CN112857394A - Intelligent shoe and action recognition method, device and storage medium thereof - Google Patents
Intelligent shoe and action recognition method, device and storage medium thereof Download PDFInfo
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- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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Abstract
The application discloses a method for recognizing actions of intelligent shoes, which comprises the following steps: acquiring motion inertia data and air pressure change data generated by triggering a body sensing device in the intelligent shoe; carrying out zero-speed correction on the motion inertia data by using the air pressure change data; calculating the corrected motion inertia data through inertial navigation attitude to obtain motion mode data; and matching the motion mode data with a preset calculation model, and identifying corresponding foot actions to output an identification result. The beneficial effect of accurately identifying the foot action is achieved. The application also discloses an action recognition device, an intelligent shoe and a computer readable storage medium simultaneously, and the action recognition device, the intelligent shoe and the computer readable storage medium have the beneficial effects in the same way.
Description
Technical Field
The application relates to the technical field of motion recognition, in particular to an intelligent shoe, a motion recognition method and device thereof, and a computer readable storage medium.
Background
The IMU (Inertial Measurement Unit) is an Inertial Measurement Unit (IMU) that detects motion signals of an object in a carrier coordinate system through an acceleration sensor and/or a gyroscope in the Unit. The IMU is often applied to peripheral devices of the motion sensing game, and the motion sensing game is a novel electronic motion sensing game which breaks through the traditional operation mode of simply inputting by using handle keys and converts the change of body motion into a mode similar to the input of the handle keys for operation.
One of the popular ways to do this is to design the relevant inputs into the smart shoe, identify the motion patterns of the user by the relevant data generated by the foot motions of the lower body of the human body, identify the relevant foot motions, and input the relevant foot motions into the game device through communication means such as bluetooth, so that the user can participate in the interaction of the motion sensing game.
However, the technical means adopted by the existing intelligent shoes are limited to be more traditional, the existing entertainment and fitness algorithms are basically limited to algorithms for analyzing the number of steps, the frequency of steps, the length and the like, and in the aspect of identifying and analyzing whether the human body runs, moves left and right and forwards, jumps and other actions through data acquired by the IMU, because the movement inertia data of the traditional inertia measurement unit is judged only based on a three-axis module of a gyroscope during zero-speed correction, and the foot actions of the user are difficult to be comprehensively described and identified only by means of the three-axis data, the identification effect is not ideal, and sometimes even the foot actions cannot be correctly identified.
Disclosure of Invention
The application aims to provide an intelligent shoe action identification method, which is used for carrying out zero-speed correction on motion inertia data by introducing air pressure change data so as to realize accurate identification of foot actions.
Another object of the present application is to provide a motion recognition apparatus, a smart shoe, and a computer-readable storage medium.
In order to achieve the above object, the present application provides a method for recognizing an action of an intelligent shoe, comprising:
acquiring motion inertia data and air pressure change data generated by triggering a body sensing device in the intelligent shoe;
carrying out zero-speed correction on the motion inertia data by using the air pressure change data;
calculating the corrected motion inertia data through inertial navigation attitude to obtain motion mode data;
and matching the motion mode data with a preset calculation model, and identifying corresponding foot actions to output an identification result.
In some embodiments, the step of acquiring motion inertia data and air pressure change data generated by triggering the body sensing device in the intelligent shoe includes:
acquiring the motion inertia data by using an inertia measurement unit in the somatosensory sensing device;
and acquiring the air pressure change data by utilizing an air pressure measuring unit in the somatosensory sensing device.
In a specific embodiment, the acquiring the motion inertia data by using an inertia measurement unit in the motion sensing device includes:
measuring acceleration and angular velocity data through an accelerometer and a gyroscope carried by the inertial measurement unit;
measuring acceleration and geomagnetic data by a magnetometer carried by the inertial measurement unit;
and taking the acceleration and angular velocity data and the acceleration and geomagnetic data as the motion inertia data.
In a specific embodiment, the step of acquiring the air pressure change data by using an air pressure measurement unit in the motion sensing device includes:
the air pressure change data of the intelligent shoe is measured through an air pressure sensor carried by the air pressure measuring unit, and the air pressure change data comprises an air pressure value.
In a preferred embodiment, the performing zero-speed correction on the motion inertia data by using the air pressure variation data includes:
setting a calculation window with the length of N, and sliding the calculation window to calculate, wherein each window comprises N air pressure values in the continuously read air pressure change data, and N is a natural number more than 2;
judging the data characteristics presented by each calculation window according to the N air pressure values, and determining whether the data characteristics represent that the corresponding air pressure change data is in a rising edge, wherein for the rising edge, the air pressure value presented by the data characteristics is greater than the previous air pressure value, and the difference value of the two air pressure values exceeds a preset threshold value;
determining a calculation window corresponding to the rising edge as entering a zero-speed interval;
and after confirming that the movement inertia data enters a zero-speed interval, performing zero-speed correction on the movement inertia data.
In a further embodiment, before performing the zero-velocity correction on the motion inertia data after confirming that the motion inertia data enters the zero-velocity interval, the method further includes:
and detecting a zero-speed interval based on the motion inertia data of the somatosensory sensing device, and confirming that the zero-speed interval enters the zero-speed interval so as to start zero-speed correction when the zero-speed interval is detected and is synchronous with the zero-speed interval determined according to the air pressure change data.
In a further embodiment, the matching the motion pattern data with a preset calculation model, and identifying a corresponding foot motion to output an identification result includes:
coordinate transformation is carried out on the posture, speed and position data included in the motion mode data to obtain the motion trail of the foot;
and matching the motion trail with a preset calculation model, and identifying corresponding foot actions to output an identification result.
To achieve the above object, the present application also provides a motion recognition apparatus, including:
the acquisition module is used for acquiring motion inertia data and air pressure change data generated by triggering the body sensing device in the intelligent shoe;
the correction module is used for performing zero-speed correction on the motion inertia data by utilizing the air pressure change data;
the resolving module is used for resolving the corrected motion inertia data through the inertial navigation attitude to obtain motion mode data;
and the recognition module is used for matching the motion mode data with a preset calculation model and recognizing corresponding foot actions so as to output recognition results.
In some embodiments, the obtaining module is specifically configured to:
acquiring the motion inertia data by using an inertia measurement unit in the somatosensory sensing device;
and acquiring the air pressure change data by utilizing an air pressure measuring unit in the somatosensory sensing device.
Wherein, utilize the inertial measurement unit among the body sensing device to obtain motion inertial data includes:
measuring acceleration and angular velocity data through an accelerometer and a gyroscope carried by the inertial measurement unit;
measuring acceleration and geomagnetic data by a magnetometer carried by the inertial measurement unit;
and taking the acceleration and angular velocity data and the acceleration and geomagnetic data as the motion inertia data.
Wherein, utilize the atmospheric pressure measuring unit among the body sensing device to obtain atmospheric pressure change data includes:
the air pressure change data of the intelligent shoe is measured through an air pressure sensor carried by the air pressure measuring unit, and the air pressure change data comprises an air pressure value.
In a preferred embodiment, the modification module is specifically configured to:
setting a calculation window with the length of N, and sliding the calculation window to calculate, wherein each window comprises N air pressure values in the continuously read air pressure change data, and N is a natural number more than 2;
judging the data characteristics presented by each calculation window according to the N air pressure values, and determining whether the data characteristics represent that the corresponding air pressure change data is in a rising edge, wherein for the rising edge, the air pressure value presented by the data characteristics is greater than the previous air pressure value, and the difference value of the two air pressure values exceeds a preset threshold value;
determining a calculation window corresponding to the rising edge as entering a zero-speed interval;
and after confirming that the movement inertia data enters a zero-speed interval, performing zero-speed correction on the movement inertia data.
Wherein, before the zero speed correction is performed on the motion inertia data after the entering of the zero speed interval is confirmed, the method further comprises the following steps:
and detecting a zero-speed interval based on the motion inertia data of the somatosensory sensing device, and confirming that the zero-speed interval enters the zero-speed interval so as to start zero-speed correction when the zero-speed interval is detected and is synchronous with the zero-speed interval determined according to the air pressure change data.
In a further embodiment, the identification module is specifically configured to:
coordinate transformation is carried out on the posture, speed and position data included in the motion mode data to obtain the motion trail of the foot;
and matching the motion trail with a preset calculation model, and identifying corresponding foot actions to output an identification result.
For realizing above-mentioned purpose, this application still provides an intelligent shoes, and sensing device is felt to this intelligent shoes embeds body, sensing device includes is felt to the body:
the inertia measurement unit is used for sensing movement inertia data generated by the intelligent shoe in an actuated mode;
the air pressure measuring unit is used for sensing air pressure change data generated by pressurization of the intelligent shoe;
the control unit is used for carrying out zero-speed correction on the motion inertia data by utilizing the air pressure change data, resolving the corrected motion inertia data through inertial navigation attitude to obtain motion mode data, matching the motion mode data with a preset calculation model and identifying corresponding foot actions;
and the communication module is used for outputting the identification result of the control unit to equipment in communication connection with the control unit.
To achieve the above object, the present application also provides an intelligent shoe, including:
the motion sensing device is used for sensing motion inertia data and air pressure change data generated by the intelligent shoe;
a memory for storing a computer program;
a processor for implementing the steps of the intelligent shoe action recognition method as described above when the computer program is executed.
To achieve the above object, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when being executed by a processor, performs the steps of the intelligent shoe action recognition method as described above.
Compared with the prior art, the technical scheme that this application provided feels sensing device and is triggered the motion inertial data and the atmospheric pressure change data that produce through acquireing, utilizes atmospheric pressure change data is right motion inertial data carries out zero-speed correction, and when motion inertial data after this correction was used for the motion mode data that inertial navigation gesture resolved the acquisition, will describe human action characteristic more accurately. Therefore, when the motion mode data obtained after zero-speed correction is carried out by the method and the device are matched with the preset calculation model according to the conventional technical scheme, the corresponding foot action can be more accurately identified. The acquisition and utilization of the air pressure change data are introduced into the body sensing device such as the intelligent shoe, and the air pressure change data can reflect the foot action of the human body more uniformly, sensitively and accurately, so that the air pressure change data is utilized to perform zero-speed correction on the traditional motion inertia data, and the accuracy of traditional motion gait recognition is improved comprehensively.
Drawings
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 introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method for intelligent shoe action recognition provided in an embodiment of the present application;
FIG. 2 is a schematic block diagram of a motion sensing device for a smart shoe according to an embodiment of the present application;
FIG. 3 is a schematic structural view of an air pressure measuring unit employed in a smart shoe to which an embodiment of the present application is applied, which generally shows a side view of a structure provided in the form of an insole;
FIG. 4 is a flow chart of a process for determining a zero speed correction starting point using air pressure variation data as described herein;
fig. 5 is a schematic block diagram of a motion recognition device according to an embodiment of the present application.
Detailed Description
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those within the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The person skilled in the art will know this: although the various methods and apparatus of the present application are described based on the same concept so as to be common to each other, they can be operated independently unless otherwise specified. In the same way, for each embodiment disclosed in the present application, it is proposed based on the same inventive concept, and therefore, concepts of the same expression and concepts of which expressions are different but are appropriately changed only for convenience should be equally understood.
The core of the application is to provide an intelligent shoe action recognition method, device, intelligent shoe and computer readable storage medium, motion inertia data and air pressure change data that sensing device is triggered to produce are felt through acquireing, and utilize air pressure change data is right motion inertia data carries out the zero-speed correction, and the motion inertia data after will revising according to conventional means is solved through inertial navigation gesture and is obtained motion pattern data, will then according to conventional means motion pattern data and predetermine the calculation model and match, can discern corresponding foot action more accurately.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a flowchart of an intelligent shoe action recognition method according to an embodiment of the present application.
The method specifically comprises the following steps:
s102: acquiring motion inertia data and air pressure change data generated by triggering a body sensing device in the intelligent shoe;
in a preferred embodiment, the motion sensing device provided by the present invention is built in an intelligent shoe, the schematic block diagram of the circuit of the motion sensing device is shown in fig. 2, and the motion sensing device uses a single chip 213 or other intelligent chips as its control unit, and is powered by a battery 214, and controls an inertial measurement unit 211 and an air pressure measurement unit 122 to collect various corresponding sensing data, which correspondingly includes the motion inertial data and air pressure change data, wherein the inertial measurement unit 211 is used to collect the motion inertial data, and the air pressure measurement unit 122 is used to collect air pressure change data, and after performing gait and motion recognition related to the foot of a human body by using the sensing data, the related recognition result and/or related data is sent to a personal computer, a mobile terminal, an intelligent television, etc. wirelessly connected with the human body through a communication module 22 to perform communication, thereby participating in a motion sensing game or performing health data interaction and the like. The communication module 22 is preferably bluetooth or other near field communication technology, although communication mechanisms based on mobile communication, WiFi and the like are not excluded, and those skilled in the art can flexibly select the communication mechanism. In addition, the one-chip microcomputer 213 may also control the vibration sensor 212 to vibrate by receiving a command from the device side through its communication module, so as to implement interaction with the user.
As mentioned above, the intelligent shoe is provided with an inertial measurement unit IMU, which is mainly used to obtain the motion inertial data, i.e. the relevant data that can be collected about the IMU and is known to those skilled in the art. More specifically, in one embodiment, the intelligent shoe measures acceleration and angular velocity data through an accelerometer and a gyroscope carried by the IMU itself, and acceleration and geomagnetic data through a magnetometer carried by the IMU itself, which collectively constitute the inertial data of the movement.
And the air pressure measuring unit 12, as shown in fig. 3, is a module added in the form of an insole 10 in the intelligent shoe. As shown in fig. 3, by providing a shoe pad-shaped air bag 121, providing a cavity inside the air bag 121, and disposing one or more air pressure sensors 122 in the cavity, when the air bag 121 is pressed by the foot of a human body, the air pressure sensors 122 can acquire the air pressure change data related to the foot movement. In order to make the data acquisition of the air pressure sensor 122 more uniform, a flexible cushion 11 may be disposed above the air bag 12, which is also convenient for improving the pressing feeling of the user. Typically, the air pressure change data may be represented and read in the form of air pressure values. Thus, in essence, the air pressure measuring unit 12 is an air pressure gauge in the form of an insole.
In the implementation of the step, the following two steps can be executed in parallel or in a time-division alternating manner:
the control unit acquires the motion inertia data by using an inertia measurement unit in the somatosensory sensing device: in this step, the following steps are mainly included: measuring acceleration and angular velocity data through an accelerometer and a gyroscope carried by the inertial measurement unit; measuring acceleration and geomagnetic data by a magnetometer carried by the inertial measurement unit; and taking the acceleration and angular velocity data and the acceleration and geomagnetic data as the motion inertia data.
The control unit acquires the air pressure change data by using an air pressure measuring unit in the body sensing device: in the step, the control unit measures the air pressure change data borne by the intelligent shoe through an air pressure sensor carried by the air pressure measuring unit, wherein the air pressure change data comprises an air pressure value.
S104: carrying out zero-speed correction on the motion inertia data by using the air pressure change data;
the zero-speed correction is a key basis for identifying foot motions based on the motion inertia data, and the fundamental purpose of the zero-speed correction is to determine a zero-speed interval for identifying the foot motions by using the motion inertia data so as to determine the zero-speed starting time and establish a calculation reference basis for subsequent various motion identifications. Therefore, as known to those skilled in the art, before gait recognition is performed by using the motion inertia data obtained by the inertia measurement unit, zero-speed correction is usually required, and conventionally, after analysis is performed by using the motion inertia data itself, correction is performed according to the correlation between various specific data therein.
According to the related traditional algorithm about the motion inertia data, when the shoe is grounded and stationary, an EKF (Extended Kalman Filter) algorithm acquires an error observed quantity, most gait detection algorithms only rely on a threshold value set by an IMU (inertial measurement Unit) for detection, but in very violent motion, the methods have some errors.
In the invention, because the air pressure measuring unit is introduced into the body sensing device and the air pressure change data is correspondingly introduced, the air pressure change data can be used for carrying out zero-speed correction on the motion inertia data. The air pressure measuring unit can effectively sense the treading dynamic of the foot of the user, so that the air pressure value is adopted independently or in combination to realize zero-speed correction. Except that the traditional IMU multi-condition discrimination algorithm is adopted, the method also depends on the air pressure sensor on the shoe pad of the intelligent shoe to detect, when the air pressure value obtained by the air pressure sensor exceeds a first threshold value, the shoe is shown to land, and at the moment, the speed and the displacement are both regarded as zero.
In one embodiment, the first threshold may be set as follows: considering that a certain pressure is applied to the air pressure measuring unit even in a static state due to the weight of a human body when the human body steps on the intelligent shoe, the zero-speed correction of the motion inertia data should be set when the air pressure value is greater than or equal to the first threshold value. The first threshold value generally represents an average starting value of the human body when the human body is pressurized at rest, and can be determined in advance by a person skilled in the art according to a statistical analysis result.
Preferably, the zero-speed detection information for starting the zero-speed correction according to the present application may be implemented by using the air pressure change data provided by the air pressure sensor alone, or by further combining the motion inertia data provided by the gyro sensor based on the air pressure change data. The air pressure sensor can detect dynamic information of feet stepping on the intelligent shoes in the process of strenuous exercise, and the gyroscope can provide motion detection information when the speed is slow. According to the respective characteristics of the two data, the zero-speed judgment accuracy can be further improved by combining the two data flexibly.
Specifically, referring to fig. 5, the process of starting the zero-velocity correction by detecting the zero-velocity interval with the air pressure sensor includes:
step S1041, setting a calculation window with a length of N, and sliding the calculation window to perform calculation, where each window includes N air pressure values in the continuously read air pressure change data, and N is a natural number greater than 2.
In one embodiment, several recent air pressure values of 10 or other nominal number are buffered using a calculation window as illustrated below.
| Pn-9 | Pn-8 | ... | Pn-1 | Pn |
Wherein p is the air pressure value and n is the data subscript.
And reading data according to the calculation window in a sliding mode continuously, and calculating the next step of each calculation window.
Step S1042, which is responsible for calculating the relationship between the air pressure values in each calculation window to determine whether the data feature represented by the calculation window is at a rising edge or a falling edge.
Specifically, in this step S1042, the data characteristics presented in each calculation window are determined according to the N air pressure values in one calculation window, and it is mainly determined whether the data representing the corresponding air pressure change is on the rising edge. For the judgment condition of the rising edge, the air pressure value of the data characteristic of the rising edge is larger than the air pressure value of the data characteristic of the rising edge, and the difference value of the air pressure value and the air pressure value exceeds a preset threshold value; for the determination condition of the falling edge, the data characteristic shows that the prior air pressure value is greater than the later air pressure value, and the difference value of the two values exceeds the preset threshold value. As for the preset threshold, the same principle can be determined by those skilled in the art through statistical averaging of the variation data of the measured air pressure measuring unit in use, and it can be understood that the specific number of the preset threshold will be an empirical, test value.
Correspondingly, when the calculation window is judged to be at a rising edge or a falling edge, the judgment method can be implemented by referring to the following codes:
max_index,max_val＝max(press_buff)
min_index,min_val＝min(press_buff)
if(max_val-min_val＞threshhold)
if(max_index＞min_index)
is_up
if(max_index＜min_index)
is_down
if the difference value between the maximum value and the minimum value in the window data exceeds a certain threshold, and the subscript max _ index of the maximum value data max _ val is greater than the subscript min _ index of the minimum value data min _ val, the section of code representation is judged to be a rising edge; if the difference between the maximum value data max _ val and the minimum value data min _ val in the window data exceeds a threshold, and the index max _ index of the maximum value data max _ val is smaller than the index min _ index of the minimum value data min _ val, it is determined as a falling edge. In an alternative embodiment, the N sampled air pressure values included in the calculation window may be divided into two halves for comparison, so as to improve the comparison efficiency.
And S1043, determining the air pressure change data corresponding to the calculation window corresponding to the rising edge as a zero-speed interval.
It is understood that if a rising edge is detected, it means that the smart shoe enters a state of contact with the ground; a liftoff condition is typically detected if a falling edge is detected. And considering a corresponding calculation window when the mobile terminal touches the ground as a zero-speed interval, and determining a zero-speed starting point through the calculation window. When the air pressure sensor is not pressed by external force, the air pressure value is at the minimum value, and the intelligent shoe is lifted off the ground or is unloaded; when external force is applied, the air pressure value rises, and the intelligent shoe lands on the ground. Therefore, by utilizing this feature, it can be known how to determine the zero speed state during the violent movement by analyzing the relationship between the rising edge and the falling edge, and as mentioned above, the air pressure variation data corresponding to the calculation window corresponding to the rising edge can be directly determined as the basis of the zero speed time, so as to prepare to implement the zero speed correction.
And step S1044 of performing zero-speed correction on the motion inertia data after confirming that the motion inertia data enters a zero-speed interval.
After the previous step is completed to determine the zero velocity interval, the zero velocity correction of the motion inertia data can be started immediately, and the specific method for zero velocity correction can be directly extended to the prior art, and some related information is also cited for reference hereinafter.
It can be understood that the zero-speed correction of the traditional motion inertia data can be realized only by adopting the air pressure change data.
In a preferred embodiment, before S1044, the method further includes: and detecting a zero-speed interval based on the motion inertia data of the somatosensory sensing device, and confirming that the zero-speed interval enters the zero-speed interval so as to start zero-speed correction when the zero-speed interval is detected and is synchronous with the zero-speed interval determined according to the air pressure change data. That is, in some embodiments of the present invention, the method of performing the zero-velocity correction by using the motion inertia data of the IMU in the prior art and the method of performing the zero-velocity correction by using the air pressure change data in the present invention may be combined, and the zero-velocity correction is started only when both the two conditions satisfy the zero-velocity interval condition.
The zero speed correction method is suitable for the embodiments, and can further introduce gyroscope data to judge the zero speed time on the basis of judging the zero speed time by using the air pressure change data, and determine whether to start the zero speed correction or not by combining the gyroscope data and the gyroscope data.
As known to those skilled in the art, a gyroscope assisted detection method for zero speed of a pedestrian at slow speed comprises the following steps:
1. similarly, by a sliding window with a fixed size, the data of the window is the mode of three axes of the gyroscope, namely the mean square value of the gyroscope:
| Gyr_norm(n-4) | Gyr_norm(n-3) | ... | Gyr_norm(n-1) | Gyr_norm(n-4) |
Gyr_norm＝norm(gyr)
2. the maximum value and the minimum value of the judgment window are in a certain range:
max_gyr_norm-min_gyr_norm＜thresh
3. the current gyroscope mode value is also within a certain specified range:
gyr_norm＜threshhold
when the above three conditions are simultaneously satisfied, the speed is determined to be zero.
That is, if the difference between the maximum value and the minimum value of the gyro mean square value in the window is not large, it means that the data is stable, and if the gyro mean square value at the current time is smaller than a certain threshold, that is, the time at which the velocity is 0.
The above is a method for determining the zero-speed interval by using a gyroscope in the prior art, and is provided for reference. From the above disclosure, those skilled in the art can know how to combine the zero-velocity correction process proposed based on the air pressure variation data with any zero-velocity correction method known in the prior art, that is, when the zero-velocity interval is determined by various technical means (including that proposed based on the air pressure variation data), the zero-velocity correction is started for the IMU, and therefore, how to implement the zero-velocity interval determination by other means should not be used to limit the spirit of the present invention. Therefore, the invention can not only use the air pressure change data of the air pressure sensor alone for implementing the zero-speed correction, but also further combine the air pressure change data and the data provided by the gyroscope together for performing the zero-speed correction, so that the zero-speed correction can be started when the zero-speed moment is judged according to the air pressure change data and the data provided by the gyroscope, the zero-speed moment can be accurately determined, and the misjudgment caused by the suspended and static feet of a human body can be avoided.
In one embodiment of the present invention, EKF (Extended Kalman Filter) is used for zero-velocity correction. Those skilled in the art know how to use EKF for zero velocity correction, so that details of the correction cannot be found.
However, in a preferred embodiment, the zero speed correction comprises the following process:
prediction process (state transition process):
wherein the content of the first and second substances,
for the state to be predicted, the index k is the sampling time, i is the i-th iteration of the operation, and G is the input increment, here the identity matrix.
Respectively, an error of an attitude angle, an error of a speed and an error of a position; wherein the state transition matrix F is
Wherein S is a three-dimensional acceleration on a geodetic coordinate system to form an antisymmetric matrix, and a gain matrix G is an identity matrix in the application. In the prediction process, the transition process of the state covariance matrix is as follows:
wherein, F is a state transition matrix, P is a covariance matrix of a system state, and Q is a covariance matrix of system noise.
And (3) updating:
the updating part of the EKF process in the application is provided by zero-speed detection, namely observation information with the three-dimensional speed of 0 is provided, and an updating detection algorithm is shown below, wherein the whole process of the EKF in the application is briefly explained.
When the observation information of the velocity 0 is obtained, the predicted state can be corrected.
a. Computing an EKF gain matrix
Wherein Hvel＝[O3×3 I3×3 O3×3]To observe a matrix means that what is observed is the dimension (three-dimensional velocity) corresponding to the identity matrix.
b. State correction
c. Covariance matrix update
S106: calculating the corrected motion inertia data through inertial navigation attitude to obtain motion mode data;
preferably, the motion inertial data after zero-speed correction is subjected to inertial navigation attitude calculation to obtain motion mode data, wherein the motion mode data comprises attitude, position and speed data, and then the attitude, the speed and the position are subjected to coordinate transformation to obtain a motion track of the foot; and updating the posture, the speed and the position of the foot according to the data measured by the somatosensory sensing device in real time, and further updating the motion trail of the foot. It is understood that since inertial navigation attitude solution using motion inertial data is a well-established technique, this step can be implemented by those skilled in the art directly using the prior art.
S108: and matching the motion mode data with a preset calculation model, and identifying corresponding foot actions.
Preferably, the motion pattern data comprises attitude, position, velocity data; the matching of the motion pattern data with a preset calculation model to identify corresponding foot actions comprises:
coordinate transformation is carried out on the posture, the speed and the position data to obtain the motion trail of the foot;
and matching the motion trail with a preset calculation model, and identifying corresponding foot actions.
Preferably, the calculation model may be a preset motion trajectory.
Those skilled in the art know how to use the motion pattern data acquired based on the IMU to perform the relevant technical means of foot motion recognition, so detailed description is forbidden. However, in a preferred embodiment, in consideration of determining the starting condition of the foot motion, when the unit time is, the change amount of the position of the user may be obtained by performing displacement calculation on the motion pattern data generated by the foot motion, and when the change amount of the position reaches the second threshold value and the direction thereof is consistent with the direction of the change of the position, the motion is determined to be effective; or, when the air pressure value continuously increases in unit time and is greater than or equal to the first threshold value, the action is judged to be effective. The second threshold is a preset distance.
Preferably, the foot motion may include: jumping, left moving, right moving, forward moving, backward moving, running or squatting.
When the intelligent shoe implementing the method is used for interacting with computer equipment such as an intelligent television, a mobile terminal, a game machine and the like, the intelligent shoe can be used as input equipment of user instructions. In this case, the intelligent shoe establishes communication connection with the computer device through the communication module of the intelligent shoe, and outputs the recognition result obtained after the intelligent shoe performs action recognition to the computer device in real time. When the computer equipment starts the related game program or the health data APP, the identification results can also be regarded as related user instructions or user data, correspondingly, the program process of the computer equipment can also feed back information or send a notice to the intelligent shoe in response to the identification results, for example, a notice instruction for controlling the vibration alarm of the vibration sensor of the intelligent shoe is sent, and the like, so that the human-computer interaction experience in the application scenes can be improved on the basis that the intelligent shoe can more accurately provide the identification results of the foot actions of the user based on the air pressure change data.
In summary, the present application makes the following related contributions based on the prior art:
firstly, initial attitude alignment is carried out by utilizing an accelerometer and a magnetometer, and an inertial navigation algorithm is deduced by considering the estimation of a filtering error;
secondly, gait detection is carried out by means of a gyroscope and an accelerometer, landing detection is carried out by means of an air pressure sensor, zero-speed correction is carried out at the time of landing the shoes, and speed error observation is provided;
thirdly, an Extended Kalman Filter (EKF) carries out optimal estimation on the position, the speed, the attitude, the acceleration and the angular acceleration to form an IPZE (INS-PDR-ZUPT-EKF) positioning algorithm;
and fourthly, identifying running, front-back left-right movement, jumping and other actions according to the information such as the position, the posture and the like, and identifying squatting actions according to the characteristic value of the change process of the air pressure sensor.
With reference to fig. 5, fig. 5 is a block diagram of a foot motion recognition device according to an embodiment of the present application. The device includes: the acquiring module 100 is used for acquiring motion inertia data and air pressure change data generated by triggering the body sensing device in the intelligent shoe; the correction module 200 is configured to perform zero-speed correction on the motion inertia data by using the air pressure change data; the calculating module 300 is used for calculating the corrected motion inertia data through the inertial navigation attitude to obtain motion mode data; and the identification module 400 is configured to match the motion pattern data with a preset calculation model, and identify a corresponding foot motion.
In some embodiments, the obtaining module 100 is specifically configured to: acquiring the motion inertia data by using an inertia measurement unit in the somatosensory sensing device; and acquiring the air pressure change data by utilizing an air pressure measuring unit in the somatosensory sensing device. Wherein, utilize the inertial measurement unit among the body sensing device to obtain motion inertial data includes: measuring acceleration and angular velocity data through an accelerometer and a gyroscope carried by the inertial measurement unit; measuring acceleration and geomagnetic data by a magnetometer carried by the inertial measurement unit; and taking the acceleration and angular velocity data and the acceleration and geomagnetic data as the motion inertia data. Wherein, utilize the atmospheric pressure measuring unit among the body sensing device to obtain atmospheric pressure change data includes: the air pressure change data of the intelligent shoe is measured through an air pressure sensor carried by the air pressure measuring unit, and the air pressure change data comprises an air pressure value.
In a preferred embodiment, the modification module 200 is specifically configured to: setting a calculation window with the length of N, and sliding the calculation window to calculate, wherein each window comprises N air pressure values in the continuously read air pressure change data, and N is a natural number more than 2; judging the data characteristics presented by each calculation window according to the N air pressure values, and determining whether the data characteristics represent that the corresponding air pressure change data is in a rising edge, wherein for the rising edge, the air pressure value presented by the data characteristics is greater than the previous air pressure value, and the difference value of the two air pressure values exceeds a preset threshold value; determining a calculation window corresponding to the rising edge as entering a zero-speed interval; and after confirming that the movement inertia data enters a zero-speed interval, performing zero-speed correction on the movement inertia data. Wherein, before the zero speed correction is performed on the motion inertia data after the entering of the zero speed interval is confirmed, the method further comprises the following steps: and detecting a zero-speed interval based on the motion inertia data of the somatosensory sensing device, and confirming that the zero-speed interval enters the zero-speed interval so as to start zero-speed correction when the zero-speed interval is detected and is synchronous with the zero-speed interval determined according to the air pressure change data.
In a further embodiment, the identification module 400 is specifically configured to: coordinate transformation is carried out on the posture, speed and position data included in the motion mode data to obtain the motion trail of the foot; and matching the motion trail with a preset calculation model, and identifying corresponding foot actions to output an identification result.
The present application further provides an embodiment of a smart shoe, comprising:
the motion sensing device is used for sensing motion inertia data and air pressure change data generated by the intelligent shoe; a memory for storing a computer program; a processor for implementing the steps of the intelligent shoe action recognition method as described above when the computer program is executed. Of course, the intelligent shoe can also comprise various necessary network interfaces, power supplies, other parts and the like.
The application still provides another embodiment of an intelligent shoes, and sensing device is felt to this intelligent shoes embeds body, sensing device includes is felt to the body: the inertia measurement unit 211 is used for sensing motion inertia data generated by the intelligent shoe being actuated; the air pressure measuring unit 122 is used for sensing air pressure change data generated by the intelligent shoe being pressurized; the control unit 213 is configured to perform zero-speed correction on the motion inertia data by using the air pressure change data, obtain motion pattern data by performing inertial navigation attitude calculation on the corrected motion inertia data, match the motion pattern data with a preset calculation model, and identify corresponding foot motions; and the communication module 22 is used for outputting the control unit identification result to the equipment in communication connection with the control unit identification result.
The present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the intelligent shoe action recognition method as described above. The storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Because the situation is complicated and cannot be illustrated by a list, a person skilled in the art can realize that many examples exist according to the basic method principle provided by the application and the practical situation, and the protection scope of the application should be protected without enough inventive work.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. An intelligent shoe action recognition method is characterized by comprising the following steps:
acquiring motion inertia data and air pressure change data generated by triggering a body sensing device in the intelligent shoe;
carrying out zero-speed correction on the motion inertia data by using the air pressure change data;
calculating the corrected motion inertia data through inertial navigation attitude to obtain motion mode data;
and matching the motion mode data with a preset calculation model, and identifying corresponding foot actions to output an identification result.
2. The method according to claim 1, wherein the step of acquiring the motion inertia data and the air pressure change data generated by triggering the body sensing device in the intelligent shoe comprises the following steps:
acquiring the motion inertia data by using an inertia measurement unit in the somatosensory sensing device;
and acquiring the air pressure change data by utilizing an air pressure measuring unit in the somatosensory sensing device.
3. The method of claim 2, wherein the obtaining the motion inertia data with an inertial measurement unit in a somatosensory sensing device comprises:
measuring acceleration and angular velocity data through an accelerometer and a gyroscope carried by the inertial measurement unit;
measuring acceleration and geomagnetic data by a magnetometer carried by the inertial measurement unit;
and taking the acceleration and angular velocity data and the acceleration and geomagnetic data as the motion inertia data.
4. The method of claim 2, wherein the step of obtaining the air pressure change data by an air pressure measuring unit in the somatosensory sensing device comprises:
the air pressure change data of the intelligent shoe is measured through an air pressure sensor carried by the air pressure measuring unit, and the air pressure change data comprises an air pressure value.
5. The method of claim 1, wherein said zero velocity correction of said inertial data using said air pressure change data comprises:
setting a calculation window with the length of N, and sliding the calculation window to calculate, wherein each window comprises N air pressure values in the continuously read air pressure change data, and N is a natural number more than 2;
judging the data characteristics presented by each calculation window according to the N air pressure values, and determining whether the data characteristics represent that the corresponding air pressure change data is in a rising edge, wherein for the rising edge, the air pressure value presented by the data characteristics is greater than the previous air pressure value, and the difference value of the two air pressure values exceeds a preset threshold value;
determining a calculation window corresponding to the rising edge as entering a zero-speed interval;
and after confirming that the movement inertia data enters a zero-speed interval, performing zero-speed correction on the movement inertia data.
6. The method of any of claim 5, wherein before performing a zero velocity correction on the motion inertia data after confirming entry into a zero velocity interval, further comprising:
and detecting a zero-speed interval based on the motion inertia data of the somatosensory sensing device, and confirming that the zero-speed interval enters the zero-speed interval so as to start zero-speed correction when the zero-speed interval is detected and is synchronous with the zero-speed interval determined according to the air pressure change data.
7. The method according to any one of claims 1 to 6, wherein the matching the motion pattern data with a preset calculation model, and identifying corresponding foot actions to output identification results comprises:
coordinate transformation is carried out on the posture, speed and position data included in the motion mode data to obtain the motion trail of the foot;
and matching the motion trail with a preset calculation model, and identifying corresponding foot actions to output an identification result.
8. An action recognition device, comprising:
the acquisition module is used for acquiring motion inertia data and air pressure change data generated by triggering the body sensing device in the intelligent shoe;
the correction module is used for performing zero-speed correction on the motion inertia data by utilizing the air pressure change data;
the resolving module is used for resolving the corrected motion inertia data through the inertial navigation attitude to obtain motion mode data;
and the recognition module is used for matching the motion mode data with a preset calculation model and recognizing corresponding foot actions so as to output recognition results.
9. The utility model provides an intelligent shoe, built-in body sense sensing device, its characterized in that, body sense sensing device includes:
the inertia measurement unit is used for sensing movement inertia data generated by the intelligent shoe in an actuated mode;
the air pressure measuring unit is used for sensing air pressure change data generated by pressurization of the intelligent shoe;
the control unit is used for carrying out zero-speed correction on the motion inertia data by utilizing the air pressure change data, resolving the corrected motion inertia data through inertial navigation attitude to obtain motion mode data, matching the motion mode data with a preset calculation model and identifying corresponding foot actions;
and the communication module is used for outputting the identification result of the control unit to equipment in communication connection with the control unit.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the intelligent shoe action recognition method according to any one of claims 1 to 7.
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