CN110006445A - Running distance calculating method and device - Google Patents
Running distance calculating method and device Download PDFInfo
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- CN110006445A CN110006445A CN201910344789.5A CN201910344789A CN110006445A CN 110006445 A CN110006445 A CN 110006445A CN 201910344789 A CN201910344789 A CN 201910344789A CN 110006445 A CN110006445 A CN 110006445A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
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Abstract
The present invention relates to wearable device technical fields, and in particular to a kind of running distance calculating method and device are applied in wearable device, while being provided with acceierometer sensor in the wearable device.Specially, receive the user movement data of acceierometer sensor acquisition, it analyzes to obtain the first user movement feature and second user motion feature based on user movement data, wherein the first user movement feature is the installation site of wearable device, second user motion feature is user's running state, and then user's running distance can be calculated to the first user movement feature and second user motion feature according to predetermined regression model.This programme is based on sensor and detects exercise data, and is calculated according to algorithm, independent of communication equipment, is suitable for each scene, has stronger practicability.
Description
Technical field
The present invention relates to wearable device technical fields, in particular to a kind of running distance calculating method and device.
Background technique
With the continuous progress of science and technology, people can monitor the exercise data of oneself with many electronic equipments, and pass through
These data analyze oneself motion state, wherein running distance is an important data.It is main to calculate running distance
There is the method based on GPS, distance, but this are calculated using the change of the mobile front and back GPS coordinate of runner based on the method for GPS
Kind mode is to environmental requirement height, once signal is disturbed to will lead to result inaccuracy.
But the running distance calculating method based on GPS has been widely used in mobile phone, and in the equipment such as sports watch, the party
Method requires equipment to have a GPS communication module, is communicated in real time with satellite, obtains the geographical coordinate of current location, and
Running distance is found out by corresponding algorithm.It is higher to demand on signal quality based on the calculation method of GPS from experience,
Usage scenario is restricted.
Summary of the invention
The purpose of the present invention is to provide a kind of running distance calculating methods, do not depend on communication equipment, at low cost, can be with
It is used in any scene.
To achieve the goals above, technical solution used in the embodiment of the present invention is as follows:
In a first aspect, it is applied to wearable device the embodiment of the invention provides a kind of running distance calculating method, it is described to wear
It wears and is provided with acceierometer sensor in equipment, which comprises receive user's fortune of the acceierometer sensor acquisition
Dynamic data；Analyze to obtain the first user movement feature and second user motion feature based on the user movement data, described
One user movement feature is the installation site of the wearable device, and the second user motion feature is user's running state；It presses
User's running distance is calculated to the first user movement feature and second user motion feature according to predetermined regression model.
Second aspect, the embodiment of the invention also provides a kind of runnings apart from computing device, is applied to wearable device, described
Acceierometer sensor is provided in wearable device, described device includes: transceiver module, for receiving the accelerometer sensing
The user movement data of device acquisition；Processing module obtains the first user movement spy for analyzing based on the user movement data
Second user of seeking peace motion feature, the first user movement feature are the installation site of the wearable device, and described second uses
Family motion feature is user's running state；The processing module is also used to according to predetermined regression model to first user movement
User's running distance is calculated in feature and second user motion feature.
A kind of running distance calculating method and device provided in an embodiment of the present invention are applied in wearable device, simultaneously
Acceierometer sensor is provided in the wearable device.Specifically, the user movement data of acceierometer sensor acquisition are received,
It analyzes to obtain the first user movement feature and second user motion feature based on user movement data, wherein the first user movement is special
Sign is the installation site of wearable device, and second user motion feature is user's running state, and then can be according to predetermined regression model
User's running distance is calculated to the first user movement feature and second user motion feature.This programme is detected based on sensor
Exercise data, and be calculated according to algorithm, independent of communication equipment, it is suitable for each scene, there is stronger practicability.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperate
Appended attached drawing, is described in detail below.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 shows a kind of flow diagram of distance calculating method of running provided in an embodiment of the present invention.
Fig. 2 shows a kind of waveform diagram schematic diagrames provided in an embodiment of the present invention.
Fig. 3 shows a kind of the functional block diagram of the running provided in an embodiment of the present invention apart from computing device.
Diagram: 200- runs apart from computing device；210- transceiver module；220- processing module.
Specific embodiment
Below in conjunction with attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Usually exist
The component of the embodiment of the present invention described and illustrated in attached drawing can be arranged and be designed with a variety of different configurations herein.Cause
This, is not intended to limit claimed invention to the detailed description of the embodiment of the present invention provided in the accompanying drawings below
Range, but it is merely representative of selected embodiment of the invention.Based on the embodiment of the present invention, those skilled in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need that it is further defined and explained in subsequent attached drawing.Meanwhile of the invention
In description, term " first ", " second " etc. are only used for distinguishing description, are not understood to indicate or imply relative importance.
One wearable device need to be tied on vamp when in the present solution, user is in running, include place in the wearable device
Chip and acceierometer sensor are managed, the acceleration information during acceierometer sensor runs real-time acquisition user is sent out
It send to processing chip, processing chip handles acceleration information to obtain the running distance of user, and can be transmitted to and wear with this
It wears and is shown in user on the bracelet or the electronic equipments such as mobile phone of equipment connection and checks.This programme is based on acceierometer sensor
User movement data are detected, and feature extraction are carried out to user movement data based on built-in algorithm and apart from calculating,
Independent of communication module, cost is lower, can be generally applicable to more scenes, improve practicability.
Fig. 1 is please referred to, is a kind of flow diagram of distance calculating method of running provided in an embodiment of the present invention, this method
Include:
S110 receives the user movement data of acceierometer sensor acquisition.
Specifically, the acceierometer sensor will acquire the user movement data during user runs, the user movement
Data include that travelling forward during user's running and moves upwards acceleration information at acceleration information, for the ease of saying
Bright, the acceleration information that will travel forward is indicated with x, and will move upwards acceleration information is indicated with z.
Further, the user movement data which will test are sent to the place in wearable device
It manages chip and carries out data processing.
The processing chip will to it is received travel forward acceleration information and move upwards acceleration information carry out it is flat
Sliding filtering, to eliminate the noise in user movement data.This carries out the concrete mode of smothing filtering to data are as follows:
Wherein, N value be 8, also i other words, after every 8 acceleration informations that travel forward take mean value to obtain smothing filtering
Travel forward acceleration, while every 8 move upwards and move upwards acceleration after acceleration information takes mean value to obtain smothing filtering
Degree evidence.Readily comprehensible, the value of the N can be configured according to actual needs.
S120 analyzes to obtain the first user movement feature and second user motion feature based on user movement data, this
One user movement feature is the installation site of wearable device, and second user motion feature is user's running state.
Firstly, analyzing to obtain the first user movement feature based on user movement data.
Specifically, the first user movement feature is the installation site of wearable device, user is by wearable device with different
Tilt angle be installed on vamp by will affect collect move upwards acceleration information and travel forward and accelerate degree
According to, therefore it needs to be determined that the installation site of wearable device is the first user movement feature.Due to wearable device installation site be from
Dissipate type variable, and then this programme characterizes the setting angle of wearable device by dummy variable, respectively by two dummy variable x1 and
X2 is indicated.The initial value range for moving upwards acceleration information and corresponding dummy variable are prefixed in the processing chip,
As when moving upwards acceleration information at [0,300], x1 value is that 1, x2 value is 0；When move upwards acceleration information (300,
When 600], x1 value is that 0, x2 value is 1；When move upwards acceleration information (600,1000] when, x1 value is that 0, x2 value is 0.
Further, the specific value for moving upwards acceleration information in initial predetermined step number is calculated, can such as be calculated initial
User moves upwards the specific value of acceleration information in two steps (i.e. using the data acquired in two steps as foundation), and determines the tool
Which initial value range at volume data, and then determine the corresponding dummy variable numerical value of initial value range locating for specific value
For the first user movement feature.Such as move upwards acceleration information specific value be 200, then fall within initial value range [0,
300] in, and then choose the corresponding dummy variable x1 of the initial value range be 1, x2 be 0 conduct the first user movement feature, the mute change
Amount can characterize the setting angle that user currently wears wearable device.
In turn, it analyzes to obtain second user motion feature based on user movement data.
Specifically, the second user motion feature is user's running state, user running state specifically includes user's race
Stride degree and user's running speed.Second user motion feature calculation are as follows:
Firstly, acceleration information and moving upwards acceleration information to travelling forward in predetermined step number and merge
To two fused datas.
Travelling forward after smothing filtering and is moved upwards by acceleration information is melted two-by-two acceleration information
Conjunction processing travels forward acceleration information and moves upwards the spy of acceleration information so that the fused data finally obtained is taken into account
Sign.The fused data passes through miIt is indicated, amalgamation mode are as follows:
mi=zi-xi
Secondly, carrying out waveforms detection to multiple fused datas obtains multiple wave crest data and trough data.
As shown in Fig. 2, being a kind of waveform diagram schematic diagram provided in an embodiment of the present invention, which characterizes according to multiple fusion numbers
According to progress waveforms detection as a result, the waveform diagram is the exercise data drafting according to acquisition two step of user as a result, abscissa table
It levies the time, ordinate characterizes acceleration, and wherein p1, p2 and p3 are the wave crest data and trough data chosen.
Finally, to multiple wave crests and trough data carrying out that second user motion feature is calculated according to pre-defined rule.
The second user motion feature includes two aspects, respectively family running amplitude and user's running speed.
Wherein, the calculation of user's running amplitude are as follows:
x3=(| m [p3]-m [p2] |+| m [p1]-m [p2] |)/23000
The ordinate of p1, p2 and p3 are brought into the formula, x3 is calculated, x3 characterizes user's running amplitude.
The calculation of speed in addition, user runs are as follows:
x4=(p3-p1)/60
The abscissa of p1 and p3 is brought into and x4 is calculated by the formula, and x4 characterizes user's running speed.
Therefore, processing chip is based on analyzing user movement data, finally obtained x1, x2, x3 and x4 tetra-
User movement feature, x1 and x2 are the first user movement feature for characterizing wearable device installation condition, and x3 and x4 are characterization user
The second user motion feature of motion state.
User is calculated to the first user movement feature and second user motion feature according to predetermined regression model in S130
Running distance.
The predetermined regression model is that training obtains, the method for training are as follows:
Acquire a large number of users running during user movement data sample, each user movement data sample include to
Upper moving acceleration data and the acceleration information that travels forward, according to above-mentioned same method to upward moving acceleration data
And the acceleration information that travels forward carries out smothing filtering, data fusion, waveforms detection, feature calculation and determines that the first user transports
Dynamic feature and second user motion feature, and bring the first user movement feature and second user motion feature into initial recurrence
Model is calculated, and will export initial user's running distance at this time.Although by a large amount of sample training, this is first
The user of beginning runs apart from still having gap with actual running distance, in order to guarantee the precision of prediction of regression model, this programme
Also initial regression model is improved, that is, compensates for the calculating error of regression model.The loss function of its linear regression are as follows:
Wherein hθ(x)=θTX is the expression of regression model.For the minimization problem (error minimum) of J (θ), need using
Gradient descent method solves, the iterative formula of θ:
After finding out optimal model parameter θ by iteration, parameter and the first user movement feature and second user are moved
Feature multiplication can find out running distance, can be modified in this way to initial regression model, so that training
Obtained predetermined regression model can accurately calculate running distance.
In turn, during user runs, the first user movement feature and second user are transported using predetermined regression model
The mode of dynamic feature calculation running distance are as follows: directly trained the first user movement feature and the input of second user motion feature
User's running distance can be obtained in complete predetermined regression model.It should be noted that since this programme early period is to user movement number
According to processing using with every two step for a unit, so when the user that is calculated by model distance of running also be user
The running distance of two steps, it is readily appreciated that, for the ease of operation, can also directly as unit of a step or multistep be unit into
Row analysis ranging.Finally, user can be obtained entirely running process user that each stage the obtains accumulative summation of distance of running
In total running distance.
In addition, detection data is likely to occur noise to acceierometer sensor during user movement or other are unstable
Factor, and then the user being finally calculated is caused to run apart from exception, in order to prevent this situation, also depositing in the processing chip
Contain the default stride table of comparisons.And then when processing chip be calculated user run distance after, by user run distance with preset
The stride table of comparisons is compared, if user runs, distance is greater than threshold value with corresponding stride difference in the default stride table of comparisons,
It is believed that and calculates error, and then user's running distance is replaced with the stride preset in the stride table of comparisons.
The default stride table of comparisons is determined according to the height and speed of user, and is prestored and be stored in processing chip, should
The step number of user movement data analysis is consistent in stride length and calculation method in the default stride table of comparisons, is such as calculated
It is using every two step as standard to user movement data in method, then the stride preset in the stride table of comparisons corresponds to the two of the user
Step-length degree.
In practical applications, user only needs for wearable device to be configured on vamp before running, adding in the wearable device
Speedometer transducer will measure the user movement data during user runs, and the processing core being sent in wearable device in real time
Piece, processing chip by according to above-mentioned method flow to received user movement data handled to obtain the total running of user away from
From, and then the total running distance of user is directly shown on wearable device, or be sent to its connecting with wearable device
He shows electronic equipment (such as bracelet, mobile phone).The program does not need additional communication module, can be real based on built-in algorithm
It is existing, while guaranteeing precision, it can be widely applied to different scenes.
It referring to figure 3., is a kind of functional module signal of the running provided in an embodiment of the present invention apart from computing device 200
Figure, which includes transceiver module 210 and processing module 220.
Transceiver module 210, for receiving the user movement data of acceierometer sensor acquisition.
In embodiments of the present invention, S110 can be executed by transceiver module 210.
Processing module 220 obtains the first user movement feature and second user fortune for analyzing based on user movement data
Dynamic feature, the first user movement feature are the installation site of wearable device, and second user motion feature is user's running state.
In embodiments of the present invention, S120 can be executed by processing module 220.
Processing module 220 is also used to according to predetermined regression model to the first user movement feature and second user motion feature
User's running distance is calculated.
In embodiments of the present invention, S130 can be executed by processing module 220.
Due to having been described in running distance calculating method part, details are not described herein.
In conclusion a kind of running distance calculating method provided in an embodiment of the present invention and device, are applied to wearing and set
In standby, while acceierometer sensor is provided in the wearable device.Specifically, receiving the user of acceierometer sensor acquisition
Exercise data is analyzed to obtain the first user movement feature and second user motion feature based on user movement data, wherein first
User movement feature is the installation site of wearable device, and second user motion feature is user's running state, and then can be according to pre-
Determine regression model and user's running distance is calculated to the first user movement feature and second user motion feature.This programme is based on
Sensor detects exercise data, and is calculated according to algorithm, independent of communication equipment, is suitable for each scene, have compared with
Strong practicability.
In several embodiments provided herein, it should be understood that disclosed device and method can also pass through
Other modes are realized.The apparatus embodiments described above are merely exemplary, for example, flow chart and block diagram in attached drawing
Show the device of multiple embodiments according to the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.In this regard, each box in flowchart or block diagram can represent the one of a module, section or code
Part, a part of the module, section or code, which includes that one or more is for implementing the specified logical function, to be held
Row instruction.It should also be noted that function marked in the box can also be to be different from some implementations as replacement
The sequence marked in attached drawing occurs.For example, two continuous boxes can actually be basically executed in parallel, they are sometimes
It can execute in the opposite order, this depends on the function involved.It is also noted that every in block diagram and or flow chart
The combination of box in a box and block diagram and or flow chart can use the dedicated base for executing defined function or movement
It realizes, or can realize using a combination of dedicated hardware and computer instructions in the system of hardware.
In addition, each functional module in each embodiment of the present invention can integrate one independent portion of formation together
Point, it is also possible to modules individualism, an independent part can also be integrated to form with two or more modules.
It, can be with if the function is realized and when sold or used as an independent product in the form of software function module
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to an entity or behaviour
Make with another entity or operate distinguish, without necessarily requiring or implying between these entities or operation there are it is any this
The actual relationship of kind or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to nonexcludability
Include so that include a series of elements process, method, article or equipment not only include those elements, but also
Including other elements that are not explicitly listed, or further include for this process, method, article or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method, article or equipment of element.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.It should also be noted that similar label and letter exist
Similar terms are indicated in following attached drawing, therefore, once being defined in a certain Xiang Yi attached drawing, are then not required in subsequent attached drawing
It is further defined and explained.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of running distance calculating method is applied to wearable device, is provided with acceierometer sensor in the wearable device,
It is characterized in that, which comprises
Receive the user movement data of the acceierometer sensor acquisition；
It analyzes to obtain the first user movement feature and second user motion feature based on the user movement data, described first uses
Family motion feature is the installation site of the wearable device, and the second user motion feature is user's running state；
User's running is calculated to the first user movement feature and second user motion feature according to predetermined regression model
Distance.
2. the method as described in claim 1, which is characterized in that the user movement data include user running during to
Upper moving acceleration data；
It is described based on the user movement data analyze the step of obtaining the first user movement feature include: be chosen at it is initial predetermined
The corresponding dummy variable numerical value of preset range locating for acceleration information is moved upwards described in step number to transport as first user
Dynamic feature, the preset range and dummy variable numerical value correspond.
3. the method as described in claim 1, which is characterized in that the user movement data include user running during to
Preceding moving acceleration data and acceleration information is moved upwards,
It is described to analyze the step of obtaining second user motion feature based on the user movement data and include:
To travel forward described in predetermined step number acceleration information and move upwards acceleration information merged to obtain it is more
A fused data；
Waveforms detection is carried out to the multiple fused data and obtains multiple wave crests and trough data；
The multiple wave crest and trough data are carried out according to pre-defined rule the second user motion feature is calculated.
4. the method as described in claim 1, which is characterized in that the method also includes:
User running distance is compared with the default stride table of comparisons, distance and the default step if the user runs
Stride difference in the width table of comparisons is greater than threshold value, then the stride selected in the default stride table of comparisons is run instead of the user
Distance, the default stride table of comparisons are determined according to the height and speed of user.
5. the method as described in claim 1, which is characterized in that the method also includes:
The user that each stage obtains is run and obtains total running distance during user's running apart from accumulative summation.
6. the method as described in claim 1, which is characterized in that the user's fortune for receiving the acceierometer sensor acquisition
It is further comprised the steps of: after dynamic data
Smothing filtering is carried out to the user movement data.
7. a kind of running is applied to wearable device, is provided with acceierometer sensor in the wearable device apart from computing device,
It is characterized in that, described device includes:
Transceiver module, for receiving the user movement data of the acceierometer sensor acquisition；
Processing module obtains the first user movement feature and second user movement spy for analyzing based on the user movement data
Sign, the first user movement feature are the installation site of the wearable device, and the second user motion feature is user's race
Step state；
The processing module is also used to move the first user movement feature and second user according to predetermined regression model special
User's running distance is calculated in sign.
8. device as claimed in claim 7, which is characterized in that the user movement data include user running during to
Upper moving acceleration data,
The processing module is specifically used for:
It is chosen at described in initial predetermined step number and moves upwards the corresponding dummy variable numerical value of preset range locating for acceleration information
As the first user movement feature, the preset range and dummy variable numerical value are corresponded.
9. device as claimed in claim 7, which is characterized in that the user movement data include user running during to
Preceding moving acceleration data and acceleration information is moved upwards,
The processing module is specifically used for:
To travel forward described in predetermined step number acceleration information and move upwards acceleration information merged to obtain it is more
A fused data；
Waveforms detection is carried out to the multiple fused data and obtains multiple wave crests and trough data；
The multiple wave crest and trough data are carried out according to pre-defined rule the second user motion feature is calculated.
10. device as claimed in claim 7, which is characterized in that the processing module is also used to:
User running distance is compared with the default stride table of comparisons, distance and the default step if the user runs
Stride difference in the width table of comparisons is greater than threshold value, then the stride selected in the default stride table of comparisons is run instead of the user
Distance, the default stride table of comparisons are determined according to the height and speed of user.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110595502A (en) * | 2019-10-23 | 2019-12-20 | 成都乐动信息技术有限公司 | Running distance estimation method and device |
| CN112308171A (en) * | 2020-11-23 | 2021-02-02 | 浙江天行健智能科技有限公司 | Vehicle position prediction modeling method based on simulated driver |
| CN113810845A (en) * | 2021-09-17 | 2021-12-17 | 广州悦跑信息科技有限公司 | Effective running distance statistical method and system based on multi-angle monitoring |
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