CN113793476A - Old people falling detection method - Google Patents

Abstract

The invention discloses a method for detecting falling of old people, which is characterized in that moving body posture data are obtained through a six-axis sensor to realize detection of body postures; preprocessing and attitude fusion processing are carried out on six-axis data acquired and transmitted by the six-axis sensor in real time; extracting a plurality of characteristic values; and comparing the extracted characteristic value with a set threshold value, if the characteristic value meets a falling condition, judging that the falling phenomenon occurs, and if the characteristic value does not meet the falling condition, judging that the falling phenomenon does not occur. According to the invention, the three-axis accelerations Ax, Ay and Az, the combined acceleration SA, the combined angular velocity SG and the combined attitude angle change amplitude Delta SAA are used as the characteristic quantity for judging whether the user falls down, and compared with the traditional method of only using the three-axis accelerations and the three-axis angular velocities as the characteristic quantity for fall detection, the method has the characteristic of high accuracy and effectively reduces the error.

Description

Old people falling detection method

Technical Field

The invention relates to the technical field of old people falling detection, in particular to an old people falling detection method.

Background

Population aging is an important trend in the world, and a population proportion of 65 years old or more in a country is defined as an aging country by more than 7% according to the definition of united nations. The population aging in China is normal, and the number of people over 65 years old in China reaches 17603 thousands at the end of 2019, and accounts for 12.6 percent of the total population proportion. Meanwhile, it is estimated that the aged 65 years old and older in China will be close to 3.1 hundred million and 3.8 hundred million in 2035 years and 2050 years old, and the proportions of the aged and older in China respectively reach 22.3 percent and 27.9 percent. Therefore, the aging population brings great impact to the social structure of China and also has profound influence on the economic development of China.

At the present stage, the aging and the number of the vacant families in China are still gradually increased, but the endowment system and the social security system in China are developing, the system is not perfect, the popularization degree is not perfect, and the mechanisms such as the endowment welfare institute and the like in the society are more short of supply and demand. According to data, the ratio of the number of beds of the nursing homes to the old people in China is only 1:150, the contradiction between the popularization degree of the social public nursing service and the requirement for meeting the care of all the old people is gradually increased, and for solving the problems, the state needs to increase financial output on nursing facilities besides greatly perfecting a nursing policy system, but the state is a large population and cannot achieve high efficiency in a short period.

Meanwhile, with the rapid development of economy, in addition to the demand of physical life, the attention degree of people to the body is stronger, and especially, the risks that the old people fall down, get lost and suffer from cardiovascular sudden diseases are increased along with the gradual increase of the physical quality and cognitive ability of the old people. The guidelines published by the ministry of health of China in 2011 indicate that the death caused by falling becomes the first factor in the accidental death of the elderly people in China, 40% of the elderly people have the accident of falling every year, and the death rate in the elderly population above 80 years is up to 60%, which shows that the statistics of the factors of the accidental death of the elderly people in China from 2010 to 2015 show that the death rates caused by falling are the first and the second highest among the elderly people in men and women respectively. The falling severity of the old is much higher than that of the old, and particularly, the old with skeletal basic diseases frosts on the snow, even causes psychological hidden dangers such as depression and fear, and seriously harms the physical and psychological health of the old. The wearable equipment is used for carrying out a falling experiment, the fused acceleration and angular velocity are mostly used as characteristic quantities, only the triaxial acceleration and the triaxial angular velocity are used as the characteristic quantities for falling detection, and the accuracy rate is not high. Therefore, we improve the problem and provide a method for detecting the fall of the old people.

Disclosure of Invention

In order to solve the technical problems, the invention provides the following technical scheme:

the invention relates to an old man falling detection method, which comprises the following steps;

step 1, acquiring moving human body posture data through a six-axis sensor to realize detection of human body posture;

step 2, preprocessing and posture fusion processing are carried out on the six-axis data acquired and transmitted by the six-axis sensor in real time;

step 3, extracting a plurality of characteristic values;

and 4, comparing the extracted characteristic value with a set threshold value, judging that the falling phenomenon occurs if the falling condition is met, judging that the falling phenomenon does not occur if the falling condition is not met, and returning to the step 1.

As a preferred technical solution of the present invention, the method for performing the attitude fusion processing on the six-axis data obtained by the six-axis sensor includes firstly defining a human body coordinate system and a reference coordinate system to obtain an attitude angle; the attitude angle is solved by utilizing a quaternion method, wherein the quaternion is expressed by the following formula,

Q(q₀，q₁，q₂，q₃)＝q₀+q₁i+q₂j+q₃k，

in the formula, q₀、q₁、q₂、q₃Is a real number, i, j, k are imaginary units that are mutually orthogonal in space;

wherein the human body coordinate system and the geographic coordinate system can be mutually converted through the rotating matrix, if,

in the formula, M^bIs a direction matrix in a human body coordinate system, NⁿIs a direction matrix in a geographic coordinate system;

then the rotation matrix in the above equation can be expressed by euler's theorem,

the rotation matrix can also be expressed in terms of attitude angles as:

the relationship between the attitude angle and the quaternion can be obtained by the two formulas as follows:

θ＝-sin^-1(2(q₁q₃-q₀q₂))，

wherein gamma is Roll angle Roll, theta is Pitch angle Pitch,

is the Yaw angle Yaw, q₀、 q₁、q₂、q₃Real numbers are quaternions.

As a preferable aspect of the present invention, the method of extracting the plurality of feature quantities includes obtaining three-axis accelerations Ax, Ay, and Az from the detection results of the six-axis sensors, calculating a resultant acceleration SA from the three-axis accelerations Ax, Ay, and Az,

in the formula, Ax, Ay and Az refer to the preprocessed triaxial acceleration values in a human body coordinate system;

a resultant angular velocity SG is obtained, in which,

in the formula, Gx, Gy and Gz represent rotational angular velocities around the X, Y and Z axes after preprocessing in a human coordinate system;

obtaining the variation amplitude Delta SAA of the attitude angle, selecting the sum of the absolute values of the variation of the Pitch angle Pitch and the Roll angle Roll as a characteristic quantity, wherein the expression is as follows,

ΔSAA＝Δ|Pitch|+Δ|Roll|。

in a preferred aspect of the present invention, the method of comparing the calculated feature amount with the set threshold value of the feature amount is,

A. when the resultant acceleration SA is greater than a set threshold value M2 and the result is unchanged after the time delay N seconds is met, the set threshold value M3 that the resultant angular speed SG is greater than is met; simultaneously, the condition that Ay in the three-axis acceleration is larger than a set threshold value M1 or Az in the three-axis acceleration is larger than a set threshold value M1 is met; if the combined angular speed SG is larger than a set threshold value M4, if the combined angular speed SG is larger than the set threshold value M4, the emergency contact is dialed and a falling signal is uploaded to the cloud server if the combined angular speed SG is simultaneously satisfied, the falling phenomenon is indicated; if the four are not simultaneously satisfied, the falling phenomenon is not generated;

B. when the combined acceleration is smaller than a set threshold value M2, if the combined angular speed SG is smaller than a set threshold value M3 and larger than two thirds of M3; the triaxial acceleration Ax is less than zero and Ay; if the three are met simultaneously, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to the cloud server; if the three are not satisfied simultaneously, the falling phenomenon is not generated;

C. when the resultant acceleration is smaller than a set threshold value M2 and the resultant angular velocity SG is larger than a set threshold value M3 or smaller than two thirds of M3, the triaxial acceleration Az is larger than a set threshold value M1; meanwhile, the Pitch angle Pitch is larger than the set 60 degrees, if the Pitch angle Pitch and the Pitch angle Pitch are simultaneously satisfied, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to a cloud server; if the four are not satisfied simultaneously, the falling phenomenon is not occurred.

The invention has the beneficial effects that:

in the invention, the six-axis sensor is used for acquiring the posture data of the moving human body, so as to realize the detection of the posture of the human body; preprocessing and attitude fusion processing are carried out on six-axis data acquired and transmitted by the six-axis sensor in real time; extracting a plurality of characteristic values; and comparing the extracted characteristic value with a set threshold value, judging that the falling phenomenon occurs if the characteristic value meets the falling condition, judging that the falling phenomenon does not occur if the characteristic value does not meet the falling condition, and returning to the step 1. The six-axis sensor utilizes a specific detection method for detecting the falling of the human body posture, wherein three-axis acceleration Ax, Ay and Az, combined acceleration SA, combined angular velocity SG and combined posture angle change amplitude Delta SAA are used as characteristic quantities for judging whether the human body falls down.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

fig. 1 is a step diagram of an old man fall detection method of the present invention;

FIG. 2 is a flow chart of the quaternion method of the present invention to solve for attitude angles;

fig. 3 is a graph of the resultant acceleration SA when a fall occurs in a human body;

fig. 4 is a graph of the resultant angular velocity SG when a fall occurs in a human body;

FIG. 5 is a graph of the total stance angle SAA when a fall occurs in a person;

fig. 6 is a flow chart of a method for fall detection of a body posture by a six-axis sensor.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

Example (b): a method for fall detection of an elderly person, comprising the steps of, as shown in figure 1,

firstly, in order to unify the standard of attitude angles, a human body coordinate system and a reference coordinate system need to be defined, wherein the reference coordinate system is a geographical coordinate system, namely east, north and sky are respectively used as an X axis, a Y axis and a Z axis of the coordinate system. The human body coordinate system actually selects a coordinate system of an MPU6050, and according to the arrangement position of a sensor in a hardware circuit, the direction from an arm to a head is specified to be an X-axis positive direction, the direction from the right front of a vertical arm is a Y-axis positive direction, and the direction from the back of the vertical arm to the outside is a Z-axis positive direction, so that the three-axis acceleration direction is specified to be a three-axis direction of the human body coordinate system, the three-axis angular speed is the rotating speed around each axis, and the attitude angles, namely the Roll angle, the Pitch angle and the Yaw angle, are defined based on the geographic coordinate system and the human body coordinate system, wherein the Roll angle Roll is the included angle between the X-axis of the human body coordinate system and the northeast of the geographic coordinate system, the Pitch angle Pitch is the included angle between the Y-axis of the human body coordinate system and the northeast of the geographic coordinate system, and the Yaw angle between the projection of the Y-axis of the human body coordinate system and the northeast direction. In daily life, because the human body may be oriented in various directions of the geography, the Yaw angle Yaw cannot be used as a reference characteristic quantity as shown in fig. 3, and then the following steps are carried out:

step 1, acquiring moving human body posture data through a six-axis sensor to realize detection of human body posture;

step 2, preprocessing and posture fusion processing are carried out on six-axis data of the sensors obtained by the six-axis sensors in real time; the method for preprocessing the six-axis data of the six-axis sensor obtained in real time is that, as shown in fig. 2, the quaternion is obtained by resolving the six-axis sensor data, and a complementary filtering method is needed because the acceleration has excellent static stability and the gyroscope has good dynamic stability. In the invention, static output of an accelerometer is used for correcting dynamic drift error of a gyroscope, and a resolving flow is shown in the following figure 2

Step 3, extracting a plurality of characteristic values;

and 4, comparing the extracted characteristic value with a set threshold value, judging that the falling phenomenon occurs if the falling condition is met, judging that the falling phenomenon does not occur if the falling condition is not met, and returning to the step 1.

The method for performing attitude fusion processing on the six-axis data obtained by the six-axis sensor is that an accelerometer in the six-axis sensor can only measure the acceleration value of each axis of a human body and cannot directly measure an attitude angle, and a gyroscope can use integration to calculate an angle, but certain accumulated errors exist. Solving for the attitude angle typically uses a quaternion method, which is capable of solving for all attitude angles with a short amount of computation. Firstly, defining a human body coordinate system and a reference coordinate system so as to obtain an attitude angle; the attitude angle is solved by utilizing a quaternion method, wherein the quaternion is expressed by the following formula,

Q(q₀，q₁，q₂，q₃)＝q₀+q₁i+q₂j+q₃k，

in the formula, q₀、q₁、q₂、q₃Is a real number, i, j, k are imaginary units that are mutually orthogonal in space;

wherein the human body coordinate system and the geographic coordinate system can be mutually converted through the rotating matrix, if,

in the formula, M^bIs a direction matrix in a human body coordinate system, NⁿIs a direction matrix in a geographic coordinate system;

then the rotation matrix in the above equation can be expressed by euler's theorem,

the rotation matrix can also be expressed in terms of attitude angles as:

the relationship between the attitude angle and the quaternion can be obtained by the two formulas as follows:

θ＝-sin^-1(2(q₁q₃-q₀q₂))，

wherein gamma is Roll angle Roll, theta is Pitch angle Pitch,

is the Yaw angle Yaw, q₀、 q₁、q₂、q₃Real numbers are quaternions.

Obtaining three-axis acceleration Ax, Ay and Az through the detection result of the six-axis sensor,

ax, Ay and Az are accelerations after preprocessing, and arithmetic mean filtering is adopted in the preprocessing, and the average value of every five sampling data is used as the acceleration and angular velocity detection value, so that the interference signal can be effectively filtered.

Because the direction has uncertainty when the person falls over, the judgment by the uniaxial acceleration is more limited, the difference of the directions can be effectively reduced by using the amplitude of the combined acceleration, the combined acceleration SA is calculated according to the triaxial accelerations Ax, Ay and Az,

in the formula, Ax, Ay and Az refer to the preprocessed triaxial acceleration values in a human body coordinate system;

a resultant angular velocity SG is obtained, in which,

in the formula, Gx, Gy and Gz represent rotational angular velocities around the X, Y and Z axes after preprocessing in a human coordinate system;

according to the definition of a coordinate system, when a human body falls down, the Pitch angle and the Roll angle obviously change, the yaw angle has unpredictability at the initial zero point, the change amplitude Delta SAA of the attitude angle is obtained, the sum of the absolute values of the change quantities of the Pitch angle Pitch and the Roll angle Roll is selected as a characteristic quantity, the expression is as follows,

ΔSAA＝Δ|Pitch|+Δ|Roll|。

and calculating the three-axis acceleration, the resultant acceleration SA, the resultant angular velocity SG and the resultant attitude angle change amplitude Delta SAA according to the four characteristic quantities. In FIG. 3, when a human body falls, the SA value is first reduced to a small extent and then rapidly fluctuates to 18m/s²The SA continuously fluctuates and is reduced to a stable stage when the SA collides with the ground; FIG. 4 shows that SG first fluctuates sharply, reaches a peak value during impact, and finally gradually enters a static state; in fig. 5 it is shown that the SAA increases by a small amount during the fall phase and then decreases sharply during the impact phase, and that the SAA value after rest is much smaller than the initial value. The change of the four characteristic values has certain regularity, so that the method has great reference value for fall detection.

As shown in fig. 6, the method of comparing the calculated feature quantity with the set threshold value of the feature quantity is,

A. when the resultant acceleration SA is greater than a set threshold value M2 and the result is unchanged after the time delay N seconds is met, the set threshold value M3 that the resultant angular speed SG is greater than is met; simultaneously, the condition that Ay in the three-axis acceleration is larger than a set threshold value M1 or Az in the three-axis acceleration is larger than a set threshold value M1 is met; if the combined angular speed SG is larger than a set threshold value M4, if the combined angular speed SG is larger than the set threshold value M4, the emergency contact is dialed and a falling signal is uploaded to the cloud server if the combined angular speed SG is simultaneously satisfied, the falling phenomenon is indicated; if the four are not simultaneously satisfied, the falling phenomenon is not generated;

B. when the combined acceleration is smaller than a set threshold value M2, if the combined angular speed SG is smaller than a set threshold value M3 and larger than two thirds of M3; the triaxial acceleration Ax is less than zero and Ay; if the three are met simultaneously, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to the cloud server; if the three are not satisfied simultaneously, the falling phenomenon is not generated;

C. when the resultant acceleration is smaller than a set threshold value M2 and the resultant angular velocity SG is larger than a set threshold value M3 or smaller than two thirds of M3, the triaxial acceleration Az is larger than a set threshold value M1; meanwhile, the Pitch angle Pitch is larger than the set 60 degrees, if the Pitch angle Pitch and the Pitch angle Pitch are simultaneously satisfied, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to a cloud server; if the four are not satisfied simultaneously, the falling phenomenon is not occurred.

Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that various changes, modifications and substitutions can be made without departing from the spirit and scope of the invention as defined by the appended claims. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. An old people falling detection method is characterized in that: comprises the following steps of (a) carrying out,

step 1, acquiring moving human body posture data through a six-axis sensor to realize detection of human body posture;

step 2, preprocessing and posture fusion processing are carried out on the six-axis data acquired and transmitted by the six-axis sensor in real time;

step 3, extracting a plurality of characteristic values;

and 4, comparing the extracted characteristic value with a set threshold value, judging that the falling phenomenon occurs if the falling condition is met, judging that the falling phenomenon does not occur if the falling condition is not met, and returning to the step 1.

2. The elderly fall detection method according to claim 5, wherein the six-axis data obtained by the six-axis sensor is processed by posture fusion by firstly defining a human coordinate system and a reference coordinate system to obtain a posture angle; the attitude angle is solved by utilizing a quaternion method, wherein the quaternion is expressed by the following formula,

Q(q₀，q₁，q₂，q₃)＝q₀+q₁i+q₂j+q₃k，

in the formula, q₀、q₁、q₂、q₃Is a real number, i, j, k are imaginary units that are mutually orthogonal in space;

wherein the human body coordinate system and the geographic coordinate system can be mutually converted through the rotating matrix, if,

in the formula, M^bIs a direction matrix in a human body coordinate system, NⁿIs a direction matrix in a geographic coordinate system;

then the rotation matrix in the above equation can be expressed by euler's theorem,

the rotation matrix can also be expressed in terms of attitude angles as:

the relationship between the attitude angle and the quaternion can be obtained by the two formulas as follows:

θ＝-sin^-1(2(q₁q₃-q₀q₂))，

wherein gamma is Roll angle Roll, theta is Pitch angle Pitch,

is the Yaw angle Yaw, q₀、q₁、q₂、q₃Real numbers are quaternions.

3. The elderly fall detection method according to claim 2, wherein the method for extracting the plurality of feature quantities includes obtaining three-axis accelerations Ax, Ay and Az from the detection result of the six-axis sensor, calculating a resultant acceleration SA from the three-axis accelerations Ax, Ay and Az,

in the formula, Ax, Ay and Az refer to the preprocessed triaxial acceleration values in a human body coordinate system;

a resultant angular velocity SG is obtained, in which,

in the formula, Gx, Gy and Gz represent rotational angular velocities around the X, Y and Z axes after preprocessing in a human coordinate system;

obtaining the variation amplitude Delta SAA of the attitude angle, selecting the sum of the absolute values of the variation of the Pitch angle Pitch and the Roll angle Roll as a characteristic quantity, wherein the expression is as follows,

ΔSAA＝Δ|Pitch|+Δ|Roll|。

4. the elderly fall detection method according to any of claims 1-3, wherein the method of comparing the calculated feature amount with the set threshold value of the feature amount is,

A. when the resultant acceleration SA is greater than a set threshold value M2 and the result is unchanged after the time delay N seconds is met, the set threshold value M3 that the resultant angular speed SG is greater than is met; simultaneously, the condition that Ay in the three-axis acceleration is larger than a set threshold value M1 or Az in the three-axis acceleration is larger than a set threshold value M1 is met; if the combined angular speed SG is larger than a set threshold value M4, if the combined angular speed SG is larger than the set threshold value M4, the emergency contact is dialed and a falling signal is uploaded to the cloud server if the combined angular speed SG is simultaneously satisfied, the falling phenomenon is indicated; if the four are not simultaneously satisfied, the falling phenomenon is not generated;

B. when the combined acceleration is smaller than a set threshold value M2, if the combined angular speed SG is smaller than a set threshold value M3 and larger than two thirds of M3; the triaxial acceleration Ax is less than zero and Ay; if the three are met simultaneously, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to the cloud server; if the three are not satisfied simultaneously, the falling phenomenon is not generated;

C. when the resultant acceleration is smaller than a set threshold value M2 and the resultant angular velocity SG is larger than a set threshold value M3 or smaller than two thirds of M3, the triaxial acceleration Az is larger than a set threshold value M1; meanwhile, the Pitch angle Pitch is larger than the set 60 degrees, if the Pitch angle Pitch and the Pitch angle Pitch are simultaneously satisfied, the falling phenomenon is indicated, the emergency contact is dialed, and a falling signal is uploaded to a cloud server; if the four are not satisfied simultaneously, the falling phenomenon is not occurred.

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