CN108837477A - A kind of detection swimming is struck several method, apparatus and intelligent wearable device - Google Patents
A kind of detection swimming is struck several method, apparatus and intelligent wearable device Download PDFInfo
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- CN108837477A CN108837477A CN201810590025.XA CN201810590025A CN108837477A CN 108837477 A CN108837477 A CN 108837477A CN 201810590025 A CN201810590025 A CN 201810590025A CN 108837477 A CN108837477 A CN 108837477A
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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
- A63B2208/00—Characteristics or parameters related to the user or player
- A63B2208/03—Characteristics or parameters related to the user or player the user being in water
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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
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/80—Special sensors, transducers or devices therefor
- A63B2220/803—Motion sensors
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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
- A63B2244/00—Sports without balls
- A63B2244/20—Swimming
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- Physical Education & Sports Medicine (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a kind of detection swimming to strike several method, apparatus and intelligent wearable device, and this method includes the exercise data for acquiring user；When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and starts buffered motion data, until when monitoring that user has swum a swimming pool length, the end time point that user has swum a swimming pool length is labeled as switch-back point, and stops buffered motion data；Processing is carried out to the exercise data between the starting point and switch-back point of caching and obtains the number of striking that user has swum a swimming pool length.This method considerably reduces calculation amount, more accurately record the swimming data of user, facilitate motion state and ability that user better grasps oneself, and check motion state when having swum one time, without reaching swimming pool edge progress button operation, it can prevent underwater button operation from destroying the waterproof performance of intelligent wearable device.
Description
Technical field
The present invention relates to intelligent wearable device field, in particular to a kind of detection swimming is struck several method, apparatus and intelligence
It can wearable device.
Background technique
With the development of the society, the run duration of people is fewer and fewer, the working method of sitting makes many human body quality
It gradually goes down hill, fat and various chronic diseases etc. have seriously affected people's lives quality.For the health of itself, people are to fortune
Dynamic also increasingly to pay attention to, domestic various marathon races at present also like the mushrooms after rain, have further confirmed movement in people
The promotion of status in mind.Along with the upsurge of movement, the motion state that user is detected using intelligent wearable device becomes heat
Point.Moving state identification is intelligent wearable device algorithm as the technical foundation for solving motion monitoring and motion state prompting
One of core and difficult point.
It is well known that swimming is the movement for needing whole body to participate in, can mobilize than other movements has more muscle
Group participates in metabolic function.It can be improved the muscle of many muscle powers and harmony, especially trunk, shoulder belt and upper limb.Cause
Need to overcome biggish resistance to swim in the water, swimming is again periodically to move, and long-term take exercise can make muscle strength, speed
The flexibility of degree, endurance and joint is all improved, and is improved cardiovascular system, is improved lung capacity, improve muscle systems ability, change
Kind Thermoregulation ability etc..Increasingly pay attention to today of health and movement in people, swimming also becomes the aerobic fortune that public heat is held in both hands
Dynamic form.Therefore also become one of the emphasis of intelligent wearable device to the monitoring of swimming exercise.
When swimmer wears the intelligent wearable device progress swimming exercise for having motion tracking function, number of striking is characterization trip
One of the most important parameters for efficiency of swimming, strike it is several number it is directly related with efficiency of swimming because striking corresponding advance every time
The parameters such as distance, time-consuming are directly related to the height of swimming efficiency, therefore it is required that intelligent wearable device can record in real time user's
It strikes number, and then accurate SWOLF can be obtained, the intuitive swimming efficiency for reflecting user helps user to promote swimming skills.And it passes
System intelligent wearable device can only record the information such as simple speed, come the information such as locomitivity, the heat consumption of estimating user, nothing
The stroke of method automatic identification user, records the number of striking of user, and then can do nothing to help user and obtain more detailed motion information, such as
The data such as rest used time, swimming distance, SWOLF, are unfavorable for motion state and ability that user preferably grasps oneself.
Summary of the invention
A kind of detection swimming provided by the invention is struck several method, apparatus and intelligent wearable device, to solve or part
It solves the problem above-mentioned.
A kind of several method according to an aspect of the invention, there is provided detection swimming is struck, this method include：
Acquire the exercise data of user；
When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and start to cache institute
Exercise data is stated, until user to have been swum to the end time of a swimming pool length when monitoring that user has swum a swimming pool length
Point is labeled as switch-back point, and stops caching the exercise data；
Processing is carried out to the exercise data between the starting point and switch-back point of caching to obtain user to have swum a swimming pool long
The number of striking of degree.
Optionally, described pair caching the starting point and switch-back point between exercise data carry out processing obtain user swum
The number of striking of a time swimming pool length includes：
Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, from filtering noise reduction after described in
Any one uniaxial data is chosen in exercise data；
The number that processing obtains corresponding effective peak between the starting point and switch-back point is carried out to the uniaxial data, it will
The number of the effective peak halves, and obtains the number of striking that user has swum a swimming pool length.
Optionally, described that corresponding effective peak between the processing acquisition starting point and switch-back point is carried out to the uniaxial data
The number of value includes：
Wave crest and trough of the uniaxial data in the starting point and switch-back point are recorded, the wave crest and trough are marked
Corresponding peak lists between the starting point and switch-back point are obtained for peak value；
One peak difference threshold value is set according to the peak change range of the uniaxial data, according to the peak difference threshold value to described
Corresponding peak lists are handled between starting point and switch-back point, obtain corresponding effective peak between the starting point and switch-back point
Number.
Optionally, it is described according to the peak difference threshold value to peak lists corresponding between the starting point and switch-back point at
Reason, the number for obtaining corresponding effective peak between the starting point and switch-back point include：
Calculate each peak value between the starting point and switch-back point in corresponding peak lists and the adjacent peak on the left of it
Between the first absolute difference and the second absolute difference between the adjacent peak on the right side of it,
When first absolute difference and second absolute difference are all larger than the peak difference threshold value, by the peak
Value is labeled as effective peak；
It, will when there is one to be less than the peak difference threshold value in first absolute difference and second absolute difference
The peak markers are invalid peak value, and are removed from the peak lists；
When first absolute difference and second absolute difference are respectively less than the peak difference threshold value, further obtain
The peak value and the absolute difference being separated by between a peak value on the left of it are taken, if the absolute difference is poor greater than the peak
The peak markers are then effective peak, and the adjacent peak at left and right sides of the peak value are labeled as invalid peak by threshold value
Value, and removed from the peak lists.
According to another aspect of the present invention, it provides a kind of detection swimming to strike several devices, described device includes depositing
By internal bus communication connection, the memory is stored with can for reservoir and processor, the memory and the processor
The computer program executed by the processor, the computer program can be realized above-mentioned inspection when being executed by the processor
Survey several method of striking of swimming.
According to a further aspect of the invention, a kind of intelligent wearable device is provided, the intelligent wearable device is built-in with
Inertial sensor, memory and processor, the inertial sensor and memory are connected to the processor respectively, the storage
Device is stored with the computer program that can be executed by the processor, and the computer program can when being executed by the processor
Realize following method and step：
Acquire the exercise data of user；
When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and start to cache institute
Exercise data is stated, until user to have been swum to the end time of a swimming pool length when monitoring that user has swum a swimming pool length
Point is labeled as switch-back point, and stops caching the exercise data；
Processing is carried out to the exercise data between the starting point and switch-back point of caching to obtain user to have swum a swimming pool long
The number of striking of degree.
Optionally, described pair caching the starting point and switch-back point between exercise data carry out processing obtain user swum
The number of striking of a time swimming pool length includes：
Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, from filtering noise reduction after described in
Any one uniaxial data is chosen in exercise data；
The number that processing obtains corresponding effective peak between the starting point and switch-back point is carried out to the uniaxial data, it will
The number of the effective peak halves, and obtains the number of striking that user has swum a swimming pool length.
Optionally, described that corresponding effective peak between the processing acquisition starting point and switch-back point is carried out to the uniaxial data
The number of value includes：
Wave crest and trough of the uniaxial data in the starting point and switch-back point are recorded, the wave crest and trough are marked
Corresponding peak lists between the starting point and switch-back point are obtained for peak value；
One peak difference threshold value is set according to the peak change range of the uniaxial data, according to the peak difference threshold value to described
Corresponding peak lists are handled between starting point and switch-back point, obtain corresponding effective peak between the starting point and switch-back point
Number.
Optionally, it is described according to the peak difference threshold value to peak lists corresponding between the starting point and switch-back point at
Reason, the number for obtaining corresponding effective peak between the starting point and switch-back point include：
Calculate each peak value between the starting point and switch-back point in corresponding peak lists and the adjacent peak on the left of it
Between the first absolute difference and the second absolute difference between the adjacent peak on the right side of it,
When first absolute difference and second absolute difference are all larger than the peak difference threshold value, by the peak
Value is labeled as effective peak；
It, will when there is one to be less than the peak difference threshold value in first absolute difference and second absolute difference
The peak markers are invalid peak value, and are removed from the peak lists；
When first absolute difference and second absolute difference are respectively less than the peak difference threshold value, further obtain
The peak value and the absolute difference being separated by between a peak value on the left of it are taken, if the absolute difference is poor greater than the peak
The peak markers are then effective peak, and the adjacent peak at left and right sides of the peak value are labeled as invalid peak by threshold value
Value, and removed from the peak lists.
Optionally, denoiser is filtered using low pass Chebyshev and noise reduction is filtered to the exercise data of caching；
And/or
Exercise data is acquired using MEMS inertial sensor.
The beneficial effect of the embodiment of the present invention is：By the exercise data for acquiring user；When monitoring that user starts to swim
When, the time point that user starts swimming is labeled as starting point, and start buffered motion data, until monitoring that user has swum once
When swimming pool length, the end time point that user has swum a swimming pool length is labeled as switch-back point, and stop buffered motion data；
Processing is carried out to the exercise data between the starting point and switch-back point of caching and obtains the number of striking that user has swum a swimming pool length.Phase
Than that can only record simple velocity information in current intelligent wearable device, such as conventional motion wrist-watch, the present invention can be accurate
Ground records the swimming data of user, accurately detects that swimming is struck number, can completely the exercise data all to user remember
Record and analysis, facilitate user and better grasp oneself motion state and ability, and check movement shape when having swum one time
State, without preventing underwater button operation from destroying the waterproof performance of intelligent wearable device in arrival swimming pool edge progress button operation,
Using easier.
Detailed description of the invention
Fig. 1 is that a kind of detection provided in an embodiment of the present invention is swum several method flow diagram of striking；
Fig. 2 is that another kind provided in an embodiment of the present invention detects several method flow diagram of striking of swimming；
Fig. 3 is the exercise data original waveform figure of non-filtered noise reduction process；
Fig. 4 is the waveforms of the motion data figure by filtering noise reduction；
Fig. 5 is the x-axis waveforms of the motion data figure chosen；
Fig. 6 is the schematic diagram that wave crest and trough are labeled as peak value；
Fig. 7 be when one fluctuate rising edge or failing edge occur small vibration when the case where schematic diagram；
Fig. 8 is the case where wave crest fluctuated when one or trough are there are when small vibration schematic diagram；
Corresponding effective peak schematic diagram when striking in a swimming that Fig. 9 is that treated；
Figure 10 is a kind of device figure that detection swimming is struck several provided in an embodiment of the present invention；
Figure 11 is a kind of intelligent wearable device schematic diagram provided in an embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached drawing to embodiment party of the present invention
Formula is described in further detail.Embodiment described in following exemplary embodiment does not represent consistent with the application
All embodiments.On the contrary, they are only and some aspects phase one as detailed in the attached claim, the application
The example of the device and method of cause.
It is only to be not intended to be limiting the application merely for for the purpose of describing particular embodiments in term used in this application.
It is also intended in the application and the "an" of singular used in the attached claims, " described " and "the" including majority
Form, unless the context clearly indicates other meaning.
Fig. 1 is that a kind of detection provided in an embodiment of the present invention is swum several method flow diagram of striking, as shown in Figure 1, the party
Method includes：
Step S11：Acquire the exercise data of user；
Step S12：When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and open
Beginning buffered motion data, until user to have been swum to the end of a swimming pool length when monitoring that user has swum a swimming pool length
Time point is labeled as switch-back point, and stops buffered motion data；
Step S13：Processing acquisition user is carried out to the exercise data between the starting point and switch-back point of caching to have swum one time
The number of striking of pond length；The specific steps are：Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, from filter
Any one uniaxial data is chosen in exercise data after wave noise reduction；The record number of axle is according to the wave crest and wave in starting point and switch-back point
Wave crest and trough are obtained corresponding peak lists between starting point and switch-back point labeled as peak value by paddy；According to the peak of uniaxial data
Be worth variation range be arranged a peak difference threshold value, according to peak difference threshold value to peak lists corresponding between starting point and switch-back point at
Reason obtains the number of corresponding effective peak between starting point and switch-back point；The number of effective peak is halved, user is obtained and has swum
The number of striking of a time swimming pool length.
" peak lists corresponding between starting point and switch-back point are handled according to peak difference threshold value, are obtained in step S13
The number of corresponding effective peak between starting point and switch-back point " includes：Corresponding peak lists between zequin and switch-back point
In each peak value and adjacent peak on the left of it between the first absolute difference and between the adjacent peak on the right side of it
The second absolute difference, when the first absolute difference and the second absolute difference are all larger than peak difference threshold value, by peak markers
For effective peak；When there is one to be less than peak difference threshold value in the first absolute difference and second absolute difference, by peak value
It is removed labeled as invalid peak value, and from peak lists；When to be respectively less than peak poor for the first absolute difference and the second absolute difference
When threshold value, peak value and the absolute difference being separated by between a peak value on the left of it are further obtained, if absolute difference is greater than
Peak markers are then effective peak by peak difference threshold value, and by the adjacent peak at left and right sides of peak value labeled as invalid peak value, and
It is removed from peak lists.
Exercise data is wherein acquired using MEMS inertial sensor；Using low pass Chebyshev filter denoiser to starting point and
Exercise data between switch-back point is filtered noise reduction.
The present invention acquires exercise data using the MEMS inertial sensor built in intelligent wearable device, and by starting point and turns back
Exercise data between point is saved in caching, then passes through Chebyshev's low-pass filtering denoiser (Chebyshev
Filter), noise reduction process is filtered to initial data, corresponding significant wave when striking every time is then extracted from waveform
It is dynamic, small sample perturbations are filtered out, to obtain the number of striking in end user every time swimming.Intelligent wearable device include Intelligent bracelet,
Smart motion wrist-watch etc. elaborates several detection method of striking of swimming by taking smart motion wrist-watch as an example, and Fig. 2 is that the present invention is real
The another of example offer is provided and detects several method flow diagram of striking of swimming, as shown in Fig. 2, this approach includes the following steps：
Step S21：Acquire exercise data；User first turns on the swimming tracking function of smart motion wrist-watch, built in
MEMS inertial sensor starts to acquire exercise data；
Step S22：Judge whether to start to strike；Whether automatic monitoring user starts arm stroke, if so, operation
Step S23, if it is not, then operating procedure S21；
Step S23：Acquisition obtains user and starts the exercise data after striking and caching, until system monitoring to user reaches
Switch-back point.The data saved in caching are the exercise data that user one plows swimming.
Step S24：Processing acquisition user is carried out to the exercise data between the starting point and switch-back point of caching to have swum one time
The number of striking of pond length；
Original exercise data includes noise, is unfavorable for handling, as shown in figure 3, Fig. 3 is the fortune of non-filtered noise reduction process
Dynamic data original waveform figure, the waveform burr of exercise data is excessive, and contains high fdrequency component, these invalid data are unfavorable for
Analysis to movement, therefore noise reduction process is filtered firstly the need of to initial data.We use a low pass Chebyshev
Filter is filtered noise reduction process to data, and cut-off frequecy of passband is set as 1Hz, after Chebyshev filter is handled,
The high frequency noise components of data are just filtered.Fig. 4 is by the waveforms of the motion data figure of filtering noise reduction, as shown in figure 4, from warp
Cross the exercise data once swum that Chebyshev filter is treated, it can be seen that when swimming is struck, exercise data
Trend having the same.Therefore we swim striking only with x-axis data counts the calculating of judgement, both ensure that judgement in this way
Accuracy, and operand can be reduced to the maximum extent.
Fig. 5 is the x-axis waveforms of the motion data figure chosen, from figure 5 it can be seen that exercise data when striking is in periodically
Fluctuation, each period correspondence are once struck, and arm stroke not only includes once significantly fluctuating, it is also possible to slightly including one
Microvariations.The present invention calculates the number of striking of user in such a way that record fluctuates number, although Fourier transformation, PCA etc. is calculated
Method extracts the periodicity of fluctuation in can also counting from movement, but its calculation amount is excessive, is limited to the calculating of smartwatch
Ability, and be not suitable for.And how therefrom calculation amount can be greatly lowered in the method for the record fluctuation number that the present invention takes, but
Removal small sample perturbations bring influence is the key point of this method, as follows：
All wave crest and trough are found in data between starting point and switch-back point, as shown in fig. 6, Fig. 6 be wave crest and
Trough is labeled as the schematic diagram of peak value, and black circle is labeled as trough, and ash circle is labeled as wave crest, wave crest and trough by finding in region
The method of maximum and minimum determines；Then it is right between peak value acquisition starting point and switch-back point to be designated generally as wave crest and trough
The peak lists answered remove the lower vibration of amplitude in waveform, retain the main component in waveform and are labeled as once effectively striking.
Specific way is that a peak difference threshold value is arranged according to the peak change range of the uniaxial data first, then calculates some peak value
Whether the absolute difference between adjacent peak is greater than the threshold value as judgment criteria, obtains corresponding between starting point and switch-back point
Effective peak number；It is specifically divided into following several situations：
Each peak value f (x first between zequin and switch-back point in corresponding peak listsn) adjacent on the left of it
Peak value f (xn-1) between the first absolute difference | f (xn-1)-f(xn) | and with the adjacent peak f (x on the right side of itn+1) between
The second absolute difference | f (xn)-f(xn+1) |,
1, when primary fluctuation itself is the main component of waveform, it is desirable that the peak value specifically shaken and its left and right sides phase
The absolute difference of adjacent peak value is all larger than threshold value.I.e.：
|f(xn)-f(xn+1) | > T& | f (xn-1)-f(xn) | > T
Meet this requirement, then judges that the secondary undulation itself is the main component of waveform, retaining the peak value is effective peak
Value.
2, it when small fluctuation occur in the rising edge or failing edge that once fluctuate, needs to disappear the influence of this minor swing
It removes.It is when the peak value and the absolute difference of its left and right peak value of this minor swing are all larger than preset threshold, i.e., in algorithm：
|f(xn)-f(xn+1) | > T& | f (xn-1)-f(xn) | > T
Then judge the peak value of the secondary minor swing for effective peak；Peak value at left and right sides of the peak value of this minor swing and its
This peak value is judged as invalid peak value when absolute difference cannot meet simultaneously greater than threshold value, while it being arranged from effective peak
It is removed in table.
As it can be seen that the decision condition is identical as the Rule of judgment in the 1st kind of situation.Fig. 7 be when one fluctuation rising edge or
The case where when small vibration occurs in failing edge schematic diagram, as shown in fig. 7, in Fig. 7 A, peak value 2 and 3 is what rising edge side occurred
Small sample perturbations judge that peak value 2 and 3 is invalid peak value by algorithm, and peak value 1,4 and 5 is effective peak.Display passes through in Fig. 7 B
This Rule of judgment has successfully filtered the peak value of invalid fluctuation within a narrow range, remains effective peak 1,4 and 5.
3, when the peak value once fluctuated nearby minor swing occurs, it is also desirable to eliminate the influence of this minor swing.At this time
The characteristics of be to occur 3 peak values near this effective peak, but one can only be retained.Method proposed by the present invention is to retain
That among 3 peak values.The characteristics of interpeak is that the absolute difference of it and two neighboring peak value is less than threshold value simultaneously,
But the peak difference values absolute value being separated by with left side meets the requirement for being greater than threshold value, i.e.,：
|f(xn)-f(xn+1) | < T& | f (xn-1)-f(xn) | < T& | f (xn)-f(xn-2) | > T
Fig. 8 is the case where wave crest fluctuated when one or trough are there are when small vibration schematic diagram, as shown in figure 8, Fig. 8 A
In, occur two small sample perturbations at left and right sides of peak value 3, the peak value of the two small sample perturbations is peak value 2 and 4, peak value 3 and peak value
2 and 4 absolute difference is respectively less than threshold value, but is greater than threshold value with the absolute difference of peak value 1, meets above-mentioned Rule of judgment, because
This peak value 3 is effective peak, and peak value 2 and 4 is invalid peak value.As shown in Figure 8 B, two at effective peak 3 have been filtered small to disturb
The raw peak value 2 and 4 of movable property, retains an effective peak 3.
The peak value of small sample perturbations generation can be filtered out by above-mentioned algorithm, retain effective peak, as shown in figure 9, Fig. 9 is
Corresponding effective peak schematic diagram when striking in a swimming that treated.Count corresponding effective peak between starting point and switch-back point
The number of value retains two effective peaks each period of waves, is 2 times between the peak value retained in this way and number of actually striking
Relationship.Finally the number for the effective peak number that processing obtains is halved, i.e., acquisition user has swum striking for a swimming pool length
Number.
Number of striking is one of the most important parameters of characterization swimming efficiency, corresponding forward travel distance, the time-consuming etc. of striking every time ginseng
Number is directly related to the height of swimming efficiency.The sports level that assistance user promotes itself is that intelligent wearable device is different from other
The important feature of Intelligent hardware.The present invention can be used to the swimming posture to user and be recorded in real time, obtain strike number, and nothing
Accurate detailed data can be provided for user by needing user to carry out any operation during exercise.
Figure 10 is a kind of device figure that detection swimming is struck several provided in an embodiment of the present invention, as shown in Figure 10, the device
100 include：Including memory 1001 and processor 1002, pass through internal bus 1003 between memory 1001 and processor 1002
Communication connection, memory 1001 are stored with the computer program that can be executed by processor 1002, and computer program is by processor
It can be realized above-mentioned detection swimming when execution to strike several method and steps.
In various embodiments, memory 1001 can be memory or nonvolatile memory.It is wherein non-volatile
Memory can be：Memory driver (such as hard disk drive), solid state hard disk, any kind of storage dish (such as CD, DVD
Deng) perhaps similar storage medium or their combination.Memory can be：RAM (Radom Access Memory, at random
Access memory), volatile memory, nonvolatile memory, flash memory.Further, nonvolatile memory and memory are as machine
Device readable storage medium storing program for executing can store the computer program executed by processor 1002 thereon, realize that detection swimming above-mentioned is struck
Several methods, this method have been elaborated in the embodiment that Fig. 1 and Fig. 2 are provided, and details are not described herein.
Figure 11 is a kind of intelligent wearable device schematic diagram provided in an embodiment of the present invention, and as shown in figure 11, this is intelligently dressed
Equipment 110 is built-in with inertial sensor 1101, memory 1001 and processor 1002, inertial sensor 1101 and memory 1001
It is connect respectively with processor 1002, memory 1001 is stored with the computer program that can be executed by processor 1002, computer
Program can be realized following method and step when being executed by processor 1002：
Exercise data is acquired using inertial sensor 1101；
When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and start caching fortune
Dynamic data, until user to have been swum to the end time point mark of a swimming pool length when monitoring that user has swum a swimming pool length
It is denoted as switch-back point, and stops buffered motion data；
Processing acquisition user is carried out to the exercise data between the starting point and switch-back point of caching and has swum a swimming pool length
It strikes number.
In some embodiments, processing acquisition user is carried out to the exercise data between the starting point of caching and switch-back point to have swum
Several step of striking of a time swimming pool length is specially：
Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, the exercise data after filtering noise reduction
It is middle to choose any one uniaxial data；
The record number of axle is risen according to the wave crest and trough in starting point and switch-back point, by wave crest and trough labeled as peak value
Corresponding peak lists between point and switch-back point；
One peak difference threshold value is set according to the peak change range of uniaxial data, according to peak difference threshold value to starting point and switch-back point
Between corresponding peak lists handled, obtain the number of corresponding effective peak between starting point and switch-back point；
The number of effective peak is halved, the number of striking that user has swum a swimming pool length is obtained.
In some embodiments, peak lists corresponding between starting point and switch-back point are handled according to peak difference threshold value,
The step of number of corresponding effective peak, is specially between acquisition starting point and switch-back point：
Each peak value in corresponding peak lists and between the adjacent peak on the left of it between zequin and switch-back point
The first absolute difference and the second absolute difference between the adjacent peak on the right side of it,
It is effective by peak markers when the first absolute difference and second absolute difference are all larger than peak difference threshold value
Peak value；
It is nothing by peak markers when there is one to be less than peak difference threshold value in the first absolute difference and the second absolute difference
Peak value is imitated, and is removed from peak lists；
When the first absolute difference and the second absolute difference are respectively less than peak difference threshold value, further obtain peak value and it is left
Peak markers are effective if absolute difference is greater than peak difference threshold value by the absolute difference of side being separated by between a peak value
Peak value, and the adjacent peak at left and right sides of peak value is labeled as invalid peak value, and remove from peak lists.
In some embodiments, denoiser is filtered using low pass Chebyshev and drop is filtered to the exercise data of acquisition
It makes an uproar；And/or exercise data is acquired using MEMS inertial sensor.
For device embodiment, since it corresponds essentially to embodiment of the method, so related place is referring to method reality
Apply the part explanation of example.The apparatus embodiments described above are merely exemplary, can select according to the actual needs
Some or all of the modules therein is selected to achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying wound
In the case that the property made is worked, it can understand and implement.
In conclusion passing through the exercise data of acquisition user；When monitoring that user starts swimming, user is started to swim
Time point be labeled as starting point, and start buffered motion data, until when monitoring that user has swum a swimming pool length, by user
The end time point of a swimming pool length has been swum labeled as switch-back point, and has stopped buffered motion data；To the starting point and folding of caching
Exercise data between returning the benefit carries out processing and obtains the number of striking that user has swum a swimming pool length.Compared to conventional motion wrist-watch
The information such as simple speed can only be recorded, the present invention can more accurately record the swimming data of user, facilitate user more
Oneself motion state and ability are grasped well, and checks motion state when having swum one time, without reaching swimming pool edge
Button operation is carried out, prevents underwater button operation from destroying the waterproof performance of intelligent wearable device；Completely useful data is carried out
Record and analysis, use are easier；And number of striking of swimming is calculated compared to using Fourier transformation or PCA scheduling algorithm, this
Invention calculates several method of striking when swimming using the Wave crest and wave trough number for extracting movement meter waveform, considerably reduces operation
Amount is more applicable in the computing capability of intelligent wearable device.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the scope of the present invention.It is all
Any modification, equivalent replacement, improvement and so within the spirit and principles in the present invention, are all contained in protection scope of the present invention
It is interior.
Claims (10)
- A kind of several method 1. detection swimming is struck, which is characterized in that the method includes：Acquire the exercise data of user；When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and start to cache the fortune Dynamic data, until user to have been swum to the end time point mark of a swimming pool length when monitoring that user has swum a swimming pool length It is denoted as switch-back point, and stops caching the exercise data；Processing acquisition user is carried out to the exercise data between the starting point and switch-back point of caching and has swum a swimming pool length It strikes number.
- 2. the method as described in claim 1, which is characterized in that the movement between the starting point and switch-back point of described pair of caching Data, which carry out processing and obtain user having swum the number of striking of a swimming pool length, includes：Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, the movement after filtering noise reduction Any one uniaxial data is chosen in data；The number that processing obtains corresponding effective peak between the starting point and switch-back point is carried out to the uniaxial data, it will be described The number of effective peak halves, and obtains the number of striking that user has swum a swimming pool length.
- 3. method according to claim 2, which is characterized in that described to carry out the processing acquisition starting point to the uniaxial data The number of corresponding effective peak includes between switch-back point：Wave crest and trough of the uniaxial data in the starting point and switch-back point are recorded, the wave crest and trough are labeled as peak Value obtains corresponding peak lists between the starting point and switch-back point；One peak difference threshold value is set according to the peak change range of the uniaxial data, according to the peak difference threshold value to the starting point Corresponding peak lists are handled between switch-back point, obtain of corresponding effective peak between the starting point and switch-back point Number.
- 4. method as claimed in claim 3, which is characterized in that it is described according to the peak difference threshold value to the starting point and switch-back point Between corresponding peak lists handled, the number for obtaining corresponding effective peak between the starting point and switch-back point includes：Calculate between the starting point and switch-back point each peak value in corresponding peak lists and between the adjacent peak on the left of it The first absolute difference and the second absolute difference between the adjacent peak on the right side of it,When first absolute difference and second absolute difference are all larger than the peak difference threshold value, by the peak value mark It is denoted as effective peak；It, will be described when there is one to be less than the peak difference threshold value in first absolute difference and second absolute difference Peak markers are invalid peak value, and are removed from the peak lists；When first absolute difference and second absolute difference are respectively less than the peak difference threshold value, institute is further obtained Peak value and the absolute difference being separated by between a peak value on the left of it are stated, if the absolute difference is greater than the peak difference threshold It is worth, then is effective peak by the peak markers, and the adjacent peak at left and right sides of the peak value is labeled as invalid peak value, And it is removed from the peak lists.
- Several device 5. a kind of detection swimming is struck, which is characterized in that described device includes memory and processor, the storage By internal bus communication connection, the memory is stored with the calculating that can be executed by the processor for device and the processor Machine program, the computer program can be realized detection described in claim 1-4 any one when being executed by the processor Swimming is struck several methods.
- 6. a kind of intelligent wearable device, which is characterized in that the intelligent wearable device is built-in with inertial sensor, memory and place Device is managed, the inertial sensor and memory are connected to the processor respectively, and the memory is stored with can be by the place The computer program that device executes is managed, the computer program can be realized following method and step when being executed by the processor：Acquire the exercise data of user；When monitoring that user starts swimming, the time point that user starts swimming is labeled as starting point, and start to cache the fortune Dynamic data, until user to have been swum to the end time point mark of a swimming pool length when monitoring that user has swum a swimming pool length It is denoted as switch-back point, and stops caching the exercise data；Processing acquisition user is carried out to the exercise data between the starting point and switch-back point of caching and has swum a swimming pool length It strikes number.
- 7. intelligent wearable device as claimed in claim 6, which is characterized in that described pair caching the starting point and switch-back point it Between exercise data carry out processing and obtain user having swum the number of striking of a swimming pool length and include：Noise reduction is filtered to the exercise data between the starting point and switch-back point of caching, the movement after filtering noise reduction Any one uniaxial data is chosen in data；The number that processing obtains corresponding effective peak between the starting point and switch-back point is carried out to the uniaxial data, it will be described The number of effective peak halves, and obtains the number of striking that user has swum a swimming pool length.
- 8. intelligent wearable device as claimed in claim 7, which is characterized in that described to carry out processing acquisition to the uniaxial data The number of corresponding effective peak includes between the starting point and switch-back point：Wave crest and trough of the uniaxial data in the starting point and switch-back point are recorded, the wave crest and trough are labeled as peak Value obtains corresponding peak lists between the starting point and switch-back point；One peak difference threshold value is set according to the peak change range of the uniaxial data, according to the peak difference threshold value to the starting point Corresponding peak lists are handled between switch-back point, obtain of corresponding effective peak between the starting point and switch-back point Number.
- 9. intelligent wearable device as claimed in claim 8, which is characterized in that it is described according to the peak difference threshold value to the starting point Corresponding peak lists are handled between switch-back point, obtain of corresponding effective peak between the starting point and switch-back point Number includes：Calculate between the starting point and switch-back point each peak value in corresponding peak lists and between the adjacent peak on the left of it The first absolute difference and the second absolute difference between the adjacent peak on the right side of it,When first absolute difference and second absolute difference are all larger than the peak difference threshold value, by the peak value mark It is denoted as effective peak；It, will be described when there is one to be less than the peak difference threshold value in first absolute difference and second absolute difference Peak markers are invalid peak value, and are removed from the peak lists；When first absolute difference and second absolute difference are respectively less than the peak difference threshold value, institute is further obtained Peak value and the absolute difference being separated by between a peak value on the left of it are stated, if the absolute difference is greater than the peak difference threshold It is worth, then is effective peak by the peak markers, and the adjacent peak at left and right sides of the peak value is labeled as invalid peak value, And it is removed from the peak lists.
- 10. intelligent wearable device as claimed in claim 8, which is characterized in thatDenoiser is filtered using low pass Chebyshev, noise reduction is filtered to the exercise data of caching；And/orExercise data is acquired using MEMS inertial sensor.
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