Fall detection method, system and device for high-integration wearable device

Abstract

The invention provides a fall detection method, system and device for a high-integration wearable device, and relates to the technical field of fall prediction, and the method comprises the steps: obtaining the acceleration and angular velocity data of a human body; estimating the Euler angle of the human body by using an extended Kalman algorithm according to the acquired acceleration and angular velocity data of the human body; setting a data threshold value of the human body acceleration as a first threshold value; when the acquired human body acceleration exceeds a first threshold value, calculating the variation of an Euler angle; setting the Euler angle variation threshold as a second threshold; and when the absolute value of the change of the Euler angle in a certain time window exceeds a second threshold value, performing fall risk early warning. And a new hardware equipment structure is constructed by using a communication module supporting secondary development. According to the invention, by optimizing the hardware architecture, the equipment size is reduced, the wearing comfort is improved, and by optimizing the tumble detection algorithm, the tumble detection precision is improved.

Description

Technical Field

[0001] The present invention belongs to the field of fall prediction technology, and in particular relates to a fall detection method, system and device for a highly integrated wearable device. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] With the continuous development of science and technology in the past few decades, high-tech products have been integrated into the daily lives of citizens. The acceptance and control of high-tech products by the elderly have significantly improved, and their demand for smart elderly care and smart elderly care products is also growing. These products can not only improve the quality of life of the elderly, but also provide necessary safety protection in emergency situations. In the process of elderly care, accidental falls often lead to serious physical injuries, and because the elderly may not be able to get up or call for help on their own, delays in treatment after a fall may have more serious consequences.

[0004] To address this issue, the smart elderly care sector needs to develop smart products that can prevent falls and respond in a timely manner. These products need to be highly intelligent and automated, able to take protective measures before the elderly fall, reduce the damage caused by falls to the human body, and notify family members or emergency rescue personnel in a timely manner after a fall occurs, so that medical treatment can be carried out as soon as possible.

[0005] At present, wearable smart devices based on inertial sensors have been tried and applied in many fields, but the penetration rate is not high. The fundamental reason is that it is difficult to make accurate decisions, the balance between missed reports and false reports is difficult to control, and falls cannot be accurately detected. At the same time, as a portable solution, how to improve the integration, reduce the size of the device, and make it more comfortable to wear while ensuring the functionality of wearable smart devices is also a problem that needs to be continuously explored and solved in the design. Summary of the invention

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a fall detection method, system and device for a highly integrated wearable device, which optimizes the hardware architecture and fall detection algorithm, can improve the accuracy of fall detection while streamlining hardware resources and reducing device size, thereby achieving dual optimization of computing performance and reducing volume.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: A first aspect of the present invention provides a fall detection method for a highly integrated wearable device.

[0008] A fall detection method for a highly integrated wearable device, comprising: Obtain human body acceleration and angular velocity data; According to the acquired human body acceleration and angular velocity data, the extended Kalman algorithm is used to estimate the Euler angle of the human body; Setting the data threshold of human body acceleration as the first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; Set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

[0009] A second aspect of the present invention provides a fall detection system for a highly integrated wearable device.

[0010] A fall detection system for a highly integrated wearable device, comprising: The data acquisition module is configured to: acquire human body acceleration and angular velocity data; The data calculation module is configured to: estimate the Euler angle of the human body by using the extended Kalman algorithm according to the acquired human body acceleration and angular velocity data; Setting the data threshold of human body acceleration as the first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; The fall warning module is configured to: set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

[0011] A third aspect of the present invention provides a highly integrated wearable device.

[0012] A highly integrated wearable device, comprising: IMU sensors, communication modules supporting secondary development, and external devices; The IMU sensor is an inertial sensor used to obtain human body acceleration and angular velocity data; The communication module supporting secondary development is specifically a highly integrated control chip that can be used for calculation, including an Internet module, a positioning module, an expandable WIFI module, and a Bluetooth module, and is used for fall detection calculation; and the positioning data of the device is obtained through the integrated positioning and communication module, and the data communication function is provided for risk warning; The IMU sensor is connected to the communication module supporting secondary development, and the acquired acceleration and angular velocity data are used for fall detection calculation; The external device includes an airbag triggering circuit, which is connected to the communication module supporting secondary development and is used to control the deployment of the airbag device.

[0013] A fourth aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in a method as described in the first aspect of the present invention are implemented.

[0014] A fifth aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in a method as described in the first aspect of the present invention.

[0015] A sixth aspect of the present invention provides a computer program product comprising instructions, which, when running on a computer, enables the computer program to implement the steps in a method as described in the first aspect of the present invention when executed by a processor.

[0016] One or more of the above technical solutions have the following beneficial effects: The present invention estimates the Euler angles of the human body by using the extended Kalman algorithm, and then applies the threshold method to achieve low overhead of the main control computing power. At the same time, it can also accurately detect falls and issue risk warnings in time after a fall occurs.

[0017] The present invention forms a new hardware architecture, using a highly integrated communication module to achieve the low power consumption, miniaturization and low cost of the device. Due to the integration of multiple functional modules, the number of required chips can be reduced without sacrificing performance, significantly reducing the size of the device, further reducing the overall power consumption, and meeting the needs of modern consumers for miniaturization and portability.

[0018] The present invention optimizes the detection algorithm by applying the threshold method and integrates it with the new hardware architecture to achieve a highly integrated device. Compared with the circuit using independent modules, the device has the advantages of small size, low cost, high computing efficiency, etc., and can also detect falls in real time.

[0019] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0021] Figure 1 This is a flow chart of a fall detection method for a highly integrated wearable device according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the structural principle of a traditional wearable device in Embodiment 3 of the present invention; Figure 3 This is a schematic diagram of the optimized highly integrated structural principle in Embodiment 3 of the present invention; Figure 4 Schematic diagram of an IMU circuit in Embodiment 3 of the present invention; Figure 5 This is a schematic diagram of a SIM card circuit in Embodiment 3 of the present invention; Figure 6 Schematic diagram of the power supply circuit in the third embodiment of the present invention; Figure 7 Schematic diagram of a buzzer circuit in Embodiment 3 of the present invention; Figure 8 This is a schematic diagram of the indicator light circuit in the third embodiment of the present invention. DETAILED DESCRIPTION

[0022] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0023] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0024] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0025] The overall idea proposed by the present invention is: By optimizing the hardware architecture, the networking module, positioning module, expandable WIFI, and Bluetooth module are highly integrated into a communication module that supports secondary development. This highly integrated module is a control chip that can be used for calculations, which is used for fall detection calculations. At the same time, it can reduce the size of the device and improve wearing comfort.

[0026] By optimizing the fall detection algorithm and improving the accuracy of fall detection, it is possible to streamline hardware resources, reduce the size of the device, and improve the accuracy of fall detection, thereby achieving dual optimization of computing performance and reducing volume.

[0027] Embodiment 1 This embodiment discloses a fall detection method for a highly integrated wearable device, which optimizes a traditional fall detection algorithm and improves the fall detection accuracy, including: Obtain human body acceleration and angular velocity data; According to the acquired human body acceleration and angular velocity data, the extended Kalman algorithm is used to estimate the Euler angle of the human body; Setting the human body acceleration data threshold as a first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; Set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

[0028] In order to explain this embodiment more clearly, Figure 1 As shown in the figure, the process of implementing fall detection through highly integrated wearable devices can be described as follows: Step 1: Obtain human body acceleration and angular velocity data.

[0029] In this embodiment, 3-axis acceleration and 3-axis angular velocity data are obtained through an IMU sensor, wherein the IMU sensor is an inertial sensor, specifically including: an accelerometer and a gyroscope.

[0030] Step 2: Estimate the Euler angle of the human body using the extended Kalman algorithm based on the acquired human body acceleration and angular velocity data.

[0031] In this embodiment, the specific steps of estimating the Euler angles of the human body using the extended Kalman algorithm are: Prediction part: ; ; Kalman gain: ; Updated part: ; ; in, yes Quaternion of attitude at the moment. The superscripts - / + represent the prior and a posteriori values ​​respectively. are the noise matrices, yes The state matrix at time, yes The measurement matrix at time, yes The measured value at the moment.

[0032] Euler angles can be expressed as: ; in, are the Euler angles of rotation around the X, Y, and Z axes, respectively. is the real part of the quaternion, Represents the imaginary part of the quaternion, composed of .

[0033] Step 3: Set the data threshold of human body acceleration to a first threshold; when the acquired human body acceleration exceeds the first threshold, calculate the change of the Euler angle.

[0034] In this embodiment, the threshold of the acquired human body acceleration data is specifically set between 6 and 12 m / s2.

[0035] Step 4: Set the Euler angle change threshold as the second threshold; when the absolute value of the Euler angle change within a certain time window exceeds the second threshold, issue a fall risk warning.

[0036] In this embodiment, the Euler angle change threshold is set as the second threshold. Specifically, by comparing the changes in the Euler angles before and after the fall and the Euler angle action range of daily behavior, the second threshold is determined to be between 30 and 50 degrees.

[0037] In this embodiment, the change amount of the Euler angle in a certain time window is expressed as the difference of the Euler angle in a certain time, and the time window is specifically 100-300 ms.

[0038] In this embodiment, the fall risk warning is specifically as follows: a buzzer on the device side emits a sound to alert pedestrians around, and sends the information to the cloud platform / App side through the networking module for information reminder.

[0039] Embodiment 2 The purpose of this embodiment is to provide a fall detection system for a highly integrated wearable device, including: The data acquisition module is configured to: acquire human body acceleration and angular velocity data; The data calculation module is configured to: estimate the Euler angle of the human body by using the extended Kalman algorithm according to the acquired human body acceleration and angular velocity data; Setting the data threshold of human body acceleration as the first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; The fall warning module is configured to: set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

[0040] Embodiment 3 The purpose of this embodiment is to provide a highly integrated wearable device, including: IMU sensors, communication modules supporting secondary development, and external devices; The IMU sensor is an inertial sensor used to obtain human body acceleration and angular velocity data; The communication module supporting secondary development is specifically a highly integrated control chip that can be used for calculation, including an Internet module, a positioning module, an expandable WIFI module, and a Bluetooth module, and is used for fall detection calculation; and the positioning data of the device is obtained through the integrated positioning and communication module, and the data communication function is provided for risk warning; The IMU sensor is connected to the communication module supporting secondary development, and the acquired acceleration and angular velocity data are used for fall detection calculation; The external device includes an airbag triggering circuit, which is connected to the communication module supporting secondary development and is used to control the deployment of the airbag device.

[0041] like Figure 3 As shown, a highly integrated wearable device specifically includes: Supports secondary development of communication modules, IMU sensors, SIM cards, buzzers, indicator lights and other external devices.

[0042] In this embodiment, the IMU sensor is an inertial sensor, and its main function is to provide 3-axis acceleration and 3-axis angular velocity data.

[0043] In this embodiment, the communication module supporting secondary development is specifically a highly integrated control chip that can be used for computing, such as a networking module, a positioning module, an expandable WIFI module, and a Bluetooth module in a traditional hardware device. By integrating these modules on a circuit board, a highly integrated module with a small size and low power consumption is formed, and this highly integrated module is used for the circuit design of a highly integrated wearable device.

[0044] Its main functions are to process the acceleration and angular velocity data provided by the IMU sensor through the chip integrated in the module, run the fall detection algorithm program, and make decisions; obtain the positioning data of the device through the positioning and communication module integrated in the module and provide data communication functions for risk warning; and control the airbag trigger circuit, buzzer, indicator light and other peripheral devices to perform their functions.

[0045] In this embodiment, the circuit design of the IMU sensor is as follows: Figure 4 When the IMU sensor acquires acceleration and angular velocity data, it is input into the communication module that supports secondary development. Since the module itself is a control chip, the acquired data can be processed by the chip to run the detection algorithm.

[0046] In this embodiment, the circuit design of the SIM card is as follows: Figure 5 It is mainly used for users to access the network and communicate with the communication module that supports secondary development through the SIM card interface.

[0047] In this embodiment, other external devices specifically include: an airbag trigger circuit and a wearing detector. The airbag trigger circuit is used to control the deployment of the airbag device. The wearing detection device mainly detects whether the highly integrated wearable device is successfully worn.

[0048] In this embodiment, the highly integrated wearable device also includes a power supply. The circuit design of the power supply part is as follows: Figure 6 As shown, the power supply is interconnected with a communication module that supports secondary development, and is used to cooperate with the software to realize charge and discharge management.

[0049] In this embodiment, a buzzer is also included, which sends out an alarm signal when it is detected that the protected object is about to fall. The circuit design of the buzzer part is as follows: Figure 7 As shown, when the secondary development communication module detects a fall risk through the detection algorithm, the buzzer on the connected device is triggered to sound to alert pedestrians around.

[0050] In this embodiment, an indicator light is also included. The circuit design of the indicator light part is as follows: Figure 8 As shown, there are three indicator lights in total. Indicator light R indicates a fault, indicator light G indicates the equipment operating status, and indicator light B indicates low battery.

[0051] In the design of modern smart devices, the optimization of hardware architecture is the key to achieving high performance, low power consumption and miniaturization. By highly integrating the networking module, positioning module, WIFI and Bluetooth module (expanded or reduced according to specific needs) with the main control MCU, and using the networking module that supports secondary development, a new hardware integration architecture is formed to achieve efficient use of hardware resources. This highly integrated module replaces the traditional discrete solution, reduces the configuration requirements of the discrete chip's own peripheral circuits, and directly reduces the size of the PCB and saves space.

[0052] In the traditional embedded field, MCU or ARM processor is usually selected as the main control, plus other circuits to form a board with control functions, and then a shell is added to form the final product.

[0053] Traditional hardware architecture design, such as Figure 2 As shown, the following functions or components are required: main control chip, IMU sensor, wearing detection, positioning module, networking module, buzzer, indicator light, charging management, WIFI and Bluetooth, airbag trigger circuit, etc.

[0054] Compared with traditional independent MCUs, the networking module, positioning module, expandable WIFI, Bluetooth module and main control chip are integrated into one module, which reduces the number of chips required, reduces the overall volume, improves portability, and meets the needs of modern consumers for miniaturization and portability.

[0055] The networking chip that supports secondary development is compared with this STM32F103 series product. The differences in performance are as follows: in terms of volume, the former is 20.2*22.2cm, and the latter is 25.5*35cm; in terms of algorithm running performance, the former is 1ms, and the latter is 4ms.

[0056] Whether in terms of hardware performance or resource configuration, the networking chip that supports secondary development is significantly better than STM32F103, providing higher processing power and richer resources. Through these optimizations, the product has been improved in computing performance and reduced size, bringing higher value to users.

[0057] Embodiment 4 The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0058] Embodiment 5 The purpose of this embodiment is to provide a computer-readable storage medium.

[0059] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0060] Embodiment 6 The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments. The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0061] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0062] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A fall detection method for a highly integrated wearable device, characterized in that: include: Obtain human body acceleration and angular velocity data; According to the acquired human body acceleration and angular velocity data, the extended Kalman algorithm is used to estimate the Euler angle of the human body; Setting the data threshold of human body acceleration as the first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; Set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

2. A fall detection method for a highly integrated wearable device as claimed in claim 1, characterized in that: The human body acceleration and angular velocity data are obtained by, specifically, obtaining 3-axis acceleration and 3-axis angular velocity data through an IMU sensor; wherein the IMU sensor specifically includes an accelerometer and a gyroscope.

3. A fall detection method for a highly integrated wearable device as claimed in claim 1, characterized in that: The setting of the Euler angle change threshold as the second threshold is specifically to determine that the second threshold is between the action intervals by comparing the changes of the Euler angles before and after the fall and the action intervals of the Euler angles in daily behavior; The change in the Euler angles within a certain time window is specifically expressed as the difference in the Euler angles within a certain time window.

4. A fall detection system for a highly integrated wearable device, characterized in that: include: The data acquisition module is configured to: acquire human body acceleration and angular velocity data; The data calculation module is configured to: estimate the Euler angle of the human body by using the extended Kalman algorithm according to the acquired human body acceleration and angular velocity data; Setting the data threshold of human body acceleration as the first threshold; When the acquired human body acceleration exceeds a first threshold, calculating a change in the Euler angle; The fall warning module is configured to: set the Euler angle change threshold as the second threshold; When the absolute value of the Euler angle change within a certain time window exceeds the second threshold, a fall risk warning is issued.

5. A highly integrated wearable device, characterized in that: include: IMU sensors, communication modules supporting secondary development, and external devices; The IMU sensor is an inertial sensor used to obtain human body acceleration and angular velocity data; The communication module supporting secondary development is specifically a highly integrated control chip that can be used for calculation, including an Internet module, a positioning module, an expandable WIFI module, and a Bluetooth module, and is used for fall detection calculation; and the positioning data of the device is obtained through the integrated positioning and communication module, and the data communication function is provided for risk warning; The IMU sensor is connected to the communication module supporting secondary development, and the acquired acceleration and angular velocity data are used for fall detection calculation; The external device includes an airbag triggering circuit, which is connected to the communication module supporting secondary development and is used to control the deployment of the airbag device.

6. A highly integrated wearable device as claimed in claim 5, characterized in that: The external device also includes a wearing detection device for detecting whether the highly integrated wearable device is successfully worn.

7. A highly integrated wearable device as claimed in claim 5, characterized in that: It also includes a buzzer and an indicator light; wherein the buzzer is used to send out an alarm signal when it detects that the protected object is about to fall; and the indicator light is used to indicate the status of the device.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 3 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 3 are performed.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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