A wireless real-time respiratory monitoring method based on RFID

Abstract

The present invention relates to a wireless real-time respiratory monitoring method based on RFID, which includes judging fever according to the average respiratory temperature of the respiratory temperature array, judging cough according to the peak size comparison of the respiratory temperature array, judging respiratory arrest according to the continuous temperature average comparison within a certain period of time of the respiratory temperature array, judging respiratory failure according to the difference between the peak and trough data of the respiratory temperature array, and judging shortness of breath according to the respiratory frequency data and the reference value calculated by the FFT algorithm. The present invention realizes real-time monitoring and display of the respiratory status of individuals and groups, and timely understands the health status through respiratory data.

Description

Technical Field

[0001] The present invention relates to the technical field of respiratory monitoring, and in particular to a wireless real-time respiratory monitoring method based on RFID. Background Art

[0002] In the prevention and control of highly contagious respiratory diseases, whether it is patients or healthy people, how to conduct real-time inspection and monitoring of the body temperature, breathing and other health conditions of various types of people is a difficult problem faced in epidemic prevention and control. During the epidemic, the most commonly used temperature measurement method for mobile personnel was infrared thermometers, which mainly measured the surface temperature of the human body. It was inefficient and easily affected by the ambient temperature and the temperature measurement distance, resulting in low reliability. In addition, before a major respiratory highly contagious epidemic, the respiratory health control and recording of community residents, employees returning to work and production in enterprises, school students or individuals consumed a lot of manpower and material resources.

[0003] In recent years, with the rapid development of Internet of Things technology, some devices and methods have been proposed for personal respiratory health monitoring. The existing wireless respiratory temperature detection methods mainly use temperature sensors and NFC near-field communication, among which: NFC near-field communication distance is often within 30 cm to read, and it is impossible to monitor the respiratory status of people in normal activities in real time, and it is impossible to monitor multiple people at the same time. In addition, the existing NFC approaching communication method only records the temperature of short-term breathing, does not extract and analyze respiratory characteristics such as respiratory rate, cough, respiratory arrest, respiratory failure, etc., does not have an abnormal reminder function, and is mainly an alternative to the existing thermometer temperature measurement method. In addition, the method of monitoring breathing based on the active circuit of the temperature sensor requires the integration of a rechargeable power supply, a microprocessor circuit, a data communication circuit, etc., which increases the burden of wearing for personnel. In addition, the existing active temperature sensor respiratory monitoring method uses the peak and valley counting calculation of the respiratory temperature. When the collected temperature data fluctuates in a small range due to problems such as equipment accuracy, it will cause a large calculation error and obtain an incorrect respiratory frequency. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a wireless real-time respiratory monitoring method based on RFID, which reduces the influence of ambient temperature, is wireless and real-time, and is suitable for respiratory health monitoring and management of individuals and groups of people. By sensing the temperature changes caused by inhalation and exhalation through the mouth and nose, the average respiratory temperature, respiratory frequency, inhalation time, exhalation time and other respiratory parameters can be measured, and it can be judged whether there are abnormal respiratory conditions such as shortness of breath, high respiratory temperature, respiratory failure, respiratory arrest, etc.

[0005] The purpose of the present invention is achieved through the following technical solutions: a wireless real-time respiratory monitoring method based on RFID, which collects human respiratory temperature data by fixing a temperature measuring RFID tag at the intersection of human mouth and nose (the temperature measuring RFID tag is made of flexible material and can be attached to objects including but not limited to helmets, masks, etc.). The temperature data is returned by the radio frequency signal and temperature measurement instruction sent by the ultra-high frequency radio frequency reader and writer, and the algorithm is designed in the application system part, the respiratory waveform is displayed in real time, and the initial respiratory data is feature extracted; it includes the following steps:

[0006] The application system software sends a temperature measurement start instruction which is transmitted to the RF reader device via the RS232 serial port line or the network port. The cyclic reading interval is 0.5S (which can be adjusted according to the accuracy requirements).

[0007] After the radio frequency reader device obtains the temperature measurement instruction, it transmits a radio frequency signal with the temperature measurement instruction to the temperature measurement RFID tag through a high-gain circularly polarized reader antenna.

[0008] Temperature measuring RFID tags can use two modes: passive and semi-passive. In passive mode, when the temperature measuring RFID tag is within the effective reading range, the energy generated by the radio frequency electromagnetic waves emitted by the reader on the temperature measuring RFID tag can drive the chip to complete decoding, analysis, reading temperature circuit data, encoding and reverse modulation, etc. No battery is required, and the distance is usually about 5 meters. In semi-passive mode, the temperature measuring RFID tag still uses reflection modulation to respond, but uses a 1.6V thin film battery to power the receiving or temperature sensing circuit, so the reading distance is farther than the passive mode, about 35 meters.

[0009] The RFID temperature tag is a passive tag, which is triggered by the radio frequency reader. The communication protocol between the temperature measuring RFID tag and the radio frequency reader can use ISO / IEC18000-6 (860MHz-960MH), ISO / IEC18000-4 (2.45GHz / 5.8GHz), ISO / IEC18000-7 (433MHz), EPC Class1 Gen2 and other RFID communication protocol standards. The temperature measuring chip is located on the RFID temperature tag. The chip has a unique electronic code, and the personnel identification information can be read and written through the inquiry command of the radio frequency reader.

[0010] The radio frequency reader device transmits temperature and tag number reading instructions at a certain interval (the cyclic reading interval can be set according to actual application requirements). After receiving the instruction, the temperature measuring RFID tag immediately reads the current breathing temperature and tag number and returns them to the radio frequency reader device, usually within 0.5S.

[0011] The application system cyclically receives the temperature data returned by the corresponding temperature measuring RFID tag at a set interval (t=0.5s interval is usually used), and the data corresponds to the tag number one by one.

[0012] After obtaining the temperature data, the application system can draw a real-time breathing temperature curve, with the horizontal axis increasing at 0.5 second intervals and the vertical axis being the temperature value in °C. When acquiring data from multiple temperature-measuring RFID tags at the same time, real-time breathing temperature curves are drawn separately according to different tag numbers, and the temperature data read by different temperature-measuring RFID tags do not affect each other.

[0013] While drawing the real-time breathing waveform, the application system software stores the breathing temperature into an array. The sampling frequency is the inverse of the temperature measurement interval of the RF reader, that is, f is the sampling frequency. When the sampling interval is 0.5s, the sampling frequency is 2Hz, and the human breathing frequency is 0.2 to 0.5 times per second, that is, 0.2Hz to 0.5Hz. The specific sampling interval and frequency can be adjusted according to the specific application needs.

[0014] According to the accuracy requirements, the Fast Fourier Transform (FFT) algorithm can be used for respiratory data of any time length, such as 10 seconds, 30 seconds, and 60 seconds. The Discrete Fourier Transform (DFT) algorithm has a large amount of calculation, and N-point DFT transformation requires N 2 The time-decimated radix-2 FFT algorithm only requires The amount of calculation is reduced, and the influence of high-order harmonics caused by measurement errors is eliminated, so that the respiratory frequency data in the corresponding time frequency band can be obtained quickly and accurately.

[0015] While calculating the respiratory rate, the collected temperature data is averaged, that is, the temperature At the same time, the algorithm sets the maximum and minimum temperature limits (30℃-37℃) to filter out abnormal temperature data caused by transmission errors and collection errors.

[0016] When drawing the respiratory waveform, collect the corresponding respiratory graphics and data of cough, shortness of breath, respiratory arrest, and respiratory failure, and extract the corresponding respiratory features. For example, the respiratory temperature data of cough will rise briefly and then drop. You can set the maximum temperature threshold within a short time, such as 1 second. For example, judge the respiratory temperature data stored at 0.5 second intervals: array temperature[t1, t2, ..., t n ], traverse and calculate the average data within 1 second such as (t1+t2) / 2, (t2+t3) / 2, ..., (t n-1 +t n) / 2, if it is greater than the average respiratory temperature by more than 0.3°, it is considered suspected coughing once;

[0017] In case of respiratory arrest, the respiratory temperature will continue to drop. The average temperature within 3 seconds is calculated by traversing, such as (t1+t2+t3+t4+t5+t6) / 6, (t4+t5+t6+t7+t8+t9) / 6, ..., (t n-5 +t n-4 +t n-3 +t n-2 +t n-1 +t n ) / 6, if the breathing temperature is less than 1.5° one minute ago, it is judged that respiratory arrest is suspected or the temperature measurement RFID tag is not placed at the intersection of the mouth and nose;

[0018] When respiratory failure occurs, the difference between the respiratory peak and trough data is smaller than that in normal situations. For example, first extract the peak data. If (t m-1 <t m , t m >t m+1 ){t p [i] = t m}, t p The array is the peak data, where i is the array number starting from 0, and m is a number greater than 1 and less than n;

[0019] If (t m-1 >t m <t m+1 ){t v [i] = t m}, t v The array is the trough data. p [i] and t v When the difference between [i] is less than 0.5 times of the preset reference peak and trough difference, suspected respiratory failure is judged;

[0020] Respiratory characteristic data such as average respiratory temperature, respiratory rate, inhalation duration, exhalation duration and other respiratory parameters, as well as whether there are abnormal respiratory conditions such as shortness of breath, high respiratory temperature, respiratory failure, respiratory arrest, etc. can be saved in the local system or uploaded to the cloud server to achieve visual management of the respiratory health of individuals or groups of people.

[0021] The beneficial effects of the present invention are: by continuously collecting the temperature measuring RFID tags fixed at the intersection of the mouth and nose at a certain interval (0.1s-0.5s) to extract the initial breathing temperature data of the personnel, the real-time dynamic breathing waveform can be displayed in combination with the radio frequency reader and the application software, and the user's average breathing temperature, breathing frequency and other breathing parameters can be given, and the presence of respiratory failure, respiratory arrest, shortness of breath, asthma cough and other abnormal breathing conditions can be judged in combination with the preset reference value, thereby realizing the real-time monitoring and display of the breathing conditions of individuals and groups, and facilitating people to understand the health status in time through the breathing condition information. In addition, the extracted key breathing feature data can be saved in the local system or uploaded to the cloud server to realize the respiratory health management of individuals or groups of people. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a flow chart of the method of the present invention;

[0023] Figure 2 It is the overall system structure diagram of the present invention;

[0024] Figure 3 is a breathing waveform of a normal breathing condition in the embodiment;

[0025] Figure 4 For Figure 3 The respiratory waveform is calculated by the FFT algorithm of the present invention to obtain the respiratory frequency;

[0026] Figure 5 is a respiratory waveform diagram of the rapid breathing situation in the embodiment;

[0027] Figure 6 It is a respiratory waveform diagram of the coughing and breathing situation in the embodiment;

[0028] Figure 7 is a respiratory waveform diagram of respiratory failure in this embodiment;

[0029] Figure 8 is a respiratory waveform diagram of a respiratory arrest in this embodiment;

[0030] Fig. 9 This is an example diagram of simultaneous detection of respiratory health conditions of multiple persons in this embodiment;

[0031] In the figure, 201 is a computer, 202 is a router, 203 is a radio frequency reader, 204 is a reader / writer antenna, and 205 is an RFID tag. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of protection of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application. The present invention is further described below in conjunction with the drawings.

[0033] like Figure 1 As shown, a wireless real-time respiratory monitoring method based on RFID technology according to an embodiment of the present invention is shown. The method of the present invention comprises:

[0034] S1. After starting the temperature measurement, the control software will cyclically send out temperature measurement instructions at a certain interval (adjustable from 0.1 seconds to 1 second according to actual application requirements);

[0035] S2, after receiving the instruction, the RF reader transmits the temperature measurement instruction to the circularly polarized antenna through the RF line and emits the RF signal;

[0036] S3, according to the different working modes of the temperature measuring RFID tags actually used, step S3 receives the radio frequency signal described in step S2 based on the passive and semi-passive temperature measuring RFID tags respectively;

[0037] S4, determine whether the temperature measurement RFID tag is within the effective identification range, if not, return to step S2 to prepare to receive the next temperature measurement instruction, if the identification is valid, proceed to the next step;

[0038] S5. After receiving enough RF signal energy and corresponding temperature measurement instructions, the temperature measurement RFID chip completes the functions of decoding, parsing, collecting temperature sensor circuit data, encoding and reverse modulation, and returns the RF signal with temperature and tag data;

[0039] S6. The valid data returned by step S5 is received by the radio frequency reader device and transmitted to the application system software through R232 or network port, etc., and the temperature and tag data obtained during the temperature measurement instruction cycle are displayed in real time, and then the real-time display of the breathing waveform and the storage of the breathing data are realized.

[0040] S7. After step S6, the RFID system software can process the received temperature data through the algorithm of the present invention to extract key respiratory characteristic data such as respiratory rate, average respiratory temperature, asthma cough, respiratory failure, respiratory arrest, etc., and issue abnormal reminders.

[0041] In the embodiment of the present invention, the number of passive temperature measurement RFID tags and semi-passive temperature measurement RFID tags is greater than or equal to 1, and tags in two modes can work simultaneously without affecting each other.

[0042] It should be noted that in the embodiment of the present invention, the temperature measurement period can be adjusted according to the needs of the actual application scenario, and the embodiment of the present invention is based on UHF RFID technology. The distance that the system can identify is usually 1-3 meters in the passive mode of the temperature measurement tag and usually 10-30 meters in the semi-passive mode.

[0043] Figure 2 This is a block diagram of the RFID system structure according to an exemplary embodiment. A computer 201 is connected to a wifi local area network. The LAN port of a router 202 is connected to a radio frequency reader 203 via a network cable. The radio frequency reader 203 is connected to a high-gain circularly polarized reader antenna 204 via a radio frequency line. A temperature measuring RFID tag 205 is placed at the intersection of the user's mouth and nose. It should be noted that the temperature measuring RFID tag 205 is not fixed in a unique manner. For example, masks, face shields, helmets, etc. can all fix the temperature measuring RFID tag 205 at the intersection of the mouth and nose.

[0044] Figure 3 According to a breathing waveform diagram shown in an exemplary embodiment, the temperature measuring RFID tag 205 is placed in a position where the actual breathing gas temperature flowing through the mouth and nose can be measured. After the detection starts, the application system outputs the monitoring data of the user's normal breathing when sitting. Calculated as one inhalation and one exhalation as one breath, the user took 20 breaths in 1 minute, the breathing frequency was about 20 times / minute, the average breathing temperature was 33.71℃, the breathing was normal, and the exhalation to inhalation time ratio was about 1:1 to 2:1.

[0045] Figure 4 is a diagram showing a respiratory frequency calculation result according to an exemplary embodiment. Figure 3 After the respiratory data shown is stored in the array, it is calculated by the FFT calculation formula to obtain the amplitude of the corresponding frequency domain. The maximum amplitude corresponds to the number of breaths of the user in one minute calculated by FFT. It should be noted that the value initially calculated by the FFT algorithm is the number of breaths per second, and the result shown in the present invention is the number of breaths in 1 minute.

[0046] It should be noted that the implementation formula of the FFT algorithm to calculate the respiratory frequency is as follows: Assume that the limited-length respiratory data array is t[n], n = 0, 1, ..., N-1, and the Fourier transform is: frequency domain amplitude k=0,1,…,N-1, t(n)=t1(n)+t2(n), where the lengths of t1(n) and t2(n) are both N / 2, t1(n) is an even sequence, and t2(n) is an odd sequence, then: (k=0,1,…,N-1), due to but have This is the butterfly operation. Finally, the N-point DFT is decomposed into N / 2 two-point DFTs. The complexity is The value corresponding to point k with the largest amplitude of frequency domain T(k) is the number of respirations per second.

[0047] Figure 5 This is a waveform diagram of shortness of breath according to an exemplary embodiment. The average breathing temperature is 34.35°C. After calculation by the FFT formula, the breathing frequency is 33 times, which is greater than the preset threshold (34°C, 30 times per minute, which is not fixed and can be adjusted according to geographical location and season). Then an abnormal breathing reminder is issued, as shown in red on the right side of the figure.

[0048] Figure 6 is a waveform diagram of coughing during breathing according to an exemplary embodiment. The average breathing temperature is 33.06°C, and the breathing frequency is 21 times, which is less than the preset threshold. According to the cough statistics algorithm, the array temperature[t1, t2, ..., t n ], traverse and calculate the average data within 1 second such as (t1+t2) / 2, (t2+t3) / 2, ..., (t n-1 +t n ) / 2, if it is greater than the average respiratory temperature by more than 0.3°, it is judged as one suspected cough, as indicated by the red circle in the figure, and finally it is judged as four suspected coughs.

[0049] Figure 7 The waveform diagram of respiratory failure shown in the embodiment of the present invention is as follows: extract the peak data, if (t m-1 <t m , t m >t m+1 ){t p [i] = t m},t p The array is the peak data, where i is the array number starting from 0, and m is a number greater than 1 and less than n. m-1 >t m <t m+1 ){t v [i] = t m},t v The array is the trough data. p [i] and t vWhen the difference between [i] is less than 0.5 times the difference between the peak and trough of the previous minute, it is judged as suspected respiratory failure, as shown by the red circle in the figure.

[0050] Figure 8 The waveform diagram of respiratory arrest shown in the embodiment of the present invention, the corresponding algorithm, traverses and calculates the average temperature within 3 seconds such as: (t1+t2+t3+t4+t5+t6) / 6, (t4+t5+t6+t7+t8+t9) / 6, ..., (t n-5 +t n-4 +t n-3 +t n-2 +t n-1 +t n ) / 6, if the breathing temperature is less than 1.5°C one minute ago, it is judged that respiratory arrest is suspected or the temperature measurement RFID tag is not placed at the intersection of the mouth, nose and breathing, as shown in the red circle in the figure.

[0051] Fig. 9 This is an example diagram of simultaneous monitoring of the respiratory health status of multiple people shown in an embodiment of the present invention. Finally, each person's respiratory characteristic data, such as average respiratory temperature, respiratory rate, inhalation time, exhalation time and other respiratory parameters, as well as whether there are abnormal respiratory conditions such as shortness of breath, high respiratory temperature, respiratory failure, respiratory arrest, etc., can be saved in the local system or uploaded to the cloud server to achieve visual management of the respiratory health of individuals or groups of people.

[0052] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A wireless real-time respiratory monitoring method based on RFID, characterized in that: The respiratory monitoring method uses an RFID temperature measurement chip to monitor a person's respiratory temperature. The RFID system software extracts respiratory characteristic data from a respiratory temperature array, and determines whether a fever occurs according to the average respiratory temperature of the respiratory temperature array, determines whether a cough occurs according to the peak of the respiratory temperature array, determines whether a respiratory arrest occurs according to a continuous temperature average comparison within a certain period of time of the respiratory temperature array, determines whether respiratory failure occurs according to the difference between the peak and trough data of the respiratory temperature array, and determines whether shortness of breath occurs according to the respiratory frequency data and the reference value calculated by the FFT algorithm; Judging whether a cough occurs according to the peak size of the respiratory temperature array includes: preliminarily processing the respiratory temperature array to extract the peak and store it in a new array, and traversing and calculating the difference between each new array element and its previous digit, next digit and next digit, if the difference between the temperature of a certain element and its previous digit, next digit and next digit is greater than a first preset temperature range, it is judged as a cough; Determining whether respiratory arrest occurs based on calculating the respiratory temperature array includes: dividing the respiratory temperature array into multiple sub-arrays at a first fixed time interval, and traversing and calculating the average respiratory temperature of each sub-array; if the average respiratory temperature of a sub-array is less than a second preset temperature range of the respiratory temperature in the previous time interval, it is determined to be respiratory arrest.

2. The wireless real-time respiratory monitoring method based on RFID according to claim 1, characterized in that: The respiratory monitoring method further includes sending a temperature measurement instruction to a temperature measurement RFID tag, and after cyclically reading the respiratory temperature data at a set time interval, sending the collected data and the tag number of the RFID tag to the background.

3. The wireless real-time respiratory monitoring method based on RFID according to claim 2, characterized in that: The respiratory monitoring method also includes the background matching the received data with the tag number one by one, drawing a respiratory temperature curve according to the respiratory temperature data, updating the respiratory temperature curve according to subsequent data sent by the RFID tag with the tag number, and storing the respiratory temperature data in an array.

4. The wireless real-time respiratory monitoring method based on RFID according to claim 3, characterized in that: The respiratory monitoring method further includes calculating the respiratory frequency of each respiratory temperature array data by a fast Fourier transform algorithm, which includes: Suppose the limited-length breathing temperature array is t[n], n=0, 1, ..., N-1, and its Fourier transform is: frequency domain amplitude t(n)=t1(n)+t2(n), where the lengths of t1(n) and t2(n) are both N / 2, t1(n) is an even sequence, and t2(n) is an odd sequence, then we have because but have The N-point DFT is decomposed into N / 2 two-point DFTs through butterfly operation, and the complexity is The value corresponding to the point k with the largest amplitude of frequency domain T(k) is the number of respirations per second, and then the number of respirations per minute is estimated. If it is greater than the preset reference value, it is judged as suspected shortness of breath.

5. The RFID-based wireless real-time respiratory monitoring method according to claim 4, characterized in that: The respiratory monitoring method further includes calculating the respiratory frequency while averaging the collected respiratory temperature data, i.e., the temperature At the same time, the algorithm sets the maximum and minimum temperature values ​​to filter out abnormal temperature data caused by transmission errors and collection errors.

Images