CN111166346A - Knee joint flexion and extension angle real-time measuring device and method based on angular velocity sensor - Google Patents

Knee joint flexion and extension angle real-time measuring device and method based on angular velocity sensor Download PDF

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CN111166346A
CN111166346A CN202010103390.0A CN202010103390A CN111166346A CN 111166346 A CN111166346 A CN 111166346A CN 202010103390 A CN202010103390 A CN 202010103390A CN 111166346 A CN111166346 A CN 111166346A
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knee joint
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李玉榕
连春快
陈建国
杜民
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Fuzhou University
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Abstract

The invention relates to a knee joint flexion and extension angle real-time measuring device based on an angular velocity sensor, which comprises two nodes, wherein a node 1 is worn on any position of a thigh, and a node 2 is worn on any position of a shank; the two nodes synchronously acquire angular velocity information; the node 2 uploads the collected angular speed data to the node 1 in real time in a wireless mode, the data are processed and calculated in the node 1, and the calculation result is uploaded to an upper PC through a serial port. The invention has no limit on the wearing position of the inertial angular velocity sensor and realizes the real-time accurate estimation of the knee joint angle.

Description

Knee joint flexion and extension angle real-time measuring device and method based on angular velocity sensor
Technical Field
The invention relates to a knee joint flexion and extension angle real-time measuring device and method based on an angular velocity sensor.
Background
The calculation of the knee joint angle has great significance in the aspects of human body rehabilitation and robot knee joint control. In the aspect of human body rehabilitation, along with the gradual aggravation of the aging phenomenon of Chinese population, China is the country with the most old population at present, according to investigation, the probability of suffering from knee joint diseases above 60 years old can reach 50%, and the probability of suffering from knee joint diseases reaches 80% to 75 years old, and the disability rate can reach 53%. It can be said that many people are afflicted with knee joint disease after entering the elderly. The knee joint movement is the main part of the human lower limb movement, and the patients can cause the movement dysfunction of the lower limbs in different degrees due to the damage of the knee joint, and the bending angle of the knee joint is affected in the normal walking process, so that the bending angle information of the knee joint of the testee in the walking process is timely and accurately obtained through a detection technology, the movement state of the knee joint in the gait movement process is analyzed, and the method is an important precondition for carrying out correct and scientific lower limb rehabilitation training on the testee.
The control of the angle of the knee joint of the robot influences the motion flexibility of the robot and whether the robot can accurately complete the designated task. The closed-loop control method is widely applied to the control of the knee joint angle of the robot, the angle of the knee joint in the current state is accurately estimated in the knee joint angle control system of the robot, and the knee joint angle is used as a feedback signal of the control system to complete the scientific control of the knee joint angle. The precision of the knee joint angle measurement directly influences the precision of the robot knee joint angle control system, and the robot system has high requirements for the real-time performance of signals, so that the robot knee joint angle measurement system has high requirements.
At present, the method capable of detecting the knee joint angle with the highest precision is to use an optical camera gait analysis system, but has the defects that the measurement can be carried out only in a specific experimental space, the implementation has higher requirements on operators, the equipment is expensive, and the like. To solve the problems of the optical system, inertial angular velocity sensors are widely used. In the knee joint angle measurement based on the inertial angular velocity sensors, the inertial angular velocity sensors can only be placed on a designed measurement part, and improper operation of a user can cause reduction of algorithm precision. In addition, the algorithm for calculating the angle by using the inertial sensor is to directly integrate angular velocity data according to time, and a large integration accumulated error is generated along with the increase of the integration time, so that the angle calculation result is drifted.
Disclosure of Invention
In view of the above, the present invention provides a device and a method for measuring knee joint flexion and extension angles in real time based on an angular velocity sensor, so as to accurately estimate knee joint angles in real time.
In order to achieve the purpose, the invention adopts the following technical scheme:
a real-time knee joint flexion and extension angle measuring device based on an angular velocity sensor comprises two nodes, wherein a node 1 is worn on any position of a thigh, and a node 2 is worn on any position of a shank; the two nodes synchronously acquire angular velocity information; the node 2 uploads the collected angular speed data to the node 1 in real time in a wireless mode, the data are processed and calculated in the node 1, and the calculation result is uploaded to an upper PC through a serial port.
Furthermore, the hardware components of the node 1 and the node 2 are the same, and the node comprises a control module, a USB module, a polar plate power supply module, a lithium battery, a motion data acquisition module and a Bluetooth module; the control module is respectively connected with the USB module, the polar plate power supply module, the motion data acquisition module and the Bluetooth module; the polar plate power supply module is also connected with a motion data acquisition module and a Bluetooth module respectively; and the USB module is respectively connected with the lithium battery and the polar plate power supply module.
A measuring method of a knee joint flexion and extension angle real-time measuring device based on an angular velocity sensor comprises the following steps:
step S1, wearing the node 1 on any position of thigh and the node 2 on any position of shank to obtain angular velocity signal;
step S2, according to the obtained angular velocity signal, optimizing and calculating the joint axis in an off-line state;
and step S3, calculating the knee joint angle on line in real time according to the obtained joint axis to obtain the knee joint flexion and extension angle.
Further, the step S1 is specifically:
step S11, obtaining a plurality of meter nodes 1 which are walked by the user in straight lineCollective angular velocity signal g1(i) And the angular velocity signal g collected by the node 22(i) I is1, 2,3, … N, N is the number of data points;
s12, synchronously transmitting the angular velocity signals collected by the node 2 to the node 1, and uploading the angular velocity signals of the two nodes from the node 1 to an upper PC (personal computer) through a serial port;
and step S13, importing the data into MATLAB, and carrying out mean value filtering processing on the data.
Further, the step S2 is specifically:
step S21, simplifying the knee joint model into a single-degree-of-freedom hinge model in a sagittal plane, and measuring the angular velocity g of two nodes at any time1(i) And g2(i) The components in the joint normal plane cancel each other and are expressed by equation (1):
Figure BDA0002387627470000043
in the formula j1，j2Respectively representing the coordinates of a vector with the length of 1 along the joint axis direction in three-dimensional coordinate systems of two different sensors of a node 1 and a node 2, wherein the arithmetic symbol | | | | |2Representing the vector quantity Euclidean norm, x represents the vector cross product operation, two vectors (a)1,a2,a3) And (b)1,b2,b3) The cross product operation of (a) is:
(a1,a2,a3)×(b1,b2,b3)＝(a2b3-a3b2,a3b1-a1b3,a1b2-a2b1)
step S22, j is1，j2The expression (1, phi, theta) in the spherical coordinate system is converted into the expression in the three-dimensional rectangular coordinate system:
Figure BDA0002387627470000041
wherein phi is a pitch angle, and theta is a direction angle;
step S23, adopting genetic algorithm to optimize and calculate the joint axis and determine phi1、φ2、θ1、θ2The values of the four parameters are obtained to obtain j1And j2The objective function used is:
Figure BDA0002387627470000042
phi in the formula1,φ2,θ1,θ2Is the decision variable to be optimized.
Further, the genetic algorithm specifically comprises:
a) setting an evolution algebra counter T to be 0, setting a maximum evolution algebra T to be 50, and randomly generating 600 individuals with variable length of 20 as an initial population P (0);
b) calculating the fitness of each individual in the population P (t), and defining a fitness function F as 1/F;
c) according to the fitness of each individual, sorting the fitness according to the size, selecting excellent individuals with high fitness from the t-generation population P (t), and then transmitting the excellent individuals to the next-generation population P (t + 1);
d) randomly collocating and pairing the individuals in the group P (t), and for each pair of individuals, calculating the cross probability Pc0.6 to exchange part of the chromosomes between them;
e) for each individual in the population P (t), the mutation probability P is usedm0.01 to change the value of one or some loci to other alleles;
f) and if T is equal to T, outputting the individual with the maximum fitness obtained in the evolution process as the optimal solution, and stopping the calculation.
Further, the step S3 is specifically:
step S31, acquiring the angular velocity signal g collected by the node 1 fixed on the thigh when the user walks in real time1Angular velocity signal g collected at node 2 fixed to the lower leg2Angular velocity signal g collected by node 22Synchronously transmitted into the node 1;
step S32, utilizing g2Judging whether the current sampling moment is at the heel landing point in real time;
step S33, if the heel is at the landing position, the knee joint angle corresponding to the point in time is reset to zero; if not, according to g1、g2the knee joint angle α (t) at the present time is calculated.
Further, the step S32 is specifically: using the angular velocity signal g measured at node 22The component of the foot which has the smallest included angle with the vertical line of the sagittal plane is used for judging that the heel lands.
Further, the step S33 is specifically:
a) g is prepared from1、g2Are respectively projected to j1，j2Then, calculating a difference value to obtain an angular velocity g (t) around the joint axis, which is perpendicular to the sagittal plane of the knee joint at the moment;
b) let the angular velocity be in one sample period Δ tsif there is no change, the knee joint angle change amount in this sampling period is Δ α (t) ═ g (t) Δtsthe knee joint angle α (t) at the current moment can be obtained by the algebraic sum of the knee joint angle at the previous moment and the angle variation in the current sampling period, and the formula is as follows:
Figure BDA0002387627470000061
the operator in the formula, a dot product operation representing a vector, and two vectors (a)1,a2,a3) And (b)1,b2,b3) The dot product of (d) is: (a)1,a2,a3)·(b1,b2,b3)＝a1b1+a2b2+a3b3。
Compared with the prior art, the invention has the following beneficial effects:
1. the knee joint angle real-time calculation device can calculate the knee joint angle in real time, is simple and small in size and is convenient to wear.
2. The sensors placed on the thighs and the calves can be placed at will without the limitation of specific installation positions.
Drawings
FIG. 1 is a block diagram of the hardware system of the present invention;
FIG. 2 is a block diagram showing the connection of modules of the node of the present invention;
FIG. 3 is a single degree of freedom hinge model in the sagittal plane in one embodiment of the present invention;
FIG. 4 is a flow chart of a genetic algorithm in one embodiment of the present invention;
FIG. 5 is a flowchart of a knee joint angle calculation algorithm according to an embodiment of the present invention;
FIG. 6 is a flowchart of a heel strike detection algorithm in accordance with an embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 1, the invention provides a real-time knee joint flexion and extension angle measuring device based on an angular velocity sensor, which comprises two nodes, wherein a node 1 is worn on any position of a thigh, and a node 2 is worn on any position of a shank; the two nodes synchronously acquire angular velocity information; the node 2 uploads the collected angular speed data to the node 1 in real time in a wireless mode, the data are processed and calculated in the node 1, and the calculation result is uploaded to an upper PC through a serial port.
In this embodiment, as shown in fig. 2, the node 1 and the node 2 have the same hardware composition, and include a control module, a USB module, a pole plate power supply module, a lithium battery, a motion data acquisition module, and a bluetooth module; the control module takes an ST micro-control chip STM32F411RET6 as a core; the connection relationship of the hardware constituent modules is shown in fig. 2. The nodes can be charged through the USB module, and program programming of the nodes can be completed. A small-volume rechargeable aluminum battery is used as a power supply of the power supply module, and the voltage provided by the aluminum battery is reduced to constant 3.3V direct-current voltage by the TPS73033 chip to supply power to other chips. The motion data acquisition module adopts an ADIS16355 chip, integrates a three-axis gyroscope and a temperature sensor, is a low-noise digital output angular velocity sensor, has a measuring range of +/-250 DEG/sec, is provided with a 24-bit analog-to-digital converter (ADC) for outputting a digital gyroscope, and ensures that acquired data have high accuracy. The bluetooth module employs an NRF52810 module, which is a bluetooth 5.0 patch module designed using Nordic NRF52810(QFN 32). In the data transmission direction, node 1 is a receiving system and node 2 is a transmitting system.
In this embodiment, the knee joint is simplified to a single degree of freedom hinge model in the sagittal plane, as shown in FIG. 3, where the dashed line is the line perpendicular to the joint axis in the sagittal plane of the knee joint. The embodiment also provides a measuring method of the knee joint flexion and extension angle real-time measuring device based on the angular velocity sensor, which comprises the following steps:
the first step is as follows: optimized calculation joint axis in off-line state
The node 1 and the node 2 are respectively worn at any positions of thighs and shanks, and an angular velocity signal g collected by the node 1 when a user walks for 10 meters in a straight line is obtained1(i) And the angular velocity signal g collected by the node 22(i) I is1, 2,3, … N, N is the number of data points.
The angular speed signals collected by the node 2 are synchronously transmitted to the node 1, and the angular speed signals of the two nodes are uploaded to an upper PC (personal computer) from the node 1 through a serial port.
Data are imported into MATLAB in an upper PC, and mean value filtering processing is carried out on the data.
The angular velocity causing the change of the flexion and extension angles of the knee joint is an angular velocity component around the direction of a joint axis, and the knee joint model is simplified into a single-degree-of-freedom hinge model in a sagittal plane, so that the knee joint model has no rotation in other directions except the rotation in the sagittal plane, and the angular velocities g measured by two nodes at any time1(i) And g2(i) The components in the joint axis normal plane cancel each other and can be expressed by equation (1):
Figure BDA0002387627470000082
in the formula j1，j2Two vectors respectively representing a vector having a length of 1 along the joint axis at nodes 1 and 2Coordinates in a three-dimensional coordinate system of the same sensor, and operation symbols in the formula2Representing the vector quantity Euclidean norm, x represents the vector cross product operation, two vectors (a)1,a2,a3) And (b)1,b2,b3) The cross product operation of (a) is:
(a1,a2,a3)×(b1,b2,b3)＝(a2b3-a3b2,a3b1-a1b3,a1b2-a2b1)
handle j1，j2The expression (1, phi, theta) in the spherical coordinate system is converted into the expression in the three-dimensional rectangular coordinate system:
Figure BDA0002387627470000081
where φ is a pitch angle and θ is a direction angle.
Since the knee joint does not only have angle change on a sagittal plane in actual motion and does not completely conform to the previously established single-degree-of-freedom hinge model of the knee joint, the left side of the formula (1) is difficult to be zero, and the minimum value on the left side of the formula can be searched in calculation to determine the joint axis.
In the embodiment, the joint axis is optimized and calculated by adopting a genetic algorithm to determine phi1、φ2、θ1、θ2The values of the four parameters are obtained to obtain j1And j2The objective function used is:
Figure BDA0002387627470000091
the meanings of the symbols in the formula (1) are the same as those in the formula (I). Phi in the handle type1,φ2,θ1,θ2As decision variables of the calculation to be optimized, the definition domain of the variables is: phi is a1,φ2∈[-0.5π,0.5π]、θ1,θ2∈[0,2π]。
The joint axis optimization calculation process in this embodiment is shown in fig. 4, and the basic operation process includes:
a) initialization: the evolution algebra counter T is set to 0, the maximum evolution algebra T is set to 50, and 600 individuals with variable length of 20 are randomly generated as an initial population P (0).
b) Individual evaluation: calculating the fitness of each individual in the population P (t), and defining a fitness function
F＝1/f。
c) Selecting and operating: and sorting the fitness according to the fitness of each individual, and selecting excellent individuals with high fitness from the t-th generation group P (t) and then transmitting the excellent individuals to the next generation group P (t + 1).
d) And (3) cross operation: randomly collocating and pairing the individuals in the group P (t), and for each pair of individuals, calculating the cross probability Pc0.6 to exchange part of the chromosome between them.
e) And (3) mutation operation: for each individual in the population P (t), the mutation probability P is usedm0.01 to change the value of a gene at one or some loci to other alleles.
f) And (4) judging termination conditions: and if T is equal to T, outputting the individual with the maximum fitness obtained in the evolution process as the optimal solution, and stopping the calculation.
The second step is that: calculating the knee joint angle on line in real time;
in the first step, obtaining j by off-line optimization1And j2After the optimal solution is obtained, the knee joint flexion and extension angle can be calculated on line in real time: acquiring angular velocity signals g collected by a node 1 fixed on a thigh of a user when the user walks1Angular velocity signal g collected at node 2 fixed to the lower leg2Angular velocity signal g collected by node 22Synchronously transmitted to the node 1, and the knee joint flexion and extension angle is obtained in the node 1 according to the real-time control method shown in fig. 5.
The specific process is as follows: real-time reading g1、g2Using g2And judging whether the current sampling moment is at the heel landing point in real time. If not, g is added1、g2Are respectively projected to j1， j2To thenCalculating the difference to obtain the angular velocity g (t) around the joint axis perpendicular to the sagittal plane of the knee joint at the moment, and assuming that the angular velocity is in a sampling period delta tsif there is no change, the knee joint angle change amount in this sampling period is Δ α (t) ═ g (t) Δtsthe algebraic sum of the knee joint angle at the previous moment and the angle variation in the current sampling period can obtain the knee joint angle α (t) at the current moment, and the formula is as follows:
Figure BDA0002387627470000101
the operator in the formula, a dot product operation representing a vector, and two vectors (a)1,a2,a3) And (b)1,b2,b3) The dot product of (d) is: (a)1,a2,a3)·(b1,b2,b3)＝a1b1+a2b2+a3b3。
If the heel is at the landing position, the knee joint angle corresponding to the point in time is reset to zero.
In this embodiment, since the inertial sensor can provide instantaneous dynamic angle change, it will generate drift error with the increase of working time due to its inherent characteristics, temperature and integration process, and in order to compensate this error, it is assumed that the heel landing point of each gait cycle in the walking on flat ground resets the knee joint angle to zero.
Preferably, the real-time heel strike detection algorithm in this embodiment specifically includes: the component of the calf angular velocity signal perpendicular to the sagittal plane is often used to detect heel strike, which in gait exhibits a periodic signal of one peak and two troughs, corresponding to the two major gait events, heel strike and toe off, respectively. Toe-off and heel-on events occur before and after the maximum positive peak of the shank-suspended swing phase, respectively.
In this embodiment, the angular velocity signal g measured by the node 2 is used2The component of the foot which has the smallest included angle with the vertical line of the sagittal plane is used for judging that the heel lands. Since the angle of rotation of the lower leg in gait is significantly greater in the sagittal plane than in the other two planes, the angular velocity of this component has a magnitude that is greater the closer the axis of the angular velocity meter is to the direction perpendicular to the sagittal plane. In actual practice, therefore, the component with the largest amplitude is found. And (3) rectifying and mean filtering the offline derived three-axis angular velocity data of the node 2, then integrating the processed data within the time from the start to the end of gait test, and taking out the original angular velocity data of the axis with the largest integral value to detect the landing position of the heel. With x-axis component g2xTo illustrate, the mean value is first filtered. Signal g corresponding to heel landing2xThe following conditions need to be satisfied: 1) a first minimum value point less than zero after the phase point appears in the swing; 2) the angular velocity variation is negative. Therefore, in order to judge the heel landing point, the swing middle phase needs to be detected firstly. The swinging middle phase point at least satisfies the following two conditions: 1) the angular velocity should be greater than a large angular velocity threshold M; 2) the angular velocity variation is positive.
Preferably, the judging of the phase point in the swing is specifically as follows: and judging whether the shank angular velocity signal acquired in real time is greater than a preset threshold value M, if so, storing the angular velocity in A, and if only the angular velocity signal acquired in the next sampling period meets the swing middle phase detection condition and the angular velocity is greater than A, covering the angular velocity with the original value in A. And when any condition is not met, exiting the current round of judgment, waiting for the data entry of the next sampling period, and then carrying out a new round of judgment. And repeating the steps until the maximum angular velocity signal A meeting the condition is obtained, namely the phase point in the swing. In practical operation, M can take the value of 100 deg/s.
1. And when the angular speed signal acquired in the next sampling period only meets the detection condition of heel landing and the angular speed is less than B, covering the angular speed with the original value in B. And when any condition is not met, exiting the current round of judgment, waiting for the data entry of the next sampling period, and then carrying out a new round of judgment. And repeating the steps until a first minimum value point B which is smaller than zero after the swing middle phase point meeting the condition is obtained, and determining the point as the heel landing point. The heel strike detection algorithm flow used in this embodiment is shown in FIG. 6.
In the present embodiment, the real-time knee flexion and extension angle measuring device based on the angular velocity sensor is specifically used as follows,
1. optimized calculation joint axis in off-line state
1) The node 1 and the node 2 are respectively placed on the thigh and the shank of a measured person, when data acquisition is started, the measured person stands still naturally for three seconds, and then walks forwards for 10 meters in a straight line according to usual gait. The data collected by the node 1 and the node 2 are uploaded to an upper computer through a serial port
2) Filtering the acquired data in an upper PC, taking out one data from the processed angular velocity data every ten sampling periods to form a new data set as training data, optimizing the minimum value by a genetic algorithm with the left side of the formula (1) as an objective function, and determining phi1、φ2、θ1、θ2And taking values of four parameters.
2. The knee joint angle is calculated on line. After the joint axes are calculated, the four parameters of the joint axes are substituted into the knee joint angle calculation program of the node 1. The gait cycle and heel landing point detection are calculated on line by using gyroscope data on the lower leg, angular velocity signals of gyroscopes respectively placed at any positions of the upper leg and the lower leg are respectively projected to an algebraic difference on a joint shaft if the gait cycle and the heel landing point are not the heel landing point to obtain an angular velocity perpendicular to a sagittal plane of the knee joint along the direction of the joint shaft, then the knee joint angle is obtained by integrating the angular velocity in time, and the knee joint angle is reset to zero degree if the knee landing point is the heel landing point.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.

Claims (9)

1. A real-time knee joint flexion and extension angle measuring device based on an angular velocity sensor is characterized by comprising two nodes, wherein a node 1 is worn on any position of a thigh, and a node 2 is worn on any position of a shank; the two nodes synchronously acquire angular velocity information; the node 2 uploads the collected angular speed data to the node 1 in real time in a wireless mode, the data are processed and calculated in the node 1, and the calculation result is uploaded to an upper PC through a serial port.
2. The device for measuring the flexion and extension angles of the knee joint based on the angular velocity sensor in real time as claimed in claim 1, wherein the hardware components of the node 1 and the node 2 are the same, and the device comprises a control module, a USB module, a polar plate power supply module, a lithium battery, a motion data acquisition module and a Bluetooth module; the control module is respectively connected with the USB module, the polar plate power supply module, the motion data acquisition module and the Bluetooth module; the polar plate power supply module is also connected with a motion data acquisition module and a Bluetooth module respectively; and the USB module is respectively connected with the lithium battery and the polar plate power supply module.
3. A measuring method of a knee joint flexion and extension angle real-time measuring device based on an angular velocity sensor is characterized by comprising the following steps:
step S1, wearing the node 1 on any position of thigh and the node 2 on any position of shank to obtain angular velocity signal;
step S2, according to the obtained angular velocity signal, optimizing and calculating the joint axis in an off-line state;
and step S3, calculating the knee joint angle on line in real time according to the obtained joint axis to obtain the knee joint flexion and extension angle.
4. The measurement method of the device for measuring flexion and extension angles of knee joint based on angular velocity sensor according to claim 3, wherein the step S1 is specifically as follows:
step S11, obtaining a plurality of meter nodes 1 which are walked by the user in straight lineCollective angular velocity signal g1(i) And the angular velocity signal g collected by the node 22(i) I is1, 2,3, … N, N is the number of data points;
s12, synchronously transmitting the angular velocity signals collected by the node 2 to the node 1, and uploading the angular velocity signals of the two nodes from the node 1 to an upper PC (personal computer) through a serial port;
and step S13, importing the data into MATLAB, and carrying out mean value filtering processing on the data.
5. The measurement method of the device for measuring flexion and extension angles of knee joint based on angular velocity sensor according to claim 4, wherein the step S2 is specifically as follows:
step S21, simplifying the knee joint model into a single-degree-of-freedom hinge model in a sagittal plane, and measuring the angular velocity g of two nodes at any time1(i) And g2(i) The components in the joint normal plane cancel each other and are expressed by equation (1):
Figure FDA0002387627460000021
in the formula j1，j2Respectively representing the coordinates of a vector with the length of 1 along the joint axis direction in three-dimensional coordinate systems of two different sensors of a node 1 and a node 2, wherein the arithmetic symbol | | | | |2Representing the vector quantity Euclidean norm, x represents the vector cross product operation, two vectors (a)1,a2,a3) And (b)1,b2,b3) The cross product operation of (a) is:
(a1,a2,a3)×(b1,b2,b3)＝(a2b3-a3b2,a3b1-a1b3,a1b2-a2b1)
step S22, j is1，j2The expression (1, phi, theta) in the spherical coordinate system is converted into the expression in the three-dimensional rectangular coordinate system:
Figure FDA0002387627460000022
wherein phi is a pitch angle, and theta is a direction angle;
step S23, adopting genetic algorithm to optimize and calculate the joint axis and determine phi1、φ2、θ1、θ2The values of the four parameters are obtained to obtain j1And j2The objective function used is:
Figure FDA0002387627460000031
phi in the formula1,φ2,θ1,θ2Is the decision variable to be optimized.
6. The measurement method of the device for measuring the flexion and extension angles of the knee joint based on the angular velocity sensor as claimed in claim 5, wherein the genetic algorithm is specifically as follows:
a) setting an evolution algebra counter T to be 0, setting a maximum evolution algebra T to be 50, and randomly generating 600 individuals with variable length of 20 as an initial population P (0);
b) calculating the fitness of each individual in the population P (t), and defining a fitness function F as 1/F;
c) according to the fitness of each individual, sorting the fitness according to the size, selecting excellent individuals with high fitness from the t-generation population P (t), and then transmitting the excellent individuals to the next-generation population P (t + 1);
d) randomly collocating and pairing the individuals in the group P (t), and for each pair of individuals, calculating the cross probability Pc0.6 to exchange part of the chromosomes between them;
e) for each individual in the population P (t), the mutation probability P is usedm0.01 to change the value of one or some loci to other alleles;
f) and if T is equal to T, outputting the individual with the maximum fitness obtained in the evolution process as the optimal solution, and stopping the calculation.
7. The measurement method of the device for measuring flexion and extension angles of knee joint based on angular velocity sensor according to claim 3, wherein the step S3 is specifically as follows:
step S31, acquiring the angular velocity signal g collected by the node 1 fixed on the thigh when the user walks in real time1Angular velocity signal g collected at node 2 fixed to the lower leg2Angular velocity signal g collected by node 22Synchronously transmitted into the node 1;
step S32, utilizing g2Judging whether the current sampling moment is at the heel landing point in real time;
step S33, if the heel is at the landing position, the knee joint angle corresponding to the point in time is reset to zero; if not, according to g1、g2the knee joint angle α (t) at the present time is calculated.
8. The measuring method of the device for measuring flexion and extension angles of knee joint based on angular velocity sensor according to claim 7, wherein the step S32 specifically comprises: using the angular velocity signal g measured at node 22The component of the foot which has the smallest included angle with the vertical line of the sagittal plane is used for judging that the heel lands.
9. The measuring method of the device for measuring flexion and extension angles of knee joint based on angular velocity sensor according to claim 7, wherein the step S33 specifically comprises:
a) g is prepared from1、g2Are respectively projected to j1，j2Then, calculating a difference value to obtain an angular velocity g (t) around the joint axis, which is perpendicular to the sagittal plane of the knee joint at the moment;
b) let the angular velocity be in one sample period Δ tsif there is no change, the knee joint angle change amount in this sampling period is Δ α (t) ═ g (t) Δtsthe knee joint angle α (t) at the current moment can be obtained by the algebraic sum of the knee joint angle at the previous moment and the angle variation in the current sampling period, and the formula is as follows:
Figure FDA0002387627460000041
the operator in the formula, a dot product operation representing a vector, and two vectors (a)1,a2,a3) And (b)1,b2,b3) The dot product of (d) is: (a)1,a2,a3)·(b1,b2,b3)＝a1b1+a2b2+a3b3。
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