Old people falling monitoring method and system based on multi-sensor fusion and trigger linkage

Abstract

The invention provides an old man falling monitoring method and system based on multi-sensor fusion and trigger linkage, and belongs to the technical field of falling monitoring. The method comprises the steps that S1, a universal interface used for being matched with various types of sensors is designed, the universal interface receives data from different types of sensors, and multi-source data is obtained; s2, preprocessing the multi-source data, and analyzing based on each single-source data to obtain a tumble event monitoring value; s3, performing fusion processing on the fall event monitoring values by using a fusion algorithm to obtain a fall event fusion value; and S4, when the tumble event fusion value reaches a preset threshold value, triggering a suspected tumble alarm signal, and starting a series of linkage processing mechanisms. Fall monitoring is carried out based on multiple sensors, the monitoring accuracy can be improved, a series of linkage processing mechanisms are adopted, and the processing timeliness can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fall monitoring, and in particular to a method and system for monitoring falls of the elderly based on multi-sensor fusion and trigger linkage. Background Art

[0002] As the global population ages, the health and safety of the elderly are receiving increasing attention from society. Falling is one of the most common accidents among the elderly, posing a serious threat to their health and safety. Therefore, it is particularly important to develop an efficient and accurate system for detecting and handling falls.

[0003] Traditional fall detection methods mainly rely on single sensors, such as accelerometers, gyroscopes, bracelets, etc., or simple video surveillance. These systems have limitations in accuracy and response speed, and have problems such as low detection accuracy, high false alarm rate, inability to respond in real time, and lack of effective linkage emergency mechanism. Summary of the invention

[0004] The present invention aims to overcome the above-mentioned shortcomings and provide a method, system, electronic device, computer storage medium and computer program product for elderly fall monitoring based on multi-sensor fusion and trigger linkage to improve the accuracy and timeliness of fall detection.

[0005] The present invention provides a method for monitoring elderly people's falls based on multi-sensor fusion and trigger linkage, comprising the following steps: S1, a universal interface designed to adapt to multiple types of sensors, which receives data from different types of sensors, i.e., obtains multi-source data; S2. Preprocessing the multi-source data, and obtaining a fall event monitoring value based on analysis of each single-source data; S3, using a fusion algorithm to fuse the fall event monitoring values ​​to obtain a fall event fusion value; S4. When the fall event fusion value reaches a preset threshold, a suspected fall alarm signal is triggered, and a series of linkage handling mechanisms are started.

[0006] Furthermore, step S1 specifically includes: A universal interface is designed to adapt to various types of sensors. The universal interface forms an internal standard KV (key-value) group of key data types (key) and data values ​​(value) of various types of sensors according to the access protocols of different types of sensors, encapsulates and modularizes the KV group to form a sensor result description, and then obtains the multi-source data.

[0007] Furthermore, the preprocessing includes data cleaning and data calibration; wherein the data calibration is used to align the data of different types of sensors in time and space scales, and align the data of various types of sensors according to the sensor with the highest frequency.

[0008] Furthermore, the fusion algorithm in step S3 includes but is not limited to weighted averaging, Kalman filter, Bayesian network, and deep learning model.

[0009] Furthermore, in step S4, the initiation of a series of linkage handling mechanisms includes: Control the surrounding dome cameras to turn to the suspected fall area to record the video, and use the fall detection algorithm to further identify and confirm the elderly person's posture, so as to accurately identify whether the elderly person is in a real fall state or other similar fall movements; If a fall event is confirmed, a linkage handling mechanism is triggered, which includes but is not limited to at least one of monitoring alarm, voice intercom, rescue linkage, and information recording.

[0010] Furthermore, the preset threshold is determined according to the age and physical health status of the monitored person; wherein, the preset threshold is negatively correlated with the age of the monitored person, and the preset threshold is positively correlated with the physical health status assessment value of the monitored person.

[0011] The present invention also provides an elderly fall monitoring system based on multi-sensor fusion and trigger linkage, comprising a universal interface, a processing module, and a storage module; the processing module is connected to the universal interface and the storage module; The universal interface is used to receive data from different types of sensors, that is, to obtain multi-source data; The storage module is used to store executable computer program code; The processing module is used to execute the method as described in any of the preceding items by calling the executable computer program code in the storage module.

[0012] The present invention also provides an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the method as described in any of the preceding items.

[0013] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, any of the above methods is executed.

[0014] The present invention further provides a computer program product, comprising a computer program stored on a non-transitory computer-readable medium, wherein the computer program is executed by a processor to perform any of the methods described above.

[0015] The beneficial effects of the present invention are at least: 1) Traditional fall detection systems may rely too much on a specific type of sensor, resulting in low system accuracy and poor adaptability. This invention reduces the system's reliance on a single sensor through multi-sensor fusion, and improves the accuracy of fall detection through multi-sensor fusion; 2) After detecting a fall, the previous elderly fall detection system often had problems with poor connection with the rescue link and delayed response. The present invention constructs a trigger linkage handling architecture, which can achieve timely handling of falls through rapid information interaction with, for example, monitoring equipment, rescue personnel terminals or surrounding medical institutions; 3) Different usage environments (such as indoors, outdoors, and different ground types) pose different challenges to the fall detection system. The present invention enhances the adaptability of the system in different environments through a flexible trigger linkage mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flow chart of a method for monitoring falls of the elderly based on multi-sensor fusion and trigger linkage disclosed in an embodiment of the present invention.

[0018] Figure 2 It is a structural schematic diagram of an elderly fall monitoring system based on multi-sensor fusion and trigger linkage disclosed in an embodiment of the present invention.

[0019] Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0022] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0023] It should be understood that although the terms first, second, third, etc. may be used to describe ... in the embodiments of the present application, these ... should not be limited to these terms. These terms are only used to distinguish .... For example, without departing from the scope of the embodiments of the present application, the first ... may also be referred to as the second ..., and similarly, the second ... may also be referred to as the first ....

[0024] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0025] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a product or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such a product or system. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the product or system including the elements.

[0026] The preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0027] like Figure 1 As shown, the embodiment of the present invention discloses a method for monitoring elderly falls based on multi-sensor fusion and trigger linkage, comprising the following steps: S1, a universal interface designed to adapt to multiple types of sensors, which receives data from different types of sensors, i.e., obtains multi-source data; S2. Preprocessing the multi-source data, and obtaining a fall event monitoring value based on analysis of each single-source data; S3, using a fusion algorithm to fuse the fall event monitoring values ​​to obtain a fall event fusion value; S4. When the fall event fusion value reaches a preset threshold, a suspected fall alarm signal is triggered, and a series of linkage handling mechanisms are started.

[0028] The above scheme of the present invention monitors whether there is a fall based on multiple types of sensors, and uses a fusion algorithm to comprehensively analyze the fall events detected by multiple sensors, thereby improving the monitoring accuracy of the fall events. At the same time, the present invention also constructs a series of linkage disposal mechanisms. When the probability of the existence of the monitored fall event is high, the fall event can be promptly handled through a variety of linkage disposal mechanisms to reduce the risk of the fall event.

[0029] Furthermore, step S1 specifically includes: A universal interface is designed to adapt to various types of sensors. The universal interface forms an internal standard KV (key-value) group of key data types (key) and data values ​​(value) of various types of sensors according to the access protocols of different types of sensors, encapsulates and modularizes the KV group to form a sensor result description, and then obtains the multi-source data.

[0030] The above access protocol is, for example, network communication, serial port communication, etc.

[0031] Sensors include but are not limited to surveillance cameras, wearable sensors (such as smart bracelets with built-in accelerometers, gyroscopes, etc.), pressure sensors, human posture sensors, and environmental monitoring sensors. Various types of sensors are distributed in different parts of the elderly's body or in their activity environment, collecting data related to the elderly's movement status and environment from multiple dimensions. For example, the accelerometer can capture the overall acceleration motion information of the body, the gyroscope sensor focuses on the body's rotation motion data, the pressure sensor can sense the pressure distribution and changes between the body and the support surface, the human posture sensor directly obtains posture data such as body joint angles, and the environmental sensor assists in determining the elderly's location and surrounding environment.

[0032] Furthermore, the preprocessing includes data cleaning and data calibration; wherein the data calibration is used to align the data of different types of sensors in time and space scales, and align the data of various types of sensors according to the sensor with the highest frequency.

[0033] On the basis of data integration, the system pre-processes multi-source data, including data cleaning (removing outliers and noise data) and data calibration (aligning different sensor data in time and space) to ensure data consistency and accuracy. The data frequencies of different types of sensors are inconsistent, so it is also necessary to align the data of various sensors according to the sensor with the highest frequency to ensure the accuracy of later data fusion.

[0034] After completing the preprocessing of each sensor data, it is necessary to analyze the fall event monitoring value based on each single source data. The details are as follows: 1) Use KV's custom rules (AND, OR, NOT) to make judgments. For example, when the acceleration sensor data (i.e., acceleration value) is within a specific range (such as exceeding the normal activity acceleration threshold, which may be caused by the sudden swing of the arm when falling) and lasts for a certain period of time (such as more than 0.5 seconds), it is preliminarily determined that there may be a suspected fall event; the gyroscope assists in detecting the change in the rotation angle of the elderly's arm. If a large angle change (such as more than 45°) occurs in a short period of time (such as within 0.3 seconds), combined with the acceleration sensor data, the suspicion of the fall event is further increased; the suspected fall alarm duration of the bracelet (such as 2 seconds); 2) suspected falls based on camera analysis; 3) Sound signals of heavy objects falling to the ground based on audio collection, etc.

[0035] Furthermore, the fusion algorithm in step S3 includes but is not limited to weighted averaging, Kalman filter, Bayesian network, and deep learning model.

[0036] A fusion framework for the monitoring results of multiple sensors is constructed. After the monitoring results are obtained based on the analysis of the data collected by each sensor, the fusion algorithm is used to fuse the monitoring results, and then the probability of falls of the elderly is comprehensively analyzed.

[0037] The fusion algorithm is the core of multi-sensor fusion technology, responsible for comprehensive analysis of feature information from different sensors, including: Weighted average method: Different weights are assigned to different sensors according to their reliability, and then the weighted average is calculated as the final decision basis.

[0038] Kalman filter: The Kalman filter algorithm is used to fuse multi-sensor data and estimate the elderly person’s status (such as whether they have fallen) through recursive prediction and update steps.

[0039] Bayesian Network: Used to fuse data from multiple sensors, taking into account the interdependencies between them.

[0040] Deep learning models: such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs), can be trained to learn how to identify falls from multi-sensor data.

[0041] Based on this multi-sensor fusion framework, different fusion algorithms can be selected for different scenarios to improve the accuracy of the system.

[0042] Furthermore, in step S4, the initiation of a series of linkage handling mechanisms includes: Control the surrounding dome cameras to turn to the suspected fall area to record the video, and use the fall detection algorithm to further identify and confirm the elderly person's posture, so as to accurately identify whether the elderly person is in a real fall state or other similar fall movements; If a fall event is confirmed, a linkage handling mechanism is triggered, which includes but is not limited to at least one of monitoring alarm, voice intercom, rescue linkage, and information recording.

[0043] The architecture includes one or more trigger conditions. When the multi-sensor fusion detection architecture determines that the possibility of an elderly person falling reaches a preset threshold, a suspected fall alarm signal is immediately triggered. This preset threshold can be dynamically adjusted and optimized based on a large amount of experimental data and actual application scenarios to balance the sensitivity and false alarm rate of detection. At the same time, the trigger mechanism architecture can carry business information (such as the identity information of the elderly, by associating with the elderly's wearable device or identity recognition system) and location information (obtained through sensor positioning function or fusion with environmental sensor data). When it is detected that the elderly's behavior or environmental changes meet these conditions, the system will start the fall detection process.

[0044] Once the triggering conditions are met, the system will automatically initiate a series of linkage actions, including but not limited to further data collection (such as personnel business information, location information, structured information, etc.), analysis and processing (analysis of another type of algorithm), alarm verification (video visualization, video refinement analysis, etc.) and other functions. In the detection of elderly falls, the linkage disposal mechanism is used to trigger the alarm verification module, control the surrounding dome cameras to turn to the fall area for video recording, and combine the fall detection algorithm to further identify and confirm the elderly's posture, so as to accurately identify whether the elderly are in a real fall state or other similar fall actions (such as squatting, bending over, etc.).

[0045] Among them, the control of the surrounding ball camera to turn to the suspected fall area for video recording can be specifically as follows: calculating the difference between the fall event fusion value and the preset threshold, obtaining the recording duration according to the difference matching, and controlling the surrounding ball camera to turn to the suspected fall area to record the video for the recording duration. In this scheme, the duration of the video recording can be determined according to the degree to which the fall event fusion value exceeds the preset threshold. When the degree of excess is low, it is necessary to record a longer video to improve the accuracy of the fall confirmation, and when the degree of excess is high, it is only necessary to record a shorter video to improve the rate of fall confirmation, which is conducive to subsequent timely disposal.

[0046] After confirming a fall event, an alarm is triggered immediately and a linkage handling mechanism is implemented. The framework usually includes: Monitoring alarm: The alarm screen and alarm information will pop up automatically on the monitoring client (C-end, B-end, mobile end, etc.). At the same time, the corresponding alarm pictures and videos are stored to form the corresponding alarm records for subsequent retrieval, query and analysis.

[0047] Voice intercom: Activate the voice interaction function of the camera to conduct preliminary communication with the fallen person and assess his / her condition.

[0048] Rescue linkage: The alarm signal triggers the rescue system at the same time. The rescue system automatically plans the best rescue route based on the location information of the elderly, and notifies the nearest rescue personnel (such as family members, community medical staff, nursing home caregivers, etc.) to go to the rescue site. In addition, the rescue system can also establish a communication connection with surrounding medical institutions or emergency centers to inform the elderly of the fall in advance so that the medical institutions can be prepared to receive and treat the elderly.

[0049] Information recording: All sensor data, test results, linkage process information, etc. are recorded and stored in a dedicated database for subsequent event analysis, system performance evaluation, and data support for elderly health management. For example, through statistical analysis of multiple fall event data, it is possible to find high-incidence areas and high-incidence periods for elderly falls, as well as the association between specific behavior patterns and falls, thus providing a basis for the formulation of personalized preventive measures.

[0050] Furthermore, the preset threshold is determined according to the age and physical health status of the monitored person; wherein, the preset threshold is negatively correlated with the age of the monitored person, and the preset threshold is positively correlated with the physical health status assessment value of the monitored person.

[0051] In this embodiment, the preset threshold value determined based on a large amount of experimental data and actual application scenarios is only a basic threshold value, which cannot accurately characterize the individual situation of the monitored person, which mainly includes the age and physical health status of the monitored person. Specifically, when the age of the monitored person is older, the probability of the monitored person falling is relatively greater. At this time, the preset threshold value is set to be smaller, that is, the sensitivity of fall monitoring is improved; otherwise, the preset threshold value is set to be larger to reduce the false alarm rate. And, when the physical health status evaluation value of the monitored person is larger (that is, the healthier the body), the probability of the monitored person falling is relatively smaller. At this time, the preset threshold value is set to be larger to reduce the false alarm rate; otherwise, the preset threshold value is set to be smaller to improve the sensitivity of fall monitoring. It should be noted that the present invention does not limit the specific expression form of the above-mentioned negative correlation and positive correlation.

[0052] Among them, the preset threshold can be determined on the basis of the basic threshold determined according to a large amount of experimental data and actual application scenarios, and further determined according to the adjustment coefficient obtained based on the age and physical health status of the monitored person, that is, the preset threshold = basic threshold * adjustment coefficient.

[0053] like Figure 2 As shown, the embodiment of the present invention discloses an elderly fall monitoring system based on multi-sensor fusion and trigger linkage, including a universal interface, a processing module, and a storage module; the processing module is connected to the universal interface and the storage module; The universal interface is used to receive data from different types of sensors, that is, to obtain multi-source data; The storage module is used to store executable computer program code; The processing module is used to execute the method as described in any of the preceding items by calling the executable computer program code in the storage module.

[0054] The specific functions of the elderly fall monitoring system based on multi-sensor fusion and trigger linkage in this embodiment refer to the above-mentioned embodiments. Since the system of this embodiment adopts all the technical solutions of the above-mentioned embodiments, it at least has all the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be described one by one here.

[0055] like Figure 3 As shown, an embodiment of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the method described in the above embodiment.

[0056] The embodiment of the present invention further discloses a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in the above embodiment is executed.

[0057] An embodiment of the present invention further discloses a computer program product, including a computer program stored on a non-transitory computer-readable medium, wherein the computer program is executed by a processor to perform the method described in the above embodiment.

[0058] The device / system according to an embodiment of the present invention may include a processor, a memory for storing program data and executing the program data, a permanent memory such as a disk drive, a communication port for processing communication with an external device, and a user interface device, etc. The method is implemented as a software module or can be stored on a computer-readable recording medium as a computer-readable code or program command that can be executed by a processor. Examples of computer-readable recording media may include magnetic storage media (e.g., read-only memory (ROM), random access memory (RAM), floppy disk, hard disk, etc.), optical reading media (e.g., CD-ROM, digital versatile disk (DVD), etc.), etc. The computer-readable recording medium may be distributed in a computer system connected in a network, and the computer-readable code may be stored and executed in a distributed manner. The medium may be computer-readable, stored in a memory and executed by a processor.

[0059] Embodiments of the present invention may be indicated as functional block components and various processing operations. Functional blocks may be implemented as various numbers of hardware and / or software components that perform specific functions. For example, embodiments of the present invention may implement direct circuit components that can perform various functions under the control of one or more microprocessors or other control devices, such as memory, processing circuits, logic circuits, lookup tables, etc. The components of the present invention may be implemented by software programming or software components. Similarly, embodiments of the present invention may include various algorithms implemented by a combination of data structures, processes, routines, or other programming components, and may be implemented by programming or scripting languages ​​(such as C, C++, Java, assemblers, etc.). Functional aspects may be implemented by algorithms executed by one or more processors. In addition, embodiments of the present invention may implement related technologies for electronic environment settings, signal processing, and / or data processing. Terms such as "mechanism", "element", "unit", etc. may be used extensively and are not limited to mechanical and physical components. These terms may represent a series of software routines associated with a processor, etc.

[0060] Specific embodiments are described in the present invention as examples, and the scope of the embodiments is not limited thereto.

[0061] Although embodiments of the present invention have been described, it will be appreciated by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the present invention as defined by the appended claims. Therefore, the above-described embodiments of the present invention should be interpreted as examples and do not limit the embodiments in all respects. For example, each component described as a single unit may be performed in a distributed manner, and similarly, components described as distributed may be performed in a combined manner.

[0062] All examples or exemplary terms (for example, etc.) used in the embodiments of the present invention are for the purpose of describing the embodiments of the present invention, but are not intended to limit the scope of the embodiments of the present invention.

[0063] Furthermore, unless explicitly stated otherwise, expressions such as “essential,” “important,” etc., associated with certain components may not indicate that the components are absolutely required.

[0064] It will be appreciated by those skilled in the art that the embodiments of the present invention may be implemented in modified forms without departing from the spirit and scope of the present invention.

[0065] Since the present invention allows various changes to the embodiments of the present invention, the present invention is not limited to specific embodiments, and it will be understood that all changes, equivalents and substitutes that do not depart from the spirit and technical scope of the present invention are included in the present invention. Therefore, the embodiments of the present invention described herein should be understood as examples in all aspects and should not be interpreted as limitations.

[0066] In addition, terms such as "unit", "module", etc. represent a unit that can be implemented as hardware or software or a combination of hardware and software to process at least one function or operation. "Units" and "modules" can be stored in a storage medium to be addressed, and can be implemented as a program that can be executed by a processor. For example, "units" and "modules" can refer to components such as software components, object-oriented software components, class components, and task components, and can include processes, functions, properties, procedures, subroutines, program code segments, drivers, firmware, microcodes, circuits, data, databases, data structures, tables, arrays, or variables.

[0067] In the present invention, the expression "A may include one of a1, a2 and a3" can broadly indicate that examples that may be included in element A include a1, a2 or a3. This expression should not be interpreted as being limited to the meaning that examples included in element A must be limited to a1, a2 and a3. Therefore, as examples included in element A, it should not be interpreted as excluding elements other than a1, a2 and a3. In addition, this expression indicates that element A may include a1, a2 or a3. This expression does not mean that the elements included in element A must be selected from a specific set of elements. That is to say, this expression should not be restrictively understood as indicating that a1, a2 or a3 that must be selected from the set including a1, a2 and a3 is included in element A.

[0068] Furthermore, in the present invention, the expression “at least one of a1, a2, and / or a3” means one of “a1,” “a2,” “a3,” “a1 and a2,” “a1 and a3,” “a2 and a3,” and “a1, a2, and a3.” Therefore, it should be noted that the expression “at least one of a1, a2, and / or a3” should not be interpreted as “at least one of a1,” “at least one of a2,” and “at least one of a3,” unless explicitly described as “at least one of a1, at least one of a2, and at least one of a3.”

Claims

1. A method for monitoring elderly falls based on multi-sensor fusion and trigger linkage, characterized in that: The steps include: S1, a universal interface designed to adapt to multiple types of sensors, which receives data from different types of sensors, i.e., obtains multi-source data; S2. Preprocessing the multi-source data, and obtaining a fall event monitoring value based on analysis of each single-source data; S3, using a fusion algorithm to fuse the fall event monitoring values ​​to obtain a fall event fusion value; S4. When the fall event fusion value reaches a preset threshold, a suspected fall alarm signal is triggered, and a series of linkage handling mechanisms are started.

2. According to claim 1, a method for monitoring elderly falls based on multi-sensor fusion and trigger linkage is characterized in that: Step S1 specifically includes: A universal interface is designed to adapt to various types of sensors. The universal interface forms an internal standard KV (key-value) group of key data types (key) and data values ​​(value) of various types of sensors according to the access protocols of different types of sensors, encapsulates and modularizes the KV group to form a sensor result description, and then obtains the multi-source data.

3. The elderly fall monitoring method based on multi-sensor fusion and trigger linkage according to claim 2 is characterized by: The preprocessing includes data cleaning and data calibration; wherein the data calibration is used to align the data of different types of sensors in time and space scales, and align the data of various types of sensors according to the sensor with the highest frequency.

4. The elderly fall monitoring method based on multi-sensor fusion and trigger linkage according to claim 3 is characterized by: The fusion algorithm in step S3 includes but is not limited to weighted averaging, Kalman filter, Bayesian network, and deep learning model.

5. The elderly fall monitoring method based on multi-sensor fusion and trigger linkage according to claim 4 is characterized in that: In step S4, a series of linkage handling mechanisms are initiated, including: Control the surrounding dome cameras to turn to the suspected fall area to record the video, and use the fall detection algorithm to further identify and confirm the elderly person's posture, so as to accurately identify whether the elderly person is in a real fall state or other similar fall movements; If a fall event is confirmed, a linkage handling mechanism is triggered, which includes but is not limited to at least one of monitoring alarm, voice intercom, rescue linkage, and information recording.

6. The elderly fall monitoring method based on multi-sensor fusion and trigger linkage according to claim 5 is characterized by: The preset threshold is determined according to the age and physical health status of the monitored person; wherein, the preset threshold is negatively correlated with the age of the monitored person, and the preset threshold is positively correlated with the physical health status assessment value of the monitored person.

7. An elderly fall monitoring system based on multi-sensor fusion and trigger linkage, comprising a universal interface, a processing module, and a storage module; the processing module is connected to the universal interface and the storage module; The universal interface is used to receive data from different types of sensors, that is, to obtain multi-source data; The storage module is used to store executable computer program code; Features: The processing module is used to execute the method according to any one of claims 1 to 6 by calling the executable computer program code in the storage module.

8. An electronic device comprising: A memory storing executable program code; A processor coupled to the memory; characterized in that: the processor calls the executable program code stored in the memory to execute the method according to any one of claims 1-6.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is executed.

10. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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