CN113729693A - Artificial intelligence-based exercise intensity detection method, device, equipment and medium - Google Patents
Artificial intelligence-based exercise intensity detection method, device, equipment and medium Download PDFInfo
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Abstract
The application relates to the technical field of artificial intelligence, and provides a method, a device, equipment and a medium for detecting motion intensity based on artificial intelligence, wherein the method comprises the following steps: acquiring sole pressure data of a user to be detected, which is sent by the intelligent shoe; acquiring output data of a gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope; determining the movement parameters of the user to be detected according to the pressure data and the angular motion parameters; determining the motion data of the user to be detected according to the movement parameters; and determining the movement score of the user to be detected according to the movement data, and determining the movement intensity of the user to be detected based on the movement score. The exercise intensity of the user to be detected can be accurately detected, and the use experience of the user to be detected is greatly improved. The present application also relates to blockchain technology, where the above-mentioned sole pressure data and exercise intensity may be stored.
Description
Technical Field
The present application relates to the field of artificial intelligence technologies, and in particular, to a method, an apparatus, a device, and a medium for detecting exercise intensity based on artificial intelligence.
Background
In recent years, the population of the aged Chinese population and the younger chronic patients is increasingly large, and the high-quality long-term body health index monitoring is the focus of people's attention. For example, physical ability is an important index for judging physical health, most of physical ability tests are performed manually at present, so that efficiency is low, corresponding tests cannot be performed according to physical qualities of each person, test results are not strict, the step number of a user is collected through terminal equipment such as a mobile phone or a smart watch, the physical ability of the user is estimated through the step number, and the step number estimation of the physical ability of the user has the defect of inaccuracy. Therefore, how to accurately detect the exercise intensity of the user to be detected is a problem to be solved urgently.
Disclosure of Invention
The application mainly aims to provide a method, a device, equipment and a medium for detecting the exercise intensity based on artificial intelligence, and aims to improve the accuracy of the exercise intensity detection of a user to be detected.
In a first aspect, the present application provides a method for detecting exercise intensity, including the following steps:
acquiring sole pressure data of a user to be detected, which are sent by an intelligent shoe, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe;
acquiring output data of a gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope, wherein the gyroscope is arranged in the intelligent shoe;
determining a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, wherein the movement parameter comprises at least one of a movement distance, a foot lifting height and a foot step change frequency;
determining motion data of the user to be detected according to the movement parameters, wherein the motion data comprises at least one of walking speed, walking steps, walking track, motion quantity and motion form;
and determining the movement score of the user to be detected according to the movement data, and determining the movement intensity of the user to be detected based on the movement score.
In a second aspect, the present application further provides an exercise intensity detection apparatus, which includes an obtaining module and a determining module, wherein:
the acquisition module is used for acquiring sole pressure data of a user to be detected, which are sent by the intelligent shoe, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe;
the acquisition module is also used for acquiring output data of the gyroscope;
the determining module is used for determining the angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope;
the determining module is further configured to determine a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, where the movement parameter includes at least one of a movement distance, a foot lifting height, and a foot step change frequency;
the determining module is further configured to determine motion data of the user to be tested according to the movement parameters, where the motion data includes at least one of a walking rate, a walking step number, a walking track, an amount of motion, and a motion form;
the determining module is further configured to determine a movement score of the user to be detected according to the movement data, and determine the movement intensity of the user to be detected based on the movement score.
In a third aspect, the present application also provides a computer device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program, when executed by the processor, implements the steps of the exercise intensity detection method as described above.
In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, where the computer program, when executed by a processor, implements the steps of the exercise intensity detection method as described above.
The application provides a method, a device, equipment and a medium for detecting exercise intensity based on artificial intelligence, and the method, the device, the equipment and the medium are used for acquiring sole pressure data of a user to be detected, wherein the sole pressure data are sent by an intelligent shoe, and comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe; then acquiring output data of the gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope; according to the pressure data and the angular motion parameters, the movement parameters of the user to be detected can be accurately determined; according to the movement parameters, the movement data of the user to be detected can be accurately determined; the movement score of the user to be detected can be accurately determined through the movement data, and the movement intensity of the user to be detected can be accurately and conveniently determined based on the movement score. The exercise intensity of the user to be detected can be accurately detected through the scheme, and the use experience of the user to be detected is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for detecting exercise intensity according to an embodiment of the present disclosure;
FIG. 2 is a schematic view of a scenario in which a plurality of pressure sensors in an intelligent shoe detect sole pressure data according to an embodiment of the present application;
fig. 3 is a schematic flowchart of another exercise intensity detection method according to an embodiment of the present application;
fig. 4 is a schematic block diagram of a exercise intensity detection apparatus provided in an embodiment of the present application;
fig. 5 is a schematic block diagram of another exercise intensity detection apparatus provided in the embodiments of the present application;
fig. 6 is a schematic block diagram of a structure of a computer device according to an embodiment of 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
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, but not all, embodiments of the present application. 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.
The flow diagrams depicted in the figures are merely illustrative and do not necessarily include all of the elements and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
The embodiment of the application provides a method, a device, equipment and a medium for detecting the exercise intensity based on artificial intelligence. The exercise intensity detection method can be applied to terminal equipment, and the terminal equipment can be electronic equipment such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant and wearable equipment.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for detecting exercise intensity according to an embodiment of the present application.
As shown in fig. 1, the exercise intensity detection method includes steps S101 to S105.
Step S101, sole pressure data of a user to be detected, which are sent by the intelligent shoe, are obtained, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe.
Wherein, the user that awaits measuring has worn intelligent shoes, and this intelligent shoes includes a plurality of pressure sensor, and these a plurality of pressure sensor are used for gathering the sole pressure in each region of the user's sole that awaits measuring. The intelligent shoe can be selected according to actual conditions, the embodiment of the application is not specifically limited to this, the pressure sensor can be arranged in an insole of the intelligent shoe or in a sole of the intelligent shoe, the pressure sensor can be selected according to actual conditions, the embodiment of the application is not specifically limited to this, and for example, the pressure sensor can be a piezoresistive pressure sensor.
In one embodiment, a plurality of pressure sensors in the intelligent shoe of the user to be detected acquire the pressure of each area of the sole of the foot of the user to be detected, so as to obtain sole pressure data of the user to be detected; the terminal equipment acquires sole pressure data of the user to be detected, which are sent by the intelligent shoe. It should be noted that the exercise intensity detection method may be applied to a terminal device, where the terminal device and the smart shoe have established a communication connection, and the communication connection mode may be set according to the actual situation, for example, the communication connection mode may be a connection mode such as a bluetooth connection, a WiFi connection, and the like. The sole pressure data of the user to be detected can be accurately acquired through the pressure sensors in the intelligent shoe.
Exemplarily, as shown in fig. 2, the intelligent shoe includes a first pressure sensor a, a second pressure sensor B, and a third pressure sensor C, and the first pressure sensor a acquires pressure data of an area 1 of a sole of a user to be measured to obtain first pressure data, the second pressure sensor B acquires pressure data of an area 2 of the sole of the user to be measured to obtain second pressure data, and the second pressure sensor C acquires pressure data of an area 3 of the sole of the user to be measured to obtain third pressure data. The sole pressure data of the user to be detected can be accurately detected through the pressure sensors.
It should be noted that the sole pressure data of the user to be measured includes total pressure data obtained by superimposing the pressure data detected by each pressure sensor and each pressure data, and the superimposition of each pressure data may be set according to an actual situation, for example, directly performing addition operation on each pressure data to obtain total pressure data, or obtaining a preset pressure weight, performing multiplication operation on each pressure data and each pressure weight respectively to obtain a plurality of pressure score data, and accumulating the plurality of pressure score data to obtain total pressure data.
And S102, acquiring output data of a gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope, wherein the gyroscope is arranged in the intelligent shoe.
The angular motion parameters comprise parameters such as the motion direction, the speed and the acceleration of the foot of the user to be detected, and the motion direction comprises forward motion, backward motion, upward foot lifting motion, downward angular motion, leftward motion, upward motion, leftward movement, rightward movement, forward movement, leftward movement, rightward movement, and the like.
In an embodiment, the sole of the intelligent shoe of the left foot of the user to be detected is provided with a first gyroscope, the sole of the intelligent shoe of the right foot of the user to be detected is provided with a second gyroscope, when the user to be detected moves, first output data of the left foot movement are output through the first gyroscope, second output data of the right foot movement are output through the second gyroscope, and the angular movement parameters of the two feet of the user to be detected are determined according to the first output data and the second output data. The first gyroscope and the second gyroscope can be selected according to actual conditions, the embodiment of the application is not particularly limited to the actual conditions, and the angular motion parameters of the feet of the user to be detected can be accurately detected through the gyroscopes.
In an embodiment, the determining the angular motion parameters of the feet of the user to be measured according to the first output data and the second output data may be: acquiring a preset angular motion weight; the angular motion weight is used for respectively carrying out multiplication operation on the first output data and the second output data to obtain a first angular motion parameter and a second angular motion parameter; and adding the first angular motion parameter and the second angular motion parameter to obtain the angular motion parameters of the feet of the user to be detected. The angular motion parameters can be accurately obtained by calculating the first output data and the second output data.
Step S103, determining a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, wherein the movement parameter comprises at least one of a movement distance, a foot lifting height and a foot step change frequency.
The moving parameters include a moving distance, a foot lifting height and a step change frequency, the moving distance is the moving distance of each step of the user to be detected, for example, the moving distance is 0.4 meter, the foot lifting height is the highest height of each foot lifting of the user to be detected, for example, the foot lifting height is 0.2 meter, and the step change frequency is the step per second of the user to be detected.
In one embodiment, the angular motion parameters include angular motion acceleration including horizontal angular acceleration in a horizontal direction and vertical angular acceleration in a vertical direction, a plurality of timestamps of any sole of the user to be detected with sole pressure data are acquired, and suspension time of the sole is determined according to the plurality of timestamps; determining a moving distance according to the suspension time and the horizontal angular acceleration, and/or determining a foot lifting height according to the suspension time and the vertical angular acceleration; and/or counting the times of changing the horizontal angular acceleration from positive to negative within a preset time period to obtain the step number of the user to be detected; and dividing the step number by the preset time period to obtain the step change frequency. It should be noted that the arc line that the foot of the user to be tested runs during walking is defined as a parabola.
Illustratively, the method for determining the suspension time of the sole of the foot according to the plurality of timestamps is as follows: the timestamp of the sole pressure data of the left foot of the user to be tested comprises 10 hours, 20 minutes, 5 seconds, 500 milliseconds, 10 hours, 20 minutes, 6 seconds and 600 milliseconds, the first suspension time is 500 milliseconds, and the second suspension time is 600 milliseconds.
In an embodiment, according to the flying time and the horizontal angular acceleration, the moving distance may be determined by: obtaining a preset acceleration displacement formula
Wherein, theAnd L is the moving distance, a is the horizontal acceleration, t is the suspension time, and the suspension time and the horizontal angular acceleration are substituted into the formula to be calculated based on the acceleration displacement formula to obtain the moving distance. The moving distance can be accurately obtained through the suspension time and the horizontal acceleration. It should be noted that the horizontal acceleration includes a forward acceleration when the foot is just lifted and a reverse acceleration when the foot decelerates after reaching the highest point, and similarly, an acceleration section movement displacement is generated according to an acceleration displacement formula, half of suspension time and the forward acceleration; and generating the moving displacement of the deceleration section according to an acceleration displacement formula, half of suspension time and reverse acceleration, and adding the moving displacement of the acceleration section and the moving displacement of the deceleration section to obtain the moving displacement. The positive acceleration and the negative acceleration are equal in magnitude and opposite in direction.
In an embodiment, according to the flying time and the vertical angular acceleration, the method for determining the height of the lifting foot may be: obtaining a preset acceleration height formula
And H is the height of the lifting foot, a is vertical acceleration, t is suspension time, and the suspension time and the vertical angular acceleration are substituted into the formula to be calculated based on the acceleration height formula to obtain the height of the lifting foot. The foot lifting height can be accurately obtained through the suspension time and the vertical acceleration. It should be noted that the vertical acceleration includes a forward acceleration when the foot is just lifted and a reverse acceleration when the foot is lowered after the foot reaches the highest point, and similarly, according to an acceleration height formula, a half of suspension time and the forward acceleration, a foot rising section height is generated, which is the foot lifting height of the user to be detected; and similarly, generating the height of the foot descending section, namely the foot lifting height of the user to be detected, according to an acceleration height formula, half of suspension time and reverse acceleration.
Illustratively, the number of times that the horizontal acceleration of the user to be tested is positive and negative within 1 minute is 80, the number of steps of the user to be tested is 80 steps, and the frequency of the steps of the user to be tested is obtained by dividing the 80 steps by 1 minute.
In one embodiment, the manner of determining the step change frequency may further be: the method comprises the steps of obtaining the number of times that the pressure of the left intelligent shoe of a user to be detected becomes zero in a preset time period, obtaining the number of times that the pressure of the right intelligent shoe becomes zero, dividing the number of times that the pressure of the left intelligent shoe becomes zero and the number of times that the pressure of the right intelligent shoe becomes zero by the preset time period, and obtaining the step change frequency of the user to be detected.
Step S104, determining the motion data of the user to be detected according to the movement parameters, wherein the motion data comprises at least one of walking speed, walking steps, walking track, motion amount and motion form.
The motion data comprises walking speed, walking steps, walking track, motion amount and motion forms, wherein the walking speed is the walking speed of a user to be tested, the walking speed is higher, the walking speed indicates that the user walks faster, the walking track is a track graph of the walking of the user to be tested, the motion amount is the consumed energy of the motion of the user to be tested, the more the motion amount is, the more the user consumes the energy, the motion forms are body forms of the user to be tested in the motion process, and the motion forms comprise light steps, heavy steps and uncoordinated steps.
In an embodiment, according to the movement parameter, the determining the walking rate of the user to be tested may be: and removing the moving position of the user to be detected to move the moving displacement time to obtain the walking speed of the user to be detected. Or multiplying the step change frequency by the preset time to obtain a displacement distance, and dividing the displacement distance by the preset time to obtain the walking speed.
In an embodiment, according to the movement parameter, the determining the number of walking steps of the user to be tested may be: and multiplying the step change frequency by the walking time of the user to be tested to obtain the walking steps. Or obtaining the number of times that the sole pressure becomes zero from the sole pressure data, wherein the number of times that the sole pressure becomes zero is the walking step number of the user to be detected.
In an embodiment, according to the movement parameter, the determining the walking track of the user to be tested may be: the method comprises the steps of obtaining Global Positioning System (GPS) Positioning data of a user to be detected, and generating a walking track of the user to be detected according to the GPS Positioning data and a displacement distance. The walking track obtained according to the GPS positioning data and the displacement distance may be calculated according to actual conditions, which is not specifically limited in the embodiment of the present application.
In an embodiment, according to the movement parameter, the method for determining the amount of movement of the user to be detected may be: and multiplying the step change frequency by the walking time of the user to be detected to obtain the walking step number of the user to be detected, acquiring a preset mapping relation table between the walking step number and the exercise amount, and searching the exercise amount corresponding to the walking step number from the mapping relation table to obtain the exercise amount of the user to be detected. The mapping relationship table is a mapping relationship table that is established in advance according to the walking step number and the exercise amount, and the establishment of the mapping relationship table can be established according to actual conditions, which is not specifically limited in the embodiment of the present application. The amount of exercise of the user to be tested can be accurately obtained through the mapping relation table.
In one embodiment, the motion profile includes light steps, heavy steps and inconsistent steps, and according to the movement parameters, the motion profile may be determined by: when the step change frequency is greater than a preset threshold value and the step change frequency tends to be stable, determining that the motion form is a step lightness index; when the step change frequency is determined to be less than or equal to the preset threshold value, determining that the motion form is heavy; and when the foot lifting height difference of the two feet of the user to be detected is larger than the preset height, determining that the motion form is inconsistent in step. The preset threshold and the preset height may be set according to actual conditions, which is not specifically limited in the embodiment of the present application. According to the step change frequency and the foot lifting height, the motion form of the user to be detected can be accurately determined.
And S105, determining the movement score of the user to be detected according to the movement data, and determining the movement intensity of the user to be detected based on the movement score.
The motion score is an evaluation score for evaluating the motion of the user, and the higher the motion score is, the more the motion of the user to be detected is. The exercise intensity includes an ultra-low exercise intensity indicating a severe lack of exercise, a low exercise intensity indicating a lack of exercise, a medium exercise intensity indicating a normal amount of exercise, and a high exercise intensity indicating an excessive exercise.
In one embodiment, a mapping relation table between preset exercise scores and exercise intensities is obtained; and searching the motion intensity corresponding to the motion score from the mapping relation table to obtain the motion intensity of the user to be detected. The mapping relation table is a mapping relation table which is established in advance according to the exercise score and the exercise intensity, and the mapping relation table is established according to actual conditions, which is not specifically limited in the embodiment of the application.
Illustratively, the exercise score of the user to be tested is 80, and the exercise intensity corresponding to the exercise score of 80 is searched from the mapping relation table, so that the exercise intensity is the medium exercise intensity. For another example, the exercise score of the user to be measured is 20 points, and the exercise intensity corresponding to the exercise score of 20 points is searched from the mapping relation table, so that the exercise intensity is the ultra-low exercise intensity.
In one embodiment, the intelligent shoe of the user to be tested is provided with a sport intensity lamp, and when the sport intensity is ultralow, the sport intensity lamp of the intelligent shoe lights a blue lamp to remind the user to be tested of serious lack of sport; when the intensity of motion is low intensity of motion, the yellow light is lighted to the intensity of motion lamp of intelligent shoes to remind the user that awaits measuring to lack the motion, and when the intensity of motion be medium intensity of motion, the green light is lighted to the intensity of motion lamp of intelligent shoes, and is normal with the amount of exercise of reminding the user that awaits measuring, and when the intensity of motion be the intensity of motion lamp bright red light of high intensity of motion intelligent shoes, in order to remind the user that awaits measuring to move the excess. The amount of exercise of the user to be tested is reminded through the lighting of the intelligent shoes, so that the current exercise intensity of the user to be tested is accurately reminded.
In an embodiment, when the movement distance of the user to be detected in one step is smaller than a preset distance, the amplitude of the horizontal deviation is larger than the preset deviation distance, and the user to be detected does not move within a subsequent preset time, it is determined that the user to be detected may wrestle, the position of the user to be detected is acquired, and the position information and the characteristic condition of the user to be detected are sent to a preset emergency contact person, so that the user to be detected is helped more quickly.
The exercise intensity detection method provided by the embodiment obtains sole pressure data of a user to be detected, which is sent by the intelligent shoe, wherein the sole pressure data comprises sole pressures acquired by a plurality of pressure sensors in the intelligent shoe; then acquiring output data of the gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope; according to the pressure data and the angular motion parameters, the movement parameters of the user to be detected can be accurately determined; according to the movement parameters, the movement data of the user to be detected can be accurately determined; the movement score of the user to be detected can be accurately determined through the movement data, and the movement intensity of the user to be detected can be accurately and conveniently determined based on the movement score. The exercise intensity of the user to be detected can be accurately detected through the scheme, and the use experience of the user to be detected is greatly improved.
Referring to fig. 3, fig. 3 is a schematic flow chart of another exercise intensity detection method according to an embodiment of the present application.
As shown in fig. 3, the exercise intensity detection method includes steps S201 to S203.
Step S201, obtaining sole pressure data of a user to be detected, wherein the sole pressure data are sent by the intelligent shoe, and the sole pressure data comprise sole pressures collected by a plurality of pressure sensors in the intelligent shoe.
A plurality of pressure sensors in the intelligent shoe of the user to be detected acquire the pressure of each area of the sole of the user to be detected, and sole pressure data of the user to be detected are obtained. And acquiring sole pressure data of the user to be detected, which is sent by the intelligent shoe, to obtain the sole pressure data of the user to be detected. It should be noted that the exercise intensity detection method may be applied to a terminal device, where the terminal device and the smart shoe have established a communication connection, and the communication connection mode may be set according to the actual situation, for example, the communication connection mode may be a connection mode such as a bluetooth connection, a WiFi connection, and the like. The sole pressure data of the user to be detected can be accurately acquired through the pressure sensors in the intelligent shoe.
And S202, determining whether the walking force of the user to be tested is correct or not according to the sole pressure data.
Acquiring a preset sole pressure distribution table, wherein the sole pressure distribution table comprises standard pressure proportion of each area of a sole; calculating the current pressure ratio of each area of the sole of the user to be detected according to the sole pressure data; when the difference value between the current pressure ratio of at least one area and the corresponding standard pressure ratio is larger than a preset threshold value, determining that the walking force of the user to be detected is incorrect; and when the difference value between the current pressure ratio of each area and the standard pressure ratio of the corresponding area is less than or equal to a preset threshold value, determining that the walking force of the user to be tested is correct. The preset threshold may be set according to an actual situation, which is not specifically limited in the embodiment of the present application. The walking force of the user to be tested is accurately determined by the difference value of the current pressure ratio of each area and the standard pressure ratio.
In an embodiment, the way of calculating the current pressure ratio of each region of the sole of the user to be measured according to the sole pressure data may be: and dividing the pressure data of each area by the pressure data of the whole sole to obtain the current pressure ratio of each area of the sole. For example, as shown in fig. 2, if the pressure data of the area 1 of the sole of the foot of the user to be measured is 130N, the pressure data of the area 2 of the sole of the foot of the user to be measured is 90N, the pressure data of the area 1 of the sole of the foot of the user to be measured is 80N, and the pressure data of the entire sole is 300N, the current pressure of the area 1 of the sole of the foot of the user to be measured accounts for 0.43%, the current pressure of the area 1 of the sole of the foot of the user to be measured accounts for 0.30%, and the current pressure of the area 1 of the sole of the foot of the user to be measured accounts for 0.27%. The current pressure fraction of each region of the sole can be obtained by dividing the pressure data of each region by the entire sole pressure data.
Step S203, if the walking force of the user to be tested is incorrect, standard walking force data are obtained, and the standard walking force data are sent to the intelligent shoe, so that the intelligent shoe controls a corresponding vibration sensor in the intelligent shoe to vibrate according to the standard walking force data, and the user to be tested is prompted to exert force correctly.
When the fact that the force of the user to be detected is incorrect is determined, standard walking force data are obtained, the standard walking force data are sent to the intelligent shoes, the intelligent shoes receive the standard walking force data to control the intelligent shoes to vibrate corresponding to the vibration sensors, so that the user to be detected is reminded of correctly exerting force, the incorrect force of the user to be detected is corrected, and the problem that the user to be detected is in an unhealthy walking posture is solved. The vibration sensor can be selected according to actual conditions, the embodiment of the application is not particularly limited to this, and the vibration sensor can be arranged in an insole of the intelligent shoe.
The exercise intensity detection method provided by the embodiment obtains sole pressure data of the user to be detected sent by the intelligent shoe, and determines whether the walking force of the user to be detected is correct or not according to the sole pressure data; if the walking force of the user to be detected is incorrect, the standard walking force data are obtained, and the standard walking force data are sent to the intelligent shoes, so that the intelligent shoes control the corresponding vibration sensors in the intelligent shoes to vibrate according to the standard walking force data, the user to be detected is prompted to correctly apply force, the walking posture of the user to be detected is corrected, and the body health degree of the user to be detected can be improved.
Referring to fig. 4, fig. 4 is a schematic block diagram of an exercise intensity detection apparatus according to an embodiment of the present disclosure.
As shown in fig. 4, the exercise intensity detection apparatus 300 includes an obtaining module 310 and a determining module 320, wherein:
the obtaining module 310 is configured to obtain sole pressure data of a user to be detected, where the sole pressure data includes sole pressures acquired by a plurality of pressure sensors in an intelligent shoe;
the obtaining module 310 is further configured to obtain output data of a gyroscope;
the determining module 320 is configured to determine angular motion parameters of the two feet of the user to be detected according to the output data of the gyroscope;
the determining module 320 is further configured to determine a movement parameter of the user to be tested according to the pressure data and the angular motion parameter, where the movement parameter includes at least one of a movement distance, a foot lifting height, and a foot step change frequency;
the determining module 320 is further configured to determine motion data of the user to be tested according to the movement parameter, where the motion data includes at least one of a walking rate, a walking step number, a walking track, an amount of motion, and a motion form;
the determining module 320 is further configured to determine a motion score of the user to be detected according to the motion data, and determine the motion intensity of the user to be detected based on the motion score.
In an embodiment, the determining module 320 is further configured to:
acquiring a preset angular motion weight;
multiplying the first output data and the second output data respectively by the angular motion weight to obtain a first angular motion parameter and a second angular motion parameter;
and adding the first angular motion parameter and the second angular motion parameter to obtain the angular motion parameters of the feet of the user to be detected.
In an embodiment, the determining module 320 is further configured to:
acquiring a plurality of timestamps of any sole of the user to be detected with the sole pressure data, and determining the suspension time of the sole according to the plurality of timestamps;
determining the movement distance based on the flying time and the horizontal angular acceleration, and/or,
determining the height of the lifting foot according to the suspension time and the vertical angular acceleration; and/or the presence of a gas in the gas,
counting the times of changing the horizontal angular acceleration from positive to negative within a preset time period to obtain the step number of the user to be detected;
and dividing the step number by the preset time period to obtain the step change frequency.
In an embodiment, the determining module 320 is further configured to:
acquiring a preset motion scoring weight;
multiplying the motion scoring weights by the walking speed, the walking step number, the walking track, the motion amount and the motion form respectively to obtain a plurality of motion sub-scores;
and accumulating the plurality of sports sub-scores to obtain the sports score of the user to be detected.
In an embodiment, the determining module 320 is further configured to:
acquiring a mapping relation table between preset exercise scores and exercise intensity;
and searching the motion intensity corresponding to the motion score from the mapping relation table to obtain the motion intensity of the user to be detected.
Referring to fig. 5, fig. 5 is a schematic block diagram of another exercise intensity detection apparatus according to an embodiment of the present application.
As shown in fig. 5, the exercise intensity detection apparatus 400 includes an obtaining module 410, a determining module 420, and a sending module 430, wherein:
the obtaining module 410 is configured to obtain sole pressure data of a user to be detected, where the sole pressure data includes sole pressures acquired by a plurality of pressure sensors in the smart shoe;
the determining module 420 is configured to determine whether the walking force of the user to be tested is correct according to the sole pressure data;
the determining module 420 is further configured to obtain standard walking exertion data if the walking exertion of the user to be tested is incorrect;
the sending module 430 is configured to send the standard walking force data to an intelligent shoe, so that the intelligent shoe controls a corresponding vibration sensor in the intelligent shoe to vibrate according to the standard walking force data, so as to prompt the user to be tested to exert force correctly.
In an embodiment, the determining module 420 is further configured to:
acquiring a preset sole pressure distribution table, wherein the sole pressure distribution table comprises standard pressure proportion of each area of a sole;
calculating the current pressure ratio of each area of the sole of the user to be detected according to the sole pressure data;
when the difference value between the current pressure ratio of at least one region and the corresponding standard pressure ratio is larger than a preset threshold value, determining that the walking force of the user to be tested is incorrect;
and when the difference value between the current pressure ratio of each area and the standard pressure ratio of the corresponding area is less than or equal to a preset threshold value, determining that the walking force of the user to be tested is correct.
It should be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the exercise intensity detection apparatus described above may refer to the corresponding process in the foregoing embodiment of the exercise intensity detection method, and is not described herein again.
Referring to fig. 6, fig. 6 is a schematic block diagram illustrating a structure of a computer device according to an embodiment of the present disclosure. The computer device may be a server or a terminal.
As shown in fig. 6, the computer device includes a processor, a memory, and a network interface connected by a system bus, wherein the memory may include a nonvolatile storage medium and an internal memory.
The non-volatile storage medium may store an operating system and a computer program. The computer program comprises program instructions which, when executed, cause a processor to perform any of the methods of motion intensity detection.
The processor is used for providing calculation and control capability and supporting the operation of the whole computer equipment.
The internal memory provides an environment for the execution of a computer program on a non-volatile storage medium, which when executed by the processor, causes the processor to perform any of the exercise intensity detection methods.
The network interface is used for network communication, such as sending assigned tasks and the like. Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
It should be understood that the Processor may be a Central Processing Unit (CPU), and the Processor may be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein, in one embodiment, the processor is configured to execute a computer program stored in the memory to implement the steps of:
acquiring sole pressure data of a user to be detected, which are sent by an intelligent shoe, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe;
acquiring output data of a gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope, wherein the gyroscope is arranged in the intelligent shoe;
determining a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, wherein the movement parameter comprises at least one of a movement distance, a foot lifting height and a foot step change frequency;
determining motion data of the user to be detected according to the movement parameters, wherein the motion data comprises at least one of walking speed, walking steps, walking track, motion quantity and motion form;
and determining the movement score of the user to be detected according to the movement data, and determining the movement intensity of the user to be detected based on the movement score.
In one embodiment, the processor, when implementing the determining of the angular motion parameters of the feet of the user to be tested according to the output data of the gyroscope, is configured to implement:
acquiring a preset angular motion weight;
multiplying the first output data and the second output data respectively by the angular motion weight to obtain a first angular motion parameter and a second angular motion parameter;
and adding the first angular motion parameter and the second angular motion parameter to obtain the angular motion parameters of the feet of the user to be detected.
In one embodiment, the processor, when implementing the determining of the movement parameter of the user to be tested according to the pressure data and the angular motion parameter, is configured to implement:
acquiring a plurality of timestamps of any sole of the user to be detected with the sole pressure data, and determining the suspension time of the sole according to the plurality of timestamps;
determining the movement distance based on the flying time and the horizontal angular acceleration, and/or,
determining the height of the lifting foot according to the suspension time and the vertical angular acceleration; and/or the presence of a gas in the gas,
counting the times of changing the horizontal angular acceleration from positive to negative within a preset time period to obtain the step number of the user to be detected;
and dividing the step number by the preset time period to obtain the step change frequency.
In one embodiment, the processor, when implementing the determining the exercise score of the user to be tested from the exercise data, is configured to implement:
acquiring a preset motion scoring weight;
multiplying the motion scoring weights by the walking speed, the walking step number, the walking track, the motion amount and the motion form respectively to obtain a plurality of motion sub-scores;
and accumulating the plurality of sports sub-scores to obtain the sports score of the user to be detected.
In one embodiment, the processor, when implementing the determining of the exercise intensity of the user to be tested based on the exercise score, is configured to implement:
acquiring a mapping relation table between preset exercise scores and exercise intensity;
and searching the motion intensity corresponding to the motion score from the mapping relation table to obtain the motion intensity of the user to be detected.
In one embodiment, the processor is further configured to implement:
determining whether the walking force of the user to be tested is correct or not according to the sole pressure data;
if the walking force of the user to be tested is incorrect, standard walking force data are obtained, and the standard walking force data are sent to the intelligent shoes, so that the intelligent shoes control the corresponding vibration sensors in the intelligent shoes to vibrate according to the standard walking force data, and the user to be tested is prompted to exert force correctly.
In one embodiment, the processor, when implementing the determining whether the walking force of the user to be tested is correct according to the sole pressure data, is configured to implement:
acquiring a preset sole pressure distribution table, wherein the sole pressure distribution table comprises standard pressure proportion of each area of a sole;
calculating the current pressure ratio of each area of the sole of the user to be detected according to the sole pressure data;
when the difference value between the current pressure ratio of at least one region and the corresponding standard pressure ratio is larger than a preset threshold value, determining that the walking force of the user to be tested is incorrect;
and when the difference value between the current pressure ratio of each area and the standard pressure ratio of the corresponding area is less than or equal to a preset threshold value, determining that the walking force of the user to be tested is correct.
It should be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the computer device may refer to the corresponding process in the foregoing embodiment of the exercise intensity detection method, and is not described herein again.
Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, where the computer program includes program instructions, and when the program instructions are executed, a method implemented by the computer program instructions may refer to the embodiments of the exercise intensity detection method of the present application.
The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the computer device.
Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It is to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. 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 system 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 system. 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 system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments. While the invention has been described with reference to specific embodiments, the scope of the invention is not limited thereto, and those skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A motion intensity detection method based on artificial intelligence is characterized by comprising the following steps:
acquiring sole pressure data of a user to be detected, which are sent by an intelligent shoe, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe;
acquiring output data of a gyroscope, and determining angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope, wherein the gyroscope is arranged in the intelligent shoe;
determining a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, wherein the movement parameter comprises at least one of a movement distance, a foot lifting height and a foot step change frequency;
determining motion data of the user to be detected according to the movement parameters, wherein the motion data comprises at least one of walking speed, walking steps, walking track, motion quantity and motion form;
and determining the movement score of the user to be detected according to the movement data, and determining the movement intensity of the user to be detected based on the movement score.
2. The exercise intensity detection method of claim 1, wherein the output data includes first output data and second output data, and the determining the angular motion parameters of the feet of the user to be tested according to the output data of the gyroscope includes:
acquiring a preset angular motion weight;
multiplying the first output data and the second output data respectively by the angular motion weight to obtain a first angular motion parameter and a second angular motion parameter;
and adding the first angular motion parameter and the second angular motion parameter to obtain the angular motion parameters of the feet of the user to be detected.
3. The exercise intensity detection method according to claim 1, wherein the angular exercise parameters include angular exercise acceleration including horizontal angular acceleration in a horizontal direction and vertical angular acceleration in a vertical direction, and the determining the movement parameters of the user to be tested according to the pressure data and the angular exercise parameters includes:
acquiring a plurality of timestamps of any sole of the user to be detected with the sole pressure data, and determining the suspension time of the sole according to the plurality of timestamps;
determining the movement distance based on the flying time and the horizontal angular acceleration, and/or,
determining the height of the lifting foot according to the suspension time and the vertical angular acceleration; and/or the presence of a gas in the gas,
counting the times of changing the horizontal angular acceleration from positive to negative within a preset time period to obtain the step number of the user to be detected;
and dividing the step number by the preset time period to obtain the step change frequency.
4. The exercise intensity detection method of claim 1, wherein the determining the exercise score of the user to be tested from the exercise data comprises:
acquiring a preset motion scoring weight;
multiplying the motion scoring weights by the walking speed, the walking step number, the walking track, the motion amount and the motion form respectively to obtain a plurality of motion sub-scores;
and accumulating the plurality of sports sub-scores to obtain the sports score of the user to be detected.
5. The exercise intensity detection method of any one of claims 1-4, wherein the determining the exercise intensity of the user to be tested based on the exercise score comprises:
acquiring a mapping relation table between preset exercise scores and exercise intensity;
and searching the motion intensity corresponding to the motion score from the mapping relation table to obtain the motion intensity of the user to be detected.
6. The exercise intensity detection method of any one of claims 1-4, further comprising:
determining whether the walking force of the user to be tested is correct or not according to the sole pressure data;
if the walking force of the user to be tested is incorrect, standard walking force data are obtained, and the standard walking force data are sent to the intelligent shoes, so that the intelligent shoes control the corresponding vibration sensors in the intelligent shoes to vibrate according to the standard walking force data, and the user to be tested is prompted to exert force correctly.
7. The method for detecting exercise intensity according to claim 6, wherein the determining whether the walking force of the user to be detected is correct according to the sole pressure data includes:
acquiring a preset sole pressure distribution table, wherein the sole pressure distribution table comprises standard pressure proportion of each area of a sole;
calculating the current pressure ratio of each area of the sole of the user to be detected according to the sole pressure data;
when the difference value between the current pressure ratio of at least one region and the corresponding standard pressure ratio is larger than a preset threshold value, determining that the walking force of the user to be tested is incorrect;
and when the difference value between the current pressure ratio of each area and the standard pressure ratio of the corresponding area is less than or equal to a preset threshold value, determining that the walking force of the user to be tested is correct.
8. An exercise intensity detection apparatus, characterized in that the exercise intensity detection apparatus comprises an acquisition module and a determination module, wherein:
the acquisition module is used for acquiring sole pressure data of a user to be detected, which are sent by the intelligent shoe, wherein the sole pressure data comprise sole pressures acquired by a plurality of pressure sensors in the intelligent shoe;
the acquisition module is also used for acquiring output data of the gyroscope;
the determining module is used for determining the angular motion parameters of the feet of the user to be detected according to the output data of the gyroscope;
the determining module is further configured to determine a movement parameter of the user to be detected according to the pressure data and the angular motion parameter, where the movement parameter includes at least one of a movement distance, a foot lifting height, and a foot step change frequency;
the determining module is further configured to determine motion data of the user to be tested according to the movement parameters, where the motion data includes at least one of a walking rate, a walking step number, a walking track, an amount of motion, and a motion form;
the determining module is further configured to determine a movement score of the user to be detected according to the movement data, and determine the movement intensity of the user to be detected based on the movement score.
9. A computer device, characterized in that the computer device comprises a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program, when executed by the processor, implements the steps of the exercise intensity detection method according to any one of claims 1 to 7.
10. A computer-readable storage medium, having a computer program stored thereon, wherein the computer program, when being executed by a processor, carries out the steps of the exercise intensity detection method according to any one of claims 1 to 7.
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