CN111297368A - Gait recognition method, device, equipment and readable storage medium - Google Patents
Gait recognition method, device, equipment and readable storage medium Download PDFInfo
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- 210000004394 hip joint Anatomy 0.000 claims description 12
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- 238000004590 computer program Methods 0.000 claims description 2
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/112—Gait analysis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6813—Specially adapted to be attached to a specific body part
- A61B5/6828—Leg
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/683—Means for maintaining contact with the body
- A61B5/6832—Means for maintaining contact with the body using adhesives
Abstract
The application discloses a gait recognition method, a device, equipment and a readable storage medium, wherein the method comprises the steps of acquiring detection data of a sensor arranged at a position of a lower leg of a gait recognition object; extracting a first included angle of the shank relative to the ground according to the detection data; and identifying the current gait of the lower leg provided with the sensor according to the variation trend of the first included angle. The sensor can detect the three-axis attitude angle and the acceleration of the shank, a first included angle of the thigh relative to the ground is extracted through detection data of the sensor, the motion state of the shank of the human body at the moment is judged according to the included trend of the first included angle, and then the current gait is identified. Compared with a gait recognition method depending on sole pressure, the gait recognition is more accurate by utilizing the change trend of the included angle of the relative ground of the crus.
Description
Technical Field
The present invention relates to the technical field of gait recognition, and in particular, to a gait recognition method, apparatus, device and readable storage medium.
Background
In order to help the patient who cannot walk restore the walking ability, a corresponding rehabilitation device is needed to assist walking. One of the key points of the device to assist the patient is to identify the patient's motor intent. One way to identify the motor intent of a patient is to identify the gait of the patient. At present, the gait of a patient is usually judged through a pressure sensor on the sole of the patient, but the method has large errors and cannot accurately identify the gait of the patient.
Disclosure of Invention
The present application is directed to a gait recognition method, apparatus, device and readable storage medium, and aims to solve the problem of inaccurate gait recognition for a patient.
In order to achieve the above object, the present application provides a gait recognition method, which includes the following steps:
acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
extracting a first included angle of the shank relative to the ground according to the detection data;
and identifying the current gait of the lower leg provided with the sensor according to the variation trend of the first included angle.
Optionally, the step of extracting a first included angle of the lower leg relative to the ground according to the detection data includes:
acquiring a sensor angle in the detection data;
and extracting a first included angle between the crus and the ground through the angle of the sensor according to an attitude calibration algorithm.
Optionally, the step of identifying the current gait according to the trend of the first included angle includes:
acquiring a numerical curve of the first included angle within preset time;
judging the variation trend of the first included angle according to the numerical curve;
if the change trend is increasing, determining that the current gait is in a swing state;
and if the change trend is reduced or kept unchanged, determining that the current gait is in a support state.
Optionally, the step of extracting a first included angle of the lower leg with respect to the ground according to the detection data includes:
in a preset time length, acquiring the angular velocity of the shank relative to the ground according to a first included angle of the shank relative to the ground;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
Optionally, the step of extracting a first included angle of the lower leg with respect to the ground according to the detection data includes:
acquiring a second included angle of the thigh of the gait recognition object relative to the ground;
determining the angle of the knee joint according to the first included angle and the second included angle;
if the angle is larger than a preset angle, determining that the current gait is in a swing state;
and if the angle is not larger than the preset angle, determining that the current gait is in a supporting state.
Optionally, the step of identifying the current gait of the lower leg on which the sensor is disposed according to the trend of the first included angle includes:
acquiring motion information of a hip joint;
acquiring the angle of the lower leg relative to the upper half part of the body of the gait recognition object according to the motion information and the first included angle;
obtaining the change rate of the angle;
if the change rate is positive, determining that the current gait is in a swing state;
and if the change rate is negative or zero, determining that the current gait is in a support state.
Optionally, the step of obtaining the angle of the lower leg relative to the upper body half of the gait recognition subject is followed by:
acquiring the angular velocity of the upper half part of the body of the lower leg relative to the gait recognition object according to the angle in a preset time length;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
The present application further provides a gait recognition device, the gait recognition device includes:
the gait recognition system comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
the extraction module is used for extracting a first included angle of the shank relative to the ground according to the detection data;
and the identification module is used for identifying the current gait of the lower leg provided with the sensor according to the change trend of the first included angle.
The present application further provides a gait recognition device, which includes: a memory, a processor and a gait recognition program stored on the memory and executable on the processor, the gait recognition program when executed by the processor implementing the steps of the gait recognition method as described above.
The present application also provides a readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the gait recognition method as described above.
The method comprises the steps of acquiring detection data of a sensor arranged at a lower leg of a gait recognition object; extracting a first included angle of the shank relative to the ground according to the detection data; and identifying the current gait of the lower leg provided with the sensor according to the variation trend of the first included angle. The IMU (Inertial Measurement Unit) can detect the three-axis attitude angle and the acceleration of the shank, extract a first included angle of the shank relative to the ground through detection data of a sensor, judge the motion state of the shank of the human body at the moment according to the included trend of the first included angle, and then recognize the current gait. Compared with a gait recognition method depending on sole pressure, the gait recognition is more accurate by utilizing the change trend of the included angle of the relative ground of the crus.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a first embodiment of a gait recognition method according to the application;
FIG. 3 is a schematic diagram illustrating the division of the human face and the axis in the first embodiment of the gait recognition method of the application;
fig. 4 is a detailed flowchart of step S20 and step S30 in fig. 2 according to a second embodiment of the gait recognition method of the application;
fig. 5 is a schematic flowchart of a step after step S10 in fig. 2 according to a third embodiment of the gait recognition method of the present application;
fig. 6 is a schematic flowchart of a step after step S10 in fig. 2 in a fourth embodiment of a gait recognition method of the present application;
fig. 7 is a detailed flowchart of step S30 in fig. 2 according to a fifth embodiment of the gait recognition method of the present application;
fig. 8 is a schematic system structure diagram of an embodiment of a gait recognition device according to the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
As shown in fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present application.
The terminal in the embodiment of the application is gait recognition equipment.
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, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that turns off the display screen and/or the backlight when the terminal device is moved to the ear. Of course, the terminal device may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a gait recognition program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call the gait recognition program stored in the memory 1005 and perform the following operations:
acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
extracting a first included angle of the shank relative to the ground according to the detection data;
and identifying the current gait of the lower leg provided with the sensor according to the variation trend of the first included angle.
Based on the above terminal hardware structure, various embodiments of the present application are provided.
The application provides a gait recognition method.
Referring to fig. 2 and 3, in a first embodiment of a gait recognition method, the method comprises:
step S10, acquiring detection data of a sensor arranged at the position of the lower leg of the gait recognition object;
the sensor here may be an IMU (Inertial Measurement Unit) module, which is exemplified below. The IMU may acquire a means of measuring the three-axis attitude angles (or angular velocities) and accelerations of the object. Typically, an IMU includes three single axis accelerometers and three single axis gyroscopes, and may also include a magnetometer. The accelerometer detects acceleration signals of an object in independent three axes of a carrier coordinate system, the gyroscope detects three-axis angular velocity signals of the carrier relative to a navigation coordinate system, angular velocity and acceleration of the object in a three-dimensional space are measured, and the magnetometer detects and outputs three-axis geomagnetic included angles so as to calculate the posture of the object. While the IMU may be affixed to the calf anywhere including the front, sides, back, etc. The acceleration and the angular velocity of each axis when the lower leg moves can be detected through the lower leg IMU. Alternatively, the IMU module may be replaced with other sensors or other devices that can detect such data, such as an angular rate meter, gyroscope, alone or in combination.
Step S20, extracting a first included angle of the lower leg relative to the ground according to the detection data;
because the IMU is posted on the lower leg, the detection data acquired by the IMU is not directly equivalent to the motion data of the lower leg itself, for example, the overall direction of the lower leg is vertical when the lower leg stands vertically, while the IMU may judge that the position is not vertical because of the difference of the posted position, that is, there is a certain deviation in the three-axis direction between the actual motion data of the lower leg and the detection data of the IMU. But the translation between the actual motion situation of the lower leg and the detected data of the IMU can be derived from the error between the two in several situations. The IMU can detect the angular velocity of three axes, and the angular velocity of the thigh horizontal axis relative to the earth is extracted from the detection data of the IMU through the obtained conversion relation. Referring to fig. 3, axes and planes in a human body are divided, and a motion state of the human body is determined by dividing the human body into different planes and axes. A first included angle of the human shank relative to the ground is used for detecting whether the thigh of the human is in a supporting state or a swinging state.
Step S30, identifying the current gait of the shank provided with the sensor according to the variation trend of the first included angle;
generally, the auxiliary equipment is divided into unilateral equipment and bilateral equipment, bilateral equipment may need to consider various gaits on the left side and the right side and the fusion of respective gaits, and unilateral equipment only needs to consider the gaits on the auxiliary side of the equipment. Here, one-sided gait can be recognized by one-sided IMU, and two-sided gait can be recognized if both sides have IMU. Generally, gait is divided into a plurality of segments, and the method for distinguishing the supporting state and the swinging state of walking is the simplest, most effective and most direct dividing method. Considering the unilateral equipment, when walking, the legs are supported on the ground and are in a supporting phase, when swinging, the legs are in a swinging phase, when supporting and swinging, the stress of the legs is different, when supporting the legs, the legs need to support the mass of the whole body, when swinging, the legs only need to bear the self swinging burden, when supporting, the legs stand on the ground and do not need to bend the knee joints, when swinging, the legs need to swing forwards and the knee joints need to bend. When a human body walks, the knee joint is bent before swinging, the lower leg can be lifted upwards first and then starts to swing forwards to enter a swinging phase, and after the lower leg stops swinging forwards, the leg just lands to enter a supporting phase. Therefore, the current state of support or swing can be judged through the swing of the lower leg. The motion state gait of the lower leg during the supporting and swinging, such as the supporting: the lower leg rotates around the foot, swings backwards relative to the ground, and swings backwards relative to the body; when swinging: the lower leg rotates around the hip joint, swings forwards relative to the ground, and swings forwards relative to the body. Therefore, the current gait can be judged by detecting the movement of the lower leg, when the lower leg swings forwards, the lower leg swings, and when the lower leg swings backwards, the lower leg supports, so that the judgment of the support and the swing can be realized by detecting the forward movement or the backward movement of the lower leg. The current gait can be identified by the trend of the change of the first angle of the lower leg relative to the ground. Because the change trend of the first included angle between the crus and the ground is increased and gradually increased from 90 degrees in the swinging state, and the change trend of the first included angle between the crus and the ground is reduced or unchanged in the supporting state, if a person stands on the ground still, the included angle cannot be changed at the moment, and the change trend is unchanged.
In the present embodiment, detection data of a sensor provided at a lower leg of a gait recognition target is acquired; extracting a first included angle of the crus relative to the ground according to the detection data; and identifying the current gait according to the angular velocity. And extracting a first included angle of the crus relative to the ground from the detection data by using the detection data passing through the sensor and a preset conversion relation, and identifying the current gait information of the crus by using the change trend of the first included angle.
Further, referring to fig. 2 and 4, on the basis of the first embodiment of the gait recognition method of the present application, a second embodiment of the gait recognition method is provided, in which, in the second embodiment,
step S20 includes:
step S21, acquiring a sensor angle in the detection data;
the sensor angle acquired by the sensor at the position of the lower leg is an included angle between the sensor in the motion state and each coordinate axis in a preset three-axis coordinate system, and the sensor angle is acquired in the state of the sensor, so although the IMU module is positioned at the lower leg, the detection data acquired by the sensor cannot be directly taken as the motion data of the lower leg in the normal situation.
Step S22, extracting a first included angle between the shank and the ground through the sensor angle according to an attitude calibration algorithm;
the posture calibration is to convert the detection data acquired by the sensor into the motion data of the lower leg, because the detection data acquired by the sensor is the detection data of three X, Y and Z axes established on the basis of the detection data acquired by the sensor, the motion data of the upper leg correspondingly determines the included angle of the relative ground according to the divided surface and axis of the human body, and the relationship between the detection data of the sensor and the actual motion data of the lower leg is determined by acquiring the detection data acquired by a plurality of known sensors and the actual motion data of the lower leg. And then, correspondingly converting the angle of the sensor acquired by the sensor into a first included angle of the shank relative to the ground according to the conversion relation.
Step S30 includes:
step S31, acquiring a numerical curve of the first included angle within preset time;
step S32, judging the variation trend of the first included angle according to the numerical curve;
step S33, if the trend is increasing, determining that the current gait is in a swing state;
step S34, if the change trend is reduced or kept unchanged, determining that the current gait is in a support state;
because when the shank is in the swing state, the shank needs to leave the ground and swing forwards at the same time, the first included angle between the shank and the ground is gradually increased, namely the change trend of the first included angle is increased, the support state comprises a state of recovering from the swing state to being completely supported on the ground, at the moment, the shank can be gradually changed into a state of being vertically supported on the ground from the highest point of swing, the first included angle between the shank and the ground is slowly reduced, or if the shank is statically supported on the ground, the included angle between the shank and the ground cannot be changed. Therefore, the variation trend of the first included angle is determined through the numerical curve of the first included angle within a certain time period, or the variation trend of the first included angle is judged through the numerical values of the first included angle at continuous time points independently. If the change trend is increasing, determining that the current gait is in a swing state; and if the change trend is reduced or kept unchanged, determining that the current gait is in a support state.
In this embodiment, a first included angle of the lower leg relative to the ground is extracted from detection data acquired by a sensor according to an attitude calibration algorithm, a variation trend of the first included angle is judged through a numerical curve of the first included angle, and current gait information of the lower leg is identified through the variation trend of the first included angle.
Further, referring to fig. 2 and 5, on the basis of the first embodiment of the gait recognition method of the present application, a third embodiment of the gait recognition method is provided, in which, in the third embodiment,
step S20 is followed by:
step S41, acquiring the angular velocity of the transverse axis of the crus relative to the ground according to the first included angle of the crus relative to the ground in a preset time period;
step S42, if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
step S43, if the angular velocity is zero or clockwise, determining that the current gait is a support state;
the angular speed of the transverse shaft of the crus relative to the ground can be obtained through the numerical value change of the first included angle in the preset time length. In the swing state, the lower leg swings upwards and forwards, the angular velocity of the transverse shaft of the lower leg relative to the ground is in the anticlockwise direction, in the support state, the lower leg swings downwards and backwards to restore to the state of contacting the ground, the angular velocity of the transverse shaft of the lower leg relative to the ground is in the clockwise direction, or the lower leg is completely supported on the ground, and the angular velocity is zero. If the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state; and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state. The counterclockwise and clockwise directions are observed by pointing the direction of the arrow of the human body axis according to the division in fig. 3 toward the observer. And (4) following the right-hand rule, holding the rotating shaft by a hand, and enabling the thumb to face the positive direction of the rotating shaft, wherein the anticlockwise direction is the direction of holding by the fingers.
Meanwhile, if the gait result obtained by the identification of the change trend of the first included angle is different from the gait result obtained by the identification of the angular velocity, the gait information of the system obtained by the identification of the change trend of the first included angle is the final gait identification result of the crus.
Meanwhile, the rotation center of the shank can be obtained through the detection data, if the rotation center of the shank can be obtained according to the angular velocity and the acceleration in the detection data, the current gait is identified according to the obtained rotation center, if the rotation center is on the upper side of the shank, the current gait of the shank is identified to be in a swing state, and if the rotation center is on the lower side of the shank, the current gait of the shank is identified to be in a support state.
In the embodiment, the angular velocity of the transverse axis of the lower leg relative to the ground is obtained through the first included angle between the lower leg and the ground, and the current gait of the lower leg is identified according to the angular velocity.
Further, referring to fig. 2 and 6, on the basis of the first embodiment of the gait recognition method of the present application, a fourth embodiment of the gait recognition method is provided, in which,
step S20 is followed by:
step S51, acquiring a second included angle of the thigh of the gait recognition object relative to the ground;
step S52, determining the angle of the knee joint according to the first included angle and the second included angle;
step S53, if the angle is larger than the preset angle, determining that the current gait is in a swing state;
step S54, if the angle is not greater than the preset angle, determining that the current gait is in the support state.
Similarly, a sensor is arranged at the thigh to acquire a second included angle of the thigh relative to the ground, the angle of the knee joint can be determined through the first included angle and the second included angle, when the thigh and the shank are completely in the same straight line, the angle of the knee joint is determined to be zero, and if the thigh and the shank are not in the same straight line, the angle exists. In the swing process, the angle of the knee joint is gradually increased, the angle is gradually decreased in the supporting state, meanwhile, due to personal differences, a preset angle is set as a mode for preventing misjudgment, and the set value of the preset angle is smaller. When the angle is larger than a preset angle, determining that the current gait is in a swing state; and when the angle is not larger than the preset angle, determining that the current gait is in a supporting state.
Meanwhile, because the habits of each person in walking are different, the change of the angle of the knee joint in the walking process is different, and certain errors exist, so that if the result of the change trend of the first included angle is different from the result of the gait recognition, the gait recognized by the change trend of the first included angle is taken as the final result.
In this embodiment, the current gait of the lower leg is identified by the angle of the knee joint.
Further, referring to fig. 2 and 7, on the basis of the first embodiment of the gait recognition method of the present application, a fifth embodiment of the gait recognition method is provided, in which,
step S30 includes:
step S35, obtaining the motion information of the hip joint;
step S36, acquiring the angle of the shank relative to the upper half part of the body of the gait recognition object according to the motion information and the first included angle;
step S37, obtaining the change rate of the angle;
step S38, if the change rate is positive, determining that the current gait is in a swing state;
step S39, if the change rate is negative or zero, determining that the current gait is a support state;
similar to the method for acquiring the motion data of the lower leg by using the sensor transformation, the motion data of the hip joint, such as the angular velocity of the hip joint and the kinematic information of the angle with the ground, can also be acquired by using the sensor. The motion state of the upper body can be obtained from the kinematic information of the hip joint, and the motion data of the lower leg relative to the upper body of the human body can be obtained from the previously acquired motion data of the upper leg and the kinematic information of the hip joint. And obtaining the angle of the shank relative to the upper half part of the body by utilizing the angle of the shank relative to the ground and the angle information of the hip joint relative to the ground. In the swing state, the lower leg approaches to the upper half of the body, and in the transition from the swing state to the support state, the lower leg gradually moves away from the upper half of the body, or when the upper leg is completely supported on the ground, the angular velocity with respect to the upper half of the body may be zero. When the change rate is positive, judging that the lower leg is close to the upper half part of the body, and determining that the current gait is in a swing state; and when the change rate is negative, judging that the lower leg is far away from the upper half part of the body, or the change rate is zero, wherein the lower leg is in a state of being completely supported on the ground, and determining that the current gait is in a supporting state.
Wherein, step S36 is followed by:
step A1, acquiring the angular velocity of the upper half part of the body of the lower leg relative to the gait recognition object according to the angle in a preset time length;
step A2, if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
step A3, if the angular velocity is zero or clockwise, determining that the current gait is in a support state;
from the angular information, the angular velocity relative to the upper body part can be derived. When the shank is in a fully supported state, the angular velocity of the thigh and the upper half part of the body is zero, when the human body starts to swing the shank, the shank is close to the upper half part of the body, and the direction of the angular velocity is in an anticlockwise direction; when in the support state, the lower leg is in the upper half away from the body, where the angular velocity is clockwise. When the angular velocity is in the anticlockwise direction, determining that the current gait is in a swing state; and when the angular velocity is zero or in the clockwise direction, determining that the current gait is in a support state. The counterclockwise and clockwise directions are observed by pointing the direction of the arrow of the human body axis according to the division in fig. 3 toward the observer.
In this embodiment, in addition to the shank sensor, the motion data related to the shank is acquired, and the motion information corresponding to the hip joint is acquired according to the other sensors, and then the angular change rate or angular velocity of the shank relative to the upper half of the body is acquired according to the motion information of the hip joint and the motion data related to the shank of the shank sensor, and the current gait is identified according to the angular change rate or angular velocity.
In addition, referring to fig. 8, an embodiment of the present application further provides a gait recognition apparatus, including:
the gait recognition system comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
the extraction module is used for extracting a first included angle of the shank relative to the ground according to the detection data;
and the identification module is used for identifying the current gait of the lower leg provided with the sensor according to the change trend of the first included angle.
Optionally, the extracting module is further configured to:
acquiring a sensor angle in the detection data;
and extracting a first included angle between the crus and the ground through the angle of the sensor according to an attitude calibration algorithm.
Optionally, the identification module is further configured to:
acquiring a numerical curve of the first included angle within preset time;
judging the variation trend of the first included angle according to the numerical curve;
if the change trend is increasing, determining that the current gait is in a swing state;
and if the change trend is reduced or kept unchanged, determining that the current gait is in a support state.
Optionally, the identification module is further configured to:
in a preset time length, acquiring the angular speed of a transverse shaft of the crus relative to the ground according to a first included angle of the crus relative to the ground;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
Optionally, the identification module is further configured to:
acquiring a second included angle of the thigh of the gait recognition object relative to the ground;
determining the angle of the knee joint according to the first included angle and the second included angle;
if the angle is larger than a preset angle, determining that the current gait is in a swing state;
and if the angle is not larger than the preset angle, determining that the current gait is in a supporting state.
Optionally, the identification module is further configured to:
acquiring motion information of a hip joint;
acquiring the angle of the lower leg relative to the upper half part of the body of the gait recognition object according to the motion information and the first included angle;
obtaining the change rate of the angle;
if the change rate is positive, determining that the current gait is in a swing state;
and if the change rate is negative or zero, determining that the current gait is in a support state.
Optionally, the identification module is further configured to:
acquiring the angular velocity of the upper half part of the body of the lower leg relative to the gait recognition object according to the angle in a preset time length;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
The specific implementation of the device and the readable storage medium (i.e., the computer readable storage medium) of the present application has substantially the same extension as that of the above embodiments of the stylus mode switching method, and thus, the detailed description thereof is omitted here.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A gait recognition method is characterized by comprising the following steps:
acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
extracting a first included angle of the shank relative to the ground according to the detection data;
and identifying the current gait of the lower leg provided with the sensor according to the variation trend of the first included angle.
2. A gait recognition method according to claim 1, characterized in that the step of extracting a first angle of the lower leg relative to the ground from the detection data comprises:
acquiring a sensor angle in the detection data;
and extracting a first included angle between the crus and the ground through the angle of the sensor according to an attitude calibration algorithm.
3. A gait recognition method according to claim 2, characterized in that the step of recognizing the current gait according to the trend of change of the first angle comprises:
acquiring a numerical curve of the first included angle within preset time;
judging the variation trend of the first included angle according to the numerical curve;
if the change trend is increasing, determining that the current gait is in a swing state;
and if the change trend is reduced or kept unchanged, determining that the current gait is in a support state.
4. A gait recognition method according to claim 1, characterized in that the step of extracting a first angle of the lower leg relative to the ground from the detection data is followed by:
in a preset time length, acquiring the angular speed of a transverse shaft of the crus relative to the ground according to a first included angle of the crus relative to the ground;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
5. A gait recognition method according to claim 1, characterized in that the step of extracting a first angle of the lower leg relative to the ground from the detection data is followed by:
acquiring a second included angle of the thigh of the gait recognition object relative to the ground;
determining the angle of the knee joint according to the first included angle and the second included angle;
if the angle is larger than a preset angle, determining that the current gait is in a swing state;
and if the angle is not larger than the preset angle, determining that the current gait is in a supporting state.
6. A gait recognition method according to claim 1, characterized in that the step of recognizing the current gait of the lower leg on which the sensor is provided based on the trend of change of the first angle comprises:
acquiring motion information of a hip joint;
acquiring the angle of the lower leg relative to the upper half part of the body of the gait recognition object according to the motion information and the first included angle;
obtaining the change rate of the angle;
if the change rate is positive, determining that the current gait is in a swing state;
and if the change rate is negative or zero, determining that the current gait is in a support state.
7. A gait recognition method according to claim 6, characterized in that the step of acquiring the angle of the lower leg relative to the upper body half of the gait recognition object is followed by:
acquiring the angular velocity of the upper half part of the body of the lower leg relative to the gait recognition object according to the angle in a preset time length;
if the angular velocity is in the counterclockwise direction, determining that the current gait is in a swing state;
and if the angular velocity is zero or in the clockwise direction, determining that the current gait is in a supporting state.
8. A gait recognition device characterized by comprising:
the gait recognition system comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring detection data of a sensor arranged at a lower leg of a gait recognition object;
the extraction module is used for extracting a first included angle of the shank relative to the ground according to the detection data;
and the identification module is used for identifying the current gait of the lower leg provided with the sensor according to the change trend of the first included angle.
9. A gait recognition device, characterized in that the gait recognition device comprises: a memory, a processor and a gait recognition program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the gait recognition method of any of claims 1 to 7.
10. A readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the gait recognition method according to any of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117357873A (en) * | 2023-12-07 | 2024-01-09 | 浙江强脑科技有限公司 | Running mode control method and device, intelligent leg prosthesis, terminal and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130131555A1 (en) * | 2011-11-17 | 2013-05-23 | William R. Hook | Gait analysis using angular rate reversal |
| CN106908021A (en) * | 2017-01-19 | 2017-06-30 | 浙江大学 | A kind of human-step length measuring method and its measuring apparatus for Wearable device |
| US20180146890A1 (en) * | 2016-11-25 | 2018-05-31 | Samsung Electronics Co., Ltd. | Apparatus and method for recognizing gait state |
| CN108095729A (en) * | 2018-01-24 | 2018-06-01 | 深圳市臻络科技有限公司 | A kind of freezing of gait recognition methods and device |
| KR20190029874A (en) * | 2017-09-13 | 2019-03-21 | 주식회사 엑스바디 | Apparatus and method of realtime gait examination using infrared camera |
-
2020
- 2020-01-20 CN CN202010068443.XA patent/CN111297368A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130131555A1 (en) * | 2011-11-17 | 2013-05-23 | William R. Hook | Gait analysis using angular rate reversal |
| US20180146890A1 (en) * | 2016-11-25 | 2018-05-31 | Samsung Electronics Co., Ltd. | Apparatus and method for recognizing gait state |
| CN106908021A (en) * | 2017-01-19 | 2017-06-30 | 浙江大学 | A kind of human-step length measuring method and its measuring apparatus for Wearable device |
| KR20190029874A (en) * | 2017-09-13 | 2019-03-21 | 주식회사 엑스바디 | Apparatus and method of realtime gait examination using infrared camera |
| CN108095729A (en) * | 2018-01-24 | 2018-06-01 | 深圳市臻络科技有限公司 | A kind of freezing of gait recognition methods and device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117357873A (en) * | 2023-12-07 | 2024-01-09 | 浙江强脑科技有限公司 | Running mode control method and device, intelligent leg prosthesis, terminal and storage medium |
| CN117357873B (en) * | 2023-12-07 | 2024-04-09 | 浙江强脑科技有限公司 | Running mode control method and device, intelligent leg prosthesis, terminal and storage medium |
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Application publication date: 20200619 |