Monitoring method and related device
By calculating the pulse repetition frequency of the FMCW radar and removing the micro-motion phase information, the respiratory and heartbeat phases are obtained using variational mode decomposition, which solves the problem of phase jump in radar under micro-motion conditions and achieves accurate monitoring of vital signs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING UNIV OF POSTS & TELECOMM
- Filing Date
- 2023-07-03
- Publication Date
- 2026-06-19
AI Technical Summary
Existing FMCW radars have difficulty effectively acquiring vital sign phase information when the human body is in a state of slight movement, which leads to phase jumps interfering with heart rate estimation. Ignoring key steps in data acquisition results in inaccurate monitoring results.
By acquiring the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of the emitted signal, the pulse repetition frequency is calculated, the micro-movement phase information is removed, and the breathing and heartbeat phase information is obtained using variational mode decomposition.
It enables the effective acquisition of vital sign phase information under micro-motion conditions, reduces phase jump interference, and ensures the feasibility and accuracy of vital sign monitoring.
Smart Images
Figure CN116999039B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of radar signal processing technology, and in particular to a monitoring method and related equipment. Background Technology
[0002] FMCW (Frequency Modulated Continuous Wave) radar can detect the vital signs of multiple people and has great potential in fields such as smart cockpits and health monitoring. FMCW radar can achieve ranging functions through frequency and phase methods. However, because the fluctuation amplitude of vital signs such as breathing and heartbeat is small, the resulting frequency changes are much smaller than the frequency resolution. That is, the echo frequency is not sensitive to micro-motion changes, while the phase is extremely sensitive to micro-motions. Even a very small micro-motion can cause a change in the phase. Therefore, phase is widely used in human vital sign monitoring to detect breathing and heartbeat.
[0003] Current research on vital sign monitoring is mostly based on the static state of the human target. Ideally, the human target is stationary, and radar echoes are minimally affected by interference. Within the range cell of the human target, the radar echo frequency and phase are modulated only by the fluctuations in the human body surface caused by breathing and heartbeat. When the pulse repetition interval is large, the phase changes caused by breathing and heartbeat do not jump between adjacent repetition pulses, and phase information can be obtained by unwinding the echo phase. However, in actual human vital sign monitoring, the human body is not always stationary; there will inevitably be slight movements. These movements will cause abrupt phase changes. When the pulse repetition interval is not set appropriately, the phase change will exceed ±π and cannot be unwound, manifesting as a phase jump. In related research on human vital sign monitoring, researchers often focus on algorithm development, neglecting the crucial step of data acquisition. This leads to the simplistic attribution of phase jumps in the case of slight movements to clutter interference, resulting in the collection of only data without phase jumps, which is inconsistent with reality. Summary of the Invention
[0004] In view of this, the purpose of this application is to propose a monitoring method and related equipment.
[0005] For the purposes described above, this application provides a monitoring method, comprising:
[0006] Acquire the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of emitted signals;
[0007] The pulse repetition frequency is calculated based on the surface undulation speed, the micro-movement speed of the human body, and the wavelength of the emitted signal.
[0008] The respiratory and heart rate were monitored based on the pulse repetition frequency to obtain monitoring results.
[0009] In one possible implementation, the pulse repetition frequency is calculated using the following formula:
[0010]
[0011] Among them, f s Δx represents the pulse repetition frequency, Δx represents the velocity of body surface fluctuations, ΔR0 represents the velocity of human body micro-movements, and λ represents the wavelength of the transmitted signal.
[0012] In one possible implementation, the method further includes:
[0013] When the speed of human body micro-movement is zero, the pulse repetition frequency is calculated using the following formula:
[0014]
[0015] Among them, f s λ represents the pulse repetition frequency, Δx represents the velocity of the body surface fluctuations, and λ represents the wavelength of the transmitted signal.
[0016] In one possible implementation, the monitoring of respiratory and cardiac rhythm based on the pulse repetition frequency to obtain monitoring results includes:
[0017] Phase information is obtained based on the pulse repetition frequency;
[0018] Remove the micro-motion phase information from the phase information to obtain the retained phase information;
[0019] The monitoring results are obtained based on the retained phase information.
[0020] In one possible implementation, obtaining the monitoring result based on the retained phase information includes:
[0021] The retained phase information is subjected to variational mode decomposition, and intrinsic mode signals that meet the requirements of breathing and heartbeat are selected.
[0022] The monitoring results are obtained based on the intrinsic mode signals.
[0023] In one possible implementation, the surface undulation speed is the amplitude of surface undulation caused by breathing and heartbeat per unit time; the human body micro-movement speed is the amplitude of human body micro-movement per unit time.
[0024] Based on the same inventive concept, this application also provides a monitoring device, including:
[0025] The acquisition module is configured to acquire the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of the emitted signal.
[0026] The calculation module is configured to calculate the pulse repetition frequency based on the surface undulation speed, the human body micro-movement speed, and the wavelength of the emitted signal;
[0027] The monitoring module is configured to monitor respiratory heartbeat based on the pulse repetition frequency and obtain monitoring results.
[0028] Based on the same inventive concept, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the monitoring method as described in any of the above.
[0029] Based on the same inventive concept, embodiments of this application also provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute any of the monitoring methods described above.
[0030] Based on the same inventive concept, embodiments of this application also provide a computer program product, which includes computer program instructions, the computer instructions being used to cause the computer program product to execute any of the monitoring methods described above.
[0031] As can be seen from the above, the monitoring method and related equipment provided in this application acquire the surface undulation velocity, human micro-movement velocity, and transmitted signal wavelength caused by breathing and heartbeat; calculate the pulse repetition frequency based on the surface undulation velocity, human micro-movement velocity, and transmitted signal wavelength; and monitor breathing and heartbeat based on the pulse repetition frequency to obtain monitoring results. This enables effective acquisition of vital sign monitoring phase information during human micro-movement, preventing phase jumps and reducing interference from phase jumps on heart rate estimation, thus ensuring the feasibility of vital sign monitoring under micro-movement conditions. Attached Figure Description
[0032] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0033] Figure 1 This is a schematic diagram of the monitoring method in an embodiment of this application;
[0034] Figure 2 This is a schematic diagram of the human target position in a static state according to an embodiment of this application;
[0035] Figure 3 This is a schematic diagram of the human target position under micro-motion state according to an embodiment of this application;
[0036] Figure 4 This is a schematic diagram of respiratory and heartbeat waveforms according to an embodiment of this application;
[0037] Figure 5 This is a schematic diagram of the phase information within the distance cell of the human target at a low pulse repetition frequency according to an embodiment of this application;
[0038] Figure 6 This is a schematic diagram of the phase information within the distance cell of the human target at a high pulse repetition frequency according to an embodiment of this application;
[0039] Figure 7 This is a schematic diagram of phase transition at a low pulse repetition frequency according to an embodiment of this application;
[0040] Figure 8 This is a schematic diagram showing that no phase jump occurred at a high pulse repetition frequency according to an embodiment of this application;
[0041] Figure 9 This is a schematic diagram of the monitoring device structure according to an embodiment of this application;
[0042] Figure 10 This is a schematic diagram of the electronic device structure according to an embodiment of this application. Detailed Implementation
[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.
[0044] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0045] As described in the background section, FMCW (Frequency Modulated Continuous Wave) radar can detect the vital signs of multiple people and has great potential in fields such as smart cockpits and health monitoring. FMCW radar can achieve ranging functions through frequency and phase methods. However, because the fluctuation amplitude of vital signs such as breathing and heartbeat is small, the resulting frequency changes are much smaller than the frequency resolution. That is, the echo frequency is not sensitive to micro-motion changes, while the phase is extremely sensitive to micro-motions. Even a very small micro-motion can cause a change in the phase. Therefore, phase is widely used in human vital sign monitoring to detect breathing and heartbeat.
[0046] Current research on vital sign monitoring is mostly based on the static state of the human target. Ideally, the human target is stationary, and radar echoes are minimally affected by interference. Within the range cell of the human target, the radar echo frequency and phase are modulated only by the fluctuations in the human body surface caused by breathing and heartbeat. When the pulse repetition interval is large, the phase changes caused by breathing and heartbeat do not jump between adjacent repetition pulses, and phase information can be obtained by unwinding the echo phase. However, in actual human vital sign monitoring, the human body is not always stationary; there will inevitably be slight movements. These movements will cause abrupt phase changes. When the pulse repetition interval is not set appropriately, the phase change will exceed ±π and cannot be unwound, manifesting as a phase jump. In related research on human vital sign monitoring, researchers often focus on algorithm development, neglecting the crucial step of data acquisition. This leads to the simplistic attribution of phase jumps in the case of slight movements to clutter interference, resulting in the collection of only data without phase jumps, which is inconsistent with reality.
[0047] In light of the above considerations, this application proposes a monitoring method and related equipment. This method acquires the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human body micro-movements, and the wavelength of the emitted signal. Based on these parameters, a pulse repetition frequency is calculated. The method then monitors breathing and heartbeats using this pulse repetition frequency to obtain monitoring results. This approach enables effective acquisition of vital sign phase information during human body micro-movements, preventing phase jumps and reducing interference from phase jumps on heart rate estimation. This ensures the feasibility of vital sign monitoring under micro-movement conditions.
[0048] The technical solutions of the embodiments of this application will be described in detail below through specific examples.
[0049] refer to Figure 1 The monitoring method of this application embodiment includes the following steps:
[0050] Step S101: Obtain the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of the emitted signal;
[0051] Step S102: Calculate the pulse repetition frequency based on the surface undulation speed, the human body micro-movement speed, and the emitted signal wavelength.
[0052] Step S103: Monitor respiratory heart rate based on the pulse repetition frequency to obtain monitoring results.
[0053] With the continuous development of radar technology, its application scope has gradually expanded from the military field to the civilian field, and it has been widely used in areas such as assisted driving, smart homes, and healthcare. In the healthcare field, radar equipment can monitor human vital signs such as breathing and heartbeat, and may use different types of radar transmission waveforms, including continuous wave (CW) radar, pulse ultra-wideband radar, and frequency modulated continuous wave (FMCW) radar. Radar systems based on different technologies have different advantages and disadvantages. CW radar directly measures phase difference but cannot measure distance or distinguish multiple targets; pulse ultra-wideband radar has strong anti-interference capabilities but requires high hardware and a high sampling rate; FMCW radar can detect human position, distinguish multiple targets, and has rich echo signal information, but its signal processing is relatively complex. It can achieve ranging function through frequency method and phase method. However, since the fluctuation amplitude of vital signs such as breathing and heartbeat is small, the resulting frequency change is much smaller than the frequency resolution. That is, the echo frequency is not sensitive to micro-motion changes, while the phase is extremely sensitive to micro-motion. Even a very small micro-motion will cause a phase change. Therefore, phase is widely used to monitor breathing and heartbeat in human vital signs monitoring.
[0054] It should be noted that this application embodiment constructs a radar simulation system based on the FMCW (Frequency Multi-Channel Wave) architecture to simulate and verify the impact of low pulse repetition frequency on respiratory and heart rate extraction. The initial parameters of the FMCW-based radar simulation system are set as follows: radar sweep start frequency is 77 GHz, sweep slope is 79 GHz / ms, ADC sampling points are 64, and ADC data acquisition rate is 4 MHz. This corresponds to a wavelength of 0.0039 m, a system bandwidth of 1.264 GHz, and a range resolution of 0.1187 m. The initial distance to the target human is 1.2 m, the respiratory rate is 0.4 Hz, accompanied by second and third harmonics, and the heart rate is 1 Hz.
[0055] Regarding step S101, in this embodiment of the application, it is first necessary to obtain the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human body micro-movements, and the wavelength of the emitted signal.
[0056] Wherein, the surface undulation speed is the amplitude of surface undulation caused by breathing and heartbeat per unit time; the human body micro-movement speed is the amplitude of human body micro-movement per unit time; and the transmitted signal wavelength refers to the wavelength of the transmitted signal of the aforementioned radar.
[0057] In some embodiments, the true phase of the distance cell to the human target within all pulse cycles is provided as follows: The phase difference within the cell containing the distance to the human target in adjacent pulse cycles is: when Within the interval [-π, π], that is, when the true phase difference between adjacent pulse cycles does not exceed ±π, if the phase difference between sampled adjacent data exceeds ±π, then starting from the distance cell where the human target is located in the first pulse cycle, by adding or subtracting 2π, the phase difference between adjacent data can be made less than ±π, and the true phase information can be restored.
[0058] However, when When the true phase difference between adjacent pulse periods exceeds ±π and is not within the range of [-π,π], a true phase transition occurs. However, due to phase entanglement, the number of phase periods entangled between adjacent phases cannot be determined, so the true phase cannot be obtained by untangling.
[0059] Regarding step S102, after obtaining the surface undulation speed, human micro-movement speed and emitted signal wavelength in step S101, the pulse repetition frequency needs to be calculated based on these three data areas.
[0060] In some feasible embodiments, the pulse repetition frequency is calculated using the following formula:
[0061]
[0062] Among them, f s Δx represents the pulse repetition frequency, Δx represents the velocity of body surface fluctuations, ΔR0 represents the velocity of human body micro-movements, and λ represents the wavelength of the transmitted signal.
[0063] In some feasible embodiments, the method further includes:
[0064] When the speed of human body micro-movement is zero, the pulse repetition frequency is calculated using the following formula:
[0065]
[0066] Among them, f s λ represents the pulse repetition frequency, Δx represents the velocity of the body surface fluctuations, and λ represents the wavelength of the transmitted signal.
[0067] Based on the foregoing statements, when If the phase is not within the interval [-π, π], a true phase transition occurs. However, due to phase entanglement, the number of phase periods between adjacent phases is unknown, so the true phase cannot be obtained by untangling the entanglement. (The aforementioned...) This is caused by the relative distance changes between the human body's location, the fluctuations in the body surface due to breathing and heartbeat, and the radar. Specifically, the distance difference ΔR between adjacent pulse period target range cells... i =△R0(t) i )+△x(t i ), where △R0(t) i ) represents the change in human body position, △x(t) i The change in body surface elevation is represented by ΔR. Assume the distance difference per unit time is ΔR, where the change in body position is ΔR0, the change in body surface elevation is Δx, and the pulse cycle repetition frequency is f. s In order to obtain true phase information, it is necessary to Within the interval [-π, π], it must satisfy...
[0068] In some embodiments, when ΔR0 is 0, that is, when the human target is in a state of absolute stillness, ΔR i If only Δx is present, then the sampling frequency requirement is... When ΔR0 is not 0, meaning the human target is in a state of slight movement, the sampling frequency requirement is...
[0069] Based on the above steps, the minimum pulse repetition frequency can be successfully calculated. Pulse repetition frequency is one of the most important characteristic parameters of a pulse radar signal. It is the rate at which pulses or pulse groups are transmitted. Generally speaking, pulse repetition frequency is the number of pulses transmitted per second, expressed in Hertz (Hz).
[0070] Furthermore, regarding step S103, after calculating the minimum pulse repetition frequency, a suitable pulse repetition frequency is selected as the final pulse repetition frequency for monitoring the human body. After setting it, breathing and heartbeat are monitored based on the pulse repetition frequency to obtain monitoring results.
[0071] In some feasible embodiments, the monitoring of respiratory and heart rate based on the pulse repetition frequency to obtain monitoring results includes:
[0072] Phase information is obtained based on the pulse repetition frequency;
[0073] Remove the micro-motion phase information from the phase information to obtain the retained phase information;
[0074] The monitoring results are obtained based on the retained phase information.
[0075] In some feasible embodiments, obtaining the monitoring results based on the retained phase information includes:
[0076] The retained phase information is subjected to variational mode decomposition, and intrinsic mode signals that meet the requirements of breathing and heartbeat are selected.
[0077] The monitoring results are obtained based on the intrinsic mode signals.
[0078] Specifically, since the phase change is large when the human target moves slightly, which is significantly different from the breathing and heartbeat waveform, the phase information of the slight movement can be marked by differentiation and zero point and removed. The retained phase information is then segmented and subjected to variational mode decomposition to screen the intrinsic mode signals that meet the requirements of breathing and heartbeat. Finally, the monitoring results are obtained based on the intrinsic mode signals.
[0079] In some embodiments, reference Figure 2 This is a schematic diagram of the human target position in a static state according to an embodiment of this application. In this diagram, the human body is in a completely static state, positioned at a distance of 1.2 meters. (Reference) Figure 3 This is a schematic diagram of the target human body position under micro-motion conditions according to an embodiment of this application. In this diagram, the human body tilts backward and forward near 7s and 17s, respectively. (Reference) Figure 4 The diagram below illustrates a respiratory and heartbeat waveform according to an embodiment of this application. In this diagram, the respiratory rate is 0.4 Hz, accompanied by second and third harmonics; the heartbeat rate is 1 Hz; the respiratory amplitude is 0.5 cm; and the heartbeat amplitude is 0.05 cm. The aim is to approximate the actual respiratory and heartbeat waveform as closely as possible. (Reference) Figure 5 This is a schematic diagram of phase information within a cell representing the distance to a human target at a low pulse repetition frequency, according to an embodiment of this application. It can be observed that phase jumps occur in the micro-motion regions of 7s and 17s, interfering with subsequent processing of breathing and heartbeats. (Reference) Figure 6 The diagram shows the phase information within the distance cell of the human target at a high pulse repetition frequency according to an embodiment of this application. It can be seen that in the micro-motion regions of 7s and 17s, the phase does not change, and the true phase information can be obtained.
[0080] Furthermore, based on the above principles and setting radar system parameters consistent with the simulation, a radar panel was used to monitor breathing and heartbeat. (Reference) Figure 7 This diagram illustrates phase transitions at low pulse repetition frequencies according to an embodiment of this application. Specifically, under low phase sampling conditions, phase transitions occur within the micro-motion region between 4s and 10s, resulting in spurious phase information that interferes with subsequent respiratory and heart rate estimation. (Refer to...) Figure 8 This is a schematic diagram of the phase not changing under high pulse repetition frequency in an embodiment of this application. That is, under high phase sampling, the phase does not change in the micro-motion region of 4s and 10s. The phase can be untangled to obtain real phase information, which is convenient for subsequent respiratory and heart rate estimation.
[0081] Furthermore, since the phase change is significant when the human target undergoes slight movements, which is clearly different from the respiratory and heartbeat waveforms, the phase information of these slight movements can be removed by marking with differentiation and zero points. The retained phase information is then segmented and decomposed using VMD to filter out intrinsic mode signals that meet the requirements of respiratory and heartbeat. Finally, the respiratory and heartbeat frequencies estimated by the method proposed in this invention are 0.38Hz and 1.14Hz, respectively, consistent with data from other monitoring devices.
[0082] As can be seen from the above embodiments, the monitoring method described in this application acquires the surface undulation velocity caused by breathing and heartbeat, the speed of human body micro-movement, and the wavelength of the emitted signal; calculates the pulse repetition frequency based on the surface undulation velocity, the speed of human body micro-movement, and the wavelength of the emitted signal; and monitors breathing and heartbeat based on the pulse repetition frequency to obtain monitoring results. Based on the pulse repetition interval calculated above, effective acquisition of vital sign monitoring phase information can be achieved when the human target is micro-moving, without phase jumps, reducing the interference of phase jumps on heart rate estimation, and ensuring the feasibility of vital sign monitoring under micro-movement conditions.
[0083] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.
[0084] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0085] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a monitoring device.
[0086] refer to Figure 9 The monitoring device includes:
[0087] The acquisition module 91 is configured to acquire the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of the emitted signal.
[0088] The calculation module 92 is configured to calculate the pulse repetition frequency based on the surface undulation speed, the human body micro-movement speed, and the wavelength of the emitted signal.
[0089] The monitoring module 93 is configured to monitor respiratory heartbeat based on the pulse repetition frequency and obtain monitoring results.
[0090] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.
[0091] The apparatus of the above embodiments is used to implement the corresponding monitoring method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0092] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the monitoring method described in any of the above embodiments.
[0093] Figure 10 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.
[0094] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.
[0095] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.
[0096] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.
[0097] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).
[0098] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.
[0099] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.
[0100] The electronic devices described above are used to implement the corresponding monitoring methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0101] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute the monitoring method as described in any of the above embodiments.
[0102] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.
[0103] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the monitoring method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0104] Based on the same inventive concept, corresponding to the monitoring method described in any of the above embodiments, this disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer to cause the computer and / or the processor to perform the monitoring method. Corresponding to the execution entity for each step in each embodiment of the monitoring method, the processor executing the corresponding step may belong to the corresponding execution entity.
[0105] The computer program product of the above embodiments is used to cause the computer and / or the processor to perform the monitoring method as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0106] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.
[0107] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.
[0108] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.
[0109] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.
Claims
1. A monitoring method characterized by, include: Acquire the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of emitted signals; The pulse repetition frequency is calculated based on the surface undulation speed, the micro-movement speed of the human body, and the wavelength of the emitted signal. The respiratory and heart rate were monitored based on the pulse repetition frequency to obtain monitoring results; The pulse repetition frequency is calculated using the following formula: in, Indicates the pulse repetition frequency. Indicates the speed of surface undulations. Indicates the speed of micro-movements in the human body. Indicates the wavelength of the transmitted signal.
2. The method according to claim 1, characterized in that, The method further includes: When the speed of human body micro-movement is zero, the pulse repetition frequency is calculated using the following formula: in, Indicates the pulse repetition frequency. Indicates the speed of surface undulations. This indicates the wavelength of the transmitted signal.
3. The method of claim 1, wherein, The monitoring of respiration and heart rate based on the pulse repetition frequency, to obtain monitoring results, includes: Phase information is obtained based on the pulse repetition frequency; Remove the micro-motion phase information from the phase information to obtain the retained phase information; The monitoring results are obtained based on the retained phase information.
4. The method of claim 3, wherein, The monitoring results obtained based on the retained phase information include: The retained phase information is subjected to variational mode decomposition, and intrinsic mode signals that meet the requirements of breathing and heartbeat are selected. The monitoring results are obtained based on the intrinsic mode signals.
5. The method of claim 1, wherein, The surface undulation speed is the amplitude of surface undulation caused by breathing and heartbeat per unit time; the human body micro-movement speed is the amplitude of human body micro-movement per unit time.
6. A monitoring device, characterized by include: The acquisition module is configured to acquire the velocity of body surface fluctuations caused by breathing and heartbeat, the velocity of human micro-movements, and the wavelength of the emitted signal. The calculation module is configured to calculate the pulse repetition frequency based on the surface undulation speed, the human body micro-movement speed, and the wavelength of the emitted signal; The monitoring module is configured to monitor respiratory and heart rate based on the pulse repetition frequency and obtain monitoring results; The pulse repetition frequency is calculated using the following formula: wherein, denotes the pulse repetition frequency, denotes the body surface fluctuation velocity, denotes the human micro-motion velocity, denotes the transmitted signal wavelength.
7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 5.
8. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 5.
9. A computer program product comprising computer program instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 5.