CN109472281A - Motion recording processing method and system, terminal and readable storage medium storing program for executing - Google Patents
Motion recording processing method and system, terminal and readable storage medium storing program for executing Download PDFInfo
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- CN109472281A CN109472281A CN201811051899.4A CN201811051899A CN109472281A CN 109472281 A CN109472281 A CN 109472281A CN 201811051899 A CN201811051899 A CN 201811051899A CN 109472281 A CN109472281 A CN 109472281A
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- G06F18/22—Matching criteria, e.g. proximity measures
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- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
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Abstract
The present invention provides a kind of motion recording processing method and system, terminal and readable storage medium storing program for executing.The motion recording processing method includes: the first exercise data sequence for obtaining corresponding wearable device and the second exercise data sequence of counterpart terminal；Similarity detection is carried out to the first exercise data sequence and the second exercise data sequence, whether within a preset range to judge the first exercise data sequence and the second exercise data sequence similarity；When the first exercise data sequence and the second exercise data sequence similarity within a preset range when, union operation is executed to the first exercise data sequence and the second exercise data sequence, merges exercise data sequence to generate.The present invention can be merged by the exercise data sequence to wearable device and terminal, and then can produce accurate motion information, and many places equipment can also be used and come while being recorded, and improve the accuracy of record.
Description
Technical field
The present invention relates to data processing field more particularly to a kind of motion recording processing methods and system, terminal and readable
Storage medium.
Background technique
This part intends to provides background for the embodiments of the present invention stated in claims and specific embodiment
Or context.Description herein recognizes it is the prior art not because not being included in this section.
Existing wearable device (such as pedometer, Intelligent bracelet, smartwatch) has movement identification function
Terminal (such as mobile phone) can by the motion conditions of sensor senses user, and by some algorithms calculate movement step number,
The exercise datas such as mileage and consumed heat.User using wearable device or is putting on terminal, wearable device and terminal
It then can record the exercise data of user.However, user's carried terminal for some reason, and wearable device is not carried；And by
Wearable device, and non-carried terminal are carried in certain because users；Or wearable device and terminal are carried simultaneously.Cause
And the exercise data of wearable device or terminal can not preferably reflect the motion conditions of user, reduce the experience of user.
Summary of the invention
In view of above-mentioned, the present invention provides a kind of motion recording processing method and system, terminal and readable storage medium storing program for executing, to have
Conducive to raising user experience.
A kind of motion recording processing method, comprising:
Obtain the first exercise data sequence of corresponding wearable device and the second exercise data sequence of counterpart terminal；
Similarity detection is carried out to the first exercise data sequence and the second exercise data sequence, to judge the first movement
Within a preset range whether data sequence and the second exercise data sequence similarity；
When the first exercise data sequence and the second exercise data sequence similarity within a preset range when, to it is described first fortune
Dynamic data sequence and the second exercise data sequence execute union operation, merge exercise data sequence to generate.
Further, described to the first exercise data sequence and second in the motion recording processing method
Exercise data sequence carries out similarity detection
Corresponding wearable device is calculated according to the first exercise data sequence first accelerates degree series；
Counterpart terminal is calculated according to the second exercise data sequence second accelerates degree series；
Calculate the Euclidean distance between first acceleration and the second acceleration；
Judge the Euclidean distance whether in the preset range；
When the Euclidean distance is in the preset range, execute described to the first exercise data sequence and second
Exercise data sequence executes union operation.
Further, described to the first exercise data sequence and second in the motion recording processing method
Exercise data sequence executes union operation
Judge in same time period whether to include the first exercise data sequence and the second exercise data sequence；
When in same time period including the first exercise data sequence and the second exercise data sequence, from the first exercise data
The first exercise data that a corresponding moment in the period is obtained in sequence, also from the second exercise data sequence described in acquisition
Second exercise data at the moment is corresponded in period；
It is calculated according to first exercise data and the second exercise data to the first weight of wearable device and right
Answer the second weight of terminal；
It obtains corresponding to the moment according to first weight, the second weight, the first exercise data and the second exercise data
Synthesis after exercise data；
Exercise data obtains the merging exercise data sequence after obtaining the synthesis for corresponding to each moment in the period.
Further, described to the first exercise data sequence and second in the motion recording processing method
Exercise data sequence executes before union operation further include:
The merging exercise data sequence is carried out according to the first exercise data sequence and the second exercise data sequence
Verification operation.
Further, described according to the first exercise data sequence and in the motion recording processing method
Two exercise data sequences carry out verification operation to the merging exercise data sequence
The merging exercise data sequence is identified, to obtain the first recognition result；
The first exercise data sequence is identified, to obtain the second recognition result；
The second exercise data sequence is identified, to obtain third recognition result；
Judge whether the first recognition result is less than second recognition result and third recognition result；
When the first recognition result is less than second recognition result and third recognition result, by the second recognition result and the
Exercise data sequence corresponding to biggish recognition result is as the merging exercise data sequence in three recognition results.
Further, in the motion recording processing method, first movement for obtaining corresponding wearable device
Data sequence and the second exercise data sequence of counterpart terminal include:
The first exercise data sequence and the second exercise data are obtained by the application programming interfaces that health application provides
Sequence；
Judge that the application programming interfaces provided from health application obtain the first exercise data sequence and the second movement number
It is whether normal according to sequence；
When the application programming interfaces provided from health application obtain the first exercise data sequence and the second exercise data
When sequence variation, the second exercise data sequence is obtained from the application programming interfaces of operating system.
Further, in the motion recording processing method, the application program for judging to provide from health application
Interface obtain the first exercise data sequence and the second exercise data sequence whether normally include:
It is default to judge whether the version of the operating system of the terminal is lower than；Or judge the application journey provided from health application
Obtain whether exercise data sequence is predetermined sequence in sequence interface；
It is preset when the version of the operating system of the terminal is lower than；Or it is obtained from the application programming interfaces that health application provides
When to take exercise data sequence be predetermined sequence, determine that the application programming interfaces provided from health application obtain first fortune
Dynamic data sequence and the second exercise data sequence variation.
A kind of motion recording processing system, comprising:
Acquiring unit, for obtaining the first exercise data sequence of corresponding wearable device and the second movement of counterpart terminal
Data sequence；
Recognition unit, for carrying out similarity detection to the first exercise data sequence and the second exercise data sequence,
Whether within a preset range to judge the first exercise data sequence and the second exercise data sequence similarity；
Combining unit, for working as the first exercise data sequence and the second exercise data sequence similarity within a preset range
When, union operation is executed to the first exercise data sequence and the second exercise data sequence, merges exercise data sequence to generate
Column.
A kind of terminal, the terminal include processor and memory, and several computer programs are stored on the memory,
The step of processor realizes the motion recording processing method when being used to execute the computer program stored in memory.
A kind of readable storage medium storing program for executing, is stored thereon with computer program, which is characterized in that the computer program is processed
The step of motion recording processing method is realized when device executes.
Above-mentioned motion recording processing method and system, terminal and readable storage medium storing program for executing pass through to wearable device and terminal
Exercise data sequence merges, and then can produce accurate motion information, particularly, according to wearable device and terminal
Weight corresponding to exercise data sequence can be remembered simultaneously come combined exercise data sequence using many places equipment
Record, and improve the accuracy of record.In addition, above-mentioned motion recording processing method, which also passes through, judges whether the version of operating system is low
In default and/or whether judge to obtain exercise data sequence from health application normally to determine whether available accurate
Exercise data sequence.
Above-mentioned motion recording processing method and system, terminal and readable storage medium storing program for executing further include to first exercise data
Sequence and the second exercise data sequence carry out similarity detection, to judge that type of sports corresponding to wearable device and terminal is
It is no identical, and then facilitate and differentiate whether exercise data sequence corresponding to wearable device and terminal belongs to identical user, when
When exercise data sequence corresponding to wearable device and terminal belongs to identical user, subsequent union operation can be performed；Separately
Outside, also school can be carried out to the merging exercise data sequence according to the first exercise data sequence and the second exercise data sequence
Operation is tested, the accuracy for merging exercise data sequence is favorably improved.
Detailed description of the invention
It, below will be to required in embodiment description in order to illustrate more clearly of the technical solution of embodiment of the present invention
The attached drawing used is briefly described, it should be apparent that, the accompanying drawings in the following description is some embodiments of the present invention, for
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is the flow chart of the better embodiment of the motion recording processing method of first embodiment of the invention；
Fig. 2 is the flow chart of the better embodiment of step 102 in figure；
In Fig. 3 in Fig. 1 the better embodiment of step 100 flow chart；
Fig. 4 is the flow chart of the better embodiment of the motion recording processing method of second embodiment of the invention；
Fig. 5 is the flow chart of the better embodiment of step 408 in Fig. 4.
Fig. 6 is the block diagram of the terminal of the present invention better embodiment synchronous with wearable device；
Fig. 7 is the illustrative block diagram for the motion recording processing system that an embodiment of the present invention provides.
Main element symbol description
Terminal 40
Processor 401
Memory 405
Input/output interface 407
Network interface 409
Bus 411
Display screen 403
Motion recording processing system 417
Wearable device 50
Acquiring unit 710
Combining unit 712
Recognition unit 714
Display unit 716
Verification unit 718
Specific embodiment
To better understand the objects, features and advantages of the present invention, with reference to the accompanying drawing and specific real
Applying mode, the present invention will be described in detail.It should be noted that in the absence of conflict, presently filed embodiment and reality
The feature applied in mode can be combined with each other.
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention, described embodiment
Only some embodiments of the invention, rather than whole embodiments.Based on the embodiment in the present invention, this field
Those of ordinary skill's every other embodiment obtained without making creative work, belongs to guarantor of the present invention
The range of shield.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The normally understood meaning of technical staff is identical.Term as used herein in the specification of the present invention is intended merely to description tool
The purpose of the embodiment of body, it is not intended that in the limitation present invention.
Embodiment one
Fig. 1 is the flow chart of the motion recording processing method of first embodiment of the invention, it should be noted that this embodiment party
The motion recording processing method of formula is not limited to step and sequence in flow chart shown in FIG. 1.According to different requirements,
Step in shown flow chart can increase, remove or change sequence.
First better embodiment of motion recording processing method of the present invention may include following steps:
Step 100, the first exercise data sequence of wearable device is obtained, and obtains the second exercise data sequence of terminal
Column.
It is to be appreciated that wearable device, terminal may be provided with sensor, for recording the motion state of user.One
In embodiment, sensor includes but is not limited to one or both of gravity accelerometer, gyro sensor,
In, the exercise data that gravity accelerometer detects includes weight caused by the gravity acted in wearable device or terminal
Power acceleration；The detectable exercise data of gyro sensor includes that wearable device or terminal are transported along an axis or several axis
Dynamic angular speed.Preferably, sensor continual can detect and generate to obtain exercise data.
In one embodiment, when user carries wearable device and/or terminal, wearable device and/or terminal can
Corresponding exercise data is generated by sensor, also can produce the time data of corresponding movement.Wearable device and/or terminal can
By exercise data and time Data Synthesis exercise data sequence, for example, wearable device and/or terminal can record in a period
The mobile step number of user.In present embodiment, wearable device produces corresponding first exercise data sequence, and terminal can produce
Corresponding second exercise data sequence.
It is to be appreciated that wearable device and/or terminal can recognize corresponding motion state according to exercise data sequence,
Corresponding type of sports can also be gone out according to exercise data recognition sequence.Wherein, motion state can include: step number, disappears at move distance
Heat consumption；Type of sports can include: go upstairs, go downstairs, running, walking, riding, body-building etc..
In one embodiment, can lead between wearable device (such as Intelligent bracelet, wrist-watch) and terminal (such as smart phone)
Cross the modes such as bluetooth, wireless network, infrared ray, NFC (Near Field Communication, near-field communication), wireless network
Connection.When terminal and wearable device are in wireless connection or the join domain of bluetooth connection, wearable device then can be by it
The exercise data sequence of interior storage is sent to terminal, to synchronize with terminal, and then can obtain the of the wearable device
One exercise data sequence.
It is to be appreciated that terminal can run operating system (such as iOS), operating system can have multiple versions, and terminal can
Multiple functions are realized by the upgrading of operating system.One or more application (APP) can be run in terminal, each application can be real
Existing different, the same or similar functions, for example, the function of telephone call can be achieved in the first application, social activity is can be achieved in the second application
Function, third application can second apply similar function, such as realize chat function.Terminal is strong convenient for the movement to user
Health is managed, and terminal can obtain the exercise data sequence of various equipment by health application.
It is to be appreciated that health application can obtain the second exercise data sequence by the sensor being set in terminal,
And then corresponding motion state, type of sports etc. can be gone out according to the second exercise data recognition sequence of acquisition.In addition, when wearable
When equipment (such as Apple Watch) is synchronous with terminal, health application can obtain the first exercise data sequence of wearable device output
Column, and then corresponding motion state, movement class can be also identified according to the first exercise data sequence that wearable device exports
Type etc..In other embodiments, wearable device also can be other third-party wearable devices, such as the intelligence of other manufacturers
Wrist-watch etc..For third wearable device, terminal can run corresponding third-party application, obtain the by the third-party application
Exercise data sequence in three wearable devices.Preferably, when third-party application acquires in third party's wearable device
When exercise data sequence, third-party application can be by exercise data sequence synchronization to health application, in this way, health application can also obtain
Exercise data sequence in third party's wearable device.
Also referring to Fig. 3, after wearable device and terminal synchronize, terminal is obtaining first exercise data
When sequence and the second exercise data sequence, it may include as follows that whether the exercise data sequence for needing to judge to acquire is reliable
Step:
Step 300, judge whether acquisition exercise data sequence is normal from health application；If so, thening follow the steps 302；
Otherwise, step 304 is executed.
In one embodiment, when the exercise data sequence of terminal to be obtained and/or wearable device, calling can be passed through
The API (Application Programming Interface, application programming interfaces) of the offer of health application.Therefore, when wearing
Wear formula equipment it is synchronous with terminal after, can be by calling the API of the health application of terminal obtain the first of corresponding wearable device
Second exercise data sequence of exercise data sequence and counterpart terminal.It is also possible in the presence of can not be by calling health application
API obtains corresponding exercise data sequence.For example, when the version of the operating system of terminal operating is lower or improper, or health
Using itself, there are calling when bug, the API of health application is possibly can not accurately to obtain exercise data sequence.
Therefore, in present embodiment, judge that the whether normal step of exercise data sequence is obtained from health application to wrap
Include: judge the version of operating system whether be lower than it is default and/or judge from health application acquisition exercise data sequence whether be
Predetermined sequence.
In one embodiment, judge to be the acquisition exercise data sequence from health application by the version of operating system
It is whether normal can include:
The version of operating system is obtained, to judge the movement number obtained from health application according to the version of operating system
It is whether normal according to sequence.It is to be appreciated that can indicate to obtain from health application when the version of operating system is lower than default version
The exercise data sequence variation taken can not obtain the first exercise data sequence and the second fortune from the API of health application
Dynamic data sequence, and then executable step 304；Otherwise, when the version of operating system is not less than default version, expression can be from strong
The exercise data sequence acquired in the API of Kang Yingyong is normal, can accurately obtain the first exercise data sequence
And the second exercise data sequence, and then executable step 302.
In one embodiment, judge that the step of whether acquisition exercise data sequence is predetermined sequence from health application can
Include:
Judge the exercise data sequence acquired from health application whether 0.In present embodiment, the predetermined sequence is
0.It is to be appreciated that then possibly exercise data sequence can not be obtained from health application when health application is there are when bug, at this point, from
The value of the exercise data sequence obtained in health application can be 0, that is, indicate that the exercise data sequence obtained from health application is different
Often.In this way, executing step 304 when exercise data sequence can not be obtained from health application；When what is obtained from health application
When the value of exercise data sequence is not 0, indicate that acquisition exercise data sequence is normal from health application, can be performed step at this time
302。
Step 302, the first exercise data sequence described in health application and the second exercise data sequence.
It is to be appreciated that the version for working as operating system is not less than default and is obtaining exercise data sequence just from health application
Chang Shi is indicated by accurately obtaining the first exercise data sequence and the second exercise data sequence from health application.
Step 304, the second exercise data sequence is directly acquired.
It is to be appreciated that lower or improper (such as version of operating system iOS of version of the operating system when terminal operating
When for iOS7), or when can not obtain from health application any exercise data sequence, the first fortune of wearable device transmission is indicated
Dynamic data sequence possibly can not obtain, at this point, can directly acquire the movement of terminal for accurate acquisition exercise data sequence
Data sequence, the API that provides such as calling system obtain the second exercise data sequence of terminal.
Step 102, merge the first exercise data sequence and the second exercise data sequence, to obtain merging exercise data sequence
Column.
It is to be appreciated that terminal can be after receiving the first exercise data sequence, by the first exercise data sequence
Column execute union operation with the second exercise data sequence that terminal generates.
Referring to Figure 2 together, the first exercise data sequence of the merging and the step of the second exercise data sequence can include:
Step 200, judge in same time period whether to include the first exercise data sequence and the second exercise data sequence；If
It is to execute step 204；If it is not, executing step 202.
It is to be appreciated that merging place to the exercise data of distinct device according to the time data in exercise data sequence
Reason, such as merges processing to the exercise data sequence of wearable device and terminal.It, can will be in a period when merging treatment
Exercise data merge processing, wherein the period includes time started and end time, the period can for one day, it is 2 small
When, 1 hour etc..The selection of specific period can be manually selected or be automatically selected by user.It is to be appreciated that at that time
Between section be selected as when automatically selecting, can be default choice 1 day；When the selection of period is means selection, 2 hours, 2 may be selected
It etc..
It is being moved it is to be appreciated that user can carry wearable device with an equipment in terminal, such as due to certain originals
Because user carries intelligent terminal, and wearable device is not carried；And user carries wearable device for some reason, and do not take
Band intelligent terminal indicates at this point, wearable device and terminal can only have a kind of exercise data sequence in the identical period
It at the same time include the first exercise data sequence or the second exercise data sequence in section.User can also carry simultaneously and wear
Formula equipment and terminal are worn, there are two kinds of exercise data sequences at this point, wearable device is with terminal at the same time section, indicate
It at the same time include the first exercise data sequence and the second exercise data sequence in section.
It is to be appreciated that can be by judging in same time period whether to include the first exercise data sequence and the second movement number
Judge according to sequence user whether and meanwhile carry wearable device and terminal.
Step 202, using the first exercise data sequence or the second exercise data sequence as the merging exercise data
Sequence.
It is to be appreciated that the first exercise data sequence and the second exercise data sequence are not deposited simultaneously when in same time period
When, the exercise data sequence that can will be present is as merging exercise data sequence.For example, being only existed in same time period
It, can be using the first exercise data sequence as the merging exercise data sequence when the first exercise data sequence；When only existing
It, can be using the second exercise data sequence as the merging exercise data sequence when the second exercise data sequence.
When there is exercise data sequence during this period of time in terminal and wearable device, it may be possible to which user is during exercise
Terminal and wearable device are carried simultaneously.Thus, it can be in the first exercise data sequence and terminal in wearable device
Second exercise data sequence merges, to obtain final motion information.
For example, during the period of time, the main movement of user is to walk, and then can be known according to the data after merging treatment
The step number of other user.Because there is exercise data sequence during the period of time in terminal and wearable device, thus, it can will obtain
The weight of the exercise data sequence of terminal and wearable device is taken, and is calculated according to corresponding weight, after being merged
Data.
Step 204, first exercise data at a corresponding moment in the period is obtained from the first exercise data sequence,
And the second exercise data that the moment is corresponded in the period is obtained from the second exercise data sequence.
It is assumed that sensor is 3 axis acceleration sensors, the second exercise data sequence (a of terminalxt, ayt, azt), wherein t is
Time series, axtIndicate sample size of the t moment terminal in X-axis, aytIndicate sample size of the t moment terminal in Y-axis,
aztIndicate sample size of the t moment terminal on Z axis.Similarly, for wearable device, corresponding second exercise data sequence
Column are represented by (bxt, byt, bzt), bxtIndicate sample size of the t moment wearable device in X-axis, bytIndicate t moment wearing
Sample size of the formula equipment in Y-axis, bztIndicate sample size of the t moment wearable device on Z axis.When therefore, for t
It carves, the first exercise data is represented by (bxt, byt, bzt), the second exercise data is represented by (axt, ayt, azt)。
Step 206, first to wearable device is calculated according to first exercise data and the second exercise data
Second weight of weight and counterpart terminal.
For t moment, the second weight w of terminal1It indicates are as follows:
For t moment, the first weight w of wearable device2It indicates are as follows:
w2=1-w1；
Step 208, it is corresponded to according to first weight, the second weight, the first exercise data and the second exercise data
Exercise data after the synthesis at the moment.
Exercise data E for t moment, after synthesistIt may be expressed as:
(w1axt+w2bxt, w1ayt+w2byt, w1azt+w2bzt)。
Step 210, exercise data obtains the merging movement number after obtaining the synthesis for corresponding to each moment in the period
According to sequence.
For the t time, exercise data after synthesis:
Et=(w1axt+w2bxt, w1ayt+w2byt, w1azt+w2bzt),
Thus, merge exercise data sequence E and is represented by (E1, E2..., Et)。
Step 104, the corresponding motion information for merging exercise data sequence of display.
It is extractable to merge exercise data sequence medium wave peak trough feature to identify the step number of user to understand ground；Wherein transport
The Wave crest and wave trough feature of dynamic data sequence is the wave crest for the curve that all data in exercise data sequence constitute corresponding point
Trough feature；Wherein, Wave crest and wave trough feature includes that the wave crest frequency of occurrences, the trough frequency of occurrences, wave crest average value, trough are average
One or more of value, Wave crest and wave trough average distance.And the step number for the user for obtaining identification is as final movement
Information.In one embodiment, movement recognition result data can be shown with various forms such as charts by user interface.
Above-mentioned motion recording processing method is merged by the exercise data sequence to wearable device and terminal, in turn
It can produce accurate motion information, particularly, the weight according to corresponding to the exercise data sequence of wearable device and terminal
It come combined exercise data sequence, can be recorded simultaneously using many places equipment, and improve the accuracy of record.Separately
Outside, above-mentioned motion recording processing method, which also passes through, judges whether the version of operating system is lower than default and/or judges to answer from health
It is whether normal to determine whether available accurate exercise data sequence with middle acquisition exercise data sequence.
Embodiment two
Fig. 4 is the flow chart of the motion recording processing method of first embodiment of the invention, it should be noted that this embodiment party
The motion recording processing method of formula is not limited to step and sequence in flow chart shown in Fig. 4.According to different requirements,
Step in shown flow chart can increase, remove or change sequence.
Second better embodiment of motion recording processing method of the present invention may include following steps:
Step 400, the first exercise data sequence of wearable device is obtained, and obtains the second exercise data sequence of terminal
Column.
Step 402, similarity detection is carried out to the first exercise data sequence and the second exercise data sequence, with judgement
Within a preset range whether the first exercise data sequence and the second exercise data sequence similarity.If it is not, executing step 404；If
It is to execute step 406.
It is to be appreciated that when existing simultaneously the first exercise data sequence and the second exercise data sequence in the identical period
When, identical user may be not belonging to due to wearable device or terminal, due to different users Duan Qiyun at the same time
Dynamic type may not be identical, and then there may be biggish differences for the type of sports for causing two kinds of exercise data sequences of identification to represent
It is different.For example, the type of sports corresponding to the second exercise data sequence of terminal is expressed as walking, and the movement of wearable device
Type of sports corresponding to data sequence is expressed as riding, since the type of sports gap of the two is larger, and it is larger for gap
Exercise data sequence when merging, can the result to data after merging generate large effect.Thus, merging the two fortune
Before dynamic data sequence, can first carry out similarity detection judge type of sports corresponding to wearable device and terminal whether phase
Together.In present embodiment, when the first exercise data sequence and the second exercise data sequence similarity within a preset range when, can table
Show that type of sports corresponding to wearable device and terminal is identical；When the first exercise data sequence and the second exercise data sequence phase
When like spending not within a preset range, the difference of type of sports corresponding to wearable device and terminal can be indicated
When the first exercise data sequence and the second exercise data sequence similarity within a preset range when, then can be performed step
406, merge the first exercise data sequence and the second exercise data sequence, to obtain merging exercise data sequence；When the first movement
Data sequence and the second exercise data sequence similarity not within a preset range when, then it represents that wearable device and terminal may
Belong to different users, in this way, executable step 404.
It is to be appreciated that preferably, similarity detects can include: calculate separately the acceleration sequence of terminal and wearable device
Arrange Sa, Sb；Degree series are accelerated to calculate the Euclidean distance dist [S between computing terminal and wearable device according to the twoa, Sb]；
Later, it can determine whether Euclidean distance whether within a preset range；When the judgment result is yes, then it can be confirmed that terminal is set with wearable
Standby type of sports is similar, can carry out subsequent merging treatment；When the judgment result is no, can determine terminal with it is wearable
The exercise data sequence of equipment is dissimilar.
The acceleration degree series S of terminalaIt is represented by (Sa1, Sa2, Sa3..., Sat), in which:
The acceleration degree series S of wearable devicebIt is represented by (Sb1, Sb2, Sb3..., Sbt), in which:
Euclidean distance dist [Sa, Sb]:
Step 404, the first exercise data sequence or the second exercise data sequence are selected, non-selected fortune is reset
Dynamic data sequence.
When the type of sports difference corresponding to the wearable device and terminal, then it represents that wearable device and terminal may
Belong to different users, the first exercise data sequence may be selected as the merging exercise data sequence, or selection institute
The second exercise data sequence is stated as the merging exercise data sequence.It is to be appreciated that when wearable device and terminal are right
When the type of sports difference answered, terminal can prompt user to select one of exercise data sequence as the merging exercise data
Sequence, or by the two one of exercise data sequence be set as default exercise data sequence.
In another embodiment, when selecting a kind of exercise data sequence, non-selected exercise data sequence can be reset.
For example, when selecting the first exercise data sequence, since the second exercise data sequence is unselected, thus, it can weigh
The second exercise data sequence is set, the second exercise data sequence as described in setting is 0.
Step 406, merge the first exercise data sequence and the second exercise data sequence, to obtain merging exercise data sequence
Column.
Step 408, according to the first exercise data sequence and the second exercise data sequence to the merging exercise data
Sequence carries out verification operation, to judge the accuracy for merging exercise data sequence.
It is to be appreciated that after executing union operation to the first exercise data sequence and the second exercise data sequence
To the accuracy of merging exercise data sequence may be subjected to influence, therefore, need to according to the first exercise data sequence and
Second exercise data sequence carries out verification operation to the merging exercise data sequence.
Please refer to fig. 5, the better embodiment of the verification operation can include:
Step 500, the merging exercise data sequence is identified, to obtain the first recognition result；To described first
Exercise data sequence is identified, to obtain the second recognition result；The second exercise data sequence is identified, to obtain
Third recognition result.
For example, for the exercise data sequence in the period, can first to the exercise data sequence that merges that treated into
The first recognition result generated after row identification, such as the third recognition result are 7000 steps；First movement number of wearable device
It is identified according to sequence, corresponding second recognition result (such as 10000 steps) is generated with this, then number is moved to the fortune second of terminal device
It is identified according to sequence, corresponding third recognition result (such as 8000 steps) is generated with this, still.
Step 502, judge whether the first recognition result is less than second recognition result and third recognition result.If it is not,
Execute step 506；If so, executing step 504.
Due in merging process exist uncertainty, so as to cause processing the first recognition result less than the second recognition result
And third recognition result, thus, in this case, maximum work in the result after can identifying terminal and wearable device
For final motion information.
Step 504, by exercise data corresponding to biggish recognition result in the second recognition result and third recognition result
Sequence is as the merging exercise data sequence.
Thus, it is maximum as final motion information in the result after can identifying terminal and wearable device, such as
Using the second above-mentioned recognition result as final motion information, i.e., number is moved using the first exercise data sequence as merging
According to sequence.
Step 506, using the first recognition result as the operation information for merging exercise data sequence.
When the first recognition result is greater than second recognition result or third recognition result, indicate to merge exercise data sequence
The accuracy of column is higher, thus can carry out subsequent processing according to exercise data sequence is merged.
Step 410, the corresponding motion information for merging exercise data sequence of display.
Above-mentioned motion recording processing method is other than the relevant technologies effect with example one, and the technical effect reached is also
Including carrying out similarity detection to the first exercise data sequence and the second exercise data sequence, with judge wearable device and
Whether type of sports corresponding to terminal is identical, and then facilitates and differentiate exercise data sequence corresponding to wearable device and terminal
Whether identical user is belonged to, it, can when the exercise data sequence corresponding to the wearable device and terminal belongs to identical user
Execute subsequent union operation；In addition, can also be according to the first exercise data sequence and the second exercise data sequence to described
Merge exercise data sequence and carry out verification operation, favorably improves the accuracy for merging exercise data sequence.
Referring to Fig. 6, terminal 40 of the present invention is communicated by network with wearable device 50, wearable device is such as obtained
50 the first exercise data sequences generated.The terminal 40 be it is a kind of can according to the instruction for being previously set or storing, automatically into
Line number value calculates and/or the equipment of information processing, and hardware includes but is not limited to microprocessor, specific integrated circuit (application
Lication Specific Integrated Circuit, ASIC), programmable gate array (Field-Programmable
Gate Array, FPGA), digital processing unit (Digital Signal Processor, DSP), embedded device etc..
The terminal 40, which may be, but not limited to, any one, to pass through keyboard, mouse, remote controler, touch tablet with user
Or the modes such as voice-operated device carry out the electronic product of human-computer interaction, for example, tablet computer, smart phone, personal digital assistant
(Personal Digital Assistant, PDA), game machine, intellectual wearable device etc..
Network locating for the terminal 40 includes, but are not limited to internet, wide area network, Metropolitan Area Network (MAN), local area network, virtual private
Network (Virtual Private Network, VPN) etc., such as terminal 40 can the access of network interface 409 internets, wide area
Net, Metropolitan Area Network (MAN), local area network, Virtual Private Network.
The memory 405 can be different type storage equipment or computer readable storage medium, all kinds of for storing
Data.For example, it may be the memory of terminal 40, can also be the storage card that can be external in the terminal 40, such as flash memory, SM card
(Smart Media Card, smart media card), SD card (Secure Digital Card, safe digital card) etc..Memory
405 for storing Various types of data, for example, the application (using lications) including information processing installed in the terminal 40,
The information such as the data be arranged using above- mentioned information processing method, obtained.
The processor 401 is used to execute all kinds of softwares installed in the computation processing method and the terminal 40,
Such as operating system, messaging software etc..The processor 401 is including but not limited to processor (Central
Processing Unit, CPU), micro-control unit (Micro Controller Unit, MCU) etc. refers to for interpretive machine
The device for enabling and handling the data in computer software, may include one or more microprocessor, digital processing unit.Institute
State display screen 403 can be touch screen etc. other be used for show picture equipment.
The module of one or more corresponding to the motion recording processing system 417 that the terminal 40 may include, described one
A or multiple modules can be stored in the memory 405 of terminal 40 and may be configured to by one or more processors
(the present embodiment is a processor 401) executes, to complete the present invention.For example, as shown in fig.6, the terminal 40 includes depositing
Reservoir 405, input/output interface 407, display screen 403 and pass through bus 411 and the memory 405, input/output interface 407
The processor 401 of data exchange is carried out with display screen 403.Wherein, the input/output interface 407 may connect to mouse and/or
Keyboard (not shown).The so-called module of the present invention is to complete the program segment of a specific function, than program more suitable for describing software
Implementation procedure in the processor.
In the present embodiment, the display screen 403 is used to provide convenience for the operation of user.The memory 405 can store
There are several program codes, to be executed by the processor 401, and then realizes the function of the motion recording processing system 417.
Referring to Figure 7 together in present embodiment, the motion recording processing system 417 may include acquiring unit 710, close
And unit 712, recognition unit 714, display unit 716 and verification unit 718.
The so-called module of the present invention or unit can be the program segment for completing a specific function, than program more suitable for description
The implementation procedure of software in the processor.
The acquiring unit 710 is used to obtain the first exercise data sequence of wearable device and the second movement number of terminal
According to sequence.
It is to be appreciated that wearable device, terminal may be provided with sensor, for recording the motion state of user.One
In embodiment, sensor includes but is not limited to one or both of gravity accelerometer, gyro sensor,
In, the exercise data that gravity accelerometer detects includes weight caused by the gravity acted in wearable device or terminal
Power acceleration；The detectable exercise data of gyro sensor includes that wearable device or terminal are transported along an axis or several axis
Dynamic angular speed.Preferably, sensor continual can detect and generate to obtain exercise data.
In one embodiment, when user carries wearable device and/or terminal, wearable device and/or terminal can
Corresponding exercise data is generated by sensor, also can produce the time data of corresponding movement.Wearable device and/or terminal can
By exercise data and time Data Synthesis exercise data sequence, for example, wearable device and/or terminal can record in a period
The mobile step number of user.In present embodiment, wearable device produces corresponding first exercise data sequence, and terminal can produce
Corresponding second exercise data sequence.
It is to be appreciated that wearable device and/or terminal can recognize corresponding motion state according to exercise data sequence,
Corresponding type of sports can also be gone out according to exercise data recognition sequence.Wherein, motion state can include: step number, disappears at move distance
Heat consumption；Type of sports can include: go upstairs, go downstairs, running, walking, riding, body-building etc..
In one embodiment, can lead between wearable device (such as Intelligent bracelet, wrist-watch) and terminal (such as smart phone)
Cross the modes such as bluetooth, wireless network, infrared ray, NFC (Near Field Communication, near-field communication), wireless network
Connection.When terminal and wearable device are in wireless connection or the join domain of bluetooth connection, wearable device then can be by it
The exercise data sequence of interior storage is sent to terminal, to synchronize with terminal, and then can obtain the of the wearable device
One exercise data sequence.
It is to be appreciated that terminal can run operating system (such as iOS), operating system can have multiple versions, and terminal can
Multiple functions are realized by the upgrading of operating system.One or more application (APP) can be run in terminal, each application can be real
Existing different, the same or similar functions, for example, the function of telephone call can be achieved in the first application, social activity is can be achieved in the second application
Function, third application can second apply similar function, such as realize chat function.Terminal is strong convenient for the movement to user
Health is managed, and terminal can obtain the exercise data sequence of various equipment by health application.
It is to be appreciated that health application can obtain the second exercise data sequence by the sensor being set in terminal,
And then corresponding motion state, type of sports etc. can be gone out according to the second exercise data recognition sequence of acquisition.In addition, when wearable
When equipment (such as Apple Watch) is synchronous with terminal, health application can obtain the first exercise data sequence of wearable device output
Column, and then corresponding motion state, movement class can be also identified according to the first exercise data sequence that wearable device exports
Type etc..In other embodiments, wearable device also can be other third-party wearable devices, such as the intelligence of other manufacturers
Wrist-watch etc..For third wearable device, terminal can run corresponding third-party application, obtain the by the third-party application
Exercise data sequence in three wearable devices.Preferably, when third-party application acquires in third party's wearable device
When exercise data sequence, third-party application can be by exercise data sequence synchronization to health application, in this way, health application can also obtain
Exercise data sequence in third party's wearable device.
After wearable device and terminal synchronize, the acquiring unit 710 is obtaining the first exercise data sequence
When column and the second exercise data sequence, whether the exercise data sequence for needing to judge to acquire is reliable.
Whether the acquiring unit 710 is also used to judge to obtain exercise data sequence from health application normal.
In one embodiment, when the exercise data sequence of terminal to be obtained and/or wearable device, calling can be passed through
The API (Application Programming Interface, application programming interfaces) of the offer of health application.Therefore, when wearing
Wear formula equipment it is synchronous with terminal after, the acquiring unit 710 can by call terminal health application API come obtain correspondence wear
Wear the first exercise data sequence of formula equipment and the second exercise data sequence of counterpart terminal.It is also possible in the presence of tune can not be passed through
Corresponding exercise data sequence is obtained with the API of health application.For example, when the version of the operating system of terminal operating is lower or not
Properly or health application itself there are when bug, call the API of health application possibly can not accurately obtain exercise data sequence
Column.
Therefore, in present embodiment, the acquiring unit 710 judges whether obtain exercise data sequence from health application
It normally include: to judge whether the version of operating system is lower than default and/or judges whether that movement can be obtained from health application
Data sequence.
In one embodiment, the acquiring unit 710 judges it is from health application by the version of operating system
Obtain exercise data sequence.
It is to be appreciated that the acquiring unit 710 obtains the version of operating system, to be sentenced according to the version of operating system
Whether the disconnected exercise data sequence obtained from health application is normal.It is to be appreciated that when the version of operating system is lower than default
When version, it can indicate that the exercise data sequence variation obtained from health application, i.e., the described acquiring unit 710 can not be answered from health
The first exercise data sequence and the second exercise data sequence are obtained in API.When the version of operating system is not less than pre-
If when version, indicating that the exercise data sequence that can be acquired from the API of health application is normal, i.e., the described acquiring unit 710
The first exercise data sequence and the second exercise data sequence can accurately be obtained.
In one embodiment, the acquiring unit 710 judges that the exercise data sequence acquired from health application is
No predetermined sequence, wherein the predetermined sequence is 0.It, then possibly can not be from strong it is to be appreciated that when health application is there are when bug
Kang Yingyong obtains exercise data sequence, at this point, the value for the exercise data sequence that the acquiring unit 710 is obtained from health application
It can be 0, that is, indicate the exercise data sequence variation obtained from health application.When the exercise data sequence obtained from health application
When the value of column is not 0, it is normal to indicate that the acquiring unit 710 obtains exercise data sequence from health application.
It is to be appreciated that lower or improper (such as version of operating system iOS of version of the operating system when terminal operating
When for iOS7), or when can not obtain from health application any exercise data sequence, the first fortune of wearable device transmission is indicated
Dynamic data sequence possibly can not obtain, at this point, the acquiring unit 710 can be straight for accurate acquisition exercise data sequence
The exercise data sequence for taking terminal is obtained, the API that provides such as calling system obtains the second exercise data sequence of terminal.
The combining unit 712 is for merging the first exercise data sequence and the second exercise data sequence, to be merged
Exercise data sequence.
It is to be appreciated that terminal can be after receiving the first exercise data sequence, the combining unit 712 will be described
The second exercise data sequence that first exercise data sequence and terminal generate executes union operation, merges exercise data sequence to generate
Column.
The combining unit 712 is also used to judge in same time period whether include the first exercise data sequence and the second fortune
Dynamic data sequence.When in same time period including the first exercise data sequence and the second exercise data sequence, the merging is single
The second exercise data sequence that the first exercise data sequence and terminal generate can be executed union operation by member 712.When identical
When including the first exercise data sequence or the second exercise data sequence in the period, the combining unit 712 can be by described first
The second exercise data sequence that exercise data sequence or terminal generate is as the merging exercise data sequence.For example, identical
In period, when only existing the first exercise data sequence, number can be moved using the first exercise data sequence as the merging
According to sequence；When only existing the second exercise data sequence, number can be moved using the second exercise data sequence as the merging
According to sequence.
It is to be appreciated that merging place to the exercise data of distinct device according to the time data in exercise data sequence
Reason, such as merges processing to the exercise data sequence of wearable device and terminal.It, can will be in a period when merging treatment
Exercise data merge processing, wherein the period includes time started and end time, the period can for one day, it is 2 small
When, 1 hour etc..The selection of specific period can be manually selected or be automatically selected by user.It is to be appreciated that at that time
Between section be selected as when automatically selecting, can be default choice 1 day；When the selection of period is means selection, 2 hours, 2 may be selected
It etc..
It is being moved it is to be appreciated that user can carry wearable device with an equipment in terminal, such as due to certain originals
Because user carries intelligent terminal, and wearable device is not carried；And user carries wearable device for some reason, and do not take
Band intelligent terminal indicates at this point, wearable device and terminal can only have a kind of exercise data sequence in the identical period
It at the same time include the first exercise data sequence or the second exercise data sequence in section.User can also carry simultaneously and wear
Formula equipment and terminal are worn, there are two kinds of exercise data sequences at this point, wearable device is with terminal at the same time section, indicate
It at the same time include the first exercise data sequence and the second exercise data sequence in section.
When there is exercise data sequence during this period of time in terminal and wearable device, it may be possible to which user is during exercise
Terminal and wearable device are carried simultaneously.Thus, the combining unit 712 can be to the first exercise data in wearable device
Sequence is merged with the second exercise data sequence in terminal, to obtain final motion information.
The recognition unit 714 can be to the first exercise data sequence, the second exercise data sequence and merging movement number
Identified according to sequence, to identify corresponding type of sports, include but is not limited to go upstairs, go downstairs, running, walking, riding,
Body-building etc..
For example, during the period of time, the main movement of user is to walk, the recognition unit 714 can be according to merging at
The step number of data identification user after reason.Because there is exercise data sequence during the period of time in terminal and wearable device
Column, thus, the combining unit 712 can will acquire the weight of the exercise data sequence of terminal and wearable device, and according to right
The weight answered is calculated, with the data after being merged.
The recognition unit 714 is also used to carry out the first exercise data sequence and the second exercise data sequence similar
Degree detection, whether within a preset range to judge the first exercise data sequence and the second exercise data sequence similarity.When first
Exercise data sequence and the second exercise data sequence similarity within a preset range when, the combining unit 712 can be to described
One exercise data sequence and the second exercise data sequence merge operation；When the first exercise data sequence and the second exercise data
Sequence similarity not within a preset range when, the combining unit 712 can using the exercise data sequence selected as merge move
Data sequence.
It is to be appreciated that the recognition unit 714 can calculate separately the acceleration degree series of terminal and wearable device；According to
The two accelerates degree series to calculate the Euclidean distance between computing terminal and wearable device；Later, it can determine whether that Euclidean distance is
It is no within a preset range；When the judgment result is yes, then it can be confirmed that terminal is similar to the type of sports of wearable device, it can be with
Carry out subsequent merging treatment；When the judgment result is no, the exercise data sequence of terminal and wearable device can be determined not
It is similar.
The verification unit 718 is used for according to the first exercise data sequence and the second exercise data sequence to the conjunction
And exercise data sequence carries out verification operation, to judge the accuracy for merging exercise data sequence.
It is to be appreciated that after executing union operation to the first exercise data sequence and the second exercise data sequence
To the accuracy of merging exercise data sequence may be subjected to influence, therefore, the verification unit 718 can be according to described first
Exercise data sequence and the second exercise data sequence carry out verification operation to the merging exercise data sequence.
The recognition unit 714 identifies the merging exercise data sequence, to obtain the first recognition result；To institute
It states the first exercise data sequence to be identified, to obtain the second recognition result；The second exercise data sequence is identified,
To obtain third recognition result.
The verification unit 718 is for judging whether the first recognition result is less than second recognition result and third identification
As a result；When the first recognition result is less than the second recognition result and third recognition result, the combining unit 712 is used for second
Biggish recognition result is as the operation information for merging exercise data sequence in recognition result and third recognition result.
The display unit 716 is used to show the corresponding motion information for merging exercise data sequence.
To understand ground, the recognition unit 714 is extractable to merge exercise data sequence medium wave peak trough feature to identify use
The step number at family；Wherein the Wave crest and wave trough feature of exercise data sequence is all data in exercise data sequence to corresponding structure
At curve Wave crest and wave trough feature；Wherein, Wave crest and wave trough feature includes that the wave crest frequency of occurrences, the trough frequency of occurrences, wave crest are flat
One or more of mean value, trough average value, Wave crest and wave trough average distance.The recognition unit 714 can recognize and obtain
User step number as final motion information.The display unit 716 can be by user interface with various forms such as charts
Show motion information.
Above-mentioned motion recording processing system is merged by the exercise data sequence to wearable device and terminal, in turn
It can produce accurate motion information, particularly, the weight according to corresponding to the exercise data sequence of wearable device and terminal
It come combined exercise data sequence, can be recorded simultaneously using many places equipment, and improve the accuracy of record.Separately
Outside, above-mentioned motion recording processing method, which also passes through, judges whether the version of operating system is lower than default and/or judges to answer from health
It is whether normal to determine whether available accurate exercise data sequence with middle acquisition exercise data sequence.
Above-mentioned motion recording processing system further include to the first exercise data sequence and the second exercise data sequence into
The detection of row similarity, it is whether identical to judge type of sports corresponding to wearable device and terminal, and then resolution is facilitated to dress
Whether exercise data sequence corresponding to formula equipment and terminal belongs to identical user, corresponding to wearable device and terminal
When exercise data sequence belongs to identical user, subsequent union operation can be performed；In addition, can also be according to the first movement number
Verification operation is carried out to the merging exercise data sequence according to sequence and the second exercise data sequence, favorably improves the merging fortune
The accuracy of dynamic data sequence.
If the integrated module of terminal of the present invention is realized in the form of SFU software functional unit and as independent product
When selling or using, it can store in a computer readable storage medium.Based on this understanding, in present invention realization
The all or part of the process in the method for controlling volume of each embodiment is stated, can also be instructed by computer program relevant
Hardware is completed, and the computer program can be stored in a computer readable storage medium, which is being located
Step, it can be achieved that in the method for controlling volume of the respective embodiments described above is managed when device executes.Wherein, the computer program includes
Computer program code, the computer program code can for source code form, object identification code form, executable file or certain
A little intermediate forms etc..The computer-readable medium may include: any entity that can carry the computer program code
Or device, recording medium, USB flash disk, mobile hard disk, magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software
Distribution medium etc..It should be noted that the content that the computer-readable medium includes can be according to making laws in jurisdiction
Requirement with patent practice carries out increase and decrease appropriate, such as in certain jurisdictions, according to legislation and patent practice, computer
Readable medium does not include electric carrier signal and telecommunication signal.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included in the present invention.Any reference signs in the claims should not be construed as limiting the involved claims.This
Outside, it is clear that one word of " comprising " does not exclude other units or steps, and odd number is not excluded for plural number.System, device or mobile terminal apparatus
Multiple units, module or the device stated in claim can also by the same unit, module or device by software or
Hardware is realized.The first, the second equal words are used to indicate names, and are not indicated any particular order.
Embodiment of above is only used to illustrate the technical scheme of the present invention and not to limit it, although referring to the above preferable embodiment party
Formula describes the invention in detail, those skilled in the art should understand that, it can be to technical solution of the present invention
It modifies or equivalent replacement should not all be detached from the spirit and scope of technical solution of the present invention.
Claims (10)
1. a kind of motion recording processing method, which is characterized in that the described method includes:
Obtain the first exercise data sequence of corresponding wearable device and the second exercise data sequence of counterpart terminal；
Similarity detection is carried out to the first exercise data sequence and the second exercise data sequence, to judge the first exercise data
Within a preset range whether sequence and the second exercise data sequence similarity；
When the first exercise data sequence and the second exercise data sequence similarity within a preset range when, to it is described first movement number
Union operation is executed according to sequence and the second exercise data sequence, merges exercise data sequence to generate.
2. motion recording processing method as described in claim 1, which is characterized in that described to the first exercise data sequence
And second exercise data sequence carry out similarity detection include:
Corresponding wearable device is calculated according to the first exercise data sequence first accelerates degree series；
Counterpart terminal is calculated according to the second exercise data sequence second accelerates degree series；
Calculate the Euclidean distance between first acceleration and the second acceleration；
Judge the Euclidean distance whether in the preset range；
When the Euclidean distance is in the preset range, execution is described to move the first exercise data sequence and second
Data sequence executes union operation.
3. motion recording processing method as described in claim 1, which is characterized in that described to the first exercise data sequence
And second exercise data sequence execute union operation include:
Judge in same time period whether to include the first exercise data sequence and the second exercise data sequence；
When in same time period including the first exercise data sequence and the second exercise data sequence, from the first exercise data sequence
Middle the first exercise data for obtaining a corresponding moment in the period, also obtains the time from the second exercise data sequence
Second exercise data at the moment is corresponded in section；
The first weight to wearable device is calculated according to first exercise data and the second exercise data and corresponds to eventually
Second weight at end；
Obtain corresponding to the conjunction at the moment according to first weight, the second weight, the first exercise data and the second exercise data
At rear exercise data；
Exercise data obtains the merging exercise data sequence after obtaining the synthesis for corresponding to each moment in the period.
4. motion recording processing method as described in claim 1, which is characterized in that described to the first exercise data sequence
And second exercise data sequence execute union operation before further include:
The merging exercise data sequence is verified according to the first exercise data sequence and the second exercise data sequence
Operation.
5. motion recording processing method as claimed in claim 4, which is characterized in that described according to the first exercise data sequence
Column and the second exercise data sequence carry out verification operation to the merging exercise data sequence and include:
The merging exercise data sequence is identified, to obtain the first recognition result；
The first exercise data sequence is identified, to obtain the second recognition result；
The second exercise data sequence is identified, to obtain third recognition result；
Judge whether first recognition result is less than second recognition result and third recognition result；
When first recognition result is less than second recognition result and third recognition result, by the second recognition result and the
Exercise data sequence corresponding to biggish recognition result is as the merging exercise data sequence in three recognition results.
6. the motion recording processing method as described in any one of claim 1-5, which is characterized in that the acquisition correspondence is worn
Second exercise data sequence of the first exercise data sequence and counterpart terminal of wearing formula equipment includes:
The first exercise data sequence and the second exercise data sequence are obtained by the application programming interfaces that health application provides；
Judge that the application programming interfaces provided from health application obtain the first exercise data sequence and the second exercise data sequence
It whether normal arranges；
When the application programming interfaces provided from health application obtain the first exercise data sequence and the second exercise data sequence
When abnormal, the second exercise data sequence is obtained from the application programming interfaces of operating system.
7. motion recording processing method as claimed in claim 6, which is characterized in that the judgement is answered from what health application provided
With routine interface obtain the first exercise data sequence and the second exercise data sequence whether normally include:
It is default to judge whether the version of the operating system of the terminal is lower than；Or judge that the application program provided from health application connects
Obtain whether exercise data sequence is predetermined sequence in mouthful；
It is preset when the version of the operating system of the terminal is lower than, or obtains fortune from the application programming interfaces that health application provides
When dynamic data sequence is predetermined sequence, determine that the application programming interfaces provided from health application obtain the first movement number
According to sequence and the second exercise data sequence variation.
8. a kind of motion recording processing system, which is characterized in that the system comprises:
Acquiring unit, for obtaining the first exercise data sequence of corresponding wearable device and the second exercise data of counterpart terminal
Sequence；
Recognition unit, for carrying out similarity detection to the first exercise data sequence and the second exercise data sequence, to sentence
Within a preset range whether disconnected first exercise data sequence and the second exercise data sequence similarity；
Combining unit, for when the first exercise data sequence and the second exercise data sequence similarity within a preset range when, it is right
The first exercise data sequence and the second exercise data sequence execute union operation, merge exercise data sequence to generate.
9. a kind of terminal, the terminal includes processor and memory, and several computer programs are stored on the memory,
It is characterized in that, is realized when the processor is for executing the computer program stored in memory as any in claim 1-7
The step of motion recording processing method described in one.
10. a kind of readable storage medium storing program for executing, is stored thereon with computer program, which is characterized in that the computer program is processed
The step of motion recording processing method as described in any one of claim 1-7 is realized when device executes.
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| CN113434738A (en) * | 2020-03-23 | 2021-09-24 | 未来穿戴技术有限公司 | Data processing method and device of wearable device, computer device and medium |
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| CN107909023A (en) * | 2017-11-13 | 2018-04-13 | 广东欧珀移动通信有限公司 | Recognition methods, device, terminal and the storage medium of kinematic parameter |
| CN108171278A (en) * | 2018-01-25 | 2018-06-15 | 武汉中体智美科技有限公司 | A kind of recognizing model of movement method and system based on training data |
| CN108362304A (en) * | 2018-02-09 | 2018-08-03 | 维沃移动通信有限公司 | A kind of data processing method and mobile terminal |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113434738A (en) * | 2020-03-23 | 2021-09-24 | 未来穿戴技术有限公司 | Data processing method and device of wearable device, computer device and medium |
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