Non-contact apnea detection method and system

Abstract

An embodiment of the present invention discloses a non-contact apnea detection method and system; the system may include: a respiratory signal acquisition part and a respiratory signal processing part; wherein the respiratory signal acquisition part is configured to acquire a respiratory signal of a detection object based on a radar reflection signal, and transmit the acquired respiratory signal to the respiratory signal processing part via a wireless transmission link; the respiratory signal processing part is configured to analyze the respiratory state of the detection object based on the received respiratory signal; and provide a prompt when the respiratory state of the detection object is abnormal.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of medical detection technology, and in particular to a non-contact apnea detection method and system. Background Art

[0002] Sleep apnea syndrome (SAS) is a common sleep disorder, primarily caused by upper airway obstruction. It carries numerous complications, including hypertension, arrhythmias, cardiovascular and cerebrovascular disease, and respiratory failure. This condition can lead to sleep impairment, reduced work efficiency, and decreased memory and reaction time, leading to an increased risk of accidents. Apnea poses a serious threat to human health, making apnea detection and remote monitoring solutions essential.

[0003] Currently, conventional sleep apnea detection methods mostly rely on restraining wearable devices, such as polysomnography (PSG) and ventilators, to collect and analyze the patient's respiratory signals. These methods require relatively expensive equipment and labor, and the contact-based respiratory signal collection imposes a restraining effect on the patient, affecting sleep quality and reducing test accuracy. Summary of the Invention

[0004] In view of this, embodiments of the present invention aim to provide a non-contact apnea detection method and system; capable of real-time non-contact acquisition of the respiratory signal of the detection subject and wireless transmission, realizing real-time and non-contact remote monitoring, apnea warning and respiratory status recording, improving detection efficiency and accuracy, and improving the comfort of the detection subject.

[0005] The technical solution of the embodiment of the present invention is achieved as follows:

[0006] In a first aspect, an embodiment of the present invention provides a non-contact apnea detection system, the system comprising: a respiratory signal acquisition part and a respiratory signal processing part; wherein,

[0007] The respiratory signal acquisition part is configured to acquire the respiratory signal of the detection object based on the radar reflection signal, and transmit the acquired respiratory signal to the respiratory signal processing part via a wireless transmission link;

[0008] The respiratory signal processing section is configured to analyze the respiratory state of the detection subject based on the received respiratory signal; and to provide a prompt when the respiratory state of the detection subject is abnormal.

[0009] In a second aspect, an embodiment of the present invention provides a non-contact apnea detection method, which is applied to the non-contact apnea detection system described in the first aspect, and the method includes:

[0010] The respiratory signal acquisition part acquires the respiratory signal of the detection object based on the radar reflection signal, and transmits the acquired respiratory signal to the respiratory signal processing part through a wireless transmission link;

[0011] analyzing the respiratory state of the subject based on the received respiratory signal by a respiratory signal processing part;

[0012] When the breathing state of the detected object is abnormal, the breathing signal processing part gives a prompt.

[0013] Embodiments of the present invention provide a non-contact apnea detection method and system. The respiratory signal acquisition portion uses radar reflection signals to perform real-time, non-contact acquisition and wireless transmission of the respiratory signal of a detection subject, such as a patient lying in a hospital bed or a patient being detected. The respiratory signal processing portion implements real-time, non-contact remote monitoring and respiratory abnormality prompts, thereby improving detection efficiency and accuracy while also enhancing the comfort of the detection subject. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic diagram of the composition of a non-contact apnea detection system provided by an embodiment of the present invention;

[0015] Figure 2 A schematic diagram of the composition of the respiratory signal acquisition part provided in an embodiment of the present invention;

[0016] Figure 3 A schematic diagram of the composition of a respiratory signal processing part provided in an embodiment of the present invention;

[0017] Figure 4 A schematic diagram of the process of configuring a LoRa module according to an embodiment of the present invention;

[0018] Figure 5 A schematic diagram of the printing result after the LoRa module configuration is completed according to an embodiment of the present invention;

[0019] Figure 6 A schematic diagram of a respiratory waveform of a human body in a normal breathing state provided by an embodiment of the present invention;

[0020] Figure 7 A schematic diagram of a respiratory waveform of a human body in a state of apnea provided by an embodiment of the present invention;

[0021] Figure 8 A schematic diagram of the working process of a non-contact apnea detection system provided in an embodiment of the present invention;

[0022] Figure 9 A schematic diagram of a specific implementation structure of a respiratory signal acquisition terminal provided by an embodiment of the present invention;

[0023] Figure 10 A schematic diagram of a specific implementation structure of a receiving and processing terminal provided by an embodiment of the present invention;

[0024] Figure 11 A schematic diagram of recording data provided by an embodiment of the present invention;

[0025] Figure 12 Another schematic diagram of recording data provided by an embodiment of the present invention;

[0026] Figure 13 A flow chart of a non-contact apnea detection method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0028] See also Figure 1 , which shows a non-contact apnea detection system 1 provided by an embodiment of the present invention. The system 1 may include: a respiratory signal acquisition part 11 and a respiratory signal processing part 12; wherein,

[0029] The respiratory signal collecting part 11 is configured to collect the respiratory signal of the detection object based on the radar reflection signal, and transmit the collected respiratory signal to the respiratory signal processing part 12 via the wireless transmission link 13;

[0030] The respiratory signal processing section 12 is configured to analyze the respiratory state of the detection subject based on the received respiratory signal; and to provide a prompt when the respiratory state of the detection subject is abnormal.

[0031] exist Figure 1 In the system 1 shown, the respiratory signal acquisition part 11 uses radar reflection signals to collect and wirelessly transmit the respiratory signals of the detection object, such as a patient lying on a hospital bed or a patient being detected, in real time and contactlessly. The respiratory signal processing part 12 realizes real-time and contactless remote monitoring and respiratory abnormality prompts, thereby improving detection efficiency and accuracy, while also improving the comfort of the detection object.

[0032] In some possible implementations, the wireless transmission link 13 is preferably a Long Range (LoRa) wireless communication link.

[0033] In some examples, such as Figure 2 As shown, the respiratory signal acquisition part 11 includes a bioradar sensor 111, a first main control module 112 and a sending module 113; wherein,

[0034] The bioradar sensor 111 is configured to collect the breathing signal of the detection object based on the radar reflection signal within the sensing range covered by the bioradar sensor 111, and transmit the breathing signal of the detection object to the first main control module 112;

[0035] The first main control module 112 is configured to convert the breathing signal of the detected object into a digital signal through an analog-to-digital converter (ADC);

[0036] The sending module 113 is configured to send the digital breathing signal of the detected subject to the wireless transmission link 13 using a communication protocol that complies with the wireless transmission link 13 .

[0037] for Figure 2 The respiratory signal acquisition section 11 shown, for example, preferably comprises a bioradar sensor 111 of model JC122-3.3UA6, configured to transmit an asymmetric wide-beam signal; acquire the echo signal generated by the chest cavity reflecting the transmitted signal during normal breathing; and amplify and filter the acquired echo signal to obtain the desired respiratory signal of the subject. Furthermore, the bioradar sensor 111 possesses extremely sensitive sensing capabilities, covering a horizontal angle range of -40° to +40°; a vertical angle range of -16° to +16°; and an axial distance equivalent to the chest cavity expansion amplitude of less than 6 meters. Furthermore, the bioradar sensor 111 is compact, low-power, and suitable for battery-powered environments, meeting the requirements for small size and low power consumption of hardware devices.

[0038] Continuing with the above example, the first main control module 112 can be implemented using the main control chip STM32F103C8T6, which is a 32-bit microcontroller based on the ARM Cortex-M core STM32 series. The program memory capacity is 64KB. The chip integrates internal resources and peripheral interfaces such as timer, controller area network (CAN), analog-to-digital converter (ADC), serial peripheral interface (SPI), two-wire synchronous serial bus (I2C, Inter-Integrated Circuit), universal serial bus (USB, Universal Serial Bus), and universal asynchronous receiver / transmitter (UART); C language programming is implemented by using the development tool KEIL and downloaded to the first main control module 112 to complete the conversion of the analog breathing signal collected by the bioradar sensor 111 into a digital signal and the configuration of LoRa communication for the sending module 113.

[0039] Continuing with the above example, when the first main control module 112 converts the analog breathing signal collected by the bioradar sensor 111 into a digital signal, the ADC conversion value can be limited to a set numerical range. Specifically, the breathing signal of the detected object can be converted into the corresponding breathing data BR according to the following formula:

[0040] BR=LSB*(ADC_ConvertedValue) / 0.033

[0041] Wherein, LSB represents the minimum quantization unit of analog-to-digital conversion, and ADC_ConvertedValue represents the value after ADC is performed on the respiratory signal.

[0042] By calculating the above formula, a set of respiratory data BR with values ranging from 0 to 100 can be obtained. This data can be plotted as a waveform in real time in the respiratory signal processing part using the software Serialchart to facilitate observation of changes in the respiratory signal of the test subject.

[0043] For some examples, see Figure 3 The respiratory signal processing part 12 may include: a receiving module 121, a second main control module 122 and a reminder device 123; wherein,

[0044] The receiving module 121 is configured to receive the digital breathing signal of the detected subject from the wireless transmission link 13 using a communication protocol that complies with the wireless transmission link 13;

[0045] The second main control module 122 is configured to transmit the received digital respiratory signal to the reminder device via serial communication;

[0046] The reminder device 123 is configured to analyze the respiratory state of the detection subject based on the digital respiratory signal received by the serial communication; and send a reminder signal in response to the respiratory state of the detection subject meeting the set abnormal state criterion.

[0047] for Figure 3 As shown, the receiving module 121 can communicate with the sending module 113 using LoRa. The second main control module 122 also needs to configure the receiving module 121 for LoRa communication. Combined with the above description, the second main control module 122 can also be implemented using the main control chip STM32F103C8T6.

[0048] It should be noted that the working mode of LoRa is point-to-point transparent transmission, that is, the data is completely transparent, and the information of the sending end and the receiving end is exactly the same. Therefore, it is necessary to configure the receiving module 121 as the LoRa receiving end and the sending module 113 as the LoRa sending end to the same communication address, channel and rate through AT commands. Therefore, the configuration process of the LoRa communication protocol by the first main control module 112 for the sending module 113 and the second main control module 122 for the receiving module 121 can be as follows: Figure 4 As shown. Since both the sending module 113 and the receiving module 121 adopt LoRa communication, the sending module 113 and the receiving module 121 are Figure 4 They can be collectively referred to as LoRa modules, see Figure 4, the process may include: S41: the main control chip detects the LoRa module. S42: Determine whether the detection is successful: if the detection fails, return to S41 to continue the detection; if the detection is successful, turn to S43: set the address for the LoRa module; then execute S44: determine whether the LoRa module detection address setting is successful; if the detection fails, return to S41 to continue the detection; if the detection is successful, turn to S45: set the channel and rate for the LoRa module; then execute S46: determine whether the LoRa module detection channel and rate setting are successful; if the detection fails, return to S41 to continue the detection; if the detection is successful, turn to S47: set the working mode, baud rate and data check bit of the LoRa module. When the above settings are completed, it is S48: the LoRa module is set successfully. In addition, after the LoRa module is set successfully, the serial port will print the configuration information and initialization information. The print results are as follows: Figure 5 As shown, if the LoRa module also has an LED with a reminder function, the corresponding LED will flash twice and then go out after the setting is successful.

[0049] For the above Figure 3 In the example shown, preferably, the reminder device 123 is configured to:

[0050] When the breathing state of the detected subject is apnea, the number of apnea episodes and the duration of the current apnea are recorded;

[0051] In response to the duration of the apnea exceeding a set duration threshold or the number of apnea occurrences exceeding a set number threshold, an alarm signal is issued.

[0052] For the above preferred example, specifically, the respiratory waveform can be observed by a pre-set simulation experiment for the apnea state, combined with Figure 6 as well as Figure 7 As shown in Figure 2, we can draw the following conclusions: Under normal breathing conditions, the respiratory waveform of the human body changes regularly, such as Figure 6 As shown in the figure, when the human body pauses breathing, the breathing waveform in the pause stage is a relatively stable waveform, as shown in the figure. Figure 7 Based on this, the changes in the respiratory waveform can be observed to achieve long-distance, non-contact, and real-time monitoring of the subject's respiratory status.

[0053] Based on the above simulation experiments, a control experiment was designed. The experimental group was divided into four groups, with two simulations each for post-inspiratory apnea and post-expiratory apnea. The control group was divided into four groups, with four simulations for shallow breathing, slow breathing, rapid breathing, and deep breathing. This simulated the respiratory states of different populations and increased experimental reliability. A comprehensive analysis of the differences between apnea and normal breathing was conducted. The respiratory rate (BR) values for different types of normal breathing and apnea cycles were recorded, as shown in Table 1. Based on Table 1, an analysis was conducted to examine central tendency and dispersion.

[0054] Table 1

[0055]

[0056] Based on the data in Table 1, the average values and standard deviations of the respiratory values (BR) of multiple groups of experiments within one cycle were calculated, as shown in Table 2:

[0057] Table 2

[0058]

[0059] From the data processing results in Table 2, we can conclude that the standard deviation of the apneic breathing data is less than 30, which is not very significant compared to normal breathing. Because bioradar detects human breathing signals by detecting the vibrations generated by the chest cavity during breathing, and different people have different breathing habits, the above method is not very effective in distinguishing normal breathing from apnea.

[0060] The above experiments provide the following insight: within a single cycle, the range of the normal breathing group is always much greater than that of the apnea group, thus establishing the threshold BS for distinguishing normal breathing from apnea. A microcontroller program periodically stores the respiratory data BR corresponding to the digital respiratory signal in an array, where the difference between the maximum and minimum values, BN, is calculated. When this value, BN, is less than BS, apnea is determined, and the number of apneas and the duration of each apnea are recorded. If the subject experiences prolonged or frequent apnea, the reminder device 123 can trigger a buzzer to sound an emergency alarm, prompting medical personnel to promptly check on the subject's condition.

[0061] Preferably, the reminder device 123 is further configured to use a set visualization scheme to perform visualization processing on the digital respiratory signal received by the serial communication to obtain a waveform corresponding to the respiratory signal of the detection object.

[0062] For the above preferred examples, specifically, the reminder device 123 can be a terminal device that can realize data transmission and information processing, which can be specifically a medical station device, a wireless device, a mobile or cellular phone (including a so-called smart phone), a personal digital assistant (PDA), a video game console (including a video display, a mobile video game device, a mobile video conferencing unit), a laptop computer, a desktop computer, a TV set-top box, a tablet computing device, an e-book reader, a fixed or mobile media player, etc.

[0063] In addition, there are many solutions for serial port data visualization, such as using the SerialChart serial port tool, calling Python's yecharts and matplotlib tool libraries, and using LabVIEW to create a serial port oscilloscope. The embodiment of the present invention preferably uses SerialChart serial port waveform display software, which can be configured through text for user-defined waveform colors, waveform channels, waveform display window background colors, etc. In addition, parameters such as the port number, baud rate, and the size range of received data can also be configured. SerialChart is used to plot the serial port data transmitted by the second main control module 122 into a waveform graph in real time to achieve real-time feedback, thereby better reflecting the respiratory status of the detected subject and effectively improving the monitoring efficiency of medical staff.

[0064] Based on the system 1 described above, in the specific implementation process, its workflow is as follows Figure 8 As shown, this may include:

[0065] S81: The bioradar sensor 111 collects a breathing signal of the detection object;

[0066] S82: The main control chip STM32F103C8T6 of the first main control module 112 performs AD conversion on the breathing signal of the detection object to obtain the digital breathing signal of the detection object and converts it into corresponding breathing data BR;

[0067] S83: The main control chip STM32F103C8T6 of the first main control module 112 transmits the breathing data BR of the detected object to the sending module 113 as the LoRa sending end through the serial port communication;

[0068] S84: The sending module 113 transmits the breathing data BR of the detection object via the LoRa wireless link;

[0069] S85: The receiving module 121 serving as the LoRa receiving end receives the breathing data BR of the detected object and transmits it to the second main control module 122 via serial communication;

[0070] S86: The main control chip STM32F103C8T6 of the second main control module 122 obtains the range BN of the breathing data BR of the detection object within a period;

[0071] S87: The second main control module 122 compares the range BN with the threshold BS obtained in advance through experimental analysis for distinguishing normal breathing from apnea to determine whether the detection object has apnea; if BN > BS, go to S88: Determine that the breathing state of the detection object is normal and record the breathing data of the detection object; if BN < BS, determine that the detection object has apnea and continue to execute S89: Judge the duration of the apnea state; if there is a long-term apnea, go to S90 to trigger the buzzer alarm and draw the breathing waveform diagram in real time; if there is a short-term apnea, go to S91: Record the apnea data and draw the breathing waveform diagram in real time.

[0072] For Figure 8 the shown process, since it also involves the part of the threshold BS obtained in advance through experimental analysis for distinguishing normal breathing from apnea, therefore, as Figure 8 shown, it may further include: S80: Analyze the normal breathing value and the apnea value to obtain the threshold BS for distinguishing normal breathing from apnea; it can be understood that after obtaining the threshold BS, it can be provided to the second main control module 122 to execute the judgment step of step S87, which will not be elaborated in the embodiments of the present invention.

[0073] Regarding the applicability of the system 1 described above, the embodiments of the present invention are tested through the following scenarios:

[0074] The first item tests the effective detection distance of the detection object. Specifically, this test method is to remotely monitor the patient using the aforementioned system 1 and observe the real-time waveform diagram of the breathing signal received by the medical care station as a reminder device. When the patient has a long-term apnea, the system will use the buzzer to alarm to prompt the medical staff to check in time. After multiple tests, the conclusion is obtained: The waveform of the relatively regular part is the detected normal breathing signal of the human body, and the relatively flat and chaotic waveform is the detected apnea signal of the human body. Place the bio-radar sensor 111 at a position 1 m in front of the human chest for detection, and increase the distance by 0.5 m each time. After testing, the effective distance of the bio-radar sensor 111 for detecting the human breathing signal can reach more than 2 m.

[0075] The second item tests the maximum communication distance of the system 1. Specifically, since the system 1 uses the LoRa wireless transmission method for communication, after analyzing the test results of multiple groups in different environments, the conclusion is obtained: The maximum communication distance L of the system 1, that is, the maximum distance of the wireless transmission link 13, can reach more than 1 km. The steps for testing the communication distance are as follows:

[0076] First, in an open environment, the position of the respiratory signal acquisition part 11 is fixed, and the distance between the respiratory signal processing part 12 and the respiratory signal acquisition part 11 is changed. The set length is gradually increased, and the maximum LoRa communication distance L obtained by the test can reach 1.2km.

[0077] Next, in an environment with multiple buildings blocking the view, the position of the respiratory signal acquisition unit 11 was fixed, and the distance between the respiratory signal processing unit 12 and the respiratory signal acquisition unit 11 was changed. By gradually increasing the set length, the maximum LoRa communication distance L obtained by the test reached 1 km.

[0078] The third item is for apnea alarm test, in detail, Figure 9 As shown, the respiratory signal acquisition terminal used to implement respiratory signal acquisition section 11 can be composed of a bioradar sensor 111, an STM32 microcontroller as a first main control module 112, a LoRa module as a transmission module 113, and components such as a buzzer and a switch. The bioradar sensor collects human respiratory signals, which are converted into digital signals by the STM32 microcontroller through A / D conversion. Finally, the LoRa module transmits the respiratory signals over long distances and in real time to the receiving and processing terminal used to implement respiratory signal processing section 12.

[0079] like Figure 10 As shown, the receiving and processing end for implementing the respiratory signal processing part 12 can include an STM32 single-chip microcomputer as the second main control module 122, a LoRa module as the receiving module 121, and a buzzer as the reminder device 123. The LoRa module sends the received respiratory signal to the STM32 single-chip microcomputer through serial communication to judge the apnea, and promptly feeds back the patient's apnea situation through the buzzer. Based on the above-mentioned respiratory signal acquisition end and receiving and processing end, when performing the third test, the respiratory signal acquisition end is placed at a position 1.5m away from the chest cavity of the test object (such as the tester). The tester simulates 10 apneas each time and performs an alarm test experiment. As shown in Table 3, the actual number of alarms is recorded for verification statistics. The results show that the average accuracy rate can reach 94%, and it is concluded that this system has high reliability.

[0080] Table 3

[0081] Experiment number Simulated apnea times / times Number of detections / times Accuracy / % 1 10 9 90 2 10 10 100 3 10 9 90 4 10 9 90 5 10 10 100 6 10 9 90 7 10 8 80 8 10 10 100 9 10 10 100 10 10 10 100

[0082] For the third test above, the specific alarm test experiment is as follows: Figure 11The recorded data shown in the figure shows that: during the periodic apnea test, the subject is in a normal breathing state, and the system 1 will record the breathing data and prompt the normal breathing information (normal breath); when the subject simulates a short apnea and the system detects abnormal breathing data, the system will record the number of apnea times and the duration of each pause (pause time). When the subject is in a long-term abnormal breathing state, the system will activate the buzzer to alarm, such as Figure 12 The recorded data shown shows that when the subject's respiratory arrest time lasts for 15 seconds or more, the system will prompt an alarm message with the words "warning!!!!" and activate the buzzer to alarm, thereby counting the number of detections to determine reliability.

[0083] Based on the same inventive concept as the above technical solution, see Figure 13 , which shows a non-contact apnea detection method provided by an embodiment of the present invention. The method can be applied to the non-contact apnea detection system 1 described in the above technical solution. The method may include:

[0084] S1301: The respiratory signal collecting part collects the respiratory signal of the detection object based on the radar reflection signal, and transmits the collected respiratory signal to the respiratory signal processing part through a wireless transmission link;

[0085] S1302: Analyzing the respiratory state of the detection subject based on the received respiratory signal by the respiratory signal processing part;

[0086] S1303: When the breathing state of the detected object is abnormal, a prompt is given through the breathing signal processing part.

[0087] For the above solution, in some examples, the step of collecting the respiratory signal of the detected object based on the radar reflection signal by the respiratory signal collecting part in S1301 and transmitting the collected respiratory signal to the respiratory signal processing part via a wireless transmission link includes:

[0088] Using the bioradar sensor in the respiratory signal acquisition part to acquire the respiratory signal of the detection object based on the radar reflection signal within the sensing range covered by the bioradar sensor, and transmitting the respiratory signal of the detection object to the first main control module in the respiratory signal acquisition part;

[0089] Using the first main control module to convert the breathing signal of the detection object into a digital signal through analog-to-digital conversion ADC;

[0090] The digital respiratory signal of the detected object is sent to the wireless transmission link by a sending module in the respiratory signal acquisition part using a communication protocol that complies with the wireless transmission link.

[0091] Understandably, due to Figure 13 The technical solution and its examples shown belong to the same inventive concept as the non-contact apnea detection system 1 described in the aforementioned technical solution. Therefore, Figure 13 The technical solution and its examples shown are described in detail. For details, please refer to the relevant description of the technical solution of the non-contact apnea detection system 1 mentioned above, and the embodiments of the present invention are not described in detail here.

[0092] It can be understood that in this embodiment, "part" can be part of a circuit, part of a processor, part of a program or software, etc., and of course it can also be a unit, a module, or a non-modular one.

[0093] In addition, the components in this embodiment may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The above-mentioned integrated units may be implemented in the form of hardware or software functional modules.

[0094] If the integrated unit is implemented as a software functional module and not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, or the portion that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0095] Therefore, this embodiment provides a computer storage medium, which stores a non-contact apnea detection program. When the non-contact apnea detection program is executed by at least one processor, it implements the steps of the non-contact apnea detection method described in the above technical solution.

[0096] It should be noted that the technical solutions described in the embodiments of the present invention can be arbitrarily combined without conflict.

[0097] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A non-contact apnea detection system, characterized in that: The system includes: a respiratory signal acquisition part and a respiratory signal processing part; wherein, The respiratory signal acquisition part is configured to acquire the respiratory signal of the detection object based on the radar reflection signal, and transmit the acquired respiratory signal to the respiratory signal processing part via a wireless transmission link; The respiratory signal processing section is configured to analyze the respiratory state of the detection subject based on the received respiratory signal; and to provide a prompt when the respiratory state of the detection subject is abnormal; The respiratory signal acquisition part includes a bioradar sensor, a first main control module and a sending module; wherein, The bioradar sensor is configured to collect a breathing signal of the detection object based on a radar reflection signal within a sensing range covered by the bioradar sensor, and transmit the breathing signal of the detection object to the first main control module; The first main control module is configured to convert the breathing signal of the detected object into a digital breathing signal through an analog-to-digital converter (ADC), and convert the breathing signal of the detected object into corresponding breathing data BR according to the following formula: BR=LSB*(ADC_ConvertedValue) / 0.033 Wherein, LSB represents the minimum quantization unit of analog-to-digital conversion, and ADC_ConvertedValue represents the value after ADC is performed on the respiratory signal; The sending module is configured to send the digital respiratory signal of the detection object to the wireless transmission link using a communication protocol that complies with the wireless transmission link; The respiratory signal processing part is also configured to periodically store the respiratory data corresponding to the digital respiratory signal into an array through a single-chip computer program to calculate the difference between the maximum and minimum values. When the difference is less than a preset threshold, it is determined to be an apnea state.

2. The system according to claim 1, wherein: The bioradar sensor is configured to transmit an asymmetric wide beam signal; and when a normal person breathes, collects an echo signal generated by the chest cavity of the detection subject reflecting the transmitted signal; Furthermore, the collected echo signal is amplified and filtered to obtain an ideal breathing signal of the detection object.

3. The system according to claim 2, characterized in that The perception range parameters covered by the bioradar sensor include: horizontal angle range of -40° to +40°; vertical angle range of -16° to +16°; axial distance equivalent to the chest cavity expansion amplitude is less than 6m.

4. The system according to claim 1, wherein: The respiratory signal processing part includes: a receiving module, a second main control module and a reminder device; wherein, The receiving module is configured to receive the digital breathing signal of the detection subject from the wireless transmission link using a communication protocol that complies with the wireless transmission link; The second main control module is configured to transmit the received digital respiratory signal to the reminder device via serial communication; The reminder device is configured to analyze the respiratory state of the detection object based on the digital respiratory signal received by the serial communication; and send a reminder signal in response to the respiratory state of the detection object meeting the set abnormal state criterion.

5. The system according to claim 4, characterized in that The reminder device is configured as follows: When the breathing state of the detected subject is apnea, the number of apnea episodes and the duration of the current apnea are recorded; In response to the duration of the apnea exceeding a set duration threshold or the number of apnea occurrences exceeding a set number threshold, an alarm signal is issued.

6. The system according to claim 4, characterized in that The reminder device is further configured to use a set visualization scheme to perform visualization processing on the digital respiratory signal received by the serial communication to obtain a waveform corresponding to the respiratory signal of the detection object.

7. A non-contact apnea detection method, characterized in that: The method is applied to the non-contact apnea detection system according to any one of claims 1 to 6, and the method comprises: The respiratory signal acquisition part acquires the respiratory signal of the detection object based on the radar reflection signal, and transmits the acquired respiratory signal to the respiratory signal processing part through a wireless transmission link; analyzing the respiratory state of the subject based on the received respiratory signal by a respiratory signal processing part; When the breathing state of the detected subject is abnormal, a prompt is given by the breathing signal processing part; The respiratory signal collecting part collects the respiratory signal of the detection object based on the radar reflection signal, and transmits the collected respiratory signal to the respiratory signal processing part through a wireless transmission link, including: Using the bioradar sensor in the respiratory signal acquisition part to acquire the respiratory signal of the detection object based on the radar reflection signal within the sensing range covered by the bioradar sensor, and transmitting the respiratory signal of the detection object to the first main control module in the respiratory signal acquisition part; The first main control module is used to convert the breathing signal of the detection object into a digital breathing signal through analog-to-digital conversion ADC, and the breathing signal of the detection object is converted into corresponding breathing data BR according to the following formula: BR=LSB*(ADC_ConvertedValue) / 0.033 Wherein, LSB represents the minimum quantization unit of analog-to-digital conversion, and ADC_ConvertedValue represents the value after ADC is performed on the respiratory signal; The digital respiratory signal of the detected object is sent to the wireless transmission link by a sending module in the respiratory signal acquisition part using a communication protocol that complies with the wireless transmission link; The analyzing the respiratory state of the detection subject based on the received respiratory signal by the respiratory signal processing part includes: The respiratory data corresponding to the digital respiratory signal is periodically stored in an array through a single chip computer program to calculate the difference between the maximum value and the minimum value. When the difference is less than a preset threshold, it is determined to be an apnea state.

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