CN105771187A - Motion state detecting method and intelligent shoe based on method - Google Patents
Motion state detecting method and intelligent shoe based on method Download PDFInfo
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- CN105771187A CN105771187A CN201610106443.8A CN201610106443A CN105771187A CN 105771187 A CN105771187 A CN 105771187A CN 201610106443 A CN201610106443 A CN 201610106443A CN 105771187 A CN105771187 A CN 105771187A
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0087—Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0087—Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
- A63B2024/0093—Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load the load of the exercise apparatus being controlled by performance parameters, e.g. distance or speed
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B2071/065—Visualisation of specific exercise parameters
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B2071/0658—Position or arrangement of display
- A63B2071/0661—Position or arrangement of display arranged on the user
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- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Physical Education & Sports Medicine (AREA)
- Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Footwear And Its Accessory, Manufacturing Method And Apparatuses (AREA)
Abstract
The invention discloses a motion state detecting method and an intelligent shoe based on the method.The intelligent shoe comprises an acceleration collecting module capable of collecting acceleration in three axial directions, a processing module used for processing acceleration signals, and a communicating module used for transmitting the processing result to the outside.In addition, the intelligent shoe further comprises a daily motion detection module and a special motion detecting module.By means of the special motion detecting module, a user analyzes motion states of the user sole landing angle, the sprint state, the take-off state and the physical ability consumption state by integrating acceleration information collected by the acceleration collecting module.The acceleration collecting module is utilized, the motion states of the user can be effectively calculated by means of the algorithm, valuable motion data can be provided for users and especially sports enthusiasts.The system is simple, cost is low, and the multiple motion states can be detected by adopting one sensor.By feeding back the analyzing result, the user can know the motion states of the user and customize the motion scheme for the user better.
Description
Technical field
The present invention relates to a kind of wearable device and detection method thereof, be specifically related to a kind of be applicable to domestic consumer's daily exercise condition detection footwear, be particularly suited for football, basketball, badminton fan understand moving situation.
Background technology
Health is increasingly paid attention to by modern, and all kinds of asf motors are rich and varied.The extensive universal of electronic product also penetrates into Sports Field.Intelligent worn device is skyrocketed through, shoes are as one way of life necessary, the intellectuality of shoes has become a kind of trend, occurs in that the intelligent shoe that can calculate step number, distance, calorie, speed according to acceleration transducer at present on the market, provide the user the function of practicality.But the function of these intelligent shoe is comparatively single, more professional exercise data is not added up, as take-off number of times, spurt number of times, sole land angle and physical consumption etc..In the training of specialty relatively, the athletic physiology sign of monitoring and the level of training are judged there is more important meaning by these data.Although also there being some intelligent shoe can detect take-off state, but needing to increase the different sensors such as pressure transducer, which increasing complexity and the energy consumption of intelligent shoe.
Summary of the invention
The invention aims to overcome the defect of above-mentioned background technology, it is provided that a kind of motion state detection method and the intelligent shoe based on the method.
A kind of motion state detection method, including the wear being worn on human foot, described wear be provided with can gather three axial acceleration acceleration acquisition module, for processing the processing module of acceleration signal and for the communication module of outside transmission process result；Specifically include following steps:
S10. the acceleration axially of three in the first special time period that processing module is occurred recently by described acceleration acquisition module continuous acquisition, and calculate resultant acceleration；
S20. processing module formed about acceleration magnitude curve, obtain crest height and the corrugation pitch of curve, calculate the resultant acceleration meansigma methods of resultant acceleration simultaneously；
S30. processing module is analyzed according to the data in step S20, it is thus achieved that the kinestate of human body, and described kinestate includes sole and lands angle, spurt state, take-off state and physical consumption state；
S40. the described communication module of processing module control is sent out analyzing result；
Wherein, in step s 30, the identification of physical consumption state includes following sub-step:
S301. described crest height, described corrugation pitch and resultant acceleration meansigma methods are normalized；
S302. respectively described crest height, described corrugation pitch and resultant acceleration meansigma methods are carried out degree of membership division by size, be divided into low, in and high Three Estate.
S303. physical state is judged according to the grade combination that described crest height, described corrugation pitch and resultant acceleration meansigma methods are current.
Further, described step S303 includes judging as follows step:
S3031., fuzzy rule is set: when described crest height, described corrugation pitch and resultant acceleration meansigma methods are currently in inferior grade, is then judged as that current physical consumption state is low consumption state；Have at least two kinds of data when being in high-grade state, to be then judged as high physical consumption state in described crest height, described corrugation pitch and described resultant acceleration meansigma methods are equal, be otherwise in higher physical consumption state；
S3032. input described crest height, described corrugation pitch and three kinds of normalization datas of resultant acceleration meansigma methods, application fuzzy reasoning and center of gravity deblurring method, obtain the output of physical consumption；Finally output institute judged result.
Further, described take-off state-detection includes:
S311. processing module judges that whether the acceleration on vertical direction is more than first threshold, if then performing step S312, wherein said first threshold is more than described resultant acceleration meansigma methods;
S312. processing module judges resultant acceleration when whether in acceleration is more than the second special time period after described first threshold resultant acceleration is equivalent to freely falling body, if being then judged to a take-off.
Further, described spurt state-detection includes:
S321. processing module judges the amplitude of variation of described corrugation pitch and crest size in the first special time period, if amplitude of variation is less than Second Threshold, then performs described step S322；
S322. processing module judge described crest size whether more than the 3rd threshold value and described corrugation pitch less than the 4th threshold value, if then judging that current motion state is spurt state.
Further, the described sole angle computation method that lands comprises the steps:
S331. processing module gathers the resultant acceleration vector of sole landing instant；
S332. processing module calculates the inner product of described resultant acceleration vector and acceleration of gravity vector, and then calculates the angle of described resultant acceleration and acceleration of gravity.
Further, processing module judges whether described resultant acceleration meansigma methods remains unchanged in the 3rd special time period, if then controlling described acceleration acquisition module to suspend collection data.
It addition, the present invention also provides for a kind of intelligent shoe, including the acceleration acquisition module of three axial acceleration can be gathered, for processing the processing module of acceleration signal and for the communication module of outside transmission process result, also include at least one in following module:
Physical consumption detection module, the meansigma methods for the interval between the acceleration peak value obtained according to described acceleration acquisition module, two peak values and resultant acceleration judges current physical consumption degree；
Take-off detection module, for the vertical direction acceleration magnitude identification take-off movement according to described acceleration acquisition module, and counts take-off movement；
Spurt detection module, for the interval identification spurt state between acceleration peak value and two peak values according to the acquisition of described acceleration acquisition module；And
Sole lands angle calculation module, for calculating, according to the inner product of resultant acceleration vector with acceleration of gravity vector, the angle that sole lands.
Further, also include gather interrupt module, described acquisition terminal module the data indeclinable time that described acceleration acquisition module gathers more than three special times time send terminate gather acceleration signal.
Further, type of sports identification module and pedometer module are also included；Described physical consumption detection module, take-off detection module, spurt detection module, and the sole angle calculation module that lands closes when not receiving the control signal of described control module.
Further, described communication module is at least one in bluetooth module, WIFI module, mobile communication module.
The motion state detection method of the present invention and the intelligent shoe based on the method, effectively calculated the kinestate of user by algorithm merely with acceleration acquisition module, can provide with the exercise data being worth for user particularly sports fan, and present system is simple, less costly, adopt a kind of sensor can complete the detection of multi-motion state.It addition, by the feedback analyzing result, user it will be seen that the moving situation of oneself better formulates motion scheme for oneself.
Accompanying drawing explanation
Fig. 1 is the method flow diagram of motion state detection method of the present invention.
Fig. 2 is the system architecture diagram of intelligent shoe of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing, a kind of motion state detection method of the present invention and the intelligent shoe based on the method are further described.
A kind of motion state detection method, including the wear being worn on human foot, described wear be provided with can gather three axial acceleration acceleration acquisition module, for processing the processing module of acceleration signal and for the communication module of outside transmission process result；As it is shown in figure 1, specifically include following steps:
S10. the acceleration axially of three in the first special time period that processing module is occurred recently by described acceleration acquisition module continuous acquisition, and calculate resultant acceleration；This first special time can be adjusted as required, it is preferable that data are processed by the mechanism adopting sliding window in situation, it is ensured that data are real-time update effectively.Add up to velocity magnitude acc calculating above, it is possible to adopt following two algorithm:
The first algorithm:；
Second algorithm:。
Wherein, x, y, z is transverse acceleration, longitudinal acceleration and vertical direction acceleration respectively.
Preferably, the first special time period can be 1 second.
S20. processing module formed about acceleration magnitude curve, obtain crest height and the corrugation pitch of curve, calculate the resultant acceleration meansigma methods of resultant acceleration simultaneously；It is wherein the size of acceleration extreme value represented by crest height, the extreme value of acceleration is more big, then the height of crest is more high, and in motor process, one paces of user can produce a crest, therefore, the two peak-to-peak spacing of adjacent wave then can reflect the cadence of user, and the more little then cadence of corrugation pitch is more big.The meansigma methods of resultant acceleration then reflects the severe degree of current motion state.
Preferably, it is possible to judge to carry out meter step according to the crest height of resultant acceleration and corrugation pitch.Simultaneously by neural network algorithm, the neutral net of this algorithm be online under obtain by gathering the training of a large number of users data.Realize the type of sports identification to user, as run or walking.
S30. processing module is analyzed according to the data in step S20, it is thus achieved that the kinestate of human body, and described kinestate includes sole and lands angle, spurt state, take-off state and physical consumption state；
S40. the described communication module of processing module control is sent out analyzing result；
In preferred embodiment, the type of sports state recognition of user can be one or more combinations that sole lands in angle, spurt state, take-off state and physical consumption state.The detection of these four kinestate can also be different from the meter step detection of routine, classify as specialized movement detection.Count step detection and type of sports identification then classifies as daily exercise detection.Processing module can control, according to user or arranging of program, unlatching or the stopping that specialized movement detects, with the satisfied different requirements used under scenes.
Concrete, physical consumption state-detection is used for the physical consumption distribution calculating user in whole motor process under specialized movement pattern.The calculating of the physical consumption of unit interval is determined by three parts: crest height, corrugation pitch and average acceleration value.Three parts adopt normalization to obtain method and calculate score.Including following sub-step:
S301. described crest height, described corrugation pitch and resultant acceleration meansigma methods are normalized；
S302. respectively described crest height, described corrugation pitch and resultant acceleration meansigma methods are carried out degree of membership division by size, be divided into low, in and high Three Estate.Under preferable case, low-grade membership function is the trapezoidal function on [0,0.4], and the membership function of middle grade is the trapezoidal function on [0.1,0.9], and high-grade membership function is the trapezoidal function on [0.6,1].
S303. physical state is judged according to the grade combination that described crest height, described corrugation pitch and resultant acceleration meansigma methods are current.
The concrete of step S303 judges that step is as follows:
S3031., fuzzy rule is set: when described crest height, described corrugation pitch and resultant acceleration meansigma methods are currently in inferior grade, is then judged as that current physical consumption state is low consumption state；Have at least two kinds of data when being in high-grade state, to be then judged as high physical consumption state in described crest height, described corrugation pitch and described resultant acceleration meansigma methods are equal, be otherwise in higher physical consumption state；
S3032. input described crest height, described corrugation pitch and three kinds of normalization datas of resultant acceleration meansigma methods, application fuzzy reasoning and center of gravity deblurring method, obtain the output of physical consumption；Finally output institute judged result.
In take-off state-detection, it is used for detecting user's take-off number of times in whole motor process accumulative take-off number of times under specialized movement pattern.Under normal circumstances, take-off movement has three features, and take-off is instantaneously in the face of the support force of sole, and take-off is proximate freedom falling bodies aloft, and falling bodies are instantaneously in the face of the support force of sole.Being only limited by acceleration of gravity in theory during freely falling body, but acceleration acquisition module has been corrected by system, now reading is zero.Concrete take-off state-detection includes:
S311. processing module judges that whether the acceleration on vertical direction is more than first threshold, if then performing step S312, wherein said first threshold is more than described resultant acceleration meansigma methods；
S312. processing module judges resultant acceleration when whether in acceleration is more than the second special time period after described first threshold resultant acceleration is equivalent to freely falling body, if being then judged to a take-off.
Under preferable case, first threshold is 0.8g, and wherein g is acceleration of gravity, and the second special time period is 100 milliseconds.
Due to the acquisition principle of acceleration acquisition module, the three axial acceleration theory wherein collected when freely falling body is 0, but owing to the decline process after actual take-off can be subject to External force interference, degree of hence speeding up can be slightly different with acceleration of gravity.In order to reduce the probability of misrecognized, it is necessary to utilize algorithm that data are done statistical analysis, calculate its average and variance.
Mean value computation:
Variance calculates:
When this average and variance are less than certain scope, then system judges that it still conforms to free falling body state.
In spurt state-detection, spurt state-detection is for detecting user's spurt number of times in whole motor process under specialized movement pattern, it mainly judges whether the crest size of resultant acceleration and corrugation pitch meet rigid condition, specifically includes following steps:
S321. processing module judges the amplitude of variation of described corrugation pitch and crest size in the first special time period, if amplitude of variation is less than Second Threshold, then performs described step S322；
S322. processing module judge described crest size whether more than the 3rd threshold value and described corrugation pitch less than the 4th threshold value, if then judging that current motion state is spurt state.
Preferably, Second Threshold is the 0.5, the 3rd threshold value be 2g(g is acceleration of gravity), the 4th threshold value is then 300 milliseconds.
In sole lands angle computation method, it is used for calculating during user foot-operated ground the angle between forefoot (accelerometer) and horizontal plane under specialized movement pattern.Comprise the steps:
S331. processing module gathers the resultant acceleration vector of sole landing instant；
S332. processing module calculates the inner product of described resultant acceleration vector and acceleration of gravity vector, is carrying out antitrigonometric function calculating, and then is calculating the angle of described resultant acceleration and acceleration of gravity.
Particularly as follows:
In the middle of preferred embodiment, in order to play more energy-conservation effect not under static state, the value of the acceleration collected will not change, therefore processing module judges whether described resultant acceleration meansigma methods remains unchanged in the 3rd special time period, if then controlling described acceleration acquisition module to suspend collection data.Preferred 3rd special time period can be 1 minute, or 2 minutes.
Based on above-mentioned motion state detection method, as shown in Figure 2, the present invention also provides for a kind of intelligent shoe, including the acceleration acquisition module that can gather three axial acceleration, for processing the processing module of acceleration signal and for the communication module of outside transmission process result, additionally, it also includes daily exercise detection module and specialized movement detection module, daily exercise detection module and specialized movement detection module detect the kinestate of user with control module cooperative, under preferable case, user does not perform physical exercises in daily life, therefore specialized movement detection module may be at holding state when daily life, not to being operated.When controlling module and sending specific instruction to specialized movement detection module, specialized movement detection module is just operated.
Wherein daily exercise detection module includes pedometer module and type of sports identification module, and type of sports identification module is used for identifying that user walks or the type of sports such as running.At least one in specialized movement module then following module:
Physical consumption detection module, the meansigma methods for the interval between the acceleration peak value obtained according to described acceleration acquisition module, two peak values and resultant acceleration judges current physical consumption degree；
Take-off detection module, for the vertical direction acceleration magnitude identification take-off movement according to described acceleration acquisition module, and counts take-off movement；
Spurt detection module, for the interval identification spurt state between acceleration peak value and two peak values according to the acquisition of described acceleration acquisition module；And
Sole lands angle calculation module, for calculating, according to the inner product of resultant acceleration vector with acceleration of gravity vector, the angle that sole lands.
In order to further save energy consumption, also include gather interrupt module, described acquisition terminal module the data indeclinable time that described acceleration acquisition module gathers more than three special times time send terminate gather acceleration signal.
It addition, communication module can be at least one in bluetooth module, WIFI module, mobile communication module.
Above in conjunction with accompanying drawing, embodiments of the present invention are explained in detail, but the present invention is not limited to above-mentioned embodiment, in the ken that those of ordinary skill in the art possess, it is also possible under the premise without departing from present inventive concept, make various change.
Claims (10)
1. a motion state detection method, it is characterized in that, including the wear being worn on human foot, described wear be provided with can gather three axial acceleration acceleration acquisition module, for processing the processing module of acceleration signal and for the communication module of outside transmission process result；Specifically include following steps:
S10. the acceleration axially of three in the first special time period that processing module is occurred recently by described acceleration acquisition module continuous acquisition, and calculate resultant acceleration；
S20. processing module formed about acceleration magnitude curve, obtain crest height and the corrugation pitch of curve, calculate the resultant acceleration meansigma methods of resultant acceleration simultaneously；
S30. processing module is analyzed according to the data in step S20, it is thus achieved that the kinestate of human body, and described kinestate includes sole and lands angle, spurt state, take-off state and physical consumption state；
S40. the described communication module of processing module control is sent out analyzing result；
Wherein, in step s 30, the identification of physical consumption state includes following sub-step:
S301. described crest height, described corrugation pitch and resultant acceleration meansigma methods are normalized；
S302. respectively described crest height, described corrugation pitch and resultant acceleration meansigma methods are carried out degree of membership division by size, be divided into low, in and high Three Estate；
S303. physical state is judged according to the grade combination that described crest height, described corrugation pitch and resultant acceleration meansigma methods are current.
2. motion state detection method as claimed in claim 1, it is characterised in that described step S303 includes judging as follows step:
S3031., fuzzy rule is set: when described crest height, described corrugation pitch and resultant acceleration meansigma methods are currently in inferior grade, is then judged as that current physical consumption state is low consumption state；Have at least two kinds of data when being in high-grade state, to be then judged as high physical consumption state in described crest height, described corrugation pitch and described resultant acceleration meansigma methods are equal, be otherwise in higher physical consumption state；
S3032. input described crest height, described corrugation pitch and three kinds of normalization datas of resultant acceleration meansigma methods, application fuzzy reasoning and center of gravity deblurring method, obtain the output of physical consumption；Finally output institute judged result.
3. motion state detection method as claimed in claim 1, it is characterised in that described take-off state-detection includes:
S311. processing module judges that whether the acceleration on vertical direction is more than first threshold, if then performing step S312, wherein said first threshold is more than described resultant acceleration meansigma methods;
S312. processing module judges resultant acceleration when whether in acceleration is more than the second special time period after described first threshold resultant acceleration is equivalent to freely falling body, if being then judged to a take-off.
4. motion state detection method as claimed in claim 1, it is characterised in that described spurt state-detection includes:
S321. processing module judges the amplitude of variation of described corrugation pitch and crest size in the first special time period, if amplitude of variation is less than Second Threshold, then performs described step S322；
S322. processing module judge described crest size whether more than the 3rd threshold value and described corrugation pitch less than the 4th threshold value, if then judging that current motion state is spurt state.
5. motion state detection method as claimed in claim 1, it is characterised in that the described sole angle computation method that lands comprises the steps:
S331. processing module gathers the resultant acceleration vector of sole landing instant；
S332. processing module calculates the inner product of described resultant acceleration vector and acceleration of gravity vector, and then calculates the angle of described resultant acceleration and acceleration of gravity；Described first special time period is 1 second；Described second special time period is 100 milliseconds；Described 3rd special time period is 1 minute or 2 minutes.
6. motion state detection method as claimed in claim 1, it is characterised in that processing module judges whether described resultant acceleration meansigma methods remains unchanged in the 3rd special time period, if then controlling described acceleration acquisition module to suspend collection data；Described first threshold is 0.8 times of acceleration of gravity, and described Second Threshold is 0.5, and described 3rd threshold value is 2 times of acceleration of gravitys, and described 4th threshold value is 300 milliseconds.
7. an intelligent shoe, including the acceleration acquisition module of three axial acceleration can be gathered, for processing the processing module of acceleration signal and for the communication module of outside transmission process result, it is characterised in that also include at least one in following module:
Physical consumption detection module, the meansigma methods for the interval between the acceleration peak value obtained according to described acceleration acquisition module, two peak values and resultant acceleration judges current physical consumption degree；
Take-off detection module, for the vertical direction acceleration magnitude identification take-off movement according to described acceleration acquisition module, and counts take-off movement；
Spurt detection module, for the interval identification spurt state between acceleration peak value and two peak values according to the acquisition of described acceleration acquisition module；And
Sole lands angle calculation module, for calculating, according to the inner product of resultant acceleration vector with acceleration of gravity vector, the angle that sole lands.
8. intelligent shoe as claimed in claim 6, it is characterised in that also include gathering interrupt module, described acquisition terminal module the data indeclinable time that described acceleration acquisition module gathers more than three special times time send the signal terminating gathering acceleration.
9. intelligent shoe as claimed in claim 6, it is characterised in that it is characterized in that, also include type of sports identification module and pedometer module；Described physical consumption detection module, take-off detection module, spurt detection module, and the sole angle calculation module that lands closes when not receiving the control signal of described control module.
10. intelligent shoe as claimed in claim 6, it is characterised in that it is characterized in that, described communication module is at least one in bluetooth module, WIFI module, mobile communication module.
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| CN107048570A (en) * | 2017-04-12 | 2017-08-18 | 佛山市量脑科技有限公司 | A kind of data analysis processing method of Intelligent insole |
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| WO2019036926A1 (en) * | 2017-08-23 | 2019-02-28 | 华为技术有限公司 | Acceleration information-based foot step counting method and apparatus, and device |
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| CN113074724A (en) * | 2021-03-26 | 2021-07-06 | 歌尔股份有限公司 | Motion time calculation method, device, equipment and computer readable storage medium |
| CN113713353A (en) * | 2021-05-12 | 2021-11-30 | 北京冰锋科技有限责任公司 | Technical action acquisition method and system for ski-jump skiers |
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