WO2019015556A1 - Terminal motion state analysis method, mobile terminal and readable storage medium - Google Patents

Abstract

Disclosed in the present invention are a terminal motion state analysis method, a mobile terminal and a readable storage medium. The terminal motion state analysis method comprises the following steps: acquiring motion data collected by a motion sensor of a terminal and pre-processing the motion data to obtain effective motion data; obtaining an acceleration standard deviation of the terminal in the effective motion data and calculating to obtain a background noise value of the terminal according to the acceleration standard deviation; and determining the motion state of the terminal according to a comparison state of the acceleration standard deviation and the background noise value and a time of duration corresponding to the comparison state. The method can precisely determine the motion state of a terminal by means of a simple device, and therefore can play a significant role in the field of burglary prevention of terminals.

Description

Terminal motion state analysis method, mobile terminal and readable storage medium Technical field

The present invention relates to the field of communications, and in particular, to a terminal motion state analysis method, a mobile terminal, and a readable storage medium.

Background technique

With the development of motion sensors, people can obtain more and more accurate related motion information data through motion sensors, and by calculating and analyzing the acquired motion information data, information about the corresponding motion state can be obtained. This development of anti-theft and other related technologies is also becoming more mature.

However, because of the ability to obtain very accurate motion information, the price is often unsatisfactory, so that the price of the corresponding devices and equipment is also rising. However, the collection of motion information by simple sensors often only results in less data, while less data leads to poor results such as low accuracy of calculation results.

Summary of the invention

The main object of the present invention is to provide a method for analyzing a state of motion of a terminal, which aims to solve the problem that the motion state of the terminal cannot be accurately determined when the motion sensor of the low price is judged.

To achieve the above objective, the present invention provides a terminal motion state analysis method, and the terminal motion state analysis method includes the following steps:

Obtaining motion data collected by a motion sensor of the terminal, and pre-processing the motion data to obtain valid motion data;

Obtaining the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal by the acceleration standard deviation;

The motion state of the terminal is determined according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state.

Optionally, the step of pre-processing the motion data to obtain valid motion data includes:

The collected motion data is separately and once differentiated. If the absolute value of the differential result is greater than the preset maximum effective value, it is determined that the collected motion data is invalid data: if the absolute value of the differential result is less than or equal to the preset The maximum effective value determines that the collected motion data is valid data:

Each vector data in the valid data is converted into scalar data by a preset conversion method, and the scalar data is used as effective motion data.

Optionally, the step of converting each vector data in the valid data into scalar data by using a preset conversion method, and using the scalar data as the effective motion data further includes:

When detecting that the acceleration in the effective motion data is greater than a preset maximum threshold, detecting whether the acceleration is less than a preset minimum threshold after being greater than the preset maximum value;

If the acceleration is less than the preset minimum threshold after being greater than the preset maximum value, it is determined that the motion state of the terminal is an emergency event state.

Optionally, the step of obtaining the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal by the acceleration standard deviation includes:

The current time back noise value is obtained by multiplying the back noise value of the previous time and the subtracted transition coefficient by the product of the acceleration standard deviation and the transition coefficient, wherein the transition coefficient determines the influence of the acceleration standard deviation on the current time back noise value, wherein The initial back noise value is a preset value.

Optionally, the step of the current time back noise value obtained by multiplying the back noise value of the previous time and the subtracted transition coefficient by the product of the acceleration standard deviation and the transition coefficient comprises:

Calculate the back noise value of the terminal according to the following formula, where the formula is:

BackgroundNoise _new =BackgroundNoise _old *(1-k)+StdDev(acc)*k

The BackgroundNoise _old is the unupdated back noise value, the initial value is 0.1; StdDev(acc) is the standard deviation of the acceleration, k is the transition coefficient of the back noise value, the initial value is 0.05, and the value range is [O, l], BackgroundNoise _new is the updated back noise value.

Optionally, the step of determining the motion state of the terminal according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state includes:

When it is detected that the comparison state of the acceleration standard deviation and the back noise value satisfies a preset movement threshold, it is determined that the terminal is currently in a moving state;

After determining that the terminal is in the moving state, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset end threshold value, and the duration of the end threshold value is greater than the preset end threshold time, it is determined that the terminal movement state ends.

Optionally, after the step of determining that the terminal is in a moving state, the method further includes:

After determining that the current state of motion is satisfied, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset artificial motion threshold value, and the duration of the artificial motion threshold value is greater than the preset artificial motion critical time, the current terminal is determined. The state of motion is artificially taken away.

Optionally, the comparison state of the acceleration standard deviation and the back noise value meets a preset movement threshold value:

StdDev(acc)>n1*BackgroundNoise∧StdDev(acc)>BackgroundNoise+min.threshold _movement

The comparison state of the acceleration standard deviation and the back noise value satisfies a preset end threshold value:

StdDev(acc)<n2*BackgroundNoise∨StdDev(acc)<BackgroundNoise+min.threshold _movement

The comparison state of the acceleration standard deviation and the back noise value satisfies a preset artificial motion threshold value, and the duration of the artificial motion threshold value is greater than the preset artificial motion critical time:

StdDev(acc)>n3*BackgroundNoise∧Time _movement >3

Where StdDev(acc) is the standard deviation of acceleration, BackgroundNoise is the calculated back noise value, n1, n2, and n3 are comparison coefficients, and the magnitude relationship is n3>n2>n1, and min.threshold _movement is the preset minimum moving threshold. Time _movement is the duration.

In addition, to achieve the above object, the present invention further provides a mobile terminal, the mobile terminal comprising: a memory, a processor, and a terminal motion state analysis program stored on the memory and operable on the processor, The steps of the terminal motion state analysis method as described above are implemented when the terminal motion state analysis program is executed by the processor.

In addition, in order to achieve the above object, the present invention further provides a computer readable storage medium, where the terminal motion state analysis program is stored, and the terminal motion state analysis program is implemented by the processor as described above. The steps of the terminal motion state analysis method.

According to the terminal motion state analysis method proposed by the present invention, motion data is collected by a relatively inexpensive three-axis sensor, and the effective data in the motion data is refined through filtering in multiple steps. Moreover, the motion data in the dynamic background can be processed, thereby eliminating the negative influence of the motion of the dynamic background on the operation result, and the calculation accuracy of the terminal is greatly improved. Achieving the need to accurately determine the state of motion of the terminal at a low cost.

DRAWINGS

1 is a schematic structural diagram of a terminal in a hardware operating environment according to an embodiment of the present invention;

2 is a schematic flowchart of a first embodiment of a method for analyzing a motion state of a terminal according to the present invention;

3 is a schematic flow chart of the steps of the S10 in FIG. 2;

4 is a schematic flow chart of a second embodiment of a method for analyzing a motion state of a terminal according to the present invention;

FIG. 5 is a schematic flowchart diagram of a third embodiment of a method for analyzing a motion state of a terminal according to the present invention.

The implementation, functional features, and advantages of the present invention will be further described in conjunction with the embodiments.

Detailed ways

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

As shown in FIG. 1, FIG. 1 is a schematic structural diagram of a terminal in a hardware operating environment according to an embodiment of the present invention.

The terminal of the embodiment of the present invention may be a portable device and a wearable device PC, or may be a smart phone, a tablet computer, an e-book reader, and a MP3 (Moving Picture Experts Group Audio Layer III) player. MP4 (Moving Picture Experts Group Audio Layer IV) is a portable terminal device with a display function such as a player or a portable computer.

As shown in FIG. 1, the terminal may include a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to implement connection communication between these components. The user interface 1003 can include a display, an input unit such as a keyboard, and the optional user interface 1003 can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a WI-FI interface). The memory 1005 may be a high speed RAM memory or a non-volatile memory such as a disk memory. The memory 1005 can also optionally be a storage device independent of the aforementioned processor 1001.

Optionally, the terminal may further include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a Bluetooth, a WiFi module, and the like. Among them, sensors such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display according to the brightness of the ambient light, and the proximity sensor may turn off the display and/or when the mobile terminal moves to the ear. Backlighting. As a kind of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (usually three axes), and can detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the mobile terminal (such as horizontal and vertical screen switching, Related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc. No longer.

It will be understood by those skilled in the art that the terminal structure shown in FIG. 1 does not constitute a limitation to the terminal, and may include more or less components than those illustrated, or a combination of certain components, or different component arrangements.

As shown in FIG. 1, a memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a terminal motion state analysis program.

In the terminal shown in FIG. 1, the network interface 1004 is mainly used to connect to the background server and perform data communication with the background server; the user interface 1003 is mainly used to connect the client (user end), and perform data communication with the client; and the processor 1001 can be used to call the terminal motion state analysis program stored in the memory 1005 and perform the following operations:

When the motion sensor collects the motion data of the terminal, the motion state of the terminal is analyzed, and the motion state analysis of the terminal includes the following steps:

Obtaining motion data collected by a motion sensor of the terminal, and pre-processing the motion data to obtain valid motion data;

Obtaining the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal by the acceleration standard deviation;

The motion state of the terminal is determined according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state.

Further, the processor 1001 may call the motion state of the terminal stored in the memory 1005 to analyze the application, and further perform the following operations:

The step of pre-processing the motion data to obtain valid motion data includes:

The collected motion data is separately and once differentiated. If the absolute value of the differential result is greater than the preset maximum effective value, it is determined that the collected motion data is invalid data; if the absolute value of the differential result is less than or equal to the preset The maximum effective value determines that the collected motion data is valid data:

Each vector data in the valid data is converted into scalar data by a preset conversion method, and the scalar data is used as effective motion data.

Referring to FIG. 2, a first embodiment of the present invention provides a terminal motion state analysis method, where the terminal motion state analysis method includes the following steps:

Step S1O, acquiring motion data collected by a motion sensor of the terminal, and pre-processing the motion data to obtain valid motion data;

Step S20, obtaining an acceleration standard deviation of the terminal in the effective motion effect data, and calculating a back noise value of the terminal by the acceleration standard deviation;

Step S30, determining the motion state of the terminal according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state.

Specifically, the terminal collects the motion information by using the motion sensor, and filters the motion data, and filters invalid data such as erroneous data and emergency event data in the motion data by using a preset filtering algorithm to obtain effective motion data. data. After the valid data is obtained, the acceleration in the valid data is obtained, and the standard deviation of the acceleration is calculated. After obtaining the standard deviation of the acceleration, the back noise value of the dynamic environment is calculated according to the corresponding calculation formula. The back noise value is a parameter, which is calculated from the standard deviation of the acceleration according to the back noise value calculation formula, and is used to describe the motion state of the environment. After the back noise value is obtained, the back noise value is compared with the standard deviation of the acceleration, and whether the terminal is in motion state can be determined whether the comparison relationship between the two meets the preset correspondence relationship.

When the motion sensor collects motion data, some of the data is more or less invalid data for various reasons. There are many reasons why the collected data is invalid data. For example, the quality, environment, design and other factors of the motion sensor chip may cause invalid data in the output motion data. Well-designed, sensitive sports high-quality sensors are expensive, and the use of expensive motion sensors in the civilian sector leads to a significant increase in costs and an increase in the price of the final product, which is not beneficial to both the enterprise and the user. Case. When enjoying the price advantage brought by the cheaper motion sensor, it is inevitable to face how to filter the invalid data from the collected data and extract the valid data for subsequent application.

After the valid data in the motion data is acquired, the acceleration standard deviation in the valid data is calculated. The back noise value is calculated based on the standard deviation of the acceleration. The back noise value is the amount used to describe the motion in the current dynamic environment. For example, in the subway, the subway itself is sporty, and the terminal will have the same movement as the subway on the subway. Although the motion data brought by the subway motion is not invalid data, the motion data brought by the subway is not the motion of the terminal itself. Therefore, when calculating and analyzing the motion state of the terminal, the motion data brought by the motion of the dynamic environment such as the subway will Influencing and interfering with the conclusions reached. The back noise value changes as the acceleration changes. Because the motion of the dynamic environment is also changing, the acceleration caused by it also changes, so the back noise value needs to be updated in real time, so as to more accurately describe the motion data of the dynamic environment.

Through the formula relationship, the back noise value of the current dynamic environment is calculated from the standard deviation of the acceleration. The back noise value is the amount describing the current environmental motion data. For example, in the subway environment, the back noise value describes the motion of the subway. By adding the dynamic environment motion data to the baseline of the calculation, it is possible to eliminate the influence of the dynamic environment on the judgment of the terminal motion state (for example, when calculating the weight, if the weight is already loaded, the weight is subtracted, or the weight is added to the baseline. In order to get accurate weight data, instead of starting from 0). The acceleration standard deviation is compared with the back noise value, and the motion state of the terminal is judged according to the comparison relationship between the two. When the comparison relationship between the two conditions satisfies the condition of the terminal movement, it is determined that the terminal is in the moving state, and when the motion state duration of the terminal satisfies the determination of the continuous movement (in the duration, if the stop condition is satisfied, the subsequent judgment is terminated, and the determination is made. The terminal movement has been stopped), and whether the comparison relationship between the acceleration standard deviation and the back noise value satisfies the comparison relationship of the artificial motion (because the invention is mainly used in the anti-theft field, the human movement refers to the human being to steal and take away), if When the two satisfy the comparison relationship of the artificial motion, it is determined that the terminal is artificially moved.

The invention collects the motion data of the terminal through the motion sensor installed in the terminal, analyzes and filters the data through the main control chip, and achieves the purpose of judging the motion state of the terminal, thereby realizing the function of theft prevention of the terminal. However, in the use of the motion sensor of the present invention, a relatively inexpensive sensor such as a three-axis sensor can be used without using an expensive and precise motion sensor such as a six-axis sensor, thereby greatly reducing the manufacturing cost of the terminal. With the problem of invalid data in the motion data, the present invention performs multiple filtering processing on the motion data collected by the motion sensor by the algorithm, and the data caused by the hardware problem, the instantaneous large-scale change data of the sudden situation, and the like. Invalid data filtering to fill the gaps caused by the sensor. Moreover, the present invention can filter motion data in a dynamic environment by an algorithm to eliminate adverse effects of environmental factors on analysis and judgment. The invention adopts a low-cost motion sensor, so the manufacturing cost is low, and the invalid data is removed by filtering multiple motion data, the adverse effects brought by the low-cost sensor are eliminated, and the accurate judgment can be made in the dynamic environment. The accuracy of the judgment and the user experience when the user is using.

Further, referring to FIG. 3, the step of pre-processing the motion data in step S10 to obtain valid motion data includes:

Step S11, performing the first and second differentiation on the collected motion data respectively. If the absolute value of the differential result is greater than the preset maximum effective value, determining that the collected motion data is invalid data; if the absolute value of the differential result is less than or equal to The preset maximum effective value determines that the collected motion data is valid data:

Step S12, converting each vector data in the valid data into scalar data by using a preset conversion method, and using the scalar data as effective motion data.

Specifically, after the motion sensor acquires the motion data, the acceleration in the motion data is first differentiated, and the acceleration changes with time. Because of the physical limit of human physique, that is, the acceleration of human motion (referring to the motion caused by the body itself without using external force and equipment) has a theoretical maximum, and the limit of the acceleration variation with time is defined as the theoretical maximum. When the change of the acceleration with time is greater than the theoretical maximum value, it means that the acceleration change is abnormal or non-human, so that all the data exceeding the theoretical maximum value of the acceleration over time is determined as invalid data. After the first differentiation, the second differential of acceleration is continued, and the second differential is used to prevent data overflow. Due to the design problem of some motion sensors, the number of bytes in the output data is insufficient to express the value, and data will appear. The situation of overflow. For example, the maximum value of a 1-byte expressed integer number is 127. When it is necessary to express 128 by 1 byte, a value of -128 is obtained, which becomes a data overflow. The characteristic of data overflow is that the data jumps suddenly from a large positive (negative) value to a large negative (positive) value. In order for the algorithm to function properly under motion sensors with data overflow problems, the overflowed data needs to be filtered.

The motion data collected by the currently used sensors such as the three-axis sensor is the data of each motion direction (the three-axis sensor is the motion data on the xyz three-axis), and the directionality of the motion data in each direction is calculated. , resulting in complication of the calculation, so the present invention transforms the motion data in all directions, using a simple formula acc _x ² +acc _y ² +acc _z ² =acc ² to convert the vector with direction into a non-directional scalar To make subsequent calculations simple.

The invention filters the data through the human limit of the motion data, the storage rule of the device, filters the invalid data collected by the motion sensor to obtain valid data, and then uses the simple conversion to move the motion data in all directions in the effective data. From vector to scalar, effective motion data is obtained, and effective motion data can greatly simplify subsequent calculation and analysis and obtain higher accuracy.

Further, referring to FIG. 3, after step S12, the method further includes:

Step S13, when it is detected that the acceleration in the effective motion data is greater than a preset maximum threshold, detecting whether the acceleration is less than a preset minimum threshold after being greater than the preset maximum value:

In step S14, if the acceleration is less than the preset minimum threshold after being greater than the preset maximum value, it is determined that the motion state of the terminal is an emergency event state.

Specifically, in the process of use, in addition to invalid data, there will be many unexpected situations. The motion data of the unexpected situation is not invalid data, but it has the effect of interference for the final analysis and calculation, so it is necessary to make an emergency. The motion data is filtered. Sudden events such as sudden accidental falling of an object, being in a vehicle, sudden sudden braking or rapid acceleration of the vehicle, and the like. The characteristics of emergencies in the motion data are: the acceleration changes in two very short periods of time and very large changes. In short, it is detected that the acceleration suddenly increases and reaches a very large value (greater than the pre- Set the maximum value), then the acceleration becomes a very large value in the opposite direction (less than the preset minimum). Therefore, by checking the amount of change in the acceleration in the effective motion data, when it is found that the amount of change is greater than the preset threshold, it is further detected whether the acceleration is greater than the preset minimum threshold after the acceleration is greater than the preset maximum value, if the acceleration is greater than After the preset maximum value and the acceleration is less than the preset minimum threshold value, the motion law of the effective motion data is consistent with the law of the sudden motion, so that the motion state of the terminal at this time is determined to be a sudden motion.

After filtering the overflow and the erroneous data, the present invention will filter the case where the motion data caused by the unexpected situation fluctuates greatly. The terminal motion caused by the sudden situation has obvious characteristics of the motion data, and the analysis of such motion data does not bring benefits to the purpose of the terminal for theft prevention, etc., so the motion data of such sudden motion motion is Filtering further simplifies the subsequent calculations and analysis steps. At the same time, because the movement characteristics of the emergency have certain similarities with the characteristics of the human movement, the meaning is different (the artificial possibility is that the sudden movement is not the risk of theft before being stolen), so the movement of the sudden movement Data filtering can improve the accuracy of judging the state of motion of the terminal.

Further, referring to FIG. 4, in the second embodiment of the present invention, the step of acquiring the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal by the acceleration standard deviation includes:

Step S21, the current time back noise value is obtained by multiplying the back noise value of the previous time plus the product standard deviation of the acceleration and the subtracted transition coefficient and the transition coefficient, wherein the transition coefficient determines the acceleration standard deviation to the current time back noise value. Effect, where the initial back noise value is the preset value.

Specifically, the back noise value changes according to the motion data of the dynamic environment, and the date of updating the current dynamic environment back noise value in real time has been reached. In the calculation, the influence of the acceleration standard deviation on the current time back noise value is determined by the transition coefficient, wherein the acceleration standard deviation refers to the acceleration standard deviation at the current time.

The back noise value is calculated from the standard deviation of the acceleration obtained in the effective motion data. The back noise value is an amount used to describe the motion state of the dynamic environment, and the back noise value is also updated in real time to adapt to the change of the motion state of the dynamic environment, ensuring that the back noise value can accurately perform the motion state of the dynamic environment. description. When calculating and analyzing the motion state of the effective motion data, the back noise value will form a new baseline with the initial baseline.

The baseline is a scale parameter or mark in the calculation, and in the present invention, the initial baseline for judging the motion state of the terminal is a stationary state, that is, the baseline is at a stationary state, but in the actual calculation, when in a dynamic environment, the dynamic environment The motion data is collected by the motion sensor of the terminal, causing interference in the calculation. Adding the back noise value to the baseline solves this problem by adding motion data from the dynamic environment to the baseline, depending on the dynamic environment. By calculating the back noise value of the dynamic environment, the error of the motion data detected in the dynamic environment is solved, and the accuracy of the analysis of the motion state of the terminal is improved.

Further, step S21 includes:

Step S211, calculating a back noise value of the terminal according to the following formula, where the formula is:

BackgroundNoise _new =BackgroundNoise _old *(1-k)+StdDev(acc)*k

The BackgroundNoise _old is the unupdated back noise value, the initial value is 0.1; StdDev(acc) is the standard deviation of the acceleration, k is the transition coefficient of the back noise value, the initial value is 0.05, and the value range is [O, l], BackgroundNoise _new is the updated back noise value.

Specifically, the calculation formula of the back noise value is as shown above, wherein BackgroundNoise _old is an _unupdated back noise value, and the initial value is 0.05 (ie, the environment is a stationary state). StdDev(acc) is the standard deviation of acceleration, and the acceleration is obtained from the effective motion data. The transition coefficient k is used to determine the transition relationship between the current environment dynamic environment and the dynamic environment of the past time. When k is the minimum value, the current environmental back noise value is the same as the past time noise value; and when k takes the maximum value, the current time The back noise value has the least dependence on the back noise value in the past, which can be understood as the current back noise value as a new back noise value. The value of k is related to the comparison of the back noise value and the effective motion data. The transition coefficient k enables the back noise value to transition from the old environment to the new environment more smoothly when the environment changes.

Further, referring to FIG. 5, in the third embodiment of the present invention, the step of determining the motion state of the terminal according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state includes:

Step S31, when it is detected that the comparison state of the acceleration standard deviation and the back noise value meets the preset movement threshold, it is determined that the terminal is currently in the moving state;

Step S311, after determining that the terminal is in the moving state, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset end threshold value, and the duration of the end threshold value is greater than the preset end critical time, determining the terminal movement state End.

Specifically, after the back noise value is obtained, when the comparison relationship between the acceleration standard deviation and the back noise value is greater than the preset movement threshold, it is determined whether the terminal is in a moving state, and the moving state indicates that the terminal currently has a significant displacement. After determining that the terminal is in the moving state, the mobile state is continuously monitored. When the comparison between the acceleration standard deviation and the back noise value is less than the preset end threshold, that is, the end condition is satisfied, it is determined that the mobile state of the terminal ends.

When judging the motion state of the terminal, it is first determined whether the terminal is in a moving state. After determining that the terminal is in the mobile terminal, it is specifically determined whether the current motion is an artificially taken away motion. Therefore, a certain acceleration or speed condition is satisfied, and it is determined that the terminal is in a moving state. However, if the mobile terminal has a very short duration (less than a preset time) in the moving state or the motion data such as acceleration rapidly decreases (the comparison between the acceleration standard deviation and the back noise value is less than the preset end threshold), then It indicates that the terminal has made a short and small displacement, and the tiny displacement does not match the characteristics of the artificial take-off movement. Therefore, the motion whose duration is less than the critical time of motion is not the movement taken by man. In the present invention, the motion state of the terminal is judged by the comparison relationship between the acceleration standard deviation and the back noise value, and the minute motion that does not satisfy the artificial motion condition can be excluded, the operation is simple, and the result accuracy is high. Further, referring to FIG. 5, after step S31, the method further includes:

Step S312, after determining that the current state of being moved, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset artificial motion threshold value, and the duration of the artificial motion threshold value is greater than the preset artificial motion critical time, then determining The current state of motion of the terminal is artificially taken away.

Specifically, after the terminal maintains the moving state, it is determined whether the motion of the terminal is caused by the human motion. Through the observation and research of the laws of human movement, when walking or running, the movement has obvious laws (for example, when walking, the acceleration of the foot is higher when the step is raised, and the acceleration is smaller when the foot is stepping down. Therefore, the acceleration is also uniformly changed) and is continued. According to the characteristics of human motion, it is judged whether the terminal is in the motion state of artificial motion by comparing the standard deviation of acceleration with the value of back noise. And when the terminal satisfies the motion state of the human motion, detecting the duration of the state of the human motion, and if the duration also satisfies the preset condition (greater than the motion critical time), determining that the current motion state of the terminal is artificial motion status.

The main purpose of the present invention is for theft prevention of the terminal, so the detection of the motion state of the terminal is also based on the characteristics of theft, and it is judged whether it is moved (his stolen) → judging whether it is a human movement (the criminals carrying the terminal after theft escape) . Therefore, after being in a moving state, it is necessary to detect whether or not to perform an artificial exercise. It is still judged by the comparison between the standard deviation of the acceleration and the back noise value. When the comparison relationship between the two is greater than the artificial motion threshold and the duration of the artificial motion threshold is greater than the preset artificial motion critical time, the terminal motion state is artificial. Movement state. The standard state of the acceleration can be used to judge the motion state of the terminal, and the principle is simple and the work efficiency is high.

Further, the comparison state of the acceleration standard deviation and the back noise value satisfies a preset movement threshold value:

StdDev(acc)>n1*BackgroundNoise∧StdDev(acc)>BackgroundNoise+min.threshold _movement

The comparison state of the acceleration standard deviation and the back noise value satisfies a preset end threshold value:

StdDev(acc)<n2*BackgroundNoise∨StdDev(acc)<BackgroundNoise+min.threshold _movement

The comparison state of the acceleration standard deviation and the back noise value satisfies a preset artificial motion threshold value, and the duration of the artificial motion threshold value is greater than the preset artificial motion critical time:

StdDev(acc)>n3*BackgroundNoise∧Time _movement >3

Where StdDev(acc) is the standard deviation of acceleration, BackgroundNoise is the calculated back noise value, n1, n2, and n3 are comparison coefficients, and the magnitude relationship is n3>n2>n1, and min.threshold _movement is the preset minimum moving threshold. Time _movement is the duration.

Specifically, in the formula for determining whether the terminal is in motion, the acceleration standard deviation is greater than the movement threshold (composed of the product of the comparison coefficient n1 and the back noise value) and is greater than the lowest movement threshold to determine the movement, wherein the comparison coefficient n1 is preset The initial value is 3; when it is judged whether the moving state is over, the acceleration standard deviation is smaller than the ending critical value (composed of the product of the comparison coefficient n2 and the back noise value) and is greater than the lowest moving threshold to determine the movement, wherein the comparison coefficient n2 is preset The initial value is 1.5; when judging whether the terminal is in the artificial motion state, the artificial standard value of the acceleration standard deviation is greater than the artificial motion threshold (composed of the product of the comparison coefficient n3 and the back noise value) and the duration of the comparison relationship is more than 3 seconds, wherein The comparison coefficient n3 presets an initial value of 4. N1, n2, and n3 can be adjusted according to the actual situation of the terminal and the environment to adapt to various situations. By comparing the state of the acceleration standard deviation with the back noise value, the conditions required for the conclusion are very simple (only need to obtain motion data), and the operation is fast (the formula is simple, no complicated operation). Therefore, the motion state of the terminal can be quickly detected, which has great significance for the use of theft prevention and the like.

In addition, an embodiment of the present invention further provides a computer readable storage medium, where the terminal readable state analysis program is stored, and when the terminal motion state analysis program is executed by the processor, the following operations are implemented:

The invention also provides a mobile terminal for analyzing terminal motion state.

The mobile terminal for analyzing the motion state of the base terminal of the present invention comprises: a memory, a processor, and a terminal motion state analysis program stored on the memory and operable on the processor, wherein the terminal motion state analysis program is processed by the terminal The terminal motion state analysis method steps as described above are implemented when the device is executed.

For the method that is implemented when the terminal motion state analysis program of the prompt information running on the processor is executed, refer to various embodiments of the method for analyzing the motion state of the terminal of the present invention, and details are not described herein again.

Furthermore, embodiments of the present invention also provide a computer readable storage medium.

The computer readable storage medium of the present invention stores a terminal motion state analysis program, and the terminal motion state analysis program is executed by the processor to implement the steps of the terminal motion state analysis method as described above.

For the method implemented when the display program of the prompt information running on the processor is executed, refer to various embodiments of the terminal motion state analysis method of the present invention, and details are not described herein again.

It is to be understood that the term "comprises", "comprising", or any other variants thereof, is intended to encompass a non-exclusive inclusion, such that a process, method, article, or It also includes other elements that are not explicitly listed, or elements that are inherent to such a process, method, item, or system. An element defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in a process, method, article, or system that includes the element, without further limitation.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, portions of the technical solution of the present invention that contribute substantially or to the prior art may be embodied in the form of a software product stored in a storage medium (such as a ROM/RAM as described above). , a disk, an optical disk, including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present invention.

The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand Modifications or equivalent substitutions are within the scope of the invention.

Claims (10)

1. A terminal motion state analysis method, characterized in that the terminal motion state analysis method comprises the following steps:

   Obtaining motion data collected by a motion sensor of the terminal, and pre-processing the motion data to obtain valid motion data;

   Obtaining the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal by the acceleration standard deviation;

   The motion state of the terminal is determined according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state.
2. The terminal motion state analysis method according to claim 1, wherein the step of pre-processing the motion data to obtain valid motion data comprises:

   The collected motion data is separately and once differentiated. If the absolute value of the differential result is greater than the preset maximum effective value, it is determined that the collected motion data is invalid data: if the absolute value of the differential result is less than or equal to the preset maximum The effective value determines that the collected motion data is valid data;

   Each vector data in the valid data is converted into scalar data by a preset conversion method, and the scalar data is used as effective motion data.
3. The terminal motion state analysis method according to claim 2, wherein the vector data in the valid data is converted into scalar data by a preset conversion method, and the scalar data is used as an effective motion data step. include:

   When it is detected that the acceleration in the effective motion data is greater than a preset maximum threshold, detecting whether the acceleration is greater than a preset minimum threshold after the acceleration is greater than a preset maximum value;

   If the acceleration is less than the preset minimum threshold after the acceleration is greater than the preset maximum value, it is determined that the motion state of the terminal is an emergency event state.
4. The terminal motion state analysis method according to claim 1, wherein the step of acquiring the acceleration standard deviation of the terminal in the effective motion effect data, and calculating the back noise value of the terminal from the acceleration standard deviation comprises:

   The current time back noise value is obtained by multiplying the back noise value of the previous time and the subtracted transition coefficient by the product of the acceleration standard deviation and the transition coefficient, wherein the transition coefficient determines the influence of the acceleration standard deviation on the current time back noise value.
5. The terminal motion state analysis method according to claim 4, wherein the current time back noise value is a product of a back noise value of a previous time and a subtracted transition coefficient plus a product of an acceleration standard deviation and a transition coefficient. The steps obtained include:

   Calculate the back noise value of the terminal according to the following formula, where the formula is:

   BackgroundNoise _new =BackgroundNoise _old *(1-k)+StdDev(acc)*k

   The BackgroundNoise _old is the unupdated back noise value, the initial value is 0.1; StdDev(acc) is the standard deviation of the acceleration, k is the transition coefficient of the back noise value, the initial value is 0.05, and the value range is [O, l], BackgroundNoise _new is the updated back noise value.
6. The terminal motion state analysis method according to claim 1, wherein the determining the motion state of the terminal according to the comparison state of the acceleration standard deviation and the back noise value and the duration corresponding to the comparison state comprises:

   When it is detected that the comparison state of the acceleration standard deviation and the back noise value satisfies a preset movement threshold, it is determined that the terminal is currently in a moving state;

   After determining that the terminal is in the moving state, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset end threshold value, and the duration of the end threshold value is greater than the preset end threshold time, it is determined that the terminal movement state ends.
7. The terminal motion state analysis method according to claim 6, wherein the step of determining that the terminal is in a moving state further comprises:

   After determining that the current state of motion is satisfied, if the comparison state of the acceleration standard deviation and the back noise value satisfies the preset artificial motion threshold value, and the duration of the artificial motion threshold value is greater than the preset artificial motion critical time, the current terminal is determined. The state of motion is artificially taken away.
8. The terminal motion state analysis method according to claim 6 or 7, wherein the comparison state of the acceleration standard deviation and the back noise value satisfies a preset movement threshold value:

   StdDev(acc)>n1*BackgroundNoise∧StdDev(acc)>BackgroundNoise+min.threshold _movement

   The comparison state of the acceleration standard deviation and the back noise value satisfies a preset end threshold value:

   StdDev(acc)<n2*BackgroundNoise∨StdDev(acc)<BackgroundNoise+min.threshold _movement

   The comparison state of the acceleration standard deviation and the back noise value satisfies a preset artificial motion threshold value, and satisfies the human motion

   The duration of the threshold is greater than the preset artificial motion critical time:

   StdDev(acc)>n3*BackgroundNoise∧Time _movement >3

   Where StdDev(acc) is the standard deviation of acceleration, BackgroundNoise is the calculated back noise value, n1, n2, and n3 are comparison coefficients, and the size is n3>n2>n1, and min.threshold _movement is the preset minimum moving threshold. Time _movement is the duration.
9. A mobile terminal, comprising: a memory, a processor, and a terminal motion state analysis program stored on the memory and operable on the processor, the terminal motion state analysis program being The step of implementing the terminal motion state analysis method according to any one of claims 1 to 8 when the processor is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a terminal motion state analysis program, and the terminal motion state analysis program is executed by the processor to implement any one of claims 1 to The steps of the terminal motion state analysis method described in the section.

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