CN104750965B - A kind of determination method and device of user movement state - Google Patents
A kind of determination method and device of user movement state Download PDFInfo
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- CN104750965B CN104750965B CN201310753804.4A CN201310753804A CN104750965B CN 104750965 B CN104750965 B CN 104750965B CN 201310753804 A CN201310753804 A CN 201310753804A CN 104750965 B CN104750965 B CN 104750965B
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Abstract
The embodiments of the invention provide a kind of determination method and device of user movement state, this method includes：Server obtains exercise data of the user of collecting device collection in default first time period；Motion step number in the exercise data of acquisition, one section of exercise data is selected from the exercise data of acquisition, and after being handled by way of variable length piecewise combination the exercise data selected, matched with predetermined movement data, by motion state corresponding to predetermined movement data, as motion state corresponding to one section of exercise data of matching degree highest.In embodiments of the present invention, collecting device such as portable set only needs the relative motion data of report of user, related resolution need not be carried out, this reduces the electric quantity consumption of collecting device, and by server by utilizing predetermined movement data, the exercise data in user's certain period of time is analyzed, obtain motion state different in user this period, operate more convenient, improve Consumer's Experience.
Description
Technical field
The present invention relates to communication technical field, more particularly to a kind of determination method and device of user movement state.
Background technology
At present, if it is desired to know running status of the user within certain time, typically use and be easy to carry in user
3-axis acceleration data of collecting device (such as portable set) the collection user within certain time with it, then, by just
Portable device carries out correlation computations to the 3-axis acceleration data in this time, and then draws the fortune of user during this period of time
Dynamic state, such as motion state are running, walking, cycling etc..
Because the power supply energy that above-mentioned portable set provides the user is limited, if user is frequently come using this equipment
The motion state of itself is determined, the electric quantity consumption that this results in equipment is very fast, and user uses inconvenience, also, is set by this
The limitation of standby computing capability, is only capable of being supplied to user's specific motion state in a short time, None- identified go out user compared with
Specific motion state in long period so that Consumer's Experience is relatively low.
The content of the invention
It is existing using just to solve the embodiments of the invention provide a kind of determination method and device of user movement state
The problem of portable device identification user movement state causes inconvenient for operation and Consumer's Experience low.
Based on above mentioned problem, a kind of determination method of user movement state provided in an embodiment of the present invention, including：
Server obtains exercise data of the user of collecting device collection in default first time period, the motion number
According to including the user motion step number in each predetermined period；
Motion step number in the exercise data of acquisition, one section of exercise data is selected from the exercise data of acquisition, and
After being handled by way of variable length piecewise combination the exercise data selected, matched with predetermined movement data,
By motion state corresponding to the predetermined movement data, as motion state corresponding to one section of exercise data of matching degree highest.
A kind of determining device of user movement state provided in an embodiment of the present invention, including：
Acquisition module, for obtaining exercise data of the user of collecting device collection in default first time period, institute
Stating exercise data includes the user motion step number in each predetermined period；
Determining module, for the motion step number in the exercise data according to acquisition, one is selected from the exercise data of acquisition
Section exercise data, and after being handled by way of variable length piecewise combination the exercise data selected, with predetermined movement
Data are matched, by motion state corresponding to the predetermined movement data, as one section of exercise data pair of matching degree highest
The motion state answered.
The beneficial effect of the embodiment of the present invention includes：
A kind of determination method and device of user movement state provided in an embodiment of the present invention, in the method, server
Obtain exercise data of the user of collecting device collection in default first time period；According to the fortune in the exercise data of acquisition
Dynamic step number, selects one section of exercise data from the exercise data of acquisition, and to selecting by way of variable length piecewise combination
Exercise data handled after, matched with predetermined movement data, by motion state corresponding to the predetermined movement data,
As motion state corresponding to one section of exercise data of matching degree highest.In embodiments of the present invention, collecting device is for example portable
Formula equipment only needs the relative motion data of report of user, and without carrying out related resolution, this reduces the electricity of collecting device
Amount consumption, and one section of exercise data is selected from the exercise data of user by server, and variable length segmentation group is utilized to it
The mode of conjunction is entered Mobile state processing and then matched with predetermined movement data, and then does not obtain user during this period of time not
Same motion state, operates more convenient, improves Consumer's Experience.
Brief description of the drawings
Fig. 1 is the flow chart of the recognition methods of user movement state provided in an embodiment of the present invention；
Fig. 2 is the flow chart that server provided in an embodiment of the present invention is handled the exercise data of acquisition；
Fig. 3 (a) is the waveform diagram of the motion segments included by predetermined movement data provided in an embodiment of the present invention；
Fig. 3 (b) is the ripple of the motion segments included by the exercise data in second time period provided in an embodiment of the present invention
Shape schematic diagram；
Fig. 3 (c)~Fig. 3 (g) is the waveform diagram of each group provided in an embodiment of the present invention exercise data to be matched；
Fig. 4 is the flow chart that server provided in an embodiment of the present invention determines the motion state in certain user day；
Fig. 5 is the structure chart of the identification device of user movement state provided in an embodiment of the present invention.
Embodiment
With reference to Figure of description, to the determination method and dress of a kind of user movement state provided in an embodiment of the present invention
The embodiment put illustrates.
The determination method of a kind of user movement state provided in an embodiment of the present invention, as shown in figure 1, specifically including following step
Suddenly：
S11：Server obtains exercise data of the user of collecting device collection in default first time period；
Herein, above-mentioned exercise data includes user the motion step number in each predetermined period；
S12：Motion step number in the exercise data of acquisition, one section of motion number is selected from the exercise data of acquisition
According to, and after being handled by way of variable length piecewise combination the exercise data selected, carried out with predetermined movement data
Matching, by motion state corresponding to predetermined movement data, as motion state corresponding to one section of exercise data of matching degree highest.
Specifically, in above-mentioned steps S11, when collecting device takes the portable set taken with oneself for ease of user,
It only needs to upload relative motion data, without analyzing these exercise datas, which saves more electricity,
User uses more convenient, that is, improves Consumer's Experience.
It should be noted that above-mentioned default first time period and above-mentioned predetermined period can be according to identifying to user movement
Actual demand determines, such as default first time period is 0：00 to 24：00, i.e., the time of one day；Such as predetermined period is 5
Minute, in this case, above-mentioned exercise data is actually certain user 0 from some day：00 starts to 24：At this section of 00
In, move step number caused by every 5 minutes.
Preferably, in above-mentioned steps S12, for server, as shown in Fig. 2 can specifically pass through following step pair
The exercise data of acquisition is handled：
S21：The exercise data in default second time period is selected from the exercise data of acquisition, and in the fortune selected
In dynamic data, select to be more than the motion piece for setting the exercise data of numerical value and being formed by the motion step number in continuous multiple predetermined periods
Section；
S22：The motion segments selected are combined, obtained by the motion segments number according to included by predetermined movement data
To each group exercise data to be matched of second time period;
Herein, above-mentioned second time period includes the period corresponding to predetermined movement data；
S23：Respectively by obtained each group exercise data to be matched, matched with predetermined movement data.
Preferably, in above-mentioned steps S21, above-mentioned default second time period also can be according to the actual conditions of user movement
To determine, in embodiments of the present invention, in order to determine the relative motion state of user according to these exercise datas, it is previously set
One or more groups of exercise datas, each a corresponding period, these exercise datas are that the exercise data of multiple users is entered
Row sampling, and obtained after correlation analysis, when generally each second time period needs to include corresponding to predetermined movement data
Between section, can subsequently to accurately determine out the period that the motion state of user specifically occurs, for example, in the default fortune of certain group
Period corresponding to dynamic data is 8：00 to 9：When 00, second time period may be set to 7：30 to 9：30.
Further, in above-mentioned steps S21, above-mentioned setting numerical value can determine according to the actual motion situation of user,
Such as be typically set at 0, i.e., a motion segments are formed by exercise data of the step number more than 0 in continuous multiple predetermined periods,
The exercise data of other parts forms non-athletic fragment.Certainly, above-mentioned setting numerical value can also be set as other numerical value.
For example, using above-mentioned second time period as 7：30 to 9：Exemplified by 30, it is assumed that the above-mentioned numerical value that sets is 0, it is assumed that Yong Hu
7：30 to 8：00 exercise data is as shown in table 1 below：
Table 1
| Cycle | Step number |
| 7：30—7:35 | 0 |
| 7：35—7:40 | 0 |
| 7：40—7:45 | 15 |
| 7：45—7:50 | 17 |
| 7：50—7：55 | 0 |
| 7：55—8：00 | 0 |
| 8：00—8：05 | 20 |
| 8：05—8：10 | 15 |
| 8：15—8：20 | 18 |
| 8：20—8：25 | 0 |
In table 1 above, above-mentioned exercise data can form two motion segments, i.e., and 7：40 to 7：50 this period section composition
One motion segments, 8：00 to 8：20 this period section form another motion segments, the exercise datas of other parts forms non-
Motion segments, i.e., 7：30 to 7：40 this period section form a non-athletic fragment, 7：50 to 8：00 this period section composition one
Individual non-athletic fragment, 8：20 to 8：25 this period section form a non-athletic fragment.
Preferably, in above-mentioned steps S22, for server, specifically it can obtain for the second time by following flows
The each group exercise data to be matched of section：, the motion segments of N number of and N+1 individual to adjacent N-1 in the motion segments selected respectively
It is combined, obtains each group motion segments after the combination of second time period；And by every group of motion segments after combination, it is and every
Non-athletic fragment between group motion segments is combined, and obtains each group exercise data to be matched of second time period.Herein,
N is the motion segments number included by predetermined movement data, and N is the integer more than 2；
That is, it is assumed that the period corresponding to predetermined movement data is 8:00 to 9：00, included motion segments are A
With this 2 motion segments (waveform segment as shown in Fig. 3 (a)) of B；Assuming that second time period (7：30 to 9：30) motion segments are
C, this 4 motion segments (waveform segment as shown in Fig. 3 (b)) of D, E and F, then, it is necessary to this 4 motions by second time period
The motion segments of adjacent 2 and adjacent 3 are combined in fragment, you can obtain each group motion number to be matched of second time period
According to specially：Formed after the exercise data to be matched (waveform segment as shown in Fig. 3 (c)), D and the E combinations that are formed after C and D combinations
Exercise data to be matched (waveform segment as shown in Fig. 3 (d)), exercise data (such as Fig. 3 to be matched for being formed after E and F combinations
(e) waveform segment shown in), the data to be matched (waveform segment as shown in Fig. 3 (f)) that are formed and D, E and F after C, D and E combination
(waveform segment as shown in Fig. 3 (g)) this 5 groups of exercise datas to be matched.
Preferably, in above-mentioned steps S23, server generally use dynamic time consolidation algorithm (Dynamic Time
Warping, DTW), respectively by obtained each group exercise data to be matched, matched with default motion model data, specifically
Matching process be prior art, will not be described in detail herein.
For example, still by taking the period that the preceding paragraph refers to as an example, will actually be formed respectively after C and D combinations to be matched
Exercise data to be matched, C, D and the E formed after the exercise data to be matched, E and the F combinations that are formed after exercise data, D and E combinations
Exercise data to be matched this 5 groups of motions to be matched formed after exercise data and D, E and F to be matched combination formed after combination
Data, matched one by one with predetermined movement data.Assuming that shape after C, D and E are combined is gone out using dynamic time consolidation algorithmic match
Into exercise data to be matched (waveform segment as shown in Fig. 3 (f)) be matching degree highest exercise data, then, C, D and E group
The motion state of the exercise data to be matched formed after conjunction, it is exactly motion state corresponding to predetermined movement data, such as default fortune
Motion state commutes to be early corresponding to dynamic data.
In embodiments of the present invention, for server, it using motion state corresponding to predetermined movement data as
After motion state corresponding to one section of exercise data of matching degree highest, one section of matching degree highest will be removed in first time period respectively
Motion state corresponding to other times section outside period corresponding to exercise data is arranged to predetermined movement state, you can obtains
Each motion state of the user in first time period.
That is, after the motion state of some special time periods is drawn using above-mentioned determination flow, above-mentioned first
In period, motion state is set in advance corresponding to the period in addition to these special time periods, so, Yong Huke
Sign in the specific motion state that oneself is checked on server in certain day, improve Consumer's Experience.
The determination method of above-mentioned user movement state is described in detail with reference to following specific embodiments：
Assuming that server gets some user of portable set collection in certain day (0：00 to 24：00) the motion number in
According to, and 3 groups of exercise datas have been preset, 3 different periods (i.e. 8 are corresponded to respectively：00-9：00、11：00-12：00
With 17：00-18：00), motion state corresponding to difference commutes for early commuting, lunch and evening；Assuming that predetermined period is 5 minutes, if
Fixed number value is 0, then, as shown in figure 4, server needs to perform following step, to complete the determination of the motion state of user：
S41：Current second time section (such as 7 is selected from the exercise data of acquisition：30-9：30, including 8：00-9：00
This period) in exercise data, the motion step number from this section of exercise data of selection in continuous multiple 5 minutes of reselection
The motion segments that exercise data more than 0 is formed；
S42：Individual to adjacent N-1 in the motion segments selected, N number of and N+1 motion segments are combined respectively, are obtained
Each group motion segments after to combination, and by every group of motion segments after combination, with non-athletic between every group of motion segments
After section is combined, current second time section (such as 7 is obtained：30-9：30) each group of this period exercise data to be matched；
Herein, N is the motion segments number included by predetermined movement sequence, and N is the integer more than 2；
S43：By each exercise data to be matched, with the predetermined movement data (such as 8 in the matching library that pre-sets：00-9：
Predetermined movement data corresponding to 00 this period) matched, by motion state corresponding to predetermined movement data (such as 8：
00-9：Early commuted corresponding to 00 this period), as motion state corresponding to one section of exercise data of matching degree highest；
S44：Whether the exercise data for judging to obtain finishes with all predetermined movement Data Matchings；If so, perform step
S45, otherwise, by next second time period (such as 10：30-12：30, including 11：00-12：00 this period) it is used as and works as
Preceding second time period, return to above-mentioned steps S41；
S45：Respectively by its in first time period in addition to the period corresponding to one section of exercise data of matching degree highest
Motion state corresponding to his is arranged to predetermined movement state period, obtains each motion state of the user in first time period.
In above-mentioned flow, server needs 3 above-mentioned flows of execution can be by above-mentioned 3 groups of predetermined movement Data Matchings
Finish, for example, after server performs above-mentioned flow, determine user 0：00 to 24：Motion state such as table 2 below institute in 00
Show.
Table 2
| Period | User movement state |
| 0：00 to 8：00 | (acquiescence) sleeps |
| 8:00 to 9：00 | Early commuting |
| 9：00 to 11：00 | (acquiescence) handles official business |
| 11：00 to 12：00 | Lunch |
| 12：00 to 17：00 | (acquiescence) handles official business |
| 17：00 to 18：00 | Evening commuting |
| 18：00 to 24：00 | (acquiescence) night moves |
Based on same inventive concept, the embodiment of the present invention additionally provides a kind of determining device of user movement state, due to
It is similar to the determination method of foregoing user movement state that the device solves the principle of problem, therefore the implementation of the device can be joined
See the implementation of preceding method, repeat part and repeat no more.
The determining device of a kind of user movement state provided in an embodiment of the present invention, as shown in figure 5, specifically including：
Acquisition module 51, for obtaining exercise data of the user of collecting device collection in default first time period；
Herein, above-mentioned exercise data includes user the motion step number in each predetermined period；
Determining module 52, for the motion step number in the exercise data according to acquisition, selected from the exercise data of acquisition
One section of exercise data, and after being handled by way of variable length piecewise combination the exercise data selected, with default fortune
The exercise data of dynamic data match, by motion state corresponding to predetermined movement data, as matching degree highest, one section is moved
Motion state corresponding to data.
Preferably, above-mentioned determining module 52, specifically for selecting default second time period from the exercise data of acquisition
Interior exercise data, and in the exercise data selected, select to be all higher than by the motion step number in continuous multiple predetermined periods
Set the motion segments that the exercise data of numerical value is formed；Motion segments number according to included by predetermined movement data, to selecting
Motion segments be combined, obtain each group exercise data to be matched of second time period；And obtained each group is treated respectively
Exercise data is matched, is matched with predetermined movement data, second time period includes the period corresponding to predetermined movement data.
Preferably, above-mentioned determining module 52, specifically for individual to adjacent N-1 in the motion segments selected, N number of respectively and
The motion segments of N+1 are combined, and obtain each group motion segments after the combination of second time period；And will be every after combination
Non-athletic fragment between group motion segments, with every group of motion segments is combined, and each group for obtaining second time period is to be matched
Exercise data.Herein, N is to state the motion segments number included by predetermined movement sequence, and N is the integer more than 2.
Preferably, above-mentioned determining module 52, specifically for utilizing dynamic time consolidation algorithm, obtained each group is treated respectively
Exercise data is matched, is matched with default motion model data.
Preferably, above-mentioned determining module 52, it is additionally operable to using motion state corresponding to predetermined movement data as matching degree
After motion state corresponding to one section of exercise data of highest, one section of motion number of matching degree highest will be removed in first time period respectively
Predetermined movement state is arranged to according to motion state corresponding to the other times section outside the corresponding period, obtains user first
Each motion state in period.
Obviously, those skilled in the art can carry out the essence of various changes and modification without departing from the present invention to the present invention
God and scope.So, if these modifications and variations of the present invention belong to the scope of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to including these changes and modification.
Claims (10)
- A kind of 1. determination method of user movement state, it is characterised in that including：Server obtains exercise data of the user of collecting device collection in default first time period, the exercise data bag Include motion step number of the user in each predetermined period；The server selects one section of motion number according to the motion step number in the exercise data of acquisition from the exercise data of acquisition According to, and after being handled by way of variable length piecewise combination the exercise data selected, carried out with predetermined movement data Matching, motion state corresponding to the predetermined movement data is moved as corresponding to one section of exercise data of matching degree highest State.
- 2. the method as described in claim 1, it is characterised in that the server walks according to the motion in the exercise data of acquisition Number, from the exercise data of acquisition select one section of exercise data, and variable length segmentation by way of it is handled after, with Predetermined movement data are matched, and are specifically included：The exercise data in default second time period is selected from the exercise data of acquisition, and in the exercise data selected In, select to be more than the motion piece for setting the exercise data of numerical value and being formed by the motion step number in continuous multiple predetermined periods Section；According to the motion segments number included by the predetermined movement data, the motion segments selected are combined, obtain institute The each group exercise data to be matched of second time period is stated, the second time period includes the time corresponding to the predetermined movement data Section；Respectively by obtained each group exercise data to be matched, matched with the predetermined movement data.
- 3. method as claimed in claim 2, it is characterised in that the server obtains second time by following manner The each group exercise data to be matched of section：Individual to adjacent N-1 in the motion segments selected, N number of and N+1 motion segments are combined the server respectively, The each group motion segments after the combination of the second time period are obtained, wherein, N is the motion included by the predetermined movement data Segments, and N is the integer more than 2；Non-athletic fragment between every group of motion segments after combination, with every group of motion segments is combined, obtains institute State each group exercise data to be matched of second time period.
- 4. method as claimed in claim 2, it is characterised in that the server by utilizing dynamic time consolidation algorithm, respectively will Obtained each group exercise data to be matched, is matched with the default exercise data.
- 5. such as the method any one of claim 1-4, it is characterised in that also include：The server is using motion state corresponding to the predetermined movement data as one section of exercise data of matching degree highest After corresponding motion state, the period corresponding to one section of exercise data of matching degree highest will be removed in the first time period respectively Outside other times section corresponding to motion state, be arranged to predetermined movement state, obtain the user in the very first time Each motion state in section.
- A kind of 6. determining device of user movement state, it is characterised in that including：Acquisition module, for obtaining exercise data of the user of collecting device collection in default first time period, the fortune Dynamic data include the user motion step number in each predetermined period；Determining module, for the motion step number in the exercise data according to acquisition, one section of fortune is selected from the exercise data of acquisition Dynamic data, and after being handled by way of variable length piecewise combination the exercise data selected, with predetermined movement data Matched, by motion state corresponding to the predetermined movement data, as corresponding to one section of exercise data of matching degree highest Motion state.
- 7. device as claimed in claim 6, it is characterised in that the determining module, specifically for the exercise data from acquisition Exercise data in the middle default second time period of selection, and in the exercise data selected, select by continuous multiple described Motion step number in predetermined period is all higher than setting the motion segments that the exercise data of numerical value is formed；According to the predetermined movement number According to included motion segments number, the motion segments selected are combined, each group for obtaining the second time period is treated With exercise data；And respectively matched obtained each group exercise data to be matched with the predetermined movement data, it is described Second time period includes the period corresponding to the predetermined movement data.
- 8. device as claimed in claim 7, it is characterised in that the determining module, specifically for the fortune to selecting respectively The motion segments that adjacent N-1 is individual in moving plate section, N number of and N+1 is individual are combined, and are obtained each after the combination of the second time period Group motion segments；And the non-athletic fragment between every group of motion segments after combination, with every group of motion segments is carried out Combination, obtains each group exercise data to be matched of the second time period, wherein, N is included by the predetermined movement data Motion segments number, and N is the integer more than 2.
- 9. device as claimed in claim 7, it is characterised in that the determining module, specifically for utilizing dynamic time consolidation Algorithm, respectively by obtained each group exercise data to be matched, matched with the default exercise data.
- 10. such as the device any one of claim 6-9, it is characterised in that the determining module, be additionally operable to by described in After motion state corresponding to predetermined movement data is as motion state corresponding to one section of exercise data of matching degree highest, respectively will Corresponding to other times section in the first time period in addition to the period corresponding to one section of exercise data of matching degree highest Motion state, predetermined movement state is arranged to, obtains each motion state of the user in the first time period.
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| CN106681997B (en) * | 2015-11-05 | 2020-09-08 | ***通信集团公司 | Information processing method and device |
| CN106200976A (en) * | 2016-07-19 | 2016-12-07 | 深圳市金立通信设备有限公司 | A kind of motion-activated method and terminal |
| CN107908497B (en) * | 2017-11-28 | 2021-08-31 | 广东乐心医疗电子股份有限公司 | Step frequency calculation method and device and wearable device |
| CN111166345A (en) * | 2020-02-13 | 2020-05-19 | 上海幂方电子科技有限公司 | Three-dimensional motion detection method, device and equipment and readable storage medium |
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