Physiological value sensing device and sensing method thereof

Abstract

The invention relates to a physiological value sensing device and a sensing method thereof. The physiological value sensing device comprises an input module and an operation module. Wherein the input module is used for providing a multiband light to irradiate a person to be tested so as to generate a plurality of optical signals, and the optical signals comprise a plurality of interference signals and a physiological signal to be tested. The operation module is used for establishing a normal physiological model, the normal physiological model has a plurality of sample physiological values corresponding to the multiband light, and the operation module converts the interference signal and the physiological signal to be measured into the normal physiological model for fitting. After the interference signal is eliminated according to the sample physiological value, a to-be-measured physiological value corresponding to the to-be-measured physiological signal is generated.

Description

Technical Field

[0001] The present invention relates to a physiological parameter sensing device and a sensing method thereof, and more particularly to a non-invasive blood glucose sensing device and a sensing method thereof. Background Art

[0002] Non-invasive blood glucose detection technology is a technology that measures the level of blood glucose without puncturing the skin or extracting a blood sample. The most obvious advantage of such technology is that it does not require the use of needles for puncture, which is more comfortable than traditional blood glucose testing methods, reducing the pain and discomfort of patients. In addition, the non-invasive detection method also reduces the risk of infection for the subjects, and more actively promotes public health. Moreover, the operation of such devices is simple and convenient for users to perform at home or in daily life without special training or the assistance of medical professionals. Most importantly, non-invasive detection can provide continuous monitoring functions, providing more detailed data at all times, which helps patients manage related diseases more conveniently.

[0003] However, non-invasive detection technology still has some disadvantages. For example, the accuracy of current non-invasive blood glucose testing technology is relatively low and is affected by various factors, including poor optical performance of the detection device, individual differences of the subjects, and interference of various physiological parameters in the subjects' bodies. As a result, the accuracy of non-invasive blood glucose detection technology is often questioned. To overcome the above problems, the industry urgently needs an innovative non-invasive physiological parameter sensing device and a sensing method thereof to improve the above-mentioned problems. Summary of the Invention

[0004] The main objective of the present invention is to provide an innovative physiological parameter sensing device and a sensing method thereof to improve the problems that affect the sensing accuracy, such as poor optical performance of traditional technology, individual differences of the subjects, and interference of various physiological parameters in the subjects' bodies.

[0005] To achieve the above objective, the present invention provides a physiological parameter sensing device, which includes an input module and an operation module. Among them, the input module is used to provide a multi-band light to irradiate a subject to generate a plurality of optical signals, and the optical signals include a plurality of interference signals and a physiological signal to be measured. The operation module is used to establish a physiological normal model, and the physiological normal model has a plurality of sample physiological parameters corresponding to the multi-band light. The operation module converts the interference signals and the physiological signal to be measured into the physiological normal model for fitting, so as to generate a physiological parameter to be measured corresponding to the physiological signal to be measured after excluding the interference signals according to the sample physiological parameters.

[0006] In an embodiment of the physiological parameter sensing device of the present invention, the input module includes a plurality of light emitting units and at least one light detecting unit. The light emitting units are used to provide the multi-band light and can adjust the light intensity of the multi-band light. The light detecting unit is used to receive the reflected light after the multi-band light is diffusely reflected by the subject to be measured, and generate an optical signal according to the reflected light.

[0007] In an embodiment of the physiological parameter sensing device of the present invention, the light emitting units can provide the multi-band light with a wavelength range of 800 nanometers (nm) to 1700 nanometers (nm) and a wavelength interval of not less than 100 nanometers (nm).

[0008] In an embodiment of the physiological parameter sensing device of the present invention, the input module further includes a microstructure disposed adjacent to the light detecting unit to prevent the multi-band light provided by the light emitting units from being received by the light detecting unit before being reflected by the subject to be measured.

[0009] In an embodiment of the physiological parameter sensing device of the present invention, the operation module includes a processing sub-module, a fitting sub-module and an evaluation sub-module. The processing sub-module is used to process and convert the interference signal and the physiological signal to be measured into a physiological normal model. The fitting sub-module is used to fit the converted interference signal and the physiological signal to be measured with the physiological normal model to generate a fitting result, and generate the physiological parameter to be measured corresponding to the physiological signal to be measured after excluding the interference signal according to the sample physiological parameter. The evaluation sub-module is used to output a feature importance evaluation according to the fitting result.

[0010] In an embodiment of the physiological parameter sensing device of the present invention, it further includes a storage module for storing the optical signal generated by the input module, the converted interference signal and the physiological signal to be measured, the physiological parameter to be measured and the feature importance evaluation.

[0011] In an embodiment of the physiological parameter sensing device of the present invention, it further includes a post-processing module for establishing a long-term trend report according to the optical signal.

[0012] In an embodiment of the physiological parameter sensing device of the present invention, it further includes an output module for outputting the physiological parameter to be measured, the feature importance evaluation and the long-term trend report.

[0013] To achieve the above object, the present invention provides a physiological parameter sensing method, including: establishing a physiological normal model, where the physiological normal model has a plurality of sample physiological parameters corresponding to a multi-band light; providing the multi-band light to irradiate a subject to be measured to generate a plurality of optical signals, where the optical signals include a plurality of interference signals and a physiological signal to be measured; converting the interference signal and the physiological signal to be measured into the physiological normal model; excluding the interference signal according to the sample physiological parameter; and generating a physiological parameter to be measured corresponding to the physiological signal to be measured.

[0014] In an embodiment of the physiological parameter sensing method of the present invention, providing multi-band light means providing multi-band light in a wavelength range of 800 nanometers (nm) to 1700 nanometers (nm) with a wavelength interval of not less than 100 nanometers (nm).

[0015] In an embodiment of the physiological parameter sensing method of the present invention, it further includes providing an artificial intelligence model for fitting the converted interference signal and the physiological signal to be measured with the sample physiological parameters of the physiological normal model to generate a fitting result, and generating the physiological parameter corresponding to the physiological signal to be measured after excluding the interference signal according to the fitting result.

[0016] After referring to the accompanying drawings and the following described embodiments, those of ordinary skill in the art can understand other objects of the present invention, as well as the technical means and implementation manners of the present invention. Description of the Drawings

[0017] Figure 1 It is a schematic diagram of the change in the relative infrared light absorption rate of various substances in human tissues;

[0018] Figure 2 It is a schematic diagram of the physiological parameter sensing device of the present invention;

[0019] Figure 3 It is a top view schematic diagram of several embodiments of the input module in the physiological parameter sensing device of the present invention;

[0020] Figure 4 It is a schematic diagram of model fitting by the fitting sub-module in an embodiment of the present invention;

[0021] Figure 5 It is a schematic diagram of the decision tree decision process in an embodiment of the present invention; and

[0022] Figure 6 It is a schematic flow chart of the physiological parameter sensing method of the present invention.

[0023] Description of the Reference Numerals

[0024] 1 Physiological parameter sensing device

[0025] 10 Input module

[0026] 12 Light emitting unit

[0027] 14 Light detecting unit

[0028] 16 Microstructure

[0029] 20 Operation module

[0030] 22 Processing sub-module

[0031] 24 Fitting sub-module

[0032] 26 Evaluation sub-module

[0033] 30 Storage module

[0034] 40 Post-processing module

[0035] 50 Output module. Detailed implementation manners

[0036] The following will explain the content of the present invention through embodiments. The embodiments of the present invention are not intended to limit the present invention to be implemented in any specific environment, application or special manner as described in the embodiments. Therefore, the description of the embodiments is only for the purpose of explaining the present invention, rather than limiting the present invention. It should be noted that in the following embodiments and drawings, devices not directly related to the present invention have been omitted and not shown, and the dimensional relationships between the devices in the drawings are only for easy understanding and are not intended to limit the actual ratio.

[0037] As Figure 1 shown, based on the theory that infrared light in the wavelength range of 600 nanometers (nm) to 2600 nanometers (nm) can be absorbed and scattered by components such as water, glucose, fat, heme, and protein in human tissues, thereby generating changes in absorption rate, the present invention discloses a physiological parameter sensing device and its sensing method, especially a blood glucose concentration sensing device with multi-band optical signals and its sensing calculation method. Specifically, the physiological parameter sensing device of the present invention is a non-invasive continuous glucose monitoring device (abbreviated as NICGM) to provide immediate, continuous, and long-term blood glucose concentration detection for the person to be tested.

[0038] Please refer to Figure 2 , which shows the physiological parameter sensing device 1 of the present invention, which includes an input module 10, an operation module 20, a storage module 30, a post-processing module 40, and an output module 50. Please refer to Figure 3 in combination, which shows a top view schematic diagram of possible implementation manners of several input modules 10 in the physiological parameter sensing device 1 of the present invention. Among them, the input module 10 includes several light-emitting units 12, at least one light-detecting unit 14, and a microstructure 16. In a preferred implementation manner, the light-emitting unit 12 has 3 or more light-emitting diodes, providing infrared light in different bands with a wavelength range of 800 nanometers (nm) to 1700 nanometers (nm) and a wavelength interval of not less than 100 nanometers (nm). Each light-emitting diode can adjust the light intensity between 0 and 100% of the luminous power, and the interval range between each light-emitting diode is preferably maintained between 1 millimeter (mm) and 2 millimeters (mm).

[0039] In addition, the light detection unit 14 has one or more photodiodes for corresponding to a plurality of light emitting units 12 to receive infrared light with multiple bands emitted by the light emitting units 12. In the use state, after the light detection unit 14 receives the reflected light after the infrared light is diffusely reflected by the human body of the subject to be measured, a plurality of optical signals will be generated according to the reflected light. When the physiological value sensing device 1 of the present invention has a plurality of light detection units 14, the interval range between each light detection unit 14 must be kept fixed, and the interval range is preferably maintained between 1 millimeter (mm) and 2 millimeters (mm). It should be noted that after the light emitting unit 12 irradiates the subject with infrared light, these optical signals generated by the light detection unit 14 include various substances in the subject's body, including signals generated after the reflection of infrared light by water, glucose, fat, hemoglobin, and protein, etc. Taking the application of the present invention to a non-invasive multi-band blood glucose concentration sensing device as an example, the above-mentioned plurality of optical signals include several interference signals such as water, fat, hemoglobin, and protein, and a physiological signal to be measured represented by the glucose concentration (i.e., blood glucose concentration).

[0040] Secondly, the microstructure 16 is used to separate the light emitting unit 12 and the light detection unit 14. According to the actual solution, the microstructure 16 has an adjustable appearance solution so that the distance range between the microstructure 16 and the light emitting unit 12 is maintained between 1 millimeter (mm) and 3 millimeters (mm), and there can be multiple interval ranges in the input module 10 to accommodate a plurality of light emitting units 12. In a preferred implementation, the configuration of the microstructure 16 must prevent the light emitted by the light emitting unit 12 from being directly received by the light detection unit 14 without being reflected by the human body of the subject to be measured. Therefore, the spatial relationship between the microstructure 16 and the light emitting unit 12 preferably limits the effective emission light angle of the light emitting unit 12 within a range of 30 degrees, so that most of the light greater than 30 degrees is substantially blocked by the microstructure 16. Moreover, the microstructure 16 is arranged adjacent to the light detection unit 14 and the interval range between the microstructure 16 and the light detection unit 14 is also kept fixed. For example, the interval range is preferably maintained between 1 millimeter (mm) and 2 millimeters (mm).

[0041] To improve the accuracy of physiological parameter sensing, one of the features of the physiological parameter sensing device of the present invention is to establish a physiological normal model. This physiological normal model correlates the optical signals obtained when human tissues are irradiated with multi-band light with multiple sample physiological parameters of the human tissues at that time. Specifically, when establishing the physiological normal model, first, various physiological characteristics (such as water, glucose, lipids, fat, hemoglobin, and protein) in the human tissues in vivo are detected by a biochemical analyzer, and then, combined with the optical signals generated by the optical detection of the input module 10 at that time, the operation module 20 performs operations to establish a normal model, so that the sample physiological parameters correspond to the optical signals. This physiological normal model can be used for fitting and prediction when future subjects are tested. More particularly, in a preferred embodiment, the light emitting unit 12 of the present invention has several light emitting diodes that provide light of different bands and different light intensities. Moreover, there are also different distances between the several light emitting diodes and the light detecting unit 14. When establishing the above-mentioned physiological normal model, by controlling the three variables of the band, distance, and light intensity, a complete physiological normal model can be established to calculate physiological parameters close to the real state and improve the accuracy of sensing.

[0042] As Figure 2 shown, the operation module 20 includes a processing sub-module 22, a fitting sub-module 24, and an evaluation sub-module 26. Among them, the processing sub-module 22 is used to process the optical signals generated by the light detecting unit 14 in the input module 10. Specifically, it converts several interference signals (such as characteristic signals of water, lipids, fat, hemoglobin, and protein, etc.) and the physiological signal to be measured (such as the characteristic signal of glucose) included in the optical signals into the physiological normal model. It should be noted that the so-called conversion of the optical signals of the input module into the physiological normal model means that the optical signals obtained by measuring the subject must be in exactly the same data format as that of the physiological normal model to meet the requirements of normal conversion. For example, when establishing the physiological normal model, if it is established in the data format of three bands of light at A nanometers (nm), B nanometers (nm), C nanometers (nm), distances of P millimeters (mm), Q millimeters (mm), R millimeters (mm), and light intensities of 100%, 90%,..., 10%, when subsequently measuring the optical signals obtained by the subject, the input module must also collect relevant signals in the above-mentioned same data format to meet the requirements of normal conversion.

[0043] Secondly, the fitting sub-module 24 is used to fit the converted optical signals with the physiological normal model, that is, to fit several interference signals and the physiological signal to be measured in the optical signals with the physiological normal model to generate a fitting result, and exclude interference signals other than glucose based on the known sample physiological parameters in the physiological normal model, and generate the physiological parameter to be measured (such as blood glucose concentration) corresponding to the physiological signal to be measured. Please refer to Figure 4, which shows a schematic diagram of the model fitting performed by the fitting sub-module in an embodiment of the present invention. In this embodiment, the processing sub-module 22 receives several optoelectronic signals corresponding to blood glucose, albumin / protein, lipids / fat, etc. collected by the input module. Each optoelectronic signal contains 18 groups of optoelectronic signals corresponding to different wavelength bands, distances, and light intensity characteristic distributions, and is then converted into multiple optoelectronic feature values according to the data form of the physiological normal model. The fitting sub-module of the present invention uses an artificial intelligence model or a machine learning model to fit the converted interference signals (including optoelectronic feature values such as albumin / protein, lipids / fat, etc.) and the physiological signal to be measured (i.e., the optoelectronic feature value of blood glucose) with the known sample physiological values in the physiological normal model to generate a fitting result, and uses the known sample physiological values to correct the interference signals belonging to the optical signals (such as optoelectronic feature values corresponding to albumin / protein, lipids / fat, etc.), and generates the physiological value to be measured corresponding to the physiological signal to be measured (i.e., the optoelectronic feature value of blood glucose). This physiological value to be measured is the physiological value that the person to be tested needs to detect, such as blood glucose concentration. In other words, the physiological value estimated by the fitting sub-module of the present invention has excluded the influence of interfering substances in the human body on this physiological value. Therefore, compared with the prior art, the physiological value of the person to be tested closer to the true state can be estimated.

[0044] The following will use an embodiment to actually illustrate how the present invention uses an artificial intelligence model to perform model fitting on the converted values with an artificial intelligence / machine learning (AI / ML) model and thereby estimate the physiological value to be measured.

[0045] As described above, it is assumed that when the present invention establishes the physiological normal model, wavelength band, distance, and light intensity are used as feature items, and these three types are further subdivided into 3 wavelength bands A nanometers (nm), B nanometers (nm), C nanometers (nm), 3 spacing distances P millimeters (mm), Q millimeters (mm), R millimeters (mm) between the light emitting unit and the light detecting unit, and 10 light intensities 100% (L00), 90% (L90),..., 10% (L10), and a total of 90 combinations of data forms are established. As mentioned above, when actually sensing the physiological value of the person to be tested subsequently, it is necessary to establish a function of various substances in the body of the person to be tested in the data form of the above 90 combinations. For a single substance, at a fixed position, its absorption rate is different for different wavelength bands, and the absorption threshold for different wavelength band light intensities is different; and different positions will affect the depth of light of different wavelength bands entering the biological tissue. The following is an example, where the function f is an artificial intelligence model, and the corresponding substance concentration value can be calculated through the optimization process:

[0046] Glucose value = f(PAL001, PAL901,..., PAL101, PBL001,..., RCL101)

[0047] Protein value = f(PAL002, PAL902, …, PAL102, PBL002, …, RCL102)

[0048] After actual measurement, the glucose values can be organized into a matrix form of data as follows:

[0049] In the data matrix, the value of each characteristic field is converted using the above physiological normal model to establish a norm formula as

[0050] where is the norm average value, s x is the norm standard deviation. Then, the function f is optimized, and the process includes error function optimization and generation of the decision process

[0051] The glucose value c a = f(PAL001, PAL901, …, PAL101, PBL001, …, RCL101). For each function f, there is a possibility of error optimization (minimization). Taking the mean square error as the error function as an example, there is

[0052]

[0053] where N is the number of samples, f i is the actual value / observed value of the function, is the calculated value of the function model

[0054] If the decision tree type is used as the decision process, there are two spatial partitions, region 1 and region 2, each time. For the j-th variable x j and the value s taken

[0055] region1(j, s) = {x|x j ≤ s}®ion2(j, s) = {x|x j > s}

[0056] And solve

[0057]

[0058] For the j-th variable x j the optimal value s can be found

[0059] For an example of the decision process of the above decision tree, reference can be made to as Figure 5 shown. It should be noted that Figure 5For illustrative purposes only, not the actual situation. For example, when the characteristic value of PAL001 (glucose characteristic item: the distance between the light-emitting unit and the light-detecting unit is P, the light-emitting band is A, and the light intensity is 100%) after being calculated by the above algorithm is less than or equal to 0.256, the decision tree will run to the left. On the contrary, when the characteristic value of PAL001 is greater than 0.256, the decision tree will run to the right. Then, continue to evaluate the next characteristic value. If when the characteristic value runs to PBL001 and is less than or equal to 1.123, according to the decision tree, the blood glucose concentration obtained by fitting and estimating at this time will be 89.56 milligrams per deciliter (mg / dL).

[0060] Secondly, another feature of the present invention is that the operation module 20 further includes an evaluation sub-module 26 for performing model analysis based on the fitting result after being fitted by the fitting sub-module 24 and outputting a feature importance evaluation, such as, but not limited to, SHAP (SHapley Additive exPlanations) feature importance evaluation. This evaluation considers the contribution of each feature to the prediction result and assigns a SHAP value to each feature. These values describe the degree of influence of each feature on the model prediction. A positive value indicates an increase in the prediction value, and a negative value indicates a decrease in the prediction value. The SHAP value can be used to explain how the artificial intelligence model uses various optical features to predict the blood glucose concentration. These optical features may include physiological values, environmental factors, etc. Using the SHAP value can evaluate the influence of each feature on the output of the artificial intelligence model, so as to better understand the prediction process of the artificial intelligence model.

[0061] According to the above content, please refer to Figure 6, the physiological value sensing method disclosed by the present invention includes the following steps: In step 601, a physiological normal model is first established, and the physiological normal model has a plurality of sample physiological values corresponding to a multi-band light. In step 602, the multi-band light is provided to irradiate a subject to generate a plurality of optical signals, wherein the optical signals include a plurality of interference signals and a physiological signal to be measured. In step 603, the interference signals and the physiological signal to be measured are converted into the physiological normal model. In step 604, the interference signals are excluded according to the sample physiological values. In step 605, a physiological value to be measured corresponding to the physiological signal to be measured is generated. Specifically, taking the measurement of blood glucose concentration as an example, the blood glucose sensing method of the present invention can correct the influence of other interfering substances in the body on the measurement of blood glucose concentration. It mainly uses the input module to perform measurements on the subject to generate a plurality of optical signals for evaluating blood glucose and interference substance exclusion, and the operation module obtains a plurality of uncorrected characteristic values related to the subject according to the optical signals, including: a set of blood substance concentration values such as blood glucose concentration value, protein concentration value, lipid concentration value, water influence value, and other substance influence values. Finally, by using the calculation of the previously established physiological signal normal model, a corrected blood glucose concentration value is generated as the blood glucose concentration close to the true value of the subject.

[0062] In addition, as Figure 2 shown, the storage module 30 of the physiological value sensing device 1 of the present invention is used to store the optical signals generated by the input module 10, the interference signals and the physiological signals to be measured after conversion by the operation module 20, the physiological values to be measured, and intermediate signals and final results such as the evaluation of characteristic importance. In addition, the post-processing module 40 of the physiological value sensing device 1 is used to calculate the values stored in the storage module 30, including the optical signals, to establish a long-term trend report after the system operates for a period of time. The output module 50 of the physiological value sensing device 1 of the present invention is used to output the physiological value to be measured, the evaluation of characteristic importance, and the long-term trend report, and can output the values and image files of the operation module, and present the results in the form of a display.

[0063] The physiological value sensing device and its sensing method of the present invention have the advantages of non-invasive, multi-band light, continuous long-term monitoring, and instant off-line detection of physiological values. Compared with the traditional technology, the present invention can solve (1) the pain caused to the subject by invasive detection devices or methods; (2) if continuous monitoring of physiological values is required, it may cause inflammation at the skin invasion site due to long-term wearing, resulting in psychological concerns and additional burdens for the subject, caregiver, or medical system; (3) there are many interference factors for physiological values to be measured in human tissues. The sensing device of the present invention and its matching sensing algorithm can exclude specific interference factors and correct related values, so it can provide physiological values close to the true values.

[0064] The above embodiments are only used to illustrate the implementation schemes of the present invention and to explain the technical features of the present invention, rather than to limit the protection scope of the present invention. Any changes that can be easily made by those skilled in the art or equivalent arrangements fall within the scope claimed by the present invention, and the scope of the protection of the present invention shall be subject to the claims.

Claims

1. A physiological parameter sensing device, comprising: An input module for providing a multi-band light to irradiate a subject to generate a plurality of optical signals, wherein the optical signals include a plurality of interference signals and a physiological signal to be measured; and An operation module for Establishing a physiological normal model, which has a plurality of sample physiological parameters corresponding to the multi-band light, Converting the interference signals and the physiological signal to be measured into the physiological normal model, Excluding the interference signals according to the sample physiological parameters, and Generating a physiological parameter corresponding to the physiological signal to be measured.

2. The physiological parameter sensing device according to claim 1, wherein the input module includes a plurality of light emitting units and at least one light detecting unit, the light emitting units are used to provide the multi-band light and can adjust the light intensity of the multi-band light, and the at least one light detecting unit is used to receive the reflected light after the multi-band light is reflected by the subject and generate the optical signals according to the reflected light.

3. The physiological parameter sensing device according to claim 2, wherein the light emitting units can provide the multi-band light with a wavelength range of 800 nm to 1700 nm and a wavelength interval of not less than 100 nm.

4. The physiological parameter sensing device according to claim 2, wherein the input module further includes a microstructure disposed adjacent to the at least one light detecting unit to prevent the multi-band light provided by the light emitting units from being received by the at least one light detecting unit before being reflected by the subject.

5. The physiological parameter sensing device according to claim 1, wherein the operation module includes a processing sub-module, a fitting sub-module and an evaluation sub-module, The processing sub-module is used to process and convert the interference signals and the physiological signal to be measured into the physiological normal model, The fitting sub-module is used to fit the converted interference signals and the physiological signal to be measured with the physiological normal model to generate a fitting result, and generate the physiological parameter corresponding to the physiological signal to be measured after excluding the interference signals according to the sample physiological parameters, The evaluation sub-module is used to output a feature importance evaluation according to the fitting result.

6. The physiological parameter sensing device according to claim 5, further comprising a storage module for storing the optical signals generated by the input module, the converted interference signals and the physiological signal to be measured, the physiological parameter and the feature importance evaluation.

7. The physiological parameter sensing device according to claim 6, further comprising a post-processing module for establishing a long-term trend report according to the optical signals.

8. The physiological parameter sensing device according to claim 7, further comprising an output module for outputting the physiological parameter, the feature importance evaluation and the long-term trend report.

9. A physiological parameter sensing method, comprising: Establishing a physiological normal model, wherein the physiological normal model has a plurality of sample physiological parameters corresponding to a multi-band light; Providing the multi-band light to irradiate a subject to generate a plurality of optical signals, wherein the optical signals include a plurality of interference signals and a physiological signal to be measured; Converting the interference signals and the physiological signal to be measured into the physiological normal model; Exclude the interference signal according to the physiological value of the sample; and Generate a physiological value to be measured corresponding to the physiological signal to be measured.

10. The physiological value sensing method according to claim 9, wherein providing the multi-band light is providing the multi-band light with a wavelength range of 800 nanometers to 1700 nanometers and a wavelength interval of not less than 100 nanometers.

11. The physiological value sensing method according to claim 9 further includes providing an artificial intelligence model for fitting the converted interference signal and the physiological signal to be measured with the physiological value of the sample of the physiological normal model to generate a fitting result, and excluding the interference signal according to the fitting result, and generating the physiological value to be measured corresponding to the physiological signal to be measured.

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