygen sensors based on lifetime measurements did not provide the expected response.

[0229] Figure 27 A schematic diagram of an oxygen sensor system with a probe is shown, which responds to different levels of intramolecular oxygen (e.g., as a function of changing interval pressure).

[0230] Acute interval syndrome (ACS) is a condition characterized by muscle ischemia due to severe injury, which can be caused by various forms of trauma. Previous studies have found that tibial fractures, soft tissue injuries, and radius fractures following traffic or sports accidents are the leading causes of ACS in the civilian population, but it can also occur after non-accidental causes such as hemorrhagic diseases or diabetes. ACS also plays a significant role in military medicine when it occurs with multiple traumas, blasts, and blunt or comminuted injuries resulting from tourniquet application. This condition primarily affects young men under 35 years of age, with an incidence rate of 7.3 per 100,000 male patients and 0.7 per 100,000 female patients.

[0231] The pathophysiology of acute coronary syndrome (ACS) is described as an increase in pressure within the confined space of the septum. This increased pressure leads to decreased perfusion pressure, impairing blood supply and drainage, resulting in tissue hypoxia, tissue necrosis, and nerve damage. Because tissue necrosis occurs within 6–12 hours after hypoxemia, ACS should be treated immediately after diagnosis. Studies have shown that ACS patients treated 6–12 hours later have a higher risk of developing worse clinical outcomes, such as loss of function, limb amputation, or life-threatening conditions, highlighting the importance of early diagnosis.

[0232] Currently, the standard clinical treatment for diastasis recti is fasciotomy, a deep incision to release pressure, leading to severe scarring and chronic pain. Current diagnostic criteria for ACS focus on neurovascular integrity assessment based on five clinical symptoms: pain, pallor, paresthesia, absence of pulse, and paralysis. Disproportionate pain is observed as the most important clinical symptom; however, pain is not specific to ACS and can be caused by other injuries. It is also noteworthy that severe pain cannot be conveyed in unconscious patients.

[0233] In some cases, neurovascular assessment is compensated for by measurements of ventricular pressure (CP) or perfusion pressure (Δp). CP measurement can be performed using simple arterial transducers or proprietary devices; for example, the C2Dx STIC pressure monitor (formerly the Stryker monitor) or the Millar solid-state pressure sensor. In practice, CP measurement is not widely used due to the high cost of proprietary devices and the pain caused by inserting large (18-gauge) needles. Furthermore, the specificity of CP is only 65% ​​when Δp < 30 mmHg. Therefore, fasciotomy is often performed prophylactically, resulting in unnecessary trauma, highlighting the need for new diagnostic tools.

[0234] Previous research has summarized numerous techniques aimed at improving the diagnosis of ACS, and these are currently under investigation, including monitoring local oxygenation, monitoring local perfusion, local metabolic analysis (glucose, pH), and systems physiology based on serum biomarkers. Of all the methods mentioned, monitoring local oxygenation has attracted considerable attention. In principle, two variables are interesting: oxygen tension (i.e., the partial pressure of oxygen (pO2) within the interstitial space) and oxygen saturation (i.e., the proportion of oxygen-carrying hemoglobin relative to total hemoglobin in the blood). Non-invasive near-infrared spectroscopy has been widely used to measure oxygen saturation and has been evaluated in ACS, but it has been found to have significant limitations due to the adverse effects of shallow penetration depth and skin color changes. On the other hand, monitoring pO2 has been found to have certain advantages over measuring pressure in diagnosing septal syndrome in mouse and canine models. Previous studies in canine models have shown that measuring pO2 has high specificity and sensitivity for diagnosing septal syndrome. A clinical study evaluating intramuscular oxygenation measurements in patients with tibial fractures found that pO2 may be a good indicator for reducing the number of unnecessary fasciotomies. Human data are very limited due to the lack of suitable clinical muscle oxygenation probes. The only currently approved (not for intramuscular measurements) and clinically available probes are Clark electrodes, which are severely limited by their long warm-up time (unsuitable for emergency setup) and frequent recalibration, and are also very fragile, highlighting the urgent need for new clinical intramuscular oxygen probes.

[0235] Oxygen tension within tissues can be measured using a method called phosphorescence quenching, where the collision of oxygen with specific phosphorescent molecules can be used to quantify oxygen concentration. Many oxygen-sensing molecules have been synthesized, among which porphyrins are particularly useful for measuring and imaging tissue oxygen tension. Recently, bright-emitting metalloporphyrin oxygen sensors have been synthesized, providing highly sensitive oxygen tension measurements. When excited with blue (λ=377 nm) or green (λ=531 nm) light, these Pt(II)-nucleoporphyrins exhibit red phosphorescence (λ=645 nm), which is inversely proportional to pO2 according to the Stern-Volmer relation, where k is the Stern-Volmer quenching constant and I0 is the phosphorescence intensity in the absence of a quencher (oxygen). The bright red light of these novel porphyrins is visible to the naked eye and can be quantified with the aid of portable imaging equipment. These new porphyrins have been clinically validated as part of liquid bandages for assessing wound healing and integrated into wearable devices for performance monitoring.

[0236] This article describes a toolkit for further developing the aforementioned portable technology into a means of sensing loss of deep tissue oxygenation associated with interstitial syndrome. This is achieved by integrating oxygen-sensing materials with optical fibers and subcutaneous needles or catheters.

[0237] To date, there are no medical devices available for clinical measurement of muscle oxygen. This is likely because most existing sensors are not designed for measuring oxygen under physiological conditions in a clinical setting, require expensive and bulky readout devices, and many have not been evaluated outside of limited in vivo models. For example, the OXY-MICRO-AOT from World Precision Instruments was evaluated in surgically exposed epididymal fat pads, while the oxygen microsensor from PreSens was evaluated in tumors on the chorionic villi of chick embryos. Furthermore, intravascular sensors (such as the discontinued Paratrand) are not directly applicable to muscle oxygen measurement where an insertion force is applied to the sensor. The oxygen sensing device described in this article can assess not only ACS but also other pathological conditions such as vascular disease, diabetic wounds, burns, cancer, and traumatic injuries that may lead to reduced tissue pO2, resulting in hypoxia.

[0238] Materials. Various compounds and formulations were tested to synthesize a high-performance material for fiber-optic deep tissue oxygen sensing. The primary objective was to find a biocompatible host matrix material that is also chemically compatible with metalloporphyrin molecules to avoid aggregation. The resulting oxygen-sensing material needed to exhibit high pO2 sensitivity over a physiological range of 0–80 mmHg under humid conditions, while remaining insensitive to pH changes. Furthermore, the material needed to adhere well to the tip of a small-diameter fiber. Developing a material and coating process compatible with the small fiber diameter was crucial, as the goal was to ultimately use the smallest possible needle to limit patient discomfort. Additionally, it was important to keep fiber pretreatment as simple as possible to facilitate rapid conversion of the device to military and civilian patients. To this end, four different matrix materials were investigated: tetraethyl orthosilicate (TEOS) sol-gel, 3M Cavilon, and others. TM Membrane formulations, poly(ethyl methacrylate) (PEMA) and poly(propyl methacrylate) (PPMA).

[0239] Tetraethyl orthosilicate (TEOS) sol-gel is a strong candidate material due to its significant compatibility with porphyrins and its insensitivity to humidity. TEOS-containing matrices have previously been used to produce spin-coated and fiber-based oxygen sensors using commercially available ruthenium and platinum complexes. However, the fibers used in these references all have a large x-diameter greater than or equal to 550 µm, which is incompatible with pinhole needles, or the fiber tips are further processed, for example, by tapering to increase signal strength. Furthermore, ruthenium complexes are unsuitable for in vivo applications due to their toxicity. In this current work, the previously in-house developed TEOS formulation containing 50 μM of alkynylene-terminated Pt(II) porphyrins was prepared using a similar approach to previous steps. The in-house synthesized porphyrin derivative was chosen for this work due to its familiarity with its properties and performance in different materials. Furthermore, the synthetic protocol used for its derivation has been determined to be suitable for future immobilization within matrix materials, whether by chemical attachment or photocrosslinking. The alkynylene-terminated porphyrin was synthesized, and its molecular structure is as follows: Figure 28 As shown.

[0240] TEOS, 1-octyl-lysine-glycerol (referred to as polyol), and dimethyl sulfoxide (DMSO) were purchased from Sigma-Aldrich. Ethanol and hydrochloric acid were purchased from Fessell Technologies. For a 50 μL TEOS / porphyrin formulation at pH 1, the TEOS solution and the polyol and porphyrin solutions were prepared in two separate microcentrifuge tubes. In the first tube, 12.5 μL of TEOS (25 wt.%) was added to 15 μL of DMSO, followed by 1.7 μL of 1M hydrochloric acid in the ethanol solution. DMSO was used here instead of ethanol to increase surface tension. In the second tube, 5 mg of 1-octyl-lysine-glycerol (10 wt.% polyol) was mixed with an aliquot of the alkyl metal porphyrin soup solution in dichloromethane (DCM), and ethanol was added to bring the total volume of both tubes to 50 μL. After vortexing, the polyol solution was added to the TEOS tube, vortexed again, and allowed to stand for 15–20 minutes. To reduce breakage, additional formulations were prepared with the addition of different amounts of surfactants (1.4 wt.% Triton X-100 and 2.8 wt.% Tween-20).

[0241] The second material studied for coating optical fibers is 3M Cavilon, a ternary copolymer. TM Non-sharp barrier membrane. 3M Cavilon TM The membrane is an FDA-approved liquid bandage that is waterproof, adheres well to various surfaces, and is breathable. (Cavilon) TM Membrane formulations include hexamethyldisiloxane, isooctane, acrylate terpolymers, and polyphenylmethylsiloxane copolymers. Due to Cavilon... TM The membrane is hydrophobic, so it was found to be immiscible with alkyne-terminated porphyrins. Instead, a more hydrophobic neopentanoyl-terminated derivative was used, which showed good miscibility. Pt(II) neopentanoyl-terminated porphyrins were synthesized. For the final solution, 3M Cavilon was vortexed in a microcentrifuge tube with the neopentanoyl-terminated porphyrin. TM Membrane preparations.

[0242] In addition to TEOS sol-gel and Cavilon TM Extracellularly, the use of PEMA and PPMA with neopentanoyl-terminated porphyrins was also investigated. These acrylate polymers were studied in conjunction with poly(methyl methacrylate) (PMMA) to coat the tapered tip of a 480-micron fiber oxygen sensor. They showed that PPMA exhibited higher sensitivity and a faster response time than both PEMA and PMMA. A previous configuration combined a PtOEP phosphor with PEMA and coated a 600-micron fiber.

[0243] To coat 200-micron fibers to produce the sensor described in this disclosure, the solution was prepared as follows: 0.25 mg / μl of PEMA or PPMA (purchased from Sigma-Aldrich and Scientific Polymers Products) was dissolved in DCM in a microcentrifuge tube. After vortexing, neopentanoyl-terminated porphyrin was added at a concentration of 50 μM, and the solution was vortexed again. Although higher and lower concentrations of PEMA and PPMA were also tested, the coating material prepared from the 0.25 mg / μl solution was found to exhibit the greatest oxygen sensing response.

[0244] To prevent direct contact between the oxygen sensing material and body fluids, and to shield the material from external light, all fiber tips are additionally coated with a breathable reflective white layer. This coating has the advantage of increasing the measured porphyrin emission signal due to retroreflection and protecting the oxygen sensing layer during future sterilization processes using ethylene oxide (EtO). EtO sterilization is used as a standard method for sterilizing biomedical sensors because it has been shown to have no destructive effect on the polymer coating and silica fibers. The protective coating of the oxygen sensor contains a white pigment based on 40% titanium dioxide and silicone. To prepare it, 0.1 g of dimethylsiloxane copolymer (Gelest, CAS68037-59-2) and 1 g of white pigment concentrate (Gelest, PGWHT01) are mixed in a microcentrifuge tube. Subsequently, approximately 0.3 g of curing retarder (Gelest, Utensil R1) and a small drop of platinum catalyst (SigmaAldrich, CAS68478-92-2) are added, and the solution is vigorously stirred. The combination of curing retarder and catalyst produces a mixture that lasts for about 10 minutes before solidification, providing ample time for coating the fiber tips.

[0245] Fabrication of the fiber optic sensor. Multimode silica fibers (Thorlabs, FP200URT) with a 200 μm core were cleaned with isopropanol, and the ends were stripped and cut. For TEOS-based coatings, the fiber tips were functionalized before coating by plasma treatment (BD-20AC plasma treatment agent) or by silanization (1 wt% aminopropyltriethoxysilane in aqueous solution) to improve the adhesion of the TEOS sol-gel layer. The fibers were immersed in a silane solution for 10 minutes and then dried at 120°C for 2 hours. Subsequently, the fiber tips were manually dip-coated (1-5 times) in a TEOS solution. Repeated dip-coating of the fiber increased the layer thickness, thereby improving signal strength. After dip-coating, the fibers were dried overnight and then placed under high vacuum for 2-3 hours the following morning.

[0246] For Cavilon TMThe membrane formulation and PEMA and PPMA matrices were used, and the fibers were not functionalized prior to coating. A drop of porphyrin matrix solution was transferred from a microcentrifuge tube to the surface of a poly(dimethylsiloxane) (PDMS) membrane, and the fibers were manually dipped into the porphyrin matrix solution. The fibers were dried overnight, followed by 2–3 hours under high vacuum. After coating with an oxygen-sensing layer, the fibers were dipped into a white silicone coating, dried with hot air at 100°C for 10–15 seconds, and finally dried in room air for 48 hours. To enhance the adhesion of the silicone layer and prevent its separation from the fibers, 3MCavilon was coated onto the fibers. TM An additional protective layer for the membrane.

[0247] Device and data acquisition. Optical and electronic hardware are housed within a 10×11×4.5 cubic centimeter 3D printed box, such as... Figure 29 As shown. To measure oxygen concentration via changes in phosphorescence intensity, a Hamamatsu C12880MA-10 microspectrometer was connected to a custom printed circuit board (PCB) for readout and driving an LED source (Thorlabs, LED375L). The PCB was connected to a particle photonics microcontroller and an external 12V power supply to provide a stable voltage. It was found that a purely USB-based power supply was unstable when simultaneously pulsed the LED and readout microspectrometer. The firmware of the photonics microcontroller was customized based on Arduino sample code.

[0248] To measure oxygen concentration via changes in phosphorescence lifetime, avalanche photodiodes can be used and have been shown to detect emitted phosphorescence transmitted through fibers. Avalanche photodiodes (e.g., Thorlabs APD 130A or APD 440A) are equipped with fiber couplers, and the fiber end is directly coupled to the avalanche photodiode for detecting red phosphorescence. Variable gain avalanche photodiodes can also be used. Alternatively, a flexible optical filter as described above can be added to the system to filter out light outside the phosphorescence bandwidth, or a fiber filter (e.g., a Bragg grating) can be implemented to achieve the same effect. The excitation light from the UVA LED is coupled into the fiber via a 3 / 32-inch diameter glass bead.

[0249] The 375 nm excitation light and 650 nm phosphorescence are guided via a 1×2 fiber coupler (Thorlabs TH200R5S1B). On the detector side of the coupler, a flexible UV filter (#39-426, 400 nm long pass) from Edmund Optics is bonded to the SMA connector to reduce the contribution of blue light that saturates the spectrometer. An SMA-to-FC / PC mating sleeve (Thorlabs ADAFCSMA1) is mounted on the wall of the housing where the fiber optic sensor is connected.

[0250] The base of the fiber optic sensor is a custom fiber optic splice cable from Thorlabs, featuring a 200μm core and a 0.5NA (FP200URT) FC / PC connector. The splice cable is cut, the tube is removed from one side, and it is prepared and coated as described previously. Along with a 24-gauge thermocouple (IT-24P, physitemp), the coated fiber is integrated into two different versions of the device. In the first version, the fiber is bonded to an 18-gauge needle (BD PrecisionGlide), as... Figure 30 As shown. To ensure adequate balance with surrounding tissue, two 1 mm side ports are drilled into the fiber 5 mm above the tip. These holes are at the same height and 180° apart. To prevent the fiber tip from breaking upon insertion into the tissue, a lightly cured medical device adhesive (Loctite 3321) is used to close the needle tip. A 1 ml syringe body (HSW Norm-Ject Tuberkulin) is used to provide stability and ease of handling for the fiber optic sensor. It should be noted that the 200 μm fiber can be fitted into a smaller needle in the future, while the 18-gauge needle was chosen solely to create the precision of the side port holes. In the second version of the device, the fiber is integrated into a flexible polyethylene tube with an outer diameter of 0.6 mm, and a Luer interface connector is added to ensure a tight fit within the standard catheter. The tube length is chosen such that the oxygen sensing portion protrudes from the tip of a standard 20-gauge catheter (ExelSafelet catheter, 20G × 1 1 / 4") when the Luer interface is locked in place.

[0251] The LED pulse duration and measurement intervals were adjusted using software settings to match the signal strength of different coatings. For the final device, a 5ms pulse duration and a 15-second measurement interval were used. The microcontroller was read from the smartphone via a USB cable. A USB connection was selected for wireless connectivity to add an additional layer of data security when processing clinical data. An Android smartphone application was developed with the help of Google's Flutter SDK and Android Studio. This application provides options for changing settings such as pulse duration, measurement interval, output filename, and pO2 calibration. In addition to the current spectrum, the application displays a pO2 timeline and offers the option to save the data file in text format to the smartphone's SD card.

[0252] For calibration and testing purposes, the oxygen sensor is placed in a small gas chamber along with a commercial laboratory oxygen sensor (Profiling OxygenMicrosensor PM-PSt7, PreSens), which provides independent readings of the chamber's pO2. The temperature of the gas chamber is regulated with the aid of a hot plate. The oxygen partial pressure in the chamber is adjusted between 0 mmHg and 160 mmHg by varying the relative flow rates of nitrogen and air with the aid of a gas mixer. A humidifier allows the system to switch between dry and humid conditions.

[0253] To extract pO2 from the data, a nonlinear least-squares fit was used, based on a two-dimensional Stern-Volmer relationship that incorporates a linear dependence on temperature, where f explains the phosphorescence of porphyrin molecules inaccessible to the quencher, kT is the temperature-dependent quenching constant, and TC is the calibrated room temperature. Intensity I was extracted from the spectrum by integrating the red spectral range and normalizing it to blue excitation. The linear temperature dependence was verified by sweeping through the temperature at a fixed value for pO2. Both pO2 and temperature varied, and no significant hysteresis effect was observed.

[0254] (5)

[0255] Two-dimensional calibration images of fibers coated with PPMA matrix are shown below. Figure 31 As shown. By extracting the fitting parameters I0, k0, and k... T By understanding the calibration temperature TC, pO2 is derived from Equation 5. The corresponding pO2 error is calculated from the same equation using Gaussian error propagation and parameter fitting error. The error of the laboratory oxygen sensor is 3%, and the error of the temperature sensor is 1°C.

[0256] The obtained pO2 response matched the design requirements within the physiological range of 0 to 80 mmHg, with an error of less than 5%. At higher pO2 values, the error increased to approximately 6%. This was expected, as the porphyrin emission intensity decreases with increasing pO2. Future improvements could be made by adding a second porphyrin or a porphyrin-containing material tuned to be more sensitive at higher pO2 values.

[0257] Pig models. To evaluate the performance of the sensors under realistic conditions, two groups of in vivo experiments were conducted on two Yorkshire pigs and one Hampshire pig, all of which were female. The similar anatomical scale between pigs and humans makes pig models particularly suitable for studying physiological changes in intramuscular oxygenation. Animal protocols were reviewed and approved by the Institutional Animal Care and Use Committee of Massachusetts General Hospital, and all procedures were performed within the Knight Surgical Facility. The studies conducted were pilot studies designed to collect meaningful but not statistically significant data. For all pigs, anesthesia was induced intramuscularly with prazosin (4.4 mg / kg) and atropine (0.4 mg / kg), followed by inhalation of isoflurane (1–3%). Throughout the procedure, the pigs were ventilated with a inspired oxygen fraction (FiO2) of 1, which is the standard procedure for pigs at Massachusetts General Hospital. In previous experiments, ventilation with lower FiO2 resulted in decreased blood oxygen saturation due to shallow breathing in these animals under anesthesia. To prevent hypoxia-related conditions, the standard protocol of FiO2=1 was used. The pigs in the current study are a transfer of another protocol on stage and have undergone previous steps associated with different laser skin treatments.

[0258] In the first experiment, limb oxygenation was measured after the pigs lost cardiac function. Figure 30 As shown, one minute after euthanasia via administration of Fatal Plus pentobarbital euthanasia solution, the prototype oxygen sensing needle was sequentially inserted into several areas of the abdominal muscle of the pig's hind limb.

[0259] In the second in vivo experiment, oxygenation of the limbs of two pigs after tourniquets were applied was measured. Figure 30 As shown, tourniquets were applied to the triceps and brachii muscles of the forelimbs above the elbows of both pigs for 30 minutes. Because the pig legs are conical and short, standard pressure tourniquets could not be used; instead, RATS GEN 2 tourniquets were applied over rubber tourniquets (SWAT-T) and tightened by hand.

[0260] Before applying a tourniquet, insert the oxygen sensor into the flexor carpi ulnaris muscle. Figure 30 (Represented by red dots). In one pig, the oxygen sensor was needle-based, while in the second pig, a catheter-based version of the oxygen sensor (e.g.) was used. Figure 30 (As shown in the bottom right). In addition to the prototype oxygen sensor, a laboratory-grade oxygen sensor (Profiling OxygenMicrosensor PM-PSt7, PreSens) was inserted in both experiments, with a conduit inserted nearby. All oxygenation measurements were temperature-compensated using the included thermocouples.

[0261] Oxygen response. During material selection, the intensity of phosphorescence signals at different pO2 levels was measured at room temperature and fitted using a one-dimensional Stern-Volmer relation, with modifications made for inaccessible molecules using a factor f. The resulting Stern-Volmer distribution is shown below. Figure 32 As shown. It can be clearly seen that Cavilon TM Neopentanoylporphyrin in the membrane matrix was the most sensitive across the entire pO2 measurement range, with k = 0.0742, f = 0.0893, and I0 = 2.2. The PEMA coating was the least sensitive, with k = 0.0442, f = 0.0771, and I0 = 1.2. TEOS sol-gel and PPMA showed comparable sensitivity; TEOS sol-gel performed slightly better at very low pO2, while PPMA performed better at high pO2. The fitting parameters for PPMA were k = 0.0593, f = 0.0784, and I0 = 1.9, while those for TEOS sol-gel were k = 0.0731, f = 0.16, and I0 = 2.2. Therefore, the TEOS sol-gel matrix had the highest proportion of inaccessible porphyrins. The coating quality of TEOS sol-gel materials varied significantly between different fibers; generally, TEOS sol-gel adhesion was poor, as observed in previous studies, which can be attributed to significant cracking. Applying minimal force to the fiber tip resulted in the loss of the oxygen sensing layer. Adding a surfactant produced a higher emission signal (TEOS sol gel + 1.4 wt.% Triton X-100 yielded the best results); however, the TEOS sol gel still did not adhere well to the fiber tip.

[0262] Humidity Sensitivity. During oxygen sensor applications, the oxygen sensor will be exposed to blood and other bodily fluids, making humidity insensitivity crucial. Humidity sensitivity was measured by calculating the ratio of the signal in the emission peak under dry and humid (>90%) conditions at 0 mmHg. Pure TEOS sol-gel matrix was considered humidity-sensitive, with a dry-to-wet ratio of 2.1. While it has been previously reported that TEOS-based sol-gels do not exhibit humidity sensitivity, the materials used in this work were prepared from formulations containing DMSO and surfactants. Additional measurements on fibers coated with TEOS sol-gels of different compositions indicated that the humidity sensitivity of the fibers was primarily a result of the addition of DMSO to the TEOS formulation. The uniformity of the coating on the supporting substrate also played a role, as it was found that adding surfactants could improve performance by minimizing the formation of cracks in the sol-gel coated on the fibers.

[0263] When a surfactant is added, the humidity sensitivity of TEOS decreases, with a wet-dry ratio reaching 1.3–2. This is likely because pure TEOS coatings exhibit significantly more cracks, thus providing more opportunities for water to penetrate the coating. No acrylate polymer-based coatings exhibited significant humidity sensitivity, which can be attributed to their hydrophobicity.

[0264] Photobleaching. The phosphorescence emission intensity of the oxygen-sensing material was measured over time to determine the photobleaching rate. For this set of experiments, the LED was set to pulse once every 15 seconds for a total duration of 1.5 hours. The irradiance of the LED on the oxygen-sensing material was estimated to be 160 nW / cm². 2 .

[0265] TEOS sol-gel exhibited the highest bleaching rate at 5.0% h⁻¹, followed by PEMA at 2.9%, while Cavilon... TM The film has a photobleaching rate of 1.8%. PPMA was observed to have the lowest bleaching rate, at only 0.2%. Since the sensing tools required for interval syndrome can only be used once for up to 10 hours, this minimal level of photobleaching will result in a slight variation in overall brightness, ensuring high accuracy during use. Furthermore, the low photobleaching rate was calibrated and taken into account by carefully counting the total number of LED pulses delivered.

[0266] Given its low photobleaching rate and insensitivity to humidity, PPMA was selected as the optimal matrix material for deep tissue oxygen sensors. Neopentanoylporphyrins in the PPMA matrix were further evaluated by acquiring phosphorescence intensity spectra and lifetime decay using an FLS1000 steady-state and phosphorescence lifetime spectrometer from Edinburgh Instruments (Livingston, UK). The resulting lifetime within the PPMA matrix was determined to be 98 μs, which is almost identical to the lifetime in DCM (τ0 = 101 μs), indicating good compatibility between the oxygen-sensing molecules and the matrix material.

[0267] pH sensitivity. pH sensitivity for PPMA, a material with the lowest photobleaching rate and insensitivity to humidity. This is particularly important for the sensor application: during muscle injury, the intramuscular pH is expected to drop from above pH 7 to below pH 5.2. Therefore, stability within this pH range is crucial. To measure pH sensitivity, the oxygen sensor was immersed in a buffer solution with a pO2 of 40 mmHg and a pH of 7.5, where the pH was slowly decreased by adding 2M hydrochloric acid drops. 40 mmHg of oxygen tension was chosen because it falls in the middle of the pO2 range of interest. No pH dependence was detected.

[0268] Reusability was assessed. All sensors were typically used within 48 hours of manufacturing; therefore, sensor aging was not critical to the measurements obtained in this study. To understand the effects of sensor insertion, removal, and cleaning, the sensors were re-evaluated more than three months after initial in vivo use and after rinsing with isopropanol. The overall signal strength of the sensors decreased by approximately 30%, while the relative sensitivity increased over time, such as... Figure 33 As shown. Further investigation revealed that the drift was prominent only in phosphorescence intensity measurements, not lifetime measurements, with the drift being less than 5% over a 3-month period. This suggests that the intensity drift originates from changes in the optical properties of the matrix (e.g., scattering), rather than from the oxygen-sensing molecules themselves. A future shift to lifetime-based readings would significantly improve potential reusability.

[0269] Response time. The final PPMA-based sensor with a silicone coating exhibited a response time of 35 seconds when transitioning from 160 mmHg to 0 mmHg, achieving 1 / e. The response time is considered to be primarily limited by the diffusion of oxygen through the silicone layer and the physical absorption of oxygen within the silicone layer. It should be noted that this response is sufficient for the intended application, as interval syndrome can develop over 30 minutes to several hours, and oxygen levels can change within smaller intervals.

[0270] Leaching Studies. To assess the biocompatibility of the material and fiber coating, the leaching of porphyrin molecules from the material was analyzed by measuring the total platinum content found in samples exposed to the coated fibers. For this purpose, different combinations of porphyrin, PPMA, and silicone recoatings were applied to the fibers using the process described above. After drying, the fibers were placed in K2EDTA blood collection tubes containing 1 ml of fresh whole pig blood and immersed for 7 hours. Additionally, the fibers were inserted into pig tissue samples (skin and muscle) via needles and left in the tissue for 7 hours. Blood and tissue were collected immediately prior to the leaching studies. Throughout the leaching studies, blood and tissue samples with fibers were maintained at 36°C and frozen immediately after fiber removal. The platinum content of the samples was analyzed using inductively coupled plasma mass spectrometry (ICP-MS) (Bosselbrooks Applied Laboratory, Washington). Results for all samples were within the margin of error and consistent with the reference samples of pure pig blood / tissue, indicating a lack of significant leaching.

[0271] In vivo results. Limb oxygenation measurement results after cardiac failure, as shown below. Figure 34 As shown.

[0272] Oxygen tension in a given tissue is the balance between the supply of oxygen via blood vessels and the demand for oxygen consumed during cellular respiration. Muscle tissue is known to rapidly deplete oxygen, while tissues such as skin utilize molecular oxygen very slowly. Excessive Fatal Plus can lead to cardiac arrest, causing pulsatile flow to cease and thus perfusion to the tissue to stop. It is expected that when inserted into muscle, the probe will measure an exponential decay of oxygen tension, similar to what has been observed in previous studies.

[0273] The pO2 measured at the first insertion site in the biceps femoris muscle was found to be stable at 130 mmHg. This value initially appears high, however, it can be explained by the high FiO2 of 1. Furthermore, due to the large size of the 18 gauge needle and the roughness of the needle tip caused by drilling, the insertion of the needle may have induced bleeding at the insertion site, leading to the observed high pO2 level.

[0274] After approximately 30 minutes of measurement, the needle was moved and inserted into the skin above the biceps femoris muscle. In the slowly oxygen-consuming skin, the prototype oxygen sensor measured a stable oxygen tension of 90 mmHg, a value consistent with previous studies measuring subcutaneous oxygenation in pigs.

[0275] Eight minutes after measurement, the needle was reinserted into the biceps femoris muscle at different locations. At the second location, a slow decrease in oxygen partial pressure was observed over 20 minutes, with a final value of approximately 60 mmHg. Since the decrease in pO2 was much slower than the sensor's equilibrium time, this decay was attributed to the slow metabolic rate of the muscle tissue and residual cardiac activity following pentobarbital injection.

[0276] It is well known that intramuscular pO2 is heterogeneous within individual muscles, varies from person to person, and has been shown to depend heavily on FiO2. In normally perfused tissues, previous studies measured values ​​between 60 and 80 mmHg in a canine model with a FiO2 of 0.5. Some previous studies measured intramuscular pO2 between 4.0 and 50.6 mmHg, with a mean difference of 19.9 mmHg at unknown FiO2 levels. Several other previous studies measured significant differences in intramuscular pO2 in mouse models between FiO2=0.21 (room air) and FiO2=1, with pO2 values ​​of 3045 and 120–220 mmHg, respectively. Others have also found results in rats and mice, respectively. These values ​​are consistent with immediate measurements in pig muscle at postmortem FiO2=1. It should be noted that conversations with large animal surgical staff confirmed these findings.

[0277] Results of the in vivo tourniquet model: Figure 35 and Figure 36As shown. The pO2 values ​​of the two pigs measured before tourniquet application were 130 mmHg, consistent with the measurements in the first experiment and the rat model with FiO2=1. In both pigs, pO2 decreased to 65 mmHg and 15 mmHg, respectively, within less than one minute upon tourniquet application. In the first pig, pO2 increased to its initial value immediately after tourniquet release, while in the second pig, pO2 increased by only about 10 to 20 mmHg within 15 minutes.

[0278] The different pO2 levels measured in the two pigs during and after tourniquet application could be explained by the different forces applied to the tourniquets. The second pig had a low pO2 of only 20 mmHg, indicating severe tissue damage due to the applied force. This is also consistent with the observed skin color changes, which were much more pronounced in the second pig.

[0279] In both pigs, the commercial oxygen sensor did not adequately reproduce the results measured using the prototype sensor. It is not yet clear why the commercial sensor exhibited this behavior; however, it must be noted that it was not designed for intramuscular or any in vivo application and may interact with blood, be damaged, or become inert due to buildup.

[0280] To measure deep tissue oxygenation, this study focused on developing, constructing, and validating a fiber-based, portable intramuscular oxygen sensing device. TEOS sol-gel and 3M Cavilon were used. TM Membranes, PEMA, and PPMA were evaluated as matrix materials to house brightly emitting porphyrin oxygen sensors. Pt(II)-trimethylacetylporphyrin in PPMA was shown to be non-dependent on humidity or pH and exhibited a low photobleaching rate, which is crucial for pO2 measurements based on intramuscular strength.

[0281] The PPMA prototype sensor was tested in two different pig models and showed an appropriate and reproducible response to changes in oxygenation. Subcutaneous measurements were consistent with early measurements in the rat model. Muscle oxygenation measured immediately after sensor insertion was approximately 130 mmHg, which could be explained by high FiO2 and additional bleeding due to needle insertion. In the future, bleeding could be reduced by using smaller needles or by using ultrasound-guided placement of the needle / catheter. Both prototype sensors showed rapid changes in pO2 after tourniquet application. After tourniquet release, intramuscular pO2 in the first pig rapidly increased to pre-tourniquet levels, while in the second pig, pO2 increased only slowly by about 10 mmHg. This was likely due to tissue damage caused by an overly tight tourniquet in the second pig. In the future, this could be controlled by applying a pneumatic tourniquet at 40–100 mmHg above the limb occlusion pressure; however, securing the tourniquet to the pig's leg while still accessing the muscle is not straightforward. Commercial oxygen sensors used in parallel, especially those that determine pO2 based on more stable lifetime measurements, do not have the expected response in vivo.

[0282] While it may have been interesting to explore lower (even a few) values ​​of FiO2 in retrospect, it should be noted that sensor performance was not significantly affected by FiO2. Furthermore, when using lower FiO2, tissue pO2 is expected to decrease to values ​​where the sensor exhibits higher sensitivity and accuracy, such as... Figure 31 As shown.

[0283] While the current prototype needle-based version appears suitable for single-point measurements, the catheter-based version can remain in tissue for a longer period due to its flexibility. Therefore, pO2 values ​​can be obtained over a longer period to measure oxygenation trends rather than overall values. This can be advantageous because intramuscular oxygenation is expected to be heterogeneous within intervals. Furthermore, individual measurements can be enhanced by additional sensors arranged longitudinally with the probe, spatially in a grid, or both, to obtain regional tissue pO2 maps for understanding pO2 distribution, thus improving the diagnosis of ACS.

[0284] While tissue oxygenation appears to be a more physiologically relevant measure of tissue health than total pressure, further investigation in large animal models of septal syndrome is necessary to understand the potential benefits of the device for assessing septal syndrome. Furthermore, septal syndrome models will provide further insight into the effects of changes in total pressure on oxygen partial pressure measurements. Measurements in chambers where total pressure was varied while maintaining a constant nitrogen-to-air ratio showed a direct correlation between changes in total pressure and changes in oxygen partial pressure. However, it must be noted that this model does not reflect the full physiological complexity during septal syndrome, and additional in vivo studies are needed to assess the interaction between total pressure and pO2.

[0285] For its first human use, the device needs further miniaturization to reduce discomfort during insertion. The 200-micron fiber used in the prototype is well-suited for this purpose, and the small needle with side ports can be customized by commercial manufacturers. To reduce the possibility of breakage, the gaps around the fiber in the needle can be filled with epoxy resin, allowing the fiber tip to be flush with the epoxy resin surface. Alternatively, the side ports can be replaced with a porous shell material.

[0286] Even though the fiber portion of the sensor will be a single-use device, it may be necessary to fabricate the probe under sterile conditions or sterilize the oxygen sensor after manufacturing for safe use in humans. As previously mentioned, the sterilization process using EtO is advantageous because it has been shown to be safe for fiber-based sensors and polymer coatings. The effects on the fibers and oxygen-sensing coating in our prototype still require investigation. Cytotoxicity testing can be used to further evaluate the biocompatibility of this oxygen sensor. The device presented in this example was specifically developed to address the unmet need for early and adequate diagnosis of ACS. In the future, a total pressure sensor could be added to the same device to measure pressure. Furthermore, this would allow physicians to make direct comparisons with current diagnostic criteria. To gain a comprehensive understanding of this disease, it may even be beneficial to measure additional parameters such as pH and lactate levels in parallel within the same device. Parallel measurement of these parameters may have additional utility in monitoring and diagnosing other hypoxia-related diseases.

[0287] Example 3

[0288] Fusion of pO2 estimates derived from lifetime and strength

[0289] Figure 37 The diagram schematically illustrates a typical measurement during a clinical trial, where p T It originates from lifetime pO2, and p I From intensity. Figure 37 In the diagram, the arrows indicate: 1. Begin measurement at atmospheric pressure. 2. Apply the device to the skin. 3. Observe motion artifacts in intensity, not lifetime. 4. Observe the change in pO2 due to blood flow alterations in both parameters. 5. Motion artifacts in intensity. 6. Changes in pO2 due to blood flow alterations. 7. Remove the device from the skin. 8. Equilibrate back to atmospheric pO2.

[0290] What we usually see is p T p I It is slightly noisier, but reliably returns to atmospheric pO2 after removal. I Enhanced detail is observed during pO2 changes, but is affected by motion artifacts and does not always recycle back to atmospheric pO2, possibly due to photobleaching by phosphorescent molecules.

[0291] Ideally, people want to keep p T Quantitative (slow trend) values ​​and p I The sensitivity of the two pO2 indices. We can combine these two indices using the following methods. These methods serve as illustrative examples of ways these signals can be averaged, combined, or combined, rather than an exhaustive list of all possible algorithmic approaches.

[0292] 1. After calibration, the linear regression coefficient p is obtained. I =m p T +b, and calculate the combined pO2 index:

[0293] pO2 = (p I -b) / m

[0294] 2. Put p T Long-term moving average and p I Combining the instantaneous changes, this can be achieved by subtracting p. I to p I This is obtained by using a long-term moving average. This can be achieved through a low-pass filter p. T (i.e., LP(p) T and high-pass filter p I (HP(p) I )) or p I -LP(p I This will be completed. The combined output will be:

[0295] pO2 = LP(p T )+HP(p I ).

[0296] 3. Define the coefficient between [0,1], which (e.g., through correlation, cross-correlation functions) reflects p. T With p I The correlation between them, their derivatives with respect to time, etc., and generate the pO2 index, which will... I and p T Different weight combinations are used. Taking into account whether the features appearing in the two curves are shared (whether there is a correlation between the signals), the weights determine the degree to which each signal constitutes the combined pO2 measure at each instant. For example,

[0297] C=abs(corr(p T , p I C=abs(corr(dp) T / dt,dp I / dt)),

[0298] And the possible combination of pO2 is defined as

[0299] pO2 = C p I + (1-C) p T ,or

[0300] pO2 = sqrt( C^2) p I ^2 + (1-C)^2 p T T^2).

[0301] This disclosure has described one or more preferred embodiments, and it should be understood that many equivalent, alternative, variation and modification examples are possible and within the scope of the invention, in addition to those explicitly stated.

[0302] It should be understood that the application of this disclosure is not limited to the details of the construction and arrangement of the components described in the following description or drawings. This disclosure can be applied to other embodiments and can be implemented or performed in various ways. Moreover, it should be understood that the wording and terminology used herein are for descriptive purposes only and should not be considered limiting. In this document, the use of "including," "comprising," or "having," and variations thereof, means to cover items listed below and their equivalents, as well as additional items. Unless otherwise specified or limited, the terms "mounted," "connected," "supported," and "coupled," and variations thereof, are used extensively and cover direct and indirect mounting, connection, support, and coupling. Furthermore, "connected" and "coupled" are not limited to physical or mechanical connections or couplings.

[0303] As used herein, unless otherwise limited or defined, discussions of particular orientations are provided by way of example only, relating to specific embodiments or related illustrations. For example, discussions of “top,” “front,” or “rear” features are generally intended only to describe the orientation of such features relative to a reference frame of a particular example or illustration. Accordingly, for example, in some arrangements or non-limiting examples, a “top” feature may sometimes be positioned below a “bottom” feature (etc.). Furthermore, references to a particular rotation or other movement (e.g., counterclockwise rotation) are generally intended only as a description of movement relative to a reference frame of a particular example.

[0304] In some embodiments, standard programming or engineering techniques may be used to implement aspects of this disclosure (including computerized implementations of methods according to this disclosure) as systems, methods, apparatus, or articles of art to produce software, firmware, hardware, or any combination thereof to control processor devices (e.g., serial or parallel general-purpose or special-purpose processor chips, single-core or multi-core chips, microprocessors, field-programmable gate arrays, control units, arithmetic logic units, and any various combinations of processor registers, etc.), computers (e.g., processor devices operatively coupled to memory), or other electronically operated controllers to implement the aspects detailed herein. Accordingly, for example, embodiments of this disclosure may be implemented as a set of instructions tangibly implemented on a non-transient computer-readable medium, enabling a processor device to implement instructions based on instructions read from the computer-readable medium. Some embodiments of this disclosure may include (or utilize) control devices, such as automated devices, special-purpose or general-purpose computers including various computer hardware, software, firmware, etc., consistent with the discussion below. As a specific example, a control device may include a processor, a microcontroller, a field-programmable gate array, a programmable logic controller, logic gates, and other typical components known in the art for implementing appropriate functions (e.g., memory, communication system, power source, user interface, and other inputs).

[0305] As used herein, the term "article" is intended to include a computer program accessible from any computer-readable device, carrier (e.g., a non-transient signal), or medium (e.g., a non-transient medium). For example, computer-readable media may include, but is not limited to: magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., cards, sticks, etc.). Additionally, it will be appreciated that carrier waves can be used to carry computer-readable electronic data, such as that used for sending and receiving emails or for accessing networks such as the Internet or local area networks (LANs). Those skilled in the art will recognize that many modifications can be made to these configurations without departing from the scope and spirit of the claimed subject matter.

[0306] Certain operations of the methods according to this disclosure, or certain operations of the systems performing those methods, may be schematically illustrated in the accompanying drawings or discussed separately herein. Unless otherwise specified or limited, the representation of specific operations in the accompanying drawings in a particular spatial order does not necessarily require that these operations be performed in a specific order corresponding to that particular spatial order. Accordingly, certain operations illustrated in the accompanying drawings or otherwise disclosed herein may be performed in a manner suitable for a particular embodiment of this disclosure, in an order different from that explicitly stated or described. Further, in some embodiments, certain operations may be performed in parallel, including by a dedicated parallel processing device or by a separate computing device configured to interact as part of a larger system.

[0307] As used herein in the context of computer implementation, unless otherwise specified or limited, the terms “component,” “system,” “module,” and the like are intended to cover part or all of a computer-related system, including hardware, software, combinations of hardware and software, or software in execution. For example, a component can be, but is not limited to, a processor device, a process being executed (or potentially executed) by a processor device, an object, an executable, a thread of execution, a computer program, or a computer. Illustrated, both an application running on a computer and the computer itself can be components. One or more components (or systems, modules, etc.) may reside within an executing process or thread, may be located on a single computer, may be distributed across two or more computers or other processor devices, or may be included within another component (or system, module, etc.).

[0308] In some implementations, methods embodying the disclosed aspects may be used to utilize or install the devices or systems disclosed herein. Accordingly, the descriptions herein of specific features, capabilities, or intended purposes of devices or systems are generally intended to inherently include disclosures of methods for using such features for the intended purpose, methods for achieving such capabilities, and methods for installing the disclosed (or other known) components to support such purposes or capabilities. Similarly, unless otherwise indicated or limited, any discussion herein of methods for making or using a particular device or system (including installing the device or system) is intended to inherently include disclosures as embodiments of this disclosure, as features and capabilities used in such devices or systems.

[0309] As used herein, unless otherwise defined or limited, for convenience of reference, numbering used herein is generally based on the order in which particular components are presented in the relevant sections of this disclosure. In this regard, designations such as “first”, “second”, etc., generally indicate only the order in which the relevant components are introduced for discussion, and generally do not indicate or require a particular spatial arrangement, functional or structural preference or order.

[0310] As used herein, unless otherwise defined or limited, directional terms are used for ease of reference in discussing a particular figure or example. For example, references to downward (or other) directions or top (or other) positions may be used to discuss aspects of a particular example or figure, but similar orientations or geometries are not necessarily required in all installations or configurations.

[0311] This discussion is presented to enable those skilled in the art to make and use embodiments of this disclosure. Various modifications to the illustrated examples will be apparent to those skilled in the art, and the general principles herein can be applied to other examples and applications without departing from the principles disclosed herein. Therefore, embodiments of this disclosure are not intended to be limited to the illustrated embodiments, but should be accorded the widest scope consistent with the principles and features disclosed herein and the following claims. Refer to the accompanying drawings, in which the same elements in different drawings have the same reference numerals. The drawings, not necessarily drawn to scale, depict selected examples and are not intended to limit the scope of this disclosure. Those skilled in the art will recognize that the examples provided herein have many useful alternatives and fall within the scope of the disclosure.

[0312] The various features and advantages of this disclosure are set forth in the appended claims.

Claims

1. A sensor system for monitoring a patient, the system comprising: A probe comprising at least one photoluminescent region, the probe being sensitive to at least one analyte and having at least a first operating range for monitoring a first luminescent response and a second operating range for monitoring a second luminescent response of a patient; A photon source configured to direct photons at the probe, the probe emitting light in response to receiving photons from the photon source; A photodetector configured to detect the light emitted from the probe; as well as A controller, which communicates with the photon source and the photodetector, is configured to: The photon source directs photons at the probe according to a first time-varying distribution, thereby exciting the probe to emit light relative to the first and second operating ranges in response to receiving the photons; Optical data is received from the photodetector based on the interaction between the light emitted from the probe and the photodetector during operation within the first and second operating ranges, wherein the optical data includes a second time-varying distribution; as well as The parameter associated with the analyte is determined based on at least one of the following: (i) the phase difference between the first time-varying distribution and the second time-varying distribution when the photons directed to the probe have the same wavelength; and (ii) Differences in frequency, wavelength, waveform, period, or amplitude between the first time-varying distribution and the second time-varying distribution.

2. The sensor system as described in claim 1, characterized in that, The probes include corresponding phosphors or corresponding phosphorescent regions, each providing one of the first operating range and the second operating range.

3. The sensor system as described in claim 1, characterized in that, The controller is further configured to select a first characteristic of the first time-varying distribution to excite the probe relative to the first operating range and to select a second characteristic of the first time-varying distribution to excite the probe relative to the second operating range.

4. The sensor system as described in claim 3, characterized in that, The controller is further configured to change the first time-varying distribution from the first characteristic to the second characteristic in order to switch the probe from the first operating range to the second operating range.

5. The sensor system as described in claim 3, characterized in that, The first characteristic is configured to excite a first phosphor or a first phosphorescent region of the probe, and the second characteristic is configured to excite a second phosphor or a second phosphorescent region of the probe.

6. The sensor system as described in claim 1, characterized in that, The controller is further configured to direct the photon source at the probe according to the first time-varying distribution to simultaneously excite the probe relative to the first operating range and the second operating range.

7. The sensor system as described in claim 1, characterized in that, The first time-varying distribution is formed by a first sub-signal and a second sub-signal, which are respectively configured to excite the probe relative to the first operating range and the second operating range.

8. The sensor system as described in claim 7, characterized in that, The first sub-signal and the second sub-signal differ from at least one of the following: frequency; wavelength; Waveform; Period; or amplitude.

9. The sensor system as described in claim 1, characterized in that, The first operating range and the second operating range have corresponding sensitivity or response curves relative to the analyte.

10. The sensor system as claimed in claim 1, characterized in that, The first operating range and the second operating range each have a corresponding sensitivity or response curve relative to the first analyte and the second analyte.

11. The sensor system as claimed in claim 1, characterized in that, The operating range of the sensor system is defined by the sum of the first operating range and the second operating range.

12. The sensor system as claimed in claim 1, characterized in that, The first time-varying distribution is formed by the controller by combining multiple sine waves, square waves, triangular waves, sawtooth waves, pulse functions, or non-periodic waves.

13. The sensor system as claimed in claim 1, characterized in that, The controller is further configured to determine the amplitude of the time-varying amplitude wave of the second time-varying distribution, and to determine the partial voltage of the analyte based on the phase difference and the amplitude.

14. The sensor system as described in claim 13, characterized in that, The voltage divider is a first voltage divider, and determining the voltage divider includes: The second voltage divider is determined based on the phase difference; The third voltage is determined based on the amplitude; and The second and third voltages are combined to determine the first voltage.

15. The sensor system as described in claim 14, characterized in that, Combining the second voltage and the third voltage includes averaging the second voltage and the third voltage, wherein averaging includes weighted averaging.

16. The sensor system as claimed in claim 1, characterized in that, The first time-varying distribution includes a first plurality of frequencies, including at least one for each of the first operating range and the second operating range.

17. The sensor system as claimed in claim 16, characterized in that, The second time-varying distribution includes a second plurality of frequencies, and wherein determining the difference in phase includes the controller performing the following operations: A first reference time-varying amplitude wave is determined based on the first plurality of frequencies and their corresponding amplitudes; The second reference time-varying amplitude wave is determined based on the second plurality of frequencies and the corresponding amplitudes; as well as Determine the phase difference between a first time-varying amplitude wave and a second time-varying amplitude wave relative to corresponding frequencies among the first plurality of frequencies and the second plurality of frequencies.

18. The sensor system as claimed in claim 17, characterized in that, The first reference time-varying amplitude wave is statistically extracted using each of the first plurality of frequencies and the corresponding amplitude, and The second reference time-varying amplitude wave is statistically extracted using each of the second plurality of frequencies and its corresponding amplitude.

19. The sensor system as claimed in claim 18, characterized in that, The first time-varying amplitude wave was statistically extracted using linear regression, and The second reference time-varying amplitude wave is extracted statistically using linear regression.

20. The sensor system as claimed in claim 1, characterized in that, The probe includes at least: a first probe or first probe region having the first operating range and a second probe or second probe region having the second operating range, and wherein the controller is further configured to create the first time-varying distribution based on at least two signals having different characteristics, the at least two signals being configured to be used for the first probe or first probe region and the second probe or second probe region, respectively.

21. The sensor system as claimed in claim 20, characterized in that, The controller is configured to process the optical data to separate the second time-varying distribution into a first sub-signal that excites the probe relative to the first operating range and a second sub-signal that excites the probe relative to the second operating range.

22. The sensor system as claimed in claim 21, characterized in that, The controller is configured to compare a first sub-signal of the second time-varying distribution with a first sub-signal of the first time-varying distribution, and to compare a second sub-signal of the second time-varying distribution with a second sub-signal of the second time-varying distribution to determine the difference between the first time-varying distribution and the second time-varying distribution.

23. The sensor system as claimed in claim 1, characterized in that, The system further includes: The parameter associated with the analyte is determined based on (i) the phase difference between the first time-varying distribution and the second time-varying distribution when the photons directed to the probe have the same wavelength.

24. The sensor system as claimed in claim 1, characterized in that, The analyte may include oxygen or the parameter may include partial pressure.

25. The sensor system as claimed in claim 1, characterized in that, The probe is in contact or fluid communication with an area of ​​the patient that is at least partially sealed off from the surrounding environment, and The area is located on a portion of the patient's tissue.

26. The sensor system as described in claim 25, characterized in that, The probe is in communication with the gas in an area of ​​the patient that is at least partially sealed off from the surrounding environment.

27. The sensor system of claim 26, further comprising a temperature sensor thermally connected to at least one of the following: the photon source, the photodetector, the region, or the material defining the region.

28. The sensor system as claimed in claim 27, characterized in that, The controller is further configured to receive temperature values ​​from the temperature sensor, and Determining the parameters includes determining the partial pressure based on the difference and the temperature value from the temperature sensor.

29. The sensor system of claim 26, further comprising a substrate defining the region, the substrate including a sheet that is semi-permeable to oxygen diffusion, the sheet defining the region, and The probe is coupled to the substrate and is sensitive to oxygen.

30. The sensor system as described in claim 29, characterized in that, The sheet includes an adhesive layer configured to adhere the sheet to the patient's tissue.

31. The sensor system as claimed in claim 1, characterized in that, The probe includes: The analyte diffuses through a semi-permeable layer; and A light-absorbing layer, a scattering layer, or a reflective layer, wherein the light-absorbing layer, scattering layer, or reflective layer is configured to absorb, scatter, or reflect light directed at the light-absorbing layer, scattering layer, or reflective layer, and The probe is positioned between the sheet and the layer.

32. The sensor system of claim 1, further comprising: A first optical filter is optically coupled to the photon source and configured to filter photons emitted from the photon source that pass through the first optical filter. as well as A second optical filter is optically coupled to the photodetector and configured to filter light passing through the second optical filter to the photodetector.

33. The sensor system as described in claim 32, characterized in that, The first optical filter is a band-stop filter having a stopband defined between substantially 500 nm and substantially 900 nm, and The second optical filter is a low-pass filter with a rotation frequency of approximately 450 nm.

34. The sensor system as described in claim 32, characterized in that, The second optical filter blocks the light emitted by the photon source from being received by the photodetector.

35. The sensor system as claimed in claim 1, characterized in that, The photon source is at least one of a blue light-emitting diode (LED) or an ultraviolet LED, and the photodetector is at least one of a spectrometer, a photodiode, or a phototransistor.

36. The sensor system as described in claim 35, characterized in that, The photodiode includes an avalanche photodiode.

37. The sensor system as claimed in claim 1, characterized in that, The parameters include the partial pressure of the analyte, and wherein the first and second operating ranges together extend over the entire range between 0 mmHg and 160 mmHg.

38. The sensor system as claimed in claim 1, characterized in that, The controller is configured to adjust the frequency of the waveform of the first time-varying distribution based on the characteristics of the second time-varying distribution.

39. The sensor system as claimed in claim 1, characterized in that, The controller is configured to select, depending on the characteristics of the second time-varying distribution, between a programmable frequency sine wave of the first time-varying distribution, a sum of programmable frequency sine waves, or a programmable frequency square wave.

40. The sensor system as claimed in claim 1, characterized in that, The probe is photoluminescent.

41. The sensor system as described in claim 40, characterized in that, The probe is phosphorescent.

42. The sensor system as claimed in claim 1, characterized in that, The probe includes a first phosphorescent material having the first operating range and a second phosphorescent material different from the first phosphorescent material and having the second operating range. Each of the first phosphorescent material and the second phosphorescent material is sensitive to different voltage ranges that define the first operating range and the second operating range.

43. The sensor system as described in claim 42, characterized in that, Each of the first phosphorescent material and the second phosphorescent material includes a different diffusion rate or phosphorescence quenching constant.

44. The sensor system as described in claim 42, characterized in that, The first phosphorescent material and the second phosphorescent material include porphyrin.

45. The sensor system as claimed in claim 1: The first time-varying distribution includes at least two first sub-signals, which are configured to excite the probe relative to both of the at least two first sub-signals; The controller is configured to determine the second time-varying distribution based on the optical data and extract at least two second sub-signals; and The controller is configured to determine the conditions of the parameters by comparing the at least two first sub-signals with the at least two second sub-signals.

46. ​​The sensor system as described in claim 45, characterized in that, The at least two first sub-signals have different frequencies, different wavelengths, different waveforms, different periods, different time constants, or different amplitudes.

47. The sensor system as described in claim 45, characterized in that, To determine the conditions for the parameters, the controller is further configured to determine at least one of the following: The phase difference between the at least two first sub-signals and at least two of the at least two second sub-signals; The time delay between the emission of the photon and the reception of the optical data; or The time constant of the second time-varying distribution.

48. The sensor system as described in claim 45, characterized in that, The controller is further configured to determine the partial pressure or concentration of the probe to which it is sensitive, based on the difference between the at least two first sub-signals and the at least two second sub-signals, in order to determine the conditions of the parameters.

49. The sensor system as described in claim 48, characterized in that, The differences include phase differences.

50. The sensor system as claimed in claim 45, characterized in that, The probe is formed by a first probe having a first operating range and a second probe having a second operating range, wherein the first operating range and the second operating range are different.

51. The sensor system as described in claim 50, characterized in that, The first operating range and the second operating range together define the operating range of the sensor system from 0 mmHg to 160 mmHg.

52. The sensor system as described in claim 45, characterized in that, The first time-varying distribution is at least one of the following: The electrical waveform applied to the photon source to emit the photons; or Additional optical data received by the photodetector, the additional optical data being based on photons emitted from the photon source that directly interact with the photodetector.

53. The sensor system as described in claim 52, characterized in that, The electrical waveform is at least one of a sine wave, a triangle wave, a sawtooth wave, or a square wave.

54. The sensor system as described in claim 45, characterized in that, The probe comprises at least two phosphorescent materials having corresponding and different operating ranges.

55. The sensor system as described in claim 54, characterized in that, Each phosphorescent material is configured to be excited by the photon source having an intensity distribution having a different frequency, wavelength, waveform, period, or amplitude, and each of the at least two first sub-signals delivers the different frequency, wavelength, waveform, period, or amplitude.

56. The sensor system as described in claim 45, characterized in that, The probe includes at least two phosphorescent materials, including a first oxygen-sensitive phosphorescent material and a second oxygen-sensitive phosphorescent material that is different from the first oxygen-sensitive phosphorescent material, wherein each of the first oxygen-sensitive phosphorescent material and the second oxygen-sensitive phosphorescent material is sensitive to a different partial pressure range, or each of the first oxygen-sensitive phosphorescent material or the second oxygen-sensitive phosphorescent material has a different diffusion rate, diffusion constant, quenching rate or quenching constant.

57. The sensor system as described in claim 45, characterized in that, The probe contains multiple phosphorescent materials, each of which is sensitive to different partial pressure ranges and has different diffusion rates, diffusion constants, quenching rates or quenching constants.

58. The sensor system as claimed in claim 57, characterized in that, Each phosphorescent material contains porphyrin.

59. The sensor system as claimed in claim 1: The first time-varying distribution is composed of a plurality of first sub-signals, and the probe emits light based on the first time-varying distribution composed of a plurality of first sub-signals in response to receiving the photon directed at the probe, wherein the first time-varying distribution is simultaneously responsive to both of the plurality of first sub-signals; The optical data forms multiple second sub-signals; The controller is configured to determine the parameter associated with the analyte based on at least one of the following: (iii) The time delay reflected in the plurality of first sub-signals and the plurality of second sub-signals; or (iv) The time constants of the plurality of second sub-signals.

60. The sensor system as described in claim 59, characterized in that, The parameter is at least one of the partial pressure, pH, temperature, humidity, or concentration of the biomarker.

61. The sensor system as described in claim 59, characterized in that, The probe is sensitive to analytes dissolved in plasma or tissue.

62. The sensor system as described in claim 61, characterized in that, The probe is sensitive to one of molecular oxygen, carbon dioxide, or nitric oxide.

63. The sensor system as described in claim 59, characterized in that, The various operating ranges extend from a partial pressure of 0 mmHg to a partial pressure of 160 mmHg.

64. The sensor system as described in claim 59, characterized in that, The controller is further configured to track changes in the lifetime of light emission from the probe.

65. A method for monitoring a patient's condition, the method comprising: The probe is positioned close to the patient to monitor the analyte, the probe having at least a first operating range of a first luminescent response and a second operating range of a second luminescent response; The photon source is positioned to deliver photons to the probe, thereby exciting the probe; The photodetector is positioned to receive light emitted by the probe in response to the withdrawal of the photon source; The controller, which communicates with the photon source and the photodetector, performs the following operations: A first time-varying distribution comprising at least two first sub-signals is generated, the at least two first sub-signals being configured to excite the probe relative to both of the at least two first sub-signals; The photon source directs photons to the probe according to the first time-varying distribution, and in response to receiving the photons, excites the probe to emit light; Optical data is received from the photodetector based on the interaction between the light emitted from the probe and the photodetector; A second time-varying distribution is determined based on the optical data, and at least two second sub-signals are extracted; as well as The parameter associated with the analyte is determined based on at least one of the following: (i) the phase difference between the first time-varying distribution and the second time-varying distribution when the photons directed to the probe have the same wavelength; and (ii) Differences in frequency, wavelength, waveform, period, or amplitude between the first time-varying distribution and the second time-varying distribution.

66. The method as described in claim 65, characterized in that, The process of receiving the optical data, determining the second time-varying distribution, and generating a report is performed within a single period (1 / f) of the first time-varying distribution.

67. The method as described in claim 65, characterized in that, The at least two first sub-signals have different frequencies.

68. The method as described in claim 67, characterized in that, Determining the second time-varying distribution includes performing a linear regression algorithm that separates the at least two first sub-signals to determine the contribution from each of the at least two first sub-signals, and wherein generating a report includes extracting lifetime and intensity information of a plurality of luminescent dyes of the probe, each of the plurality of luminescent dyes being simultaneously excited at different frequencies of the at least two first sub-signals.

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