Nasal alar pulse wave signal processing method and device, medium and wearable device

Abstract

This invention belongs to the field of nasal alar pulse wave signal processing technology, and provides a method, apparatus, medium, and wearable device for nasal alar pulse wave signal processing. The method includes: extracting the respiratory cycle based on the respiratory signal; determining the length of the mean sliding filter window to filter out the DC component of the original nasal alar pulse wave signal, obtaining a filtered nasal alar pulse wave signal; extracting the amplitude of the AC component of the filtered nasal alar pulse wave signal; adjusting the current of the light source element corresponding to the pulse wave signal sensing element to make the amplitude of the AC component of the filtered nasal alar pulse wave signal greater than or equal to a preset amplitude threshold; further filtering the nasal alar pulse wave signal using an adaptive weighted moving average filtering algorithm; and determining whether a nasal alar pulse wave signal meeting preset quality requirements is obtained based on a comparison between the noise figure of the further filtered nasal alar pulse wave signal and a preset noise figure threshold.

Description

Technical Field

[0001] This invention belongs to the field of nasal pulse wave signal processing technology, and particularly relates to a method, device, medium and wearable device for nasal pulse wave signal processing. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Acute sleep apnea refers to the sudden cessation or significant reduction of breathing within a short period of time, usually triggered by large-scale disasters or critical emergencies (such as cardiac arrest, suffocation, or asthma attacks). Currently available commercial monitoring instruments in hospitals and laboratories are complex to operate, bulky, and expensive, making them inconvenient for daily real-time monitoring at home. Some newer wearable health monitoring devices, such as electronic bracelets and breathing belts, also have limitations in their physiological parameter detection; breathing belts can only monitor respiration, while electronic bracelets can only monitor heart rate. There is a lack of wearable multi-parameter monitoring devices related to the respiratory system.

[0004] Patent CN112120710A, "A Nose Clip-Type Parameter Detection Probe," describes a nose clip-type detection probe device, but it still requires a wired connection to transmit the collected data, necessitating the use of external devices or computers for processing, thus lacking portability and home use capabilities. Furthermore, it focuses solely on detecting photoelectric signals at the nasal alar, neglecting the possibility of detecting respiratory gases when the device is inserted into the nasal cavity. Patent CN110236503A, "A Flexible Wearable Sleep Physiological Parameter Detection Method and Device," proposes a device for detecting three parameters during sleep: respiration, heart rate, and blood oxygenation. However, in pulse wave signal processing, it fails to consider individual differences, skin condition (melanin content and skin thickness), and interference from facial movements at that location. Moreover, research has shown that the nasal alar region provides a very large pulse wave signal compared to other parts of the body (including fingers, toes, and ears), and provides a relatively high-quality signal due to its lack of sympathetic innervation. However, due to factors such as respiratory movements, facial expressions, and individual differences, pulse wave signals also contain a large number of interference signals, which can affect the perception and measurement of pulse waves. The relevant technical solution of patent CN110236503A "A flexible wearable method and device for detecting sleep physiological parameters" is not universal and requires an external terminal to process data, so it cannot work independently. Summary of the Invention

[0005] To address the technical problems mentioned above, this invention provides a method, apparatus, medium, and wearable device for processing pulse wave signals at the nasal ala, which can improve the accuracy and applicability of monitoring parameters of nose clip devices.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of the present invention provides a method for processing pulse wave signals at the nasal ala.

[0008] A method for processing pulse wave signals at the nasal ala, comprising:

[0009] Acquire raw pulse wave signals and respiratory signals at the nasal ala;

[0010] The respiratory cycle is extracted from the respiratory signal. Then, based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, the mean sliding filtering window length is determined to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the filtered pulse wave signal at the nasal ala.

[0011] Extract the AC component amplitude of the pulse wave filter signal at the nasal ala and compare it with a preset amplitude threshold. If the former is less than the latter, increase the current of the light source element corresponding to the pulse wave signal sensing element until the AC component amplitude of the pulse wave filter signal at the nasal ala is greater than or equal to the preset amplitude threshold.

[0012] If the amplitude of the AC component of the pulse wave filtered signal at the nasal ala is greater than or equal to the preset amplitude threshold, the pulse wave filtered signal at the nasal ala is filtered again using an adaptive weighted moving average filtering algorithm. The result of comparing the noise figure of the pulse wave signal at the nasal ala after the second filtering with the preset noise figure threshold determines whether a pulse wave signal at the nasal ala that meets the preset quality requirements is obtained.

[0013] As one implementation method, if the noise figure of the pulse wave signal at the nasal ala after further filtering is less than or equal to a preset noise figure threshold, then a pulse wave signal at the nasal ala that meets the preset quality requirements is obtained.

[0014] As one implementation method, if the noise figure of the pulse wave signal at the nasal ala after filtering again is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm is adjusted, and filtering is performed again until the noise figure of the pulse wave signal at the nasal ala is less than the preset noise figure threshold.

[0015] As one implementation method, the process of calculating the noise figure of the pulse wave signal at the nasal ala is as follows:

[0016] The number of maximum points of the filtered nasal pulse wave signal is n, and the x-coordinates of the maximum points {x1, x2, ... x} are obtained. i ,...x n} and the ordinates {y1, y2, ... y i ,...y n};

[0017] Calculate the average value of the ordinate y. mean If y i ≥d*y mean , keep y i We get {y1, y2, ... y i ,...y m} and the corresponding x-coordinates {x1, x2, ... x i ,...x m}, where d is a known constant; calculate the spacing between the m retained x-coordinates to obtain D = {D1, D2, ... D}. i ,...D m-1}; Calculate the standard deviation D of D. std According to the known relation K = f(n, m, D) std ), calculate the noise figure K.

[0018] As one implementation, the filter coefficients of the adaptive weighted moving average filtering algorithm include the weighted moving average filtering window length L. w And the weight matching coefficient w.

[0019] As one implementation method, when the noise figure K > the preset noise figure threshold K ref When this happens, increase the length L of the weighted moving average filter window. w Meanwhile, if D std >D ref Decrease the value of w until the minimum value of w is 1; when D std ≤D ref When, the value of w remains unchanged; where, D ref This is the standard deviation threshold.

[0020] A second aspect of the present invention provides a pulse wave signal processing device at the nasal ala.

[0021] A pulse wave signal processing device at the nasal ala, comprising:

[0022] The signal acquisition module is used to acquire the raw pulse wave signal and respiratory signal at the nasal ala.

[0023] The initial filtering module is used to extract the respiratory cycle from the respiratory signal, and then determine the mean sliding filtering window length based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, so as to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the filtered pulse wave signal at the nasal ala.

[0024] The amplitude comparison module is used to extract the AC component amplitude of the pulse wave filter signal at the nasal ala and compare it with a preset amplitude threshold. If the former is less than the latter, the current of the light source element corresponding to the pulse wave signal sensing element is increased until the AC component amplitude of the pulse wave filter signal at the nasal ala is greater than or equal to the preset amplitude threshold.

[0025] The noise figure comparison module is used to filter the nasal pulse wave signal again using an adaptive weighted moving average filtering algorithm if the amplitude of the AC component of the nasal pulse wave filter signal is greater than a preset amplitude threshold. The module then determines whether a nasal pulse wave signal that meets the preset quality requirements is obtained based on the comparison between the noise figure of the nasal pulse wave signal after the second filtering and the preset noise figure threshold.

[0026] As one implementation, in the noise figure comparison module, if the noise figure of the pulse wave signal at the nasal ala after further filtering is less than or equal to a preset noise figure threshold, then a pulse wave signal at the nasal ala that meets the preset quality requirements is obtained.

[0027] If the noise figure of the pulse wave signal at the nasal ala after filtering again is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm is adjusted and filtered again until the noise figure of the pulse wave signal at the nasal ala is less than or equal to the preset noise figure threshold.

[0028] A third aspect of the present invention provides a computer-readable storage medium.

[0029] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for processing pulse wave signals at the nasal ala.

[0030] A fourth aspect of the present invention provides a wearable device.

[0031] A wearable device, comprising:

[0032] Clamping element, used to clamp at the wing of the nose;

[0033] The sensing element, which is arranged on the clamping element, is used to collect the raw pulse wave signal and respiratory signal at the nasal ala;

[0034] A processor, which is disposed on the clamping element;

[0035] The processor is connected to the sensing element, and the processor is used for:

[0036] When the program is executed, the steps in the above-described method for processing pulse wave signals at the nasal ala are implemented to obtain a pulse wave signal at the nasal ala that meets the preset quality requirements.

[0037] Feature values ​​are extracted from respiratory signals and nasal pulse wave signals that meet preset quality requirements, and physiological parameters are calculated.

[0038] The beneficial effects of this invention are:

[0039] This invention utilizes the respiratory cycle of the respiratory signal to filter out the DC component of the original pulse wave signal at the nasal ala. Furthermore, based on the comparison results of the AC component amplitude of the filtered pulse wave signal at the nasal ala and the noise figure of the filtered pulse wave signal at the nasal ala with the corresponding preset amplitude threshold and preset noise figure threshold, it determines whether a pulse wave signal at the nasal ala that meets the preset quality requirements has been obtained. By monitoring the pulse wave signal and nasal breathing signal in the nasal ala region in real time, the quality of the pulse wave signal obtained at the nasal ala is improved, and the problems of respiratory interference and individual differences are solved.

[0040] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0041] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0042] Figure 1(a) shows the pulse wave at the alar of the nose when the skin at the alar of the nose is in good condition;

[0043] Figure 1(b) shows the pulse wave at the nasal alar when the skin condition at the nasal alar is poor;

[0044] Figure 2 This is a flowchart of the pulse wave signal processing method at the nasal ala according to an embodiment of the present invention;

[0045] Figure 3(a) shows the nasal ala pulse wave signal when the LED current is 22.2mA;

[0046] Figure 3(b) shows the nasal ala pulse wave signal when the LED current is 35mA;

[0047] Figure 3(c) shows the nasal ala pulse wave signal when the LED current is 44.6mA;

[0048] Figure 4(a) shows the original pulse wave signal;

[0049] Figure 4(b) shows the pulse wave signal obtained using the adaptive filtering method;

[0050] Figure 4(c) shows the pulse wave signal obtained using the ordinary sliding filter method;

[0051] Figure 5 This is a flowchart of the physiological parameter calculation process according to an embodiment of the present invention;

[0052] Figure 6 This is a consistency analysis of respiratory rate detection in an embodiment of the present invention;

[0053] Figure 7 This is a consistency analysis of heart rate detection in an embodiment of the present invention;

[0054] Figure 8 This is a blood oxygen saturation tracking and detection method according to an embodiment of the present invention. Detailed Implementation

[0055] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0056] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0057] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0058] Example 1

[0059] The condition of the nasal ala (melanin content and skin thickness), breathing, and facial expressions may have a certain impact on the perception and measurement of pulse waves, as shown in Figure 1(a) and Figure 1(b). In order to improve the accuracy and versatility of physiological index measurement, it is very important to screen out high-quality pulse wave waveforms.

[0060] A typical PPG signal has two main components: an AC component representing the pulsed nature of blood flow and a DC component reflecting the baseline or non-pulsating components. When the skin condition of the nasal ala is poor, the pulse wave exhibits problems such as low AC amplitude, abrupt changes, and high-frequency noise. Respiratory movements can also cause signal baseline instability. This invention provides a method for processing pulse wave signals at the nasal ala to obtain high-quality pulse wave waveforms, such as... Figure 2 As shown.

[0061] The following is combined with Figure 2 The implementation process of the pulse wave signal processing method at the nasal ala of this invention will be described in detail below.

[0062] according to Figure 2 This embodiment provides a method for processing pulse wave signals at the nasal ala, which includes:

[0063] Step 1: Obtain the raw pulse wave signal and respiratory signal at the nasal ala.

[0064] Using respiratory signals as a reference can help filter out some noise that may originate from breathing movements, thereby improving the quality of pulse wave signals.

[0065] In this embodiment, a wearable device clipped to the nose of the human body is used to collect PPG signal S1 by photoelectric method and respiratory signal R1 by temperature method or humidity method.

[0066] Step 2: Extract the respiratory cycle from the respiratory signal, and then determine the mean sliding filter window length based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, so as to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the filtered pulse wave signal at the nasal ala.

[0067] The calculation process for the mean sliding filter window length during implementation is as follows:

[0068] The respiratory cycle T is extracted from the respiratory signal R1. The PPG signal S1 is filtered, including median filtering to remove abrupt changes and mean sliding filtering to remove the DC component. Under normal circumstances, when a person breathes, the heart rate, i.e., the number of pulse waves, will change accordingly. Respiratory movements will cause baseline interference to the pulse wave signal, so it is necessary to determine an appropriate baseline removal window length.

[0069] Mean sliding filter window length L S1 The calculation process:

[0070] The human respiratory rate can be between 10 and 30 breaths per minute, corresponding to a respiratory cycle T of 2 to 6 seconds.

[0071] When T∈[2,6], the window length L S1 =f s *k*T;

[0072] When T < 2, the window length L S1 =f s *k*2;

[0073] When T>6, the window length L S1 =f s *k*6;

[0074] Among them, f s denoted as the sampling frequency of the PPG signal point, and k as an adjustment coefficient, obtained based on experimental data. The PPG signal S1 is filtered to remove the DC component (DC) through a mean-sliding filter, resulting in the filtered signal S2.

[0075] Step 3: Extract the AC component amplitude of the pulse wave filtered signal at the nasal ala and compare it with the preset amplitude threshold. If the former is less than the latter, increase the current of the light source element corresponding to the pulse wave signal sensing element until the AC component amplitude of the pulse wave filtered signal at the nasal ala is greater than or equal to the preset amplitude threshold.

[0076] For example, the amplitude AC of the AC component of the filtered signal S2 is extracted and evaluated. Through experimental testing, an amplitude threshold AC that meets the requirements of subsequent signal processing is set. ref .

[0077] Since AC is related to light intensity, the AC amplitude can be increased by increasing the LED current, with the following effect: Figures 3(a)-3(c) LED current is divided into different levels. When AC... <AC ref At this time, increase the LED current rating until AC ≥ AC ref The adjustment is now complete.

[0078] Step 4: If the amplitude of the AC component of the pulse wave filtered signal at the nasal ala is greater than the preset amplitude threshold, the pulse wave filtered signal at the nasal ala is filtered again using an adaptive weighted moving average filtering algorithm; the comparison between the noise figure of the pulse wave signal at the nasal ala after the second filtering and the preset noise figure threshold is used to determine whether a pulse wave signal at the nasal ala that meets the preset quality requirements is obtained.

[0079] In its implementation, the adaptive weighted moving average filtering algorithm includes two self-adjusting filtering parameters L. w and w, L w is the length of the weighted moving average filter window, and w is the weighted matching coefficient of the original signal value.

[0080] The algorithm formula is set as follows:

[0081]

[0082] Where y(n) is the filtered value of the current point x(n), and x(i) is the value of x at time i.

[0083] Specifically, the process of calculating the noise figure of the pulse wave signal at the nasal ala is as follows:

[0084] The number of maximum points of the filtered nasal pulse wave signal is n, and the x-coordinates of the maximum points {x1, x2, ... x} are obtained. i ,...x n} and the ordinates {y1, y2, ... y i ,...y n};

[0085] Calculate the average value of the ordinate y. mean If yi ≥d*y mean , keep y i We get {y1, y2, ... y i ,...y m} and the corresponding x-coordinates {x1, x2, ... x i ,...x m}, where d is a known constant derived from experimental data; calculate the interval between m x-coordinates to obtain D = {D1, D2, ... D}. i ,...D m-1}; Calculate the standard deviation D of D. std According to the known relation K = f(n, m, D) std ), calculate the noise figure K.

[0086] It should be noted here that K = f(n, m, D) std This relationship can be obtained by curve fitting based on multiple sets of known data.

[0087] To verify the effectiveness of the processing method in this embodiment, from... Figures 4(a)-4(c) It can be seen that the pulse wave signal obtained by using the adaptive filtering method in this embodiment is better than the pulse wave signal obtained by using the ordinary sliding filtering method.

[0088] according to Figure 2 If the noise figure of the pulse wave signal at the nasal wing after further filtering is less than or equal to the preset noise figure threshold, then a pulse wave signal at the nasal wing that meets the preset quality requirements is obtained.

[0089] If the noise figure of the pulse wave signal at the nasal ala after further filtering is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm is adjusted until the noise figure of the pulse wave signal at the nasal ala is less than or equal to the preset noise figure threshold.

[0090] In practical implementation, the filter coefficients of the adaptive weighted moving average filtering algorithm include the weighted moving average filter window length L. w And the weight matching coefficient w;

[0091] When the noise figure K > the preset noise figure threshold K ref When this happens, increase the length L of the weighted moving average filter window. w Meanwhile, if D std >D ref Decrease the value of w until the minimum value of w is 1; when D std ≤D ref When, the value of w remains unchanged; where, D ref This is the standard deviation threshold.

[0092] It should be noted here that the threshold Kref D ref It is derived from experimental data and is related to the required signal quality.

[0093] Example 2

[0094] A pulse wave signal processing device at the nasal ala, comprising:

[0095] (1) Signal acquisition module, which is used to acquire the raw pulse wave signal and respiratory signal at the nasal ala;

[0096] (2) Initial filtering module, which is used to extract the respiratory cycle based on the respiratory signal, and then determine the mean sliding filtering window length based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, so as to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the pulse wave filtered signal at the nasal ala.

[0097] (3) Amplitude comparison module, which is used to extract the AC component amplitude of the pulse wave filter signal at the nasal wing and compare it with the preset amplitude threshold. If the former is less than the latter, the current of the light source element corresponding to the pulse wave signal sensing element is increased until the AC component amplitude of the pulse wave filter signal at the nasal wing is greater than or equal to the preset amplitude threshold.

[0098] (4) Noise figure comparison module, which is used to filter the pulse wave signal at the nasal wing again using an adaptive weighted moving average filtering algorithm if the amplitude of the AC component of the pulse wave filter signal at the nasal wing is greater than the preset amplitude threshold; and to determine whether a pulse wave signal at the nasal wing that meets the preset quality requirements is obtained based on the comparison result between the noise figure of the pulse wave signal at the nasal wing after the second filtering and the preset noise figure threshold.

[0099] In the noise figure comparison module, if the noise figure of the pulse wave signal at the nasal wing after further filtering is less than or equal to the preset noise figure threshold, then a pulse wave signal at the nasal wing that meets the preset quality requirements is obtained.

[0100] If the noise figure of the pulse wave signal at the nasal ala after further filtering is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm will be adjusted until the noise figure of the pulse wave signal at the nasal ala is less than or equal to the preset noise figure threshold.

[0101] It should be noted that each module in this embodiment corresponds one-to-one with each step in Embodiment 1, and their specific implementation process is the same, so it will not be described in detail here.

[0102] Example 3

[0103] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the above-described method for processing pulse wave signals at the nasal ala.

[0104] Example 4

[0105] This embodiment provides a wearable device, including:

[0106] Clamping element, used to clamp at the wing of the nose;

[0107] The sensing element, which is arranged on the clamping element, is used to collect the raw pulse wave signal and respiratory signal at the nasal ala;

[0108] A processor, which is disposed on the clamping element;

[0109] The processor is connected to the sensing element, and the processor is used for:

[0110] When the program is executed, the steps in the above-described method for processing pulse wave signals at the nasal ala are implemented to obtain a pulse wave signal at the nasal ala that meets the preset quality requirements.

[0111] Feature values ​​are extracted from respiratory signals and nasal pulse wave signals that meet preset quality requirements, and physiological parameters are calculated.

[0112] For example, the wearable device provided in this embodiment can be clipped onto the nose of a human body, and can monitor the pulse wave signal of the nasal alar area and the breathing gas in the nasal cavity in real time. It contains a processor to calculate relevant indicators, can work independently, and can also upload data to a mobile phone or computer in real time.

[0113] In one embodiment of the wearable device, the wearable device comprises a first clamp with a docking portion, a second clamp, an elastic element for driving the first and second clamps to clamp together, and a fixed shaft. The first and second clamps can clamp the nostrils from both inside and outside the nasal cavity under the elastic force of the elastic element. The surface of the first clamp is equipped with an OLED display screen with a resolution of 96*16, capable of displaying device status information and monitoring indicators in real time. The part in contact with the nose uses deformable silicone, allowing the medical nose clip device to adapt to the user's nose shape while ensuring uniform force and providing a comfortable wearing experience. An auxiliary positioning design structure is used to assist in wearing the device, assist in calibrating the photoelectric signal acquisition position, reduce the impact of individual differences, and provide assurance for subsequent signal processing.

[0114] The first clamp contacts the nasal ala and, under the action of the elastic element, adheres tightly to the nasal ala. Internally, it contains a power supply module, a PCB control motherboard, and the motherboard includes a processor, power management module, Bluetooth module, and photoelectric module. The photoelectric module uses a reflection method to collect pulse waves at the nasal ala and consists of an LED and a photoelectric acquisition module (PD). The LED can emit red light at wavelengths of 650nm and 950nm, and infrared light, respectively. The light emitted by the LED passes through the skin, tissue, and blood vessels of the nasal ala and is reflected. The photoelectric acquisition module (PD) converts the reflected light signal into an electrical signal. The processor can process the signal in real time and calculate physiological indicators such as heart rate and blood oxygenation.

[0115] In one or more embodiments, the Bluetooth module can transmit data to mobile phones and computers. The power supply module is powered by a small-sized lithium battery. A second clip is inserted into the nasal cavity, and a PCB sub-board is placed within the second clip. A temperature detection module is included to extract breathing signals based on temperature changes in inhaled and exhaled air from the nasal cavity.

[0116] The workflow of the wearable device in this embodiment is as follows: Figure 5 As shown, the wearable device collects respiratory signals and pulse wave signals from the nasal ala, calculating respiratory parameters, heart rate, and blood oxygen saturation. The data can be uploaded to a smart terminal, where multi-indicator analysis enables rapid disease prediction and assessment, detecting abnormalities and providing timely warnings.

[0117] The following is a specific implementation example of extracting feature values ​​from respiratory signals and nasal pulse wave signals that meet preset quality requirements, and calculating set physiological parameters:

[0118] Feature values ​​were extracted from the acquired respiratory signals and high-quality pulse wave signals to calculate respiratory parameters and heart rate and blood oxygenation parameters.

[0119] The calculated respiratory parameters include: Respiratory rate (RR): the number of breaths per minute, calculated by the time interval between the peaks of each respiratory waveform. Respiratory amplitude (RA): the vertical distance between the peaks and troughs of each respiratory waveform. Inspiratory time (T). i Expiratory time (T) refers to the time taken to complete one exhalation, which is the time interval between the peak and the trough of each respiratory waveform. e The time taken to complete one inhalation is the time interval between the trough and the next peak of each breathing waveform.

[0120] Feature points are extracted from high-quality pulse wave signals to calculate the time N of a single pulse wave. Since each pulse wave corresponds to one heartbeat, i.e., one N value corresponds to the time of one heartbeat, the validity of N is assessed to accurately calculate heart rate (HR). Experimental testing derives an effective range using the average of multiple N values ​​over a specified time period.mean Sum of standard deviation N std This filters out abnormal values ​​caused by interference such as movement. Heart rate calculation formula:

[0121]

[0122] e is a constant derived from experimental data.

[0123] Based on high-quality pulse wave signals, the AC and DC components of the PPG signal are extracted. According to Lambert-Beer's optical law and the absorbance difference between Hb and HbO2, the characteristic parameter R is calculated.

[0124]

[0125] Therefore, the formula for calculating blood oxygen saturation SpO2 is:

[0126] SpO2=a*R 2 +b*R+c, where AC 650 and DC 650 AC 950 and DC 950 These are the AC and DC components of the PPG signal at wavelengths of 650nm and 950nm, respectively, and a, b, and c are constants obtained from calibration.

[0127] The signal processing method in this embodiment does not require external intelligent terminals for computation, and the detection results show a high degree of consistency compared to standard equipment. The correlation coefficient R between respiratory rate detection and heart rate detection is... 2 The values ​​were 0.98 and 0.95 respectively. The blood oxygen saturation tracking and detection also demonstrated the reliability of the algorithm, enabling real-time tracking of blood oxygen changes. Among them, Figure 6 A consistency analysis of respiratory rate detection in this embodiment is presented; Figure 7 The consistency analysis of heart rate detection in this embodiment is presented; Figure 8 The blood oxygen saturation tracking and detection in this embodiment is presented.

[0128] This embodiment establishes a physiological parameter calculation model based on extracted respiratory and pulse wave signals, ensuring the accuracy of respiratory, heart rate, and blood oxygen saturation detection and improving the detection precision of wearable devices. Simultaneously, without the need for a smart terminal, the smart terminal can use real-time data for health status assessment, such as for cardiovascular diseases, and respiratory diseases including COPD, asthma, and sleep disorders.

[0129] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0130] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for processing pulse wave signals at the nasal ala, characterized in that, include: Acquire raw pulse wave signals and respiratory signals at the nasal ala; The respiratory cycle is extracted from the respiratory signal. Then, based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, the mean sliding filtering window length is determined to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the filtered pulse wave signal at the nasal ala. Extract the AC component amplitude of the pulse wave filter signal at the nasal ala and compare it with a preset amplitude threshold. If the former is less than the latter, increase the current of the light source element corresponding to the pulse wave signal sensing element until the AC component amplitude of the pulse wave filter signal at the nasal ala is greater than or equal to the preset amplitude threshold. If the amplitude of the AC component of the pulse wave filter signal at the nasal ala is greater than the preset amplitude threshold, the pulse wave filter signal at the nasal ala will be filtered again using an adaptive weighted moving average filtering algorithm. The determination of whether a pulse wave signal at the nasal ala that meets the preset quality requirements is made is based on the comparison between the noise figure of the filtered pulse wave signal at the nasal ala and the preset noise figure threshold.

2. The method for processing pulse wave signals at the nasal ala as described in claim 1, characterized in that, If the noise figure of the pulse wave signal at the nasal ala after further filtering is less than or equal to the preset noise figure threshold, then a pulse wave signal at the nasal ala that meets the preset quality requirements is obtained.

3. The method for processing nasal pulse wave signals as described in claim 1, characterized in that, If the noise figure of the pulse wave signal at the nasal ala after further filtering is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm will be adjusted until the noise figure of the pulse wave signal at the nasal ala is less than or equal to the preset noise figure threshold.

4. The method for processing pulse wave signals at the nasal ala as described in claim 1, characterized in that, The process of calculating the noise figure of the pulse wave signal at the nasal ala is as follows: The number of maximum points of the filtered nasal pulse wave signal is n, and the x-coordinates of the maximum points {x1, x2, ... x} are obtained. i ,...x n } and the ordinates {y1, y2, ... y i ,...y n }; Calculate the average value of the ordinate y. mean If y i ≥d*y mean , keep y i We get {y1, y2, ... y i ,...y m } and the corresponding x-coordinates {x1, x2, ... x i ,...x m }, where d is a known constant; calculate the spacing between the m retained x-coordinates to obtain D = {D1, D2, ... D}. i ,...D m-1 }; Calculate the standard deviation D of D. std According to the known relation K = f(n, m, D) std ), calculate the noise figure K.

5. The method for processing nasal pulse wave signals as described in claim 4, characterized in that, The filter coefficients of the adaptive weighted moving average filtering algorithm include the weighted moving average filter window length L. w And the weight matching coefficient w.

6. The method for processing pulse wave signals at the nasal ala as described in claim 5, characterized in that, When the noise figure K > the preset noise figure threshold K ref When this happens, increase the length L of the weighted moving average filter window. w Meanwhile, if D std >D ref Decrease the value of w until the minimum value of w is 1; when D std ≤D ref When, the value of w remains unchanged; where, D ref This is the standard deviation threshold.

7. A device for processing pulse wave signals at the nasal ala, characterized in that, include: The signal acquisition module is used to acquire the raw pulse wave signal and respiratory signal at the nasal ala. The initial filtering module is used to extract the respiratory cycle from the respiratory signal, and then determine the mean sliding filtering window length based on the correspondence between the respiratory cycle and the DC component filtering window length of the pulse wave at the nasal ala, so as to filter out the DC component of the original pulse wave signal at the nasal ala and obtain the filtered pulse wave signal at the nasal ala. The amplitude comparison module is used to extract the AC component amplitude of the pulse wave filter signal at the nasal ala and compare it with a preset amplitude threshold. If the former is less than the latter, the current of the light source element corresponding to the pulse wave signal sensing element is increased until the AC component amplitude of the pulse wave filter signal at the nasal ala is greater than or equal to the preset amplitude threshold. The noise figure comparison module is used to filter the pulse wave filter signal at the nasal ala again using an adaptive weighted moving average filtering algorithm if the amplitude of the AC component of the pulse wave filter signal at the nasal ala is greater than a preset amplitude threshold. The determination of whether a pulse wave signal at the nasal ala that meets the preset quality requirements is made is based on the comparison between the noise figure of the filtered pulse wave signal at the nasal ala and the preset noise figure threshold.

8. The nasal pulse wave signal processing device as described in claim 7, characterized in that, In the noise figure comparison module, if the noise figure of the pulse wave signal at the nasal wing after further filtering is less than or equal to the preset noise figure threshold, then a pulse wave signal at the nasal wing that meets the preset quality requirements is obtained. If the noise figure of the pulse wave signal at the nasal ala after further filtering is greater than the preset noise figure threshold, the filtering coefficient of the adaptive weighted moving average filtering algorithm is adjusted until the noise figure of the pulse wave signal at the nasal ala is less than the preset noise figure threshold.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the method for processing pulse wave signals at the nasal ala as described in any one of claims 1-6.

10. A wearable device, characterized in that, include: Clamping element, used to clamp at the wing of the nose; The sensing element, which is arranged on the clamping element, is used to collect the raw pulse wave signal and respiratory signal at the nasal ala; A processor, which is disposed on the clamping element; The processor is connected to the sensing element, and the processor is used for: When the program is executed, the steps in the nasal alar pulse wave signal processing method as described in any one of claims 1-6 are implemented to obtain a nasal alar pulse wave signal that meets the preset quality requirements; Feature values ​​are extracted from respiratory signals and nasal pulse wave signals that meet preset quality requirements, and physiological parameters are calculated.

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