Health detection method and system based on fingertip touch

Abstract

The invention relates to a health detection method and system based on fingertip touch, and the method comprises the following steps: using a fingertip detection device installed on a massage chair to emit light sources with different wavelengths to irradiate fingertip skin, and collecting reflected light intensity change data; preprocessing the collected light intensity change data, and extracting characteristic parameters from the preprocessed data according to the relationship between the light intensity change and the blood volume; calculating heart rate and oxyhemoglobin saturation according to the characteristic parameters, and generating a health detection report; and the generated health detection report is transmitted to an applet server side through encryption, and a user checks the health detection report through a mobile phone applet.

Description

Technical Field

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

[0002] Fingertip health detection technology mainly uses sensors, such as tactile sensors, optical sensors, etc., to detect the touch position and force of the finger, thereby realizing 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. Although fingertip health detection technology has made remarkable progress, in some complex scenarios, its detection accuracy and stability still pose certain challenges. For example, in cases of light changes, finger occlusion, or motion blur, the difficulty of fingertip detection will increase significantly, which may lead to false detections or missed detections. In addition, there are differences in the finger shapes, sizes, usage habits, etc. of different users, which may result in differences in the adaptability of fingertip health detection technology among different users. Therefore, how to design a more general and adaptable fingertip detection algorithm to better meet the needs of different users is also a current challenge. At the same time, the hand area contains a large amount of redundant information, and these parts may cause interference during the fingertip detection process, increasing the computational complexity and difficulty. Therefore, how to effectively remove redundant information and improve the accuracy and efficiency of fingertip detection is an important issue currently faced. In a human-computer interaction system, real-time performance is a very important performance indicator. However, fingertip health detection technology is often limited by factors such as computing resources and algorithm complexity in practical applications and is difficult to meet the real-time requirements. This may cause users to feel delays or lags during operation, affecting the user experience. With the wide application of fingertip health detection technology in intelligent devices, privacy and security issues have become increasingly prominent. For example, some malicious software may use this technology to steal users' sensitive information or perform malicious operations. Therefore, how to strengthen the security and privacy protection of fingertip health detection technology is also one of the problems that need to be solved urgently.

[0003] The prior art, as disclosed in the Chinese patent application with the publication number "CN118000689A", discloses a health detection device and a health detection method. The method includes: responding to a health detection instruction, obtaining a user's hand image of a corresponding area of a bearing part through a position determination device; determining a fingertip to be detected of the user and fingertip feature information of the fingertip to be detected according to the user's hand image; determining position information of the fingertip to be detected according to the fingertip feature information; and controlling a detection part to perform health detection according to the position information. In this way, the fingertip to be detected and the fingertip feature information of the fingertip to be detected are determined based on the user's hand image, the position of the user's hand fingertip is automatically located based on the fingertip feature information, and then, according to the position information of the fingertip, the detection part is controlled to perform health detection, realizing automatic positioning of the detection area, improving the accuracy and efficiency of health detection, and enhancing the user experience.

[0004] The problems existing in the above prior art are that specific detection indexes are not clear, making it difficult to accurately evaluate the health status; although the detection area can be automatically located, the influence of differences in finger shapes, sizes, and usage habits of different users on detection is not considered. Summary of the Invention

[0005] To solve the above technical problems, the present invention proposes a health detection method and system based on fingertip touch.

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

[0007] The present invention proposes a health detection method based on fingertip touch, including the following steps:

[0008] Step S1, using a fingertip detection device installed on a massage chair to emit light sources of different wavelengths to irradiate the fingertip skin, and collecting data on the change in reflected light intensity;

[0009] Step S2, preprocessing the collected data on the change in light intensity, and extracting characteristic parameters from the preprocessed data based on the relationship between the change in light intensity and blood volume;

[0010] Step S3, calculating the heart rate and blood oxygen saturation according to the characteristic parameters, and generating a health detection report;

[0011] Step S4, transmitting the generated health detection report to the applet server side through encryption, and the user views the health detection report through a mobile applet.

[0012] As a preferred implementation manner, the preprocessing of the collected data on the change in light intensity includes band-pass filtering processing and removing motion artifacts, wherein:

[0013] The band-pass filtering processing uses a band-pass filter to process the collected reflected light intensity signal, and extracts a pulse wave signal based on the photoplethysmography technology. The transfer function of the band-pass filter is:

[0014]

[0015] Where: H(f) is the response frequency of the filter at frequency f; f is the frequency of the input signal; j is the imaginary unit; f c is the cut-off frequency of the filter;

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

[0017] w(n + 1) = w(n) + μ·e(n)·x(n);

[0018] Where: 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] As a preferred embodiment, the relationship between the light intensity change and the blood volume is specifically:

[0020] I(t) = I 0 ·e -α·ΔV(t)-β·S(t) ;

[0021] Where: I(t) is the change of the received light intensity with time; I 0 is the initial light intensity; α is the absorption coefficient, which is used to measure the ability of light to be absorbed by blood and related tissues; ΔV(t) is the change in blood volume with time; S(t) is the change in the scattering coefficient; β is the scattering coefficient influence factor.

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

[0023] As a preferred embodiment, the heart rate and blood oxygen saturation are calculated based on the characteristic parameters. Among them, the calculation of the heart rate is specifically:

[0024]

[0025] Where: HR is the calculated heart rate; K is the number of detected pulse wave peak values within a period of time; T peak (k) is the time interval between two pulse wave peak values.

[0026] As a preferred embodiment, the heart rate and blood oxygen saturation are calculated based on the characteristic parameters. Among them, the blood oxygen saturation is calculated using the dual-wavelength detection method, and the specific calculation formula is:

[0027]

[0028] Where: SpO 2 is the calculated blood oxygen saturation; I red (t) is the change in red light intensity; I infrared(t) is the change in infrared light intensity; I 0,red is the initial red light intensity; I 0,infrare is the initial infrared light intensity; α red and α infrared are the absorption coefficients of red light and infrared light respectively; A is the blood oxygen saturation calibration constant.

[0029] As a preferred embodiment, the generated health detection report is encrypted and transmitted to the applet server side. Among them, the original data collected by the fingertip detection device is encrypted by AES-256 and stored locally on the device, and only the de-identified health detection report is uploaded to the cloud, and the user identity is associated through the hash algorithm.

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

[0031] A data acquisition module that uses a fingertip detection device installed on a massage chair to emit light sources of different wavelengths to irradiate the fingertip skin and collect the reflected light intensity change data;

[0032] A preprocessing and feature extraction module that preprocesses the collected light intensity change data and extracts feature parameters from the preprocessed data according to the relationship between the light intensity change and the blood volume;

[0033] A report generation module that calculates the heart rate and blood oxygen saturation according to the feature parameters and generates a health detection report;

[0034] A report viewing module that encrypts and transmits the generated health detection report to the applet server side, and the user views the health detection report through a mobile applet.

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

[0036] On yet another aspect, the present invention also provides a computer-readable medium for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused 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, band-pass filtering and adaptive filtering algorithms are utilized. The band-pass filter sets the upper and lower cut-off frequencies according to the human pulse fluctuation range, which can effectively remove low-frequency and high-frequency noises and retain the pulse wave signal. The adaptive filtering algorithm can remove motion artifacts in real time, making the subsequent extraction of characteristic parameters more accurate, thereby improving the accuracy of heart rate and blood oxygen saturation calculations.

[0039] 2. By setting up a fingertip contact confidence calculation step, comprehensively considering the real-time pressure value collected by the flexible pressure sensor and the variance of the light intensity signal, subsequent detection and report generation steps are only carried out when the fingertip contact confidence is greater than 0.8. This method can better adapt to the differences in finger shapes, sizes, and usage habits of different users, and solves the problem of poor adaptability among different users in the existing technology.

[0040] 3. During the process of extracting characteristic parameters, key features such as the peak value, valley value, rise time, and fall time of the pulse wave are extracted based on the periodicity, amplitude, and change rate of the blood volume change, effectively removing redundant information in the hand area, reducing the calculation amount, and improving the accuracy and efficiency of detection.

[0041] 4. For the original data collected by the fingertip detection device, it is encrypted using AES-256 and stored locally on the device. Only the de-identified health detection report is uploaded to the cloud, and the user identity is associated through a hash algorithm. This encryption and de-identification processing method greatly enhances the security and privacy protection of user data and solves the potential risks in privacy and security of existing fingertip health detection technologies.

[0042] 5. The generated health detection report is transmitted to the mini-program server side through encryption, and users can view it through the mobile mini-program. This method combines modern mobile Internet technology, which is convenient for users to obtain health detection reports anytime and anywhere, improves the user experience, and provides convenience for user health management. Brief Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is a schematic flowchart of the method of the present invention. Detailed Embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] It should be understood that the step numbers used in the text are only for convenient description and do not limit the execution order of the steps.

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

[0048] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

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

[0050] Embodiment 1:

[0051] To make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present application and with reference to the appended Figure 1 , drawings.

[0052] To solve the problems of the prior art, the present invention provides a health detection method based on fingertip touch, including the following steps:

[0053] Step S1, using a fingertip detection device installed on a massage chair to emit light sources of different wavelengths to irradiate the fingertip skin, and collecting the data of the reflected light intensity change;

[0054] The fingertip detection device includes: an optical sensor component, a detection groove, an opaque plastic housing, and a flexible pressure sensor; the optical sensor component integrates a light source and a photoelectric receiver; the light source and the photoelectric receiver are arranged at a specific angle to ensure that the light emitted by the light source can effectively irradiate the user's fingertip skin and make as much reflected or refracted light as possible be received by the photoelectric receiver. A groove is provided above the fingertip detection device, and the size of the groove is designed to ensure that the finger pulp test parts of different users completely cover the sensor surface, and an opaque plastic shell is used to wrap and shield the periphery of the test part of the optical sensor component. Through this design, light leakage can be effectively avoided, the interference of ambient light on the detection result can be reduced, and the detection accuracy can be improved.

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

[0056] Before the step of preprocessing the collected light intensity change data, calculate the fingertip contact confidence according to the data collected by the optical sensor component and the flexible pressure sensor. The specific calculation formula is:

[0057]

[0058] In the formula: C score is the fingertip contact confidence; w 1 , w 2 are the pressure confidence weight and the light intensity signal confidence weight respectively; P is the real-time pressure value collected by the flexible pressure sensor; P threshold is the preset pressure threshold; σ 2 is the variance of the light intensity signal, which is used to measure the fluctuation degree of the light intensity signal; is the threshold of the light intensity signal variance; only when C score > 0.8, perform the subsequent steps of health detection and health report generation.

[0059] The preprocessing of the collected light intensity change data includes band-pass filtering and removing motion artifacts, where:

[0060] The band-pass filtering process uses a band-pass filter to process the collected reflected light intensity signal, and extracts the pulse wave signal based on the photoplethysmography technology. The transfer function of the band-pass filter is:

[0061]

[0062] In the formula: H(f) is the response frequency of the filter at frequency f; f is the frequency of the input signal; j is the imaginary unit; f cLet \(f_c\) be the cut-off frequency of the filter. The lower cut-off frequency of the band-pass filter is set to \(0.5\ Hz\) and the upper cut-off frequency is set to \(5\ Hz\) 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), and retain the useful pulse wave signal;

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

[0064] \(w(n + 1)=w(n)+\mu\cdot e(n)\cdot x(n)\);

[0065] In the formula: \(w(n + 1)\) is the updated filter coefficient; \(w(n)\) is the filter coefficient vector at the \(n\)-th iteration; \(\mu\) is the step size factor; \(e(n)\) is the error signal at the \(n\)-th iteration; \(x(n)\) is the input sample at the \(n\)-th iteration. Among them, the calculation formula for \(e(n)\) is:

[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 relationship between the light intensity change and the blood volume is specifically:

[0069] \(I(t)=I\) 0 \(\cdot e\) -α·ΔV(t)-β·S(t) ;

[0070] In the formula: \(I(t)\) is the change of the received light intensity over time; \(I\) 0 is the initial light intensity; \(\alpha\) is the absorption coefficient, which is used to measure the ability of light to be absorbed by blood and related tissues; \(\Delta V(t)\) is the change of blood volume over time; \(S(t)\) is the change of the scattering coefficient; \(\beta\) is the scattering coefficient influence factor, which is calibrated through preliminary experiments.

[0071] Extract characteristic parameters according to the periodicity, amplitude and change rate of the blood volume change amount, and obtain the peak value, valley value, rise time and fall time of the pulse wave.

[0072] Step S3, calculate the heart rate and blood oxygen saturation according to the characteristic parameters, and generate a health detection report;

[0073] The calculation of the heart rate and blood oxygen saturation according to the characteristic parameters, among which the calculation of the heart rate is specifically:

[0074]

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

[0076] Calculating the heart rate and blood oxygen saturation according to the characteristic parameters, wherein the blood oxygen saturation is calculated by a dual-wavelength detection method, and the specific calculation formula is:

[0077]

[0078] In the formula: SpO 2 is the calculated blood oxygen saturation; I red (t) is the change in red light intensity; I infrared(t) is the change in infrared light intensity; I 0,red is the initial red light intensity; I 0,infrare is the initial infrared light intensity; α red and α infrared are the absorption coefficients of red light and infrared light respectively; A is the blood oxygen saturation calibration constant.

[0079] Step S4: Transmit the generated health detection report to the applet server side through encryption, and the user can view the health detection report through the mobile applet.

[0080] For the above-mentioned transmitting the generated health detection report to the applet server side through encryption, the original data collected by the fingertip detection device is encrypted by AES-256 and stored locally on the device, and only the de-identified health detection report is uploaded to the cloud, and the user identity is associated through the hash algorithm.

[0081] Embodiment 2:

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

[0083] A data acquisition module that uses a fingertip detection device installed on a massage chair to emit light sources of different wavelengths to irradiate the fingertip skin and collect the reflected light intensity change data;

[0084] A preprocessing and feature extraction module that preprocesses the collected light intensity change data and extracts characteristic parameters from the preprocessed data according to the relationship between the light intensity change and the blood volume;

[0085] A report generation module that calculates the heart rate and blood oxygen saturation according to the characteristic parameters and generates a health detection report;

[0086] A report viewing module that transmits the generated health detection report to the applet server side through encryption, and the user can view the health detection report through the mobile applet.

[0087] Embodiment 3:

[0088] This embodiment provides an electronic device with a computer program stored thereon, and when the computer program is executed by a processor, it 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. When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement a health detection method based on fingertip touch as described in any embodiment of the present invention.

[0091] In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent the cases of A existing alone, A and B existing simultaneously, and B existing alone. Where A and B may be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c may represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c may be single or multiple.

[0092] Those of ordinary skill in the art can realize that the units and algorithm steps described in the embodiments disclosed herein can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

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

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

[0095] The above are only the embodiments of the present invention, and thus do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A health detection method based on fingertip touch, characterized in that: The following steps are involved: Step S1, using a fingertip detection device installed on the massage chair to emit light sources of different wavelengths to illuminate the fingertip skin and collect reflected light intensity change data; Step S2, preprocessing the collected light intensity change data, and extracting characteristic parameters from the preprocessed data based on the relationship between the light intensity change and the blood volume; Step S3, calculating the heart rate and blood oxygen saturation according to the characteristic parameters, and generating a health detection report; Step S4, encrypt and transmit the generated health check report to the mini program server, and the user views the health check 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 collected light intensity change data includes bandpass filtering and removing motion artifacts, wherein: Bandpass filtering uses a bandpass filter to process the collected reflected light intensity signal, and extracts the pulse wave signal based on the photoplethysmography technology. The transfer function of the bandpass filter is: Where: H(f) is the response frequency of the filter at frequency f; f is the frequency of the input signal; j is the imaginary unit; f c is the filter cut-off frequency; Preprocessing also includes using an adaptive filtering algorithm to remove motion artifacts. The update formula of the filter coefficient is: w(n+1)=w(n)+μ·e(n)·x(n); Where: w(n+1) is the updated filter coefficient; w(n) is the filter coefficient vector at the nth iteration; μ is the step factor; e(n) is the error signal at the nth iteration; x(n) is the input sample at the nth iteration.

3. The health detection method based on fingertip touch according to claim 1, characterized in that: The relationship between the light intensity change and the blood volume is specifically: I(t)=I0·e -α·ΔV(t)-β·S(t) ; Where: I(t) is the change of received light intensity over time; I0 is the initial light intensity; α is the absorption coefficient, which is used to measure the ability of light to be absorbed by blood and related tissues; ΔV(t) is the change of blood volume over time; S(t) is the change of scattering coefficient; β 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, valley value, rise time and fall time of the pulse wave.

5. The health detection method based on fingertip touch according to claim 1, characterized in that: The heart rate and blood oxygen saturation are calculated according to the characteristic parameters, wherein the heart rate calculation is specifically as follows: Where: HR is the calculated heart rate; K is the number of pulse wave peaks detected within a period of time; T peak (k) is 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 according to the characteristic parameters, wherein the blood oxygen saturation is calculated using a dual-wavelength detection method, and the specific calculation formula is: Where: SpO2 is the calculated blood oxygen saturation; I red (t) is the change of red light intensity; I infrared(t) is the change of infrared light intensity; I 0,red is the initial red light intensity; I 0,infrare is the initial infrared light intensity; α red , α infrared are the absorption coefficients of red light and infrared light respectively; A is the blood oxygen saturation calibration constant.

7. The health detection method based on fingertip touch according to claim 1, characterized in that: The generated health check report is transmitted to the mini program server through encryption, wherein the original data collected by the fingertip detection device is encrypted by AES-256 and stored locally on the device, and only the de-identified health check report is uploaded to the cloud and associated with the user 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 illuminate the fingertip skin and collect reflected light intensity change data; 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 the light intensity change and the blood volume; The report generation module calculates the heart rate and blood oxygen saturation based on the characteristic parameters and generates a health test report; The report viewing module transmits the generated health check report to the mini program server through encryption, and users can view the health check report through 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, the health detection method based on fingertip touch as described in any one of claims 1 to 7 is implemented.

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

Images