CN116259416A - Non-contact maintenance monitoring method and device, electronic equipment and medium - Google Patents

Non-contact maintenance monitoring method and device, electronic equipment and medium Download PDF

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CN116259416A
CN116259416A CN202310100617.XA CN202310100617A CN116259416A CN 116259416 A CN116259416 A CN 116259416A CN 202310100617 A CN202310100617 A CN 202310100617A CN 116259416 A CN116259416 A CN 116259416A
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vital sign
heart rate
time sequence
rate
features
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张帅军
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Zhuhai Haorui Technology Co ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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Abstract

The invention provides a non-contact maintenance monitoring method, a non-contact maintenance monitoring device, electronic equipment and a medium, wherein the non-contact maintenance monitoring method comprises the following steps: responding to a non-contact maintenance monitoring request, and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate; extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveforms; fusing heart rate characteristics and respiratory rate characteristics to obtain fused characteristics, classifying the fused characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of vital sign time sequence waveforms; and determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result, and continuously monitoring the heart rate and the respiration rate. The technical scheme of the invention realizes non-contact efficient maintenance monitoring.

Description

Non-contact maintenance monitoring method and device, electronic equipment and medium
Technical Field
The invention relates to the technical field of computer human medical treatment, in particular to a non-contact maintenance monitoring method, a non-contact maintenance monitoring device, electronic equipment and a non-contact maintenance monitoring medium.
Background
Along with the progress of society, the living standard of people is increasingly improved, but negative effects are brought, more and more people have three high symptoms such as hypertension, hyperlipidemia, hyperglycemia and the like, and the health of people is seriously threatened, so that people hope to quickly and conveniently obtain the support of doctors once the monitored person has unstable or abnormal physiological parameters, and maintain or treat under the advice of the doctors. For some early or recessive heart disease patients, conventional electrocardiography is difficult to find, because the electrocardiography can only show abnormality under certain conditions, such as emotional agitation, work tension, mental or physical overload, if the electrocardiography can not monitor dynamic electric signals for a long time, timely capture the change of the electrocardiograph signals during the onset and timely diagnose, the recessive heart disease patient can not be timely treated, and sudden cardiac death is often caused.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a non-contact maintenance monitoring method, a non-contact maintenance monitoring device, electronic equipment and a medium, so that non-contact efficient maintenance monitoring is realized.
One aspect of the present invention provides a non-contact maintenance monitoring method, which is characterized by comprising:
responding to a non-contact maintenance monitoring request, and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate;
extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveforms;
fusing heart rate characteristics and respiratory rate characteristics to obtain fusion characteristics, and classifying the fusion characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms;
and determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result, and continuously monitoring the heart rate and the respiration rate.
The non-contact maintenance monitoring method, wherein acquiring the vital sign time sequence waveform of the area to be detected, comprises the following steps:
the method comprises the steps of positioning a target monitoring area through an infrared sensing device, determining the position of the monitoring target, and acquiring a vital sign time sequence waveform through a vital sign acquisition device, wherein the vital sign acquisition device comprises a heart rate acquisition device and a respiratory rate acquisition device.
According to the non-contact maintenance monitoring method, the feature extraction of the vital sign time sequence waveform to obtain the corresponding heart rate feature and respiratory rate feature of the vital sign time sequence waveform respectively includes:
and extracting the vital sign time sequence wave through a circulating neural network.
According to the non-contact maintenance monitoring method, the feature extraction is performed on the vital sign time sequence waveform to obtain the corresponding heart rate feature and respiratory rate feature of the vital sign time sequence waveform, respectively, including:
separating the vital sign time sequence waveforms to obtain the vital sign time sequence waveforms of heart rate and respiratory rate respectively;
and extracting the vital sign time sequence waveforms of the heart rate and the respiration rate by adopting a multidimensional convolutional neural network to obtain heart rate characteristics and respiration rate characteristics.
The non-contact maintenance monitoring method, wherein the vital sign time sequence waveforms of heart rate and respiration rate are extracted by adopting a multidimensional convolutional neural network to obtain heart rate characteristics and respiration rate characteristics, comprises the following steps:
dividing the vital sign time sequence waveforms of heart rate features and respiratory rate features into time slices, inputting the heart rate features and the respiratory rate features into a multidimensional convolutional neural network to obtain a convolutional feature map, and obtaining the heart rate features and the respiratory rate features through long-short-term memory neural network and pooling processing of the convolutional feature map.
According to the non-contact maintenance monitoring method, the heart rate and the respiration rate of the target monitoring personnel in the area to be monitored are determined according to the classification result, and the heart rate and the respiration rate are continuously monitored, and the non-contact maintenance monitoring method further comprises the following steps:
and detecting the monitoring personnel in the area to be monitored by adopting a human body identification mode.
Another aspect of the embodiment of the present invention provides a non-contact maintenance monitoring device, including:
the first module is used for responding to a non-contact maintenance monitoring request and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate;
the second module is used for extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiratory rate features of the vital sign time sequence waveforms;
the third module is used for fusing heart rate characteristics and respiratory rate characteristics to obtain fusion characteristics, classifying the fusion characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms;
and the fourth module is used for determining the heart rate and the respiration rate of the target monitoring personnel in the area to be monitored according to the classification result and continuously monitoring the heart rate and the respiration rate.
Another aspect of an embodiment of the present invention provides an electronic device, including a processor and a memory;
the memory is used for storing programs;
the processor executes the program to implement the method as described above.
Embodiments of the present invention also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, cause the computer device to perform the method described previously.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flow chart of a method according to an embodiment of the invention.
Fig. 2 is a schematic diagram of a heart rate feature and respiration rate feature extraction flow according to an embodiment of the invention.
Fig. 3 is a schematic diagram of a feature extraction process performed by the multidimensional convolutional neural network according to an embodiment of the present invention.
Fig. 4 is a view of a non-contact maintenance monitoring analysis device according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. In the following description, suffixes such as "module", "part" or "unit" for representing elements are used only for facilitating the description of the present invention, and have no particular meaning in themselves. Thus, "module," "component," or "unit" may be used in combination. "first", "second", etc. are used for the purpose of distinguishing between technical features only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated. In the following description, the continuous reference numerals of the method steps are used for facilitating examination and understanding, and the technical effects achieved by the technical scheme of the invention are not affected by adjusting the implementation sequence among the steps in combination with the overall technical scheme of the invention and the logic relations among the steps. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
Term interpretation:
as shown in fig. 1, an embodiment of the present invention provides a flow of a non-contact maintenance monitoring method, which specifically includes, but is not limited to, steps S100-S500.
S100, responding to a non-contact maintenance monitoring request, and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate.
In some embodiments, the target monitoring area is positioned by an infrared sensing device, the monitoring target position is determined, the vital sign time sequence waveform is acquired by a vital sign acquisition device, and the vital sign acquisition device comprises a heart rate acquisition device and a respiratory rate acquisition device.
In some embodiments, for example, a collection of devices including a rate acquisition device, a respiratory rate acquisition device, a processor, an infrared sensing device.
And S200, extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiratory rate features of the vital sign time sequence waveforms.
In some embodiments, the vital sign timing wave is extracted through a recurrent neural network.
S300, fusing heart rate characteristics and respiratory rate characteristics to obtain fusion characteristics, classifying the fusion characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms.
In some embodiments, referring to the heart rate feature and respiration rate feature extraction flow chart of fig. 2, including but not limited to steps S310-S320:
s310, separating vital sign time sequence waveforms to obtain vital sign time sequence waveforms of heart rate and respiratory rate respectively;
s320, extracting vital sign time sequence waveforms of heart rate and respiration rate by adopting a multidimensional convolutional neural network to obtain heart rate characteristics and respiration rate characteristics.
In some embodiments, a feature extraction flow diagram is performed with reference to the multidimensional convolutional neural network shown in fig. 3, which includes, but is not limited to, S321-S322:
s321, dividing vital sign time sequence waveforms of heart rate features and respiration rate features into time slices, and inputting the heart rate features and the respiration rate features into a multidimensional convolutional neural network to obtain a convolutional feature map;
s322, obtaining heart rate characteristics and respiratory rate characteristics through long-short-term memory neural network and pooling processing of the convolution characteristic map.
And S400, determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result, and continuously monitoring the heart rate and the respiration rate.
In some embodiments, a human body recognition mode is also adopted to detect monitoring personnel in the area to be monitored, so as to realize accurate personnel positioning.
Fig. 4 is a view of a non-contact maintenance monitoring analysis device according to an embodiment of the present invention. The device comprises a first module, a second module, a third module and a fourth module.
The first module is used for responding to a non-contact maintenance monitoring request and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate; the second module is used for extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiratory rate features of the vital sign time sequence waveforms; the third module is used for fusing the heart rate characteristics and the respiratory rate characteristics to obtain fusion characteristics, classifying the fusion characteristics to obtain classification results, and the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms; and the fourth module is used for determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result and continuously monitoring the heart rate and the respiration rate.
The device of the embodiment may implement any one of the foregoing non-contact maintenance monitoring methods under the cooperation of the first module, the second module, the third module, and the fourth module in the device, that is, obtain, in response to a non-contact maintenance monitoring request, a vital sign time-sequence waveform of the area to be detected, where the vital sign includes at least one of a heart rate and a respiration rate; extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveforms; fusing heart rate characteristics and respiratory rate characteristics to obtain fused characteristics, classifying the fused characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of vital sign time sequence waveforms; and determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result, and continuously monitoring the heart rate and the respiration rate. The embodiment of the invention realizes non-contact efficient maintenance monitoring.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a memory;
the memory stores a program;
the processor executes a program to execute the non-contact maintenance monitoring method; the electronic device has the function of carrying and running the software system of the non-contact maintenance monitoring provided by the embodiment of the invention, such as a personal computer (Personal Computer, PC), a mobile phone, a smart phone, a personal digital assistant (Personal Digital Assistant, PDA), a wearable device, a palm computer PPC (Pocket PC), a tablet computer and the like.
The embodiment of the invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the non-contact maintenance monitoring method as described above.
In some alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed, and in which sub-operations described as part of a larger operation are performed independently.
Embodiments of the present invention also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, to cause the computer device to perform the aforementioned non-contact maintenance monitoring method.
Furthermore, while the invention is described in the context of functional modules, it should be appreciated that, unless otherwise indicated, one or more of the described functions and/or features may be integrated in a single physical device and/or software module or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Accordingly, one of ordinary skill in the art can implement the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative and are not intended to be limiting upon the scope of the invention, which is to be defined in the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
While the preferred embodiment of the present invention has been described in detail, the present invention is not limited to the embodiments described above, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are included in the scope of the present invention as defined in the appended claims.

Claims (9)

1. A non-contact maintenance monitoring method, comprising:
responding to a non-contact maintenance monitoring request, and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate;
extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveforms;
fusing heart rate characteristics and respiratory rate characteristics to obtain fusion characteristics, and classifying the fusion characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms;
and determining the heart rate and the respiration rate of target monitoring personnel in the area to be monitored according to the classification result, and continuously monitoring the heart rate and the respiration rate.
2. The method for non-contact maintenance monitoring according to claim 1, wherein the acquiring the vital sign timing waveform of the area to be detected comprises:
the method comprises the steps of positioning a target monitoring area through an infrared sensing device, determining the position of the monitoring target, and acquiring a vital sign time sequence waveform through a vital sign acquisition device, wherein the vital sign acquisition device comprises a heart rate acquisition device and a respiratory rate acquisition device.
3. The method for non-contact maintenance monitoring according to claim 1, wherein the step of extracting features of the vital sign time sequence waveform to obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveform, respectively, comprises:
and extracting the vital sign time sequence wave through a circulating neural network.
4. The method for non-contact maintenance monitoring according to claim 3, wherein the step of extracting features of the vital sign time sequence waveform to obtain corresponding heart rate features and respiration rate features of the vital sign time sequence waveform, respectively, comprises:
separating the vital sign time sequence waveforms to obtain the vital sign time sequence waveforms of heart rate and respiratory rate respectively;
and extracting the vital sign time sequence waveforms of the heart rate and the respiration rate by adopting a multidimensional convolutional neural network to obtain heart rate characteristics and respiration rate characteristics.
5. The method of claim 4, wherein the extracting the vital sign time sequence waveforms of the heart rate and the respiration rate by using a multidimensional convolutional neural network to obtain heart rate features and respiration rate features comprises:
dividing the vital sign time sequence waveforms of heart rate features and respiratory rate features into time slices, inputting the heart rate features and the respiratory rate features into a multidimensional convolutional neural network to obtain a convolutional feature map, and obtaining the heart rate features and the respiratory rate features through long-short-term memory neural network and pooling processing of the convolutional feature map.
6. The non-contact maintenance monitoring method according to claim 1, wherein determining the heart rate and the respiration rate of the target monitoring person in the area to be monitored according to the classification result continuously monitors the heart rate and the respiration rate, further comprising:
and detecting the monitoring personnel in the area to be monitored by adopting a human body identification mode.
7. A non-contact maintenance monitoring device, comprising:
the first module is used for responding to a non-contact maintenance monitoring request and acquiring a vital sign time sequence waveform of a region to be detected, wherein the vital sign comprises at least one of heart rate and respiratory rate;
the second module is used for extracting features of the vital sign time sequence waveforms to respectively obtain corresponding heart rate features and respiratory rate features of the vital sign time sequence waveforms;
the third module is used for fusing heart rate characteristics and respiratory rate characteristics to obtain fusion characteristics, classifying the fusion characteristics to obtain classification results, wherein the classification results are used for representing corresponding heart rate signals and respiratory rate signals of the vital sign time sequence waveforms;
and the fourth module is used for determining the heart rate and the respiration rate of the target monitoring personnel in the area to be monitored according to the classification result and continuously monitoring the heart rate and the respiration rate.
8. An electronic device comprising a processor and a memory;
the memory is used for storing programs;
execution of the program by the processor implements the contactless maintenance monitoring method according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that the storage medium stores a program that is executed by a processor to implement the noncontact maintenance monitoring method according to any one of claims 1 to 6.
CN202310100617.XA 2023-02-07 2023-02-07 Non-contact maintenance monitoring method and device, electronic equipment and medium Pending CN116259416A (en)

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