US-12622587-B2 - Non-invasive sensor and measuring method

US12622587B2US 12622587 B2US12622587 B2US 12622587B2US-12622587-B2

Abstract

Method for measuring a parameter of interest in a target environment ( 2 ) by means of a non-invasive sensor ( 1 ) based on photoacoustic detection or photothermal detection, comprises: a) a sensor that comprises an adaptation module ( 14 ) is provided comprising a processor that implements an inverse modelling algorithm; b) the adaptation module chooses an initial model irradiation configuration; c) it determines, in a correspondence table, the optimal irradiation case; d) a light source irradiates the target environment according to the optimal irradiation case; e) a detection cell detects a signal; f) the processor of the adaptation module returns a current model configuration (CMmes) and an estimated value for the parameter of interest (Pest); g) the processor of the adaptation module evaluates the chosen model irradiation configuration, and only if this irradiation model configuration differs from the current model configuration; g1) it receives the current model configuration (CMmes).

Inventors

Cyrielle MONPEURT
Alexandre GALLEGOS
ROMAIN BLANC

Assignees

ECLYPIA

Dates

Publication Date: 20260512
Application Date: 20230317
Priority Date: 20220318

Claims (7)

1 . A method of measuring a parameter of interest in a target environment by means of a non-invasive sensor based on photoacoustic detection or photothermal detection, wherein the method comprises: a) providing a sensor, the sensor comprising: a light source, a device configured to control the irradiation parameters of the light source, a detection cell configured to detect an acoustic or thermal signal, a memory in which a correspondence table is stored, the correspondence table comprising model configurations each representative of a given state of a target environment and optimal irradiation cases each comprising a set of irradiation parameters, each model configuration being associated with an optimal irradiation case of the optimal irradiation cases, and an adaptation module configured to exchange information with the detection cell and the light source irradiation parameter control device, said adaptation module comprising a processor adapted to implement an inverse modeling algorithm configured to receive, as an input, an irradiation case comprising a set of irradiation parameters and an acoustic or thermal signal and configured to provide, as an output, a model configuration and a value of the parameter of interest; b) selecting, by the adaptation module, an initial irradiation model configuration; c) determining, by the adaptation module, the optimum irradiation case for the selected irradiation model configuration from the correspondence table as the irradiation case that allows the parameter of interest to be measured with a pre-determined accuracy and/or the quantity of measurement data allowing the lowest energy consumption; d) irradiating, by the light source, the target environment according to the set of irradiation parameters of said optimal irradiation case; e) detecting, by the detection cell, an acoustic or thermal signal generated in response to the irradiation by the light source; f) implementing, by the processor of the adaptation module, the inverse modeling algorithm, receiving the acoustic or thermal signal detected by the detection cell and the optimal irradiation case used for irradiation, and returning a current model configuration and an estimated value of the parameter of interest; g) evaluating, by the processor, the selected irradiation model configuration by comparison with the current model configuration, and only if the selected irradiation model configuration is different from the current model configuration: g1) receiving, by the adaptation module, the current model configuration, and returning, as an output, a new irradiation model configuration, and repeating steps c), d), e) and f), wherein the value of the parameter of interest measured by the sensor is the last value of the estimated parameter of interest.
2 . The measurement method according to claim 1 , further comprising repeating step g) after performing step f).
3 . The measuring method according to claim 1 , further comprising: generating the correspondence table by a first processor and a database of model configurations comprising sets of respective model configurations, irradiation cases, and parameters of interest, and an acoustic or thermal signal detected by the detection cell associated with each set, wherein the correspondence table is stored in the memory of the non-invasive sensor.
4 . The measurement method according to claim 3 , wherein the first processor learns the inverse modeling algorithm from the database of model configurations and the inverse modeling algorithm is stored in the memory of the non-invasive sensor.
5 . The measurement method according to claim 3 , in which at least some of the acoustic or thermal signals detected by the sensor cell associated with the sets stored in the model configuration database are generated by a computerized simulation device.
6 . A non-invasive sensor configured to measure a parameter of interest in a target environment based on photoacoustic or photothermal detection, the non-invasive sensor comprising: a light source; a device configured to control the irradiation parameters of the light source; a detection cell configured to detect an acoustic or thermal signal; a memory storing a correspondence table comprising model configurations each representative of a given state of the target environment and optimal irradiation cases each comprising a set of irradiation parameters, each model configuration being associated with one of the optimal irradiation cases; and an adaptation module adapted to exchange information with the detection cell and the light source for controlling the irradiation parameters of the light source, the adaptation module comprising a processor adapted to implement an inverse modeling algorithm configured to receive, as an input, an irradiation case comprising a set of irradiation parameters and an acoustic or thermal signal and configured to provide, as an output, a model configuration and a value of the parameter of interest, wherein the adaptation module is configured to: i—select an initial irradiation model configuration, ii—determine an optimal irradiation case corresponding to an irradiation model configuration from the correspondence table, iii—transmit the determined optimal irradiation case to the light source irradiation parameter control device, iv—receive a signal detected by the detection cell, v—determine a current model configuration and an estimated value of the parameter of interest based on a detected photoacoustic or photothermal signal received and the determined optimal irradiation case, vi—evaluate the selected irradiation model configuration by comparison with the current model configuration, vii—only if the selected irradiation model configuration of a selected target stratified environment and the model configuration of a current target stratified environment are different, determine a new irradiation model configuration when the adaptation module receives the current model configuration, determine a new optimum irradiation case from a look-up table, corresponding to the new irradiation model configuration, and transmit the new optimum irradiation case to the irradiation parameter control device, so that the light source irradiates the target stratified environment according to the irradiation parameter set of the new optimum irradiation case, and the detection cell detects a new thermal or acoustic signal generated in response to this irradiation, and transmits it to the adaptation module configured to reiterate steps iv, v, vi and vii, and determine the value of the measured parameter of interest based on the last estimated value of the parameter of interest.
7 . A non-transitory computer readable medium storing instructions which, when executed by a processor, cause the non-invasive sensor of claim 6 to perform steps i, ii, iii, iv, v, vi, and vii of claim 6 .

Description

CROSS-REFERENCE TO RELATED APPLICATION This application is a national stage application, filed under 35 U.S.C. § 371, of International Patent Application No. PCT/EP2023/056879, filed on Mar. 17, 2023, which claims the priority to European application No. 22163111.2 filed Mar. 18, 2022, the contents of which are incorporated by reference. FIELD OF THE INVENTION The present invention relates to a process measurement and a non-invasive sensor making it possible to measure one or more parameters of interest in a target environment. More precisely, the invention relates to a non-invasive sensor based on the detection of a photothermal effect or photoacoustic, in particular configured to measure parameters in a target environment, such a stratified and/or evolving environment. A measured parameter can for example be blood sugar in the skin. TECHNOLOGY BACKGROUND In the field of sensors for living organisms, it is known to realize non-invasive sensors based on photoacoustic or photothermal detection. A zone of interest of an environment to be analyzed, called target, is irradiated by means of a laser beam of chosen wavelength and modulation frequency depending on the parameter of interest to be measured. The laser beam is absorbed by the target over a depth which depends on the structuring of the target. Energy absorption light causes local heating of the target. In reaction to this heating, a thermal wave of frequency equal to the laser modulation frequency is generated in the target. This wave propagates in the target and in particular up to the exterior surface of the target. The thermal wave can be directly detected and analyzed. We then speak of photothermy. Photoacoustics detection exploits the fact that the thermal wave is associated with a pressure wave frequency identical to the modulation frequency. In the case of photoacoustic detection indirect, we detect the pressure wave generated in the fluid external environment when the thermal wave generated in the target reaches, after propagation, the interface target—fluid external environment. This photoacoustic effect has been the subject of numerous theoretical studies. Allan Rosencwaig and Allen Gersho have notably developed a theoretical model of the photoacoustic signal. This model involves the physico-chemical properties of the sample to be analyzed, including the optical diffusion length, the thickness and the thermal diffusion length of the sample. (Rosencwaig, A. and Gersho, A. (1976), Theory of the photoacoustic effect with solids, Journal of Applied Physics, 47, 64). Hu et al. have developed a theory generalized photoacoustic effect in a stratified material. (Hu, H., Wang, X., & Xu, X. (1999). Generalized theory of the photoacoustic effect in a multilayer material. Journal of Applied Physics, 86, 3953-3958.) Photoacoustic detection presents many advantages compared to other techniques of detection among which we can cite the orthogonal aspect of transduction: the optical signal at the input of the environment to be analyzed is converted into an acoustic signal which is very specific to the phenomenon to be observed and which allows the use of inexpensive and miniaturized sensors. The difficulty of photoacoustic detection or photothermal comes among others: the number of parameters generally influencing the detected signal and,for certain analytes of interest present in concentration weak in the environment to be analyzed, of the weak proportion of the detected signal specific to each of these parameters of interest. In a stratified material, to be able to deduce of the photoacoustic or photothermal signal the concentration of a given layer into an analyte of interest, it is therefore necessary to know all the other parameters influencing this signal. In particular, it is necessary to know the structure of the material, that is to say the thicknesses of the different layers constituting the material, their physico-chemical compositions (at the exception of the parameter of interest to be measured), as well that possibly their thermal conductivities or even the thermal resistance associated with each interface between two successive layers. Calibration once and for all (or at all less for a significant duration of use) of a sensor based on photoacoustic or photothermal detection is only possible if only the parameter of interest varies in the target. On the other hand, when the characteristics of the stratified environment to be analyzed vary, it is necessary to calibrate the sensor regularly to obtain a measurement with acceptable precision. This problem arises more particularly for sensors intended for use on living organisms. For example, in the case of a non-invasive sensor of interstitial blood glucose monitoring, calibration of a non-invasive sensor based on photoacoustic detection or photothermal can only be obtained with a limited accuracy because the composition of the skin varies not only from one patient to another but also during the time