A health detection method and system based on fingertip touch

Abstract

This application relates to a health detection method and system based on fingertip touch, comprising the following steps: using a fingertip detection device installed on a massage chair to emit light sources of different wavelengths to irradiate the fingertip skin and collect data on the changes in reflected light intensity; preprocessing the collected light intensity change data and extracting feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume; calculating heart rate and blood oxygen saturation based on the feature parameters and generating a health detection report; and transmitting the generated health detection report to a mini-program server via encryption, allowing users to view the health detection report through a mobile mini-program.

Description

Technical Field

[0001] This application relates to the fields of shared massage chairs and health management technology, and more specifically, to a health detection method and system based on fingertip touch. Background Technology

[0002] Fingertip health detection technology primarily uses sensors, such as tactile sensors and optical sensors, to detect the touch position and force of fingers, thereby enabling human-computer interaction. With the continuous development of technologies such as MEMS (Micro-Electro-Mechanical Systems), the accuracy and sensitivity of fingertip health detection technology have been significantly improved. Despite these significant advancements, the accuracy and stability of fingertip health detection technology still face challenges in certain complex scenarios. For example, changes in lighting, finger occlusion, or motion blur greatly increase the difficulty of fingertip detection, potentially leading to false positives or false negatives. Furthermore, differences in finger shape, size, and usage habits among users can result in varying adaptability of fingertip health detection technology across different users. Therefore, designing more universal and adaptable fingertip detection algorithms to better meet the needs of diverse users is a current challenge. Simultaneously, the hand region contains a large amount of redundant information, which can interfere during fingertip detection, increasing computational load and difficulty. Therefore, effectively removing redundant information and improving the accuracy and efficiency of fingertip detection is a crucial issue. In human-computer interaction systems, real-time performance is a very important performance indicator. However, in practical applications, fingertip health detection technology is often limited by factors such as computing resources and algorithm complexity, making it difficult to meet real-time requirements. This may lead to users experiencing delays or lag during operation, affecting the user experience. With the widespread application of fingertip health detection technology in smart devices, privacy and security issues are becoming increasingly prominent. For example, some malicious software may exploit this technology to steal sensitive user information or perform malicious operations. Therefore, how to strengthen the security and privacy protection of fingertip health detection technology is one of the urgent problems to be solved.

[0003] Existing technologies, such as Chinese patent application publication number "CN118000689A", disclose a health detection device and a health detection method. The method includes: responding to a health detection command, acquiring a user's hand image in a region corresponding to the support unit via a position measuring device; determining the user's fingertip to be detected and its fingertip feature information based on the user's hand image; determining the position information of the fingertip to be detected based on the fingertip feature information; and controlling the detection unit to perform health detection based on the position information. In this way, the user's fingertip position is automatically located based on the fingertip image, and then controlled to perform health detection based on the fingertip position information. This achieves automatic positioning of the detection area, improves the accuracy and efficiency of health detection, and enhances the user experience.

[0004] The problem with the existing technology is that it does not specify specific detection indicators, making it difficult to accurately assess health status; although it can automatically locate the detection area, it does not consider the impact of differences in finger shape, size, and usage habits among different users on the detection. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes a health detection method and system based on fingertip touch.

[0006] The technical solution of this invention is as follows:

[0007] This invention proposes a health detection method based on fingertip touch, comprising the following steps:

[0008] Step S1: Use a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity.

[0009] Step S2: Preprocess the collected light intensity change data, and extract feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume.

[0010] Step S3: Calculate heart rate and blood oxygen saturation based on characteristic parameters and generate a health monitoring report;

[0011] Step S4: The generated health test report is transmitted to the mini-program server in encrypted form, and the user can view the health test report through the mobile mini-program.

[0012] In a preferred embodiment, the preprocessing of the acquired light intensity change data includes bandpass filtering and motion artifact removal, wherein:

[0013] Bandpass filtering is used to process the acquired reflected light intensity signal. The pulse wave signal is extracted based on photoplethysmography (PPG) technology. The transfer function of the bandpass filter is:

[0014]

[0015] In the formula: H(f) is the filter response frequency at frequency f; f is the frequency of the input signal; j is the imaginary unit; f c This is the filter cutoff frequency;

[0016] Preprocessing also includes removing motion artifacts using an adaptive filtering algorithm. The update formula for the filter coefficients is:

[0017] w(n+1)=w(n)+μ·e(n)·x(n);

[0018] In the formula: w(n+1) is the updated filter coefficient; w(n) is the filter coefficient vector at the nth iteration; μ is the step size factor; e(n) is the error signal at the nth iteration; x(n) is the input sample at the nth iteration.

[0019] In a preferred embodiment, the relationship between the change in light intensity and blood volume is specifically as follows:

[0020] I(t) = I0·e -α·ΔV(t)-β·S(t) ;

[0021] In the formula: I(t) represents the change of received light intensity over time; I0 represents the initial light intensity; α represents the absorption coefficient, which measures the ability of light to be absorbed by blood and related tissues; ΔV(t) represents the change of blood volume over time; S(t) represents the change of scattering coefficient; and β represents the scattering coefficient influencing factor.

[0022] In a preferred embodiment, the characteristic parameters include: the peak value, trough value, rise time, and fall time of the pulse wave.

[0023] In a preferred embodiment, the calculation of heart rate and blood oxygen saturation based on characteristic parameters includes, specifically, the heart rate calculation as follows:

[0024]

[0025] In the formula: HR is the calculated heart rate; K is the number of pulse wave peaks detected over a period of time; T peak (k) represents the time interval between two pulse peaks.

[0026] In a preferred embodiment, the heart rate and blood oxygen saturation are calculated based on characteristic parameters, wherein the blood oxygen saturation is calculated using a dual-wavelength detection method, and the specific calculation formula is as follows:

[0027]

[0028] In the formula: SpO2 is the calculated blood oxygen saturation; Ired (t) represents the change in red light intensity; I infrared(t) For changes in infrared light intensity; I 0,red I represents the initial red light intensity. 0,infrare α represents the initial infrared light intensity. red α infrared , respectively, are the absorption coefficients of red light and infrared light; A is the blood oxygen saturation calibration constant.

[0029] In a preferred embodiment, the generated health test report is transmitted to the mini-program server in an encrypted manner. The raw data collected by the fingertip detection device is encrypted with AES-256 and stored locally on the device. Only the de-identified health test report is uploaded to the cloud and associated with the user's identity through a hash algorithm.

[0030] On the other hand, the present invention also provides a health detection system based on fingertip touch, comprising:

[0031] The data acquisition module uses a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity.

[0032] The preprocessing and feature extraction module preprocesses the collected light intensity change data and extracts feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume.

[0033] The report generation module calculates heart rate and blood oxygen saturation based on characteristic parameters and generates a health monitoring report.

[0034] The report viewing module transmits the generated health test report to the mini-program server in an encrypted manner, allowing users to view the health test report via the mobile mini-program.

[0035] In another aspect, the present invention also provides an electronic device having a computer program stored thereon, which, when executed by a processor, implements a health detection method based on fingertip touch as described in any embodiment of the present invention.

[0036] In another aspect, the present invention also provides a computer-readable medium for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement a health detection method based on fingertip touch as described in any embodiment of the present invention.

[0037] The present invention has the following beneficial effects:

[0038] 1. In the data preprocessing stage, bandpass filtering and adaptive filtering algorithms are used. The bandpass filter sets upper and lower cutoff frequencies based on the range of human pulse fluctuations, which can effectively remove low-frequency and high-frequency noise while preserving the pulse wave signal; the adaptive filtering algorithm removes motion artifacts in real time, making subsequent feature parameter extraction more accurate, thereby improving the accuracy of heart rate and blood oxygen saturation calculations.

[0039] 2. By incorporating a fingertip contact confidence calculation step, which comprehensively considers the real-time pressure values ​​and light intensity signal variance collected by the flexible pressure sensor, subsequent detection and report generation steps are only performed when the fingertip contact confidence is greater than 0.8. This approach better adapts to the differences in finger shape, size, and usage habits among different users, solving the problem of poor adaptability of existing technologies among different users.

[0040] 3. During the feature parameter extraction process, key features such as the peak value, trough value, rise time, and fall time of the pulse wave are extracted based on the periodicity, amplitude, and rate of change of blood volume. This effectively removes redundant information from the hand area, reduces computation, and improves the accuracy and efficiency of detection.

[0041] 4. The raw data collected by the fingertip detection device is encrypted using AES-256 and stored locally on the device. Only the de-identified health detection report is uploaded to the cloud, and user identity is associated with it using a hash algorithm. This encryption and de-identification process greatly enhances the security and privacy protection of user data, resolving the privacy and security vulnerabilities of existing fingertip health detection technologies.

[0042] 5. The generated health test report is transmitted to the mini-program server in encrypted form, and users can view it through the mini-program on their mobile phones. This method combines modern mobile internet technology, allowing users to access health test reports anytime, anywhere, improving user experience and providing convenience for users' health management. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0047] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0048] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0049] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0050] Example 1:

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, specific embodiments of this application will be described below, with reference to the accompanying drawings. Figure 1 The technical solution of the present invention will be clearly and completely described.

[0052] To address the problems of existing technologies, this invention provides a health detection method based on fingertip touch, comprising the following steps:

[0053] Step S1: Use a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity.

[0054] The fingertip detection device includes: an optical sensor component, a detection groove, an opaque plastic shell, and a flexible pressure sensor. The optical sensor component integrates a light source and a photodetector. The light source and photodetector are arranged at a specific angle to ensure that the light emitted by the light source can effectively illuminate the user's fingertip skin, and that as much reflected or refracted light as possible is received by the photodetector. A groove is provided at the top of the fingertip detection device. The groove's size is designed to ensure that the fingertip testing area of ​​different users completely covers the sensor surface, and an opaque plastic shell is used to cover and shield the testing area of ​​the optical sensor component. This design effectively avoids light leakage, reduces interference from ambient light on the detection results, and improves detection accuracy.

[0055] Step S2: Preprocess the collected light intensity change data, and extract feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume.

[0056] Before the preprocessing step of the collected light intensity change data, the fingertip contact confidence level is calculated based on the data collected by the optical sensor component and the flexible pressure sensor. The specific calculation formula is as follows:

[0057]

[0058] In the formula: C score The confidence level is the fingertip contact confidence level; w1 and w2 are the pressure confidence level weights and light intensity signal confidence level weights, respectively; P is the real-time pressure value collected by the flexible pressure sensor; P threshold The preset pressure threshold; σ 2 The variance of a light intensity signal is used to measure the degree of fluctuation in the light intensity signal. The threshold value for the variance of the light intensity signal; only when C score When the value is >0.8, proceed with subsequent health testing and health report generation.

[0059] The preprocessing of the acquired light intensity variation data includes bandpass filtering and motion artifact removal, wherein:

[0060] Bandpass filtering is used to process the acquired reflected light intensity signal. The pulse wave signal is extracted based on photoplethysmography (PPG) technology. The transfer function of the bandpass filter is:

[0061]

[0062] In the formula: H(f) is the filter response frequency at frequency f; f is the frequency of the input signal; j is the imaginary unit; f cThe lower cutoff frequency of the bandpass filter is set to 0.5Hz and the upper cutoff frequency is set to 5Hz according to the range of human pulse fluctuations. This can effectively remove low-frequency noise (such as baseline drift) and high-frequency noise (such as environmental electromagnetic interference) while retaining useful pulse wave signals.

[0063] Preprocessing also includes removing motion artifacts using an adaptive filtering algorithm. The update formula for the filter coefficients is:

[0064] w(n+1)=w(n)+μ·e(n)·x(n);

[0065] In the formula: w(n+1) are the updated filter coefficients; w(n) is the filter coefficient vector at the nth iteration; μ is the step size factor; e(n) is the error signal at the nth iteration; x(n) is the input sample at the nth iteration; where e(n) is calculated using the following formula:

[0066] e(n) = d(n) - y(n);

[0067] In the formula: d(n) is the desired signal; y(n) is the filter output signal.

[0068] The specific relationship between the change in light intensity and blood volume is as follows:

[0069] I(t) = I0·e -α·ΔV(t)-β·S(t) ;

[0070] In the formula: I(t) represents the change of received light intensity over time; I0 represents the initial light intensity; α represents the absorption coefficient, which measures the ability of light to be absorbed by blood and related tissues; ΔV(t) represents the change of blood volume over time; S(t) represents the change of scattering coefficient; and β represents the scattering coefficient influencing factor, which is calibrated through preliminary experiments.

[0071] Feature parameters are extracted based on the periodicity, amplitude, and rate of change of blood volume to obtain the peak value, trough value, rise time, and fall time of the pulse wave.

[0072] Step S3: Calculate heart rate and blood oxygen saturation based on characteristic parameters and generate a health monitoring report;

[0073] The calculation of heart rate and blood oxygen saturation based on characteristic parameters, specifically the heart rate calculation, is as follows:

[0074]

[0075] In the formula: HR is the calculated heart rate; K is the number of pulse wave peaks detected over a period of time; T peak (k) represents the time interval between two pulse peaks.

[0076] The heart rate and blood oxygen saturation are calculated based on characteristic parameters. Blood oxygen saturation is calculated using a dual-wavelength detection method, and the specific calculation formula is as follows:

[0077]

[0078] In the formula: SpO2 is the calculated blood oxygen saturation; I red (t) represents the change in red light intensity; I infrared(t) For changes in infrared light intensity; I 0,red I represents the initial red light intensity. 0,infrare α represents the initial infrared light intensity. red α infrared , respectively, are the absorption coefficients of red light and infrared light; A is the blood oxygen saturation calibration constant.

[0079] Step S4: The generated health test report is transmitted to the mini-program server in encrypted form, and the user can view the health test report through the mobile mini-program.

[0080] The generated health test report is transmitted to the mini-program server in an encrypted manner. The raw data collected by the fingertip detection device is encrypted with AES-256 and stored locally on the device. Only the de-identified health test report is uploaded to the cloud and associated with the user's identity through a hash algorithm.

[0081] Example 2:

[0082] This embodiment provides a health detection system based on fingertip touch, including:

[0083] The data acquisition module uses a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity.

[0084] The preprocessing and feature extraction module preprocesses the collected light intensity change data and extracts feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume.

[0085] The report generation module calculates heart rate and blood oxygen saturation based on characteristic parameters and generates a health monitoring report.

[0086] The report viewing module transmits the generated health test report to the mini-program server in an encrypted manner, allowing users to view the health test report via the mobile mini-program.

[0087] Example 3:

[0088] This embodiment provides an electronic device that stores a computer program, which, when executed by a processor, implements a health detection method based on fingertip touch as described in any embodiment of the present invention.

[0089] Example 4:

[0090] This embodiment provides a computer-readable medium for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement a health detection method based on fingertip touch as described in any embodiment of the present invention.

[0091] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0092] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0093] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0094] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0095] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A health detection method based on fingertip touch, characterized in that, Includes the following steps: Step S1: Use a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity; at the same time, collect the real-time pressure value of the fingertip contact through a flexible pressure sensor. Step S2: Based on the light intensity change data and real-time pressure value, calculate the fingertip contact confidence level. The formula for calculating the fingertip contact confidence level is: ； In the formula: For fingertip contact confidence; , These are the confidence weights for pressure and light intensity signals, respectively. P is the real-time pressure value collected by the flexible pressure sensor; The preset pressure threshold; The variance of the light intensity signal; The threshold value is the variance of the light intensity signal. Step S3: When the confidence level of fingertip contact is greater than the preset threshold, the collected light intensity change data is preprocessed, and feature parameters are extracted from the preprocessed data based on the relationship between light intensity change and blood volume. Step S4: Calculate heart rate and blood oxygen saturation based on characteristic parameters and generate a health monitoring report; Step S5: The generated health test report is transmitted to the mini-program server in encrypted form, and the user can view the health test report through the mobile mini-program.

2. The health detection method based on fingertip touch according to claim 1, characterized in that, The preprocessing of the acquired light intensity variation data includes bandpass filtering and motion artifact removal, wherein: Bandpass filtering is used to process the acquired reflected light intensity signal. The pulse wave signal is extracted based on photoplethysmography (PPG) technology. The transfer function of the bandpass filter is: ； In the formula: The frequency of the filter is the frequency response at frequency f; f is the frequency of the input signal; j is the imaginary unit. This is the filter cutoff frequency; Preprocessing also includes removing motion artifacts using an adaptive filtering algorithm. The update formula for the filter coefficients is: ； In the formula: These are the updated filter coefficients; This is the filter coefficient vector at the nth iteration; Step size factor; This is the error signal during the nth iteration; This is the input sample for the nth iteration.

3. The health detection method based on fingertip touch according to claim 1, characterized in that, The specific relationship between the change in light intensity and blood volume is as follows: ； In the formula: This shows how the received light intensity changes over time. The initial light intensity; The absorption coefficient measures the ability of light to be absorbed by blood and related tissues. This represents the change in blood volume over time. This represents the change in the scattering coefficient. This is the influencing factor of the scattering coefficient.

4. The health detection method based on fingertip touch according to claim 1, characterized in that, The characteristic parameters include: peak value, trough value, rise time, and fall time of the pulse wave.

5. A health detection method based on fingertip touch according to claim 1, characterized in that, The calculation of heart rate and blood oxygen saturation based on characteristic parameters, specifically the heart rate calculation, is as follows: ； In the formula: HR is the calculated heart rate; K is the number of pulse wave peaks detected over a period of time; The time interval between two pulse wave peaks.

6. The health detection method based on fingertip touch according to claim 1, characterized in that, The heart rate and blood oxygen saturation are calculated based on characteristic parameters. Blood oxygen saturation is calculated using a dual-wavelength detection method, and the specific calculation formula is as follows: ； In the formula: For calculating blood oxygen saturation; This represents the change in red light intensity; This refers to changes in infrared light intensity. The initial red light intensity; The initial infrared light intensity; , , respectively, are the absorption coefficients of red light and infrared light; A is the blood oxygen saturation calibration constant.

7. A health detection method based on fingertip touch according to claim 1, characterized in that, The generated health test report is transmitted to the mini-program server in an encrypted manner. The raw data collected by the fingertip detection device is encrypted with AES-256 and stored locally on the device. Only the de-identified health test report is uploaded to the cloud and associated with the user's identity through a hash algorithm.

8. A health detection system based on fingertip touch, characterized in that, include: The data acquisition module uses a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to irradiate the skin of the fingertips and collect data on the changes in reflected light intensity. The preprocessing and feature extraction module preprocesses the collected light intensity change data and extracts feature parameters from the preprocessed data based on the relationship between light intensity change and blood volume. The report generation module calculates heart rate and blood oxygen saturation based on characteristic parameters and generates a health monitoring report. The report viewing module transmits the generated health test report to the mini-program server in an encrypted manner, allowing users to view the health test report via the mobile mini-program.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a health detection method based on fingertip touch as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a health detection method based on fingertip touch as described in any one of claims 1 to 7.

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