CN107289966A - Method and apparatus for counting step number - Google Patents
Method and apparatus for counting step number Download PDFInfo
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- CN107289966A CN107289966A CN201610190802.2A CN201610190802A CN107289966A CN 107289966 A CN107289966 A CN 107289966A CN 201610190802 A CN201610190802 A CN 201610190802A CN 107289966 A CN107289966 A CN 107289966A
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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
- G01C22/006—Pedometers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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Abstract
Present disclose provides a kind of method and apparatus for counting step number.This method includes:(a) the first step number is calculated based on the data from first sensor;(b) the second step number is calculated based on the data from second sensor;And (c) calculates final step number according to the first sensor and the respective confidence level of the second sensor based on first step number and second step number.The equipment includes:First step number computing unit, for calculating the first step number based on the data from first sensor;Second step number computing unit, for calculating the second step number based on the data from second sensor;And final step number computing unit, for according to the first sensor and the respective confidence level of the second sensor, final step number to be calculated based on first step number and second step number.
Description
Technical field
This disclosure relates to electronics field, more particularly relate to count step number method and
Equipment.
Background technology
With the popularization of health idea, health is increasingly valued by people, and is walked and run
Step also turns into the simple effective motion mode that people like.In this motion, people
Most important demand be easily to allow oneself know how many step walked, disappear so as to extrapolate oneself
How many energy consumed.
Current step-recording method is related to mostly carries out meter step information system to the acceleration information collected
Meter.However, meter step is carried out using accelerometer data can cause problems with:Due to accelerating
Degree meter has steady-state characteristic, therefore when people carry accelerometer progress uniform motion, according to
The data of accelerometer can count step count information;But people can not possibly be all the time in motion
Stable uniform motion is kept, therefore in the speed-change process of motion, is counted by accelerometer
The step count information gone out is often less accurate.
In addition, also there is the scheme for carrying out counting step using gyro data.But based on gyro
There is problems with the scheme of instrument:Because meter step equipment is generally worn on hand, gyroscope is utilized
Arm cycle swings the characteristic for the angle change brought, but people when meter step is generally basede on people's motion
Action during motion on hand is different, and somebody gets used to both hands being placed on pocket in motion
In do not swing, now the degree of periodicity for the signal that the gyroscope on arm is collected is poor,
Therefore meter step result is also not accurate enough.
The content of the invention
In order to solve the above problems there is provided according to the disclosure be used for count step number method and
Equipment.
According to the first aspect of the disclosure, there is provided a kind of method for counting step number.The party
Method includes:(a) the first step number is calculated based on the data from first sensor;(b) it is based on
Data from second sensor calculate the second step number;And (c) is according to the described first sensing
Device and the respective confidence level of the second sensor, based on first step number and the second step
Count to calculate final step number.
In certain embodiments, the first sensor is accelerometer, and described second passes
Sensor is gyroscope.In certain embodiments, the confidence level be according to respective sensor across
The standard deviation that is consumed during step is determined.In certain embodiments, the standard deviation consumed when striding is root
Determined according to below equation:
Wherein, step_len_std represents the standard deviation consumed when striding of respective sensor,
Step_len (i) represents being consumed when striding for the i-th step, step_lenavgWhat expression n consumed when striding is averaged
Value, and n is natural number.In certain embodiments, the confidence level of the first sensor and described
The confidence level of second sensor is calculated according to below equation respectively:
Wherein, Cred1Represent the confidence level of the first sensor, Cred2Represent described second
The confidence level of sensor, step_len_std1The standard deviation consumed when striding of first sensor is represented,
And step_len_std2Represent the standard deviation consumed when striding of second sensor.In some embodiments
In, the final step number is calculated based on below equation:The step number of final step number=first ×
The confidence level of the step number of confidence level+the second × second sensor of first sensor.
In addition, according to the second aspect of the disclosure, there is provided a kind of equipment for counting step number.
The equipment includes:First step number computing unit, for based on the data from first sensor come
Calculate the first step number;Second step number computing unit, for based on the data from second sensor
To calculate the second step number;And final step number computing unit, for according to the first sensor
With the respective confidence level of the second sensor, based on first step number and second step number
To calculate final step number.
In certain embodiments, the confidence level is the mark consumed when striding according to respective sensor
Quasi- difference is determined, and the standard deviation consumed when striding determines according to below equation:
Wherein, step_len_std represents the standard deviation consumed when striding of respective sensor,
Step_len (i) represents being consumed when striding for the i-th step, step_lenavgWhat expression n consumed when striding is averaged
Value, and n is natural number.In certain embodiments, the confidence level of the first sensor and described
The confidence level of second sensor is calculated according to below equation respectively:
Wherein, Cred1Represent the confidence level of the first sensor, Cred2Represent described second
The confidence level of sensor, step_len_std1The standard deviation consumed when striding of first sensor is represented,
And step_len_std2Represent the standard deviation consumed when striding of second sensor.In some embodiments
In, the final step number is calculated based on below equation:The step number of final step number=first ×
The confidence level of the step number of confidence level+the second × second sensor of first sensor.
By using the method and apparatus for counting step number of the embodiment of the present disclosure, it can pass through
Fusion to a variety of meter step datas (for example, accelerometer data and gyro data), is improved
Meter step precision, enhancing meter step algorithm expands step counting system to difference to the adaptability of different crowd
The coverage rate of crowd.
Brief description of the drawings
By illustrating preferred embodiment of the present disclosure below in conjunction with the accompanying drawings, the above-mentioned of the disclosure will be made
And other objects, features and advantages are clearer, wherein:
Fig. 1 is the exemplary hardware configuration for showing the meter step equipment according to the first embodiment of the present disclosure
Block diagram.
Fig. 2 is the example flow diagram for showing the step-recording method according to the first embodiment of the present disclosure.
Fig. 3~5 are to show that the part in method shown in Fig. 1 for accelerometer data is handled
Example flow diagram.
Fig. 6~8 are to show showing for the part processing that gyro data is directed in method shown in Fig. 1
Example flow chart.
Fig. 9 is to show the universal method for being used to count step number according to the second embodiment of the present disclosure
Example flow diagram.
Figure 10 is shown according to the second embodiment of the present disclosure for performing method shown in Fig. 9
The block diagram of each illustrative functions unit of meter step equipment.
Embodiment
It is understood in advance that:Although the reality of one or more other embodiments of the present disclosure is provided below
It is existing, but any technology can essentially be used (either currently known is still existing)
To realize disclosed equipment and/or method.The disclosure should not be limited in any way by following theory
Bright illustrative realization including example design shown and described herein and including realizing, accompanying drawing
And technology, but this public affairs can be changed in the range of appended claims and its equivalent thing
Open.
Further it is to be noted that:Although describing some specific embodiments below, these are not represented
Specific embodiment is the minimum/optimal case for realizing the disclosure.In other words, these realities can be used
The some technical characteristics in example are applied as a complete technical scheme, it would however also be possible to employ these realities
Apply the skill that other unaccounted of equal value, replacements, alternative technique feature are combined with the disclosure in example
Art scheme is used as a complete technical scheme.Therefore, the protection domain of the disclosure is not limited to this
A little specific embodiments, but covering those skilled in the art can make according to the training centre of the disclosure
Various modifications, replacement, addition, deletion etc..
Before formally description embodiment of the disclosure, hereinafter may it will introduce first
The term used.These terms are used to help those skilled in the art's scheme of this disclosure and carried out
Comprehensive and thorough explanation.Therefore, unless context separately clear stipulaties, otherwise term should
It is identical with the implication that those skilled in the art usually understand, without should too stick to its word
Look like or excessively understood in face.
MEMS(Micro-ElectroMechanical Systems):MEMS sensor is to adopt
The novel sensor manufactured with microelectronics and micromachining technology.With traditional sensors phase
Than it has, and small volume, lightweight, cost are low, low in energy consumption, reliability is high, suitable for batch
Metaplasia produces, is easily integrated and realizes intelligentized feature.Meanwhile, the characteristic size of micron dimension
It is allowd to complete the irrealizable function of some tradition machinery sensor institutes.
Step number is detected:According to human body motion feature, motion step number detection is realized using software algorithm
Method.
Gait:Refer to the mode of human body walking, be a kind of complicated behavioural characteristic, through studying human body
Gait have stronger individual monopolizing characteristic.
Stride and take or consumed when striding:Typically refer to the time consumed across a step.
As described above, the step number statistical project based on accelerometer is usually directed to following operation.It is first
First, it is necessary to gather acceleration magnitude by acceierometer sensor.For example, user wears
When pedometer with acceierometer sensor carries out road-work, the 3-axis acceleration of pedometer
Sensor can export the acceleration in three mutually perpendicular directions, if its be respectively X-axis acceleration,
Y-axis acceleration and Z axis acceleration.Generally, X-axis, the Y-axis of identical quantity are gathered
With Z axis acceleration information, if collection data bulk be N1It is individual.
Then, calculating benchmark axle is selected according to each acceleration information.For example, to collection
X-axis, Y-axis, the N on Z axis1Individual acceleration value calculates the average value of its acceleration respectively,
And axle of the selection with maximum average value is used as calculating benchmark axle.Next, to each acceleration
Data carry out real-time digital filtering.Specifically, the continuous N exported for calculating benchmark axle2It is individual to add
Speed values, are exported after being averaged as filtered acceleration value.Then,
The effective acceleration numerical value for filtering output is stored to N3In individual register.If N3Individual deposit
Device is full, then for example can delete the acceleration value of oldest stored, to store newest add
Speed values.Then, N is found out3The maximum max of the acceleration stored in individual register
With minimum value min, real-time dynamic threshold is obtained using formula dyn_threshold=(max+min)/2
Value dyn_threshold.
Next, most freshly harvested filtering post-acceleration numerical value and the acceleration number of degrees of last collection
Value makes the difference, and judges whether the absolute value of difference is more than predefined precision precision, its
In, precision > 0.If greater than predefined precision, then next step is performed;If less than
Or equal to predefined precision, then show that the acceleration value according to this output is not enough to judgement and made
Whether user has effectively stepped a step, performs Real-Time Filtering.Then, most freshly harvested filter is judged
Whether ripple post-acceleration numerical value is more than real-time dynamic threshold.If greater than real-time dynamic threshold, then
Judge whether most freshly harvested filtering post-acceleration numerical value is more than the last acceleration value gathered
Set up.If set up, show the slope of now accelerating curve for just, it is possible to determine that to use
Person has effectively stepped a step.If invalid, the slope for showing now accelerating curve is
Negative, undecidable user has effectively stepped a step.If accelerated after most freshly harvested filtering
Number of degrees value is less than or equal to real-time dynamic threshold, then is cast out.
However, because accelerometer has steady-state characteristic, when people's carrying accelerometer progress is even
During speed motion, step count information can be relatively accurately counted according to the data of accelerometer.But people
Can not possibly remain stable uniform motion in motion, therefore in the speed-change process of motion
In, the step count information counted by accelerometer is less accurate.
In view of accelerometer there is good steady-state characteristic and measured value change over time it is minimum, but
It is small by external disturbance easily by external disturbance, and in view of gyroscope has high dynamic characteristic, but
Measured value is changed over time greatly, therefore in embodiment of the disclosure, can by accelerometer and
The advantage and disadvantage of gyroscope are complementary.In other words, both can be carried out into data with appropriate mode to melt
Close, the step precision in terms of effectively improving, expand the universality of meter step equipment.More generally, it is right
In a variety of (for example, 2 kinds or two or more) meter step mode with different qualities, Ke Yigen
Their meter step data is merged according to appropriate mode, the step precision in terms of improving.
For example, in the speed-change process of motion (running of/being walked with vigorous strides/for example, taking a walk), according to top
The high dynamic characteristic of spiral shell instrument, the data for having merged gyroscope can accurate statistics step count information.
And during motion (/ walking with vigorous strides/to run for example, taking a walk), when the swing form and leg of arm
(such as somebody gets used to both hands being placed on mouth in motion when the swing form in portion is less consistent
Do not swung in bag), now the degree of periodicity for the signal that the gyroscope on arm is collected compares
Difference, but the data of fusion accelerometer can accurate statistics step count information.By to accelerating
Degree counts the fusion with gyro data, improves meter step precision, enhancing meter step algorithm is to difference
The adaptability of crowd, expands coverage rate of the step counting system to different crowd.
Hereinafter, be described in detail Fig. 1~8 are combined according to the disclosure some embodiments be used for will
The compound step-recording method that accelerometer data and gyro data are merged.
Fig. 1 is the example arrangement for showing the meter step equipment 100 according to the first embodiment of the present disclosure
Block diagram.In the example illustrated in figure 1, meter step equipment 100 can include processor 110, deposit
Reservoir 120, acceierometer sensor 130 and gyro sensor 140.As shown in figure 1, this
A little components can be communicated with one another by bus 150.However, disclosure not limited to this, actually
Can be with direct communication, and without bus 150 between part or all of component.For example, storage
Device 120, acceierometer sensor 130 and gyro sensor 140 can be with processors 110
It is joined directly together (for example, respective pin and lead for being provided via processor 110).However, being
The convenience of explanation and directly perceived, still by taking Fig. 1 as an example.
More specifically, meter step equipment 100 can be mobile device, can also such as mobile phone
It is wearable device, such as Intelligent bracelet, intelligent glasses, intelligent headband, intelligent shoe.Its
Any particular form can be used according to the need for user.In addition, in some alternative implementations
In example, meter step equipment 100 can also not include acceierometer sensor 130 and gyroscope biography
The equipment of sensor 140.For example, it can be desktop computer, laptop computer, flat board
Computer, base station, set top box etc..Although itself not having the biography of detection user movement data
Sensor (for example, acceierometer sensor 130 and/or gyro sensor 140), it can be with
Corresponding data is received by the motion sensor carried with from user, and carried out according to the disclosure
The compound meter step work of embodiment.As long as that is, resulting in the above-mentioned motion number of user
According to (including but not limited to:Gyro data and/or acceleration information etc.), any electronic equipment
Equipment 100 can be walked as the meter of the embodiment of the present disclosure.
The processor 110 of meter step equipment 100 can be general processor, such as CPU (centers
Processing unit), microprocessor, microcontroller (MCU) etc., it can also be dedicated processes
Device, such as field programmable gate array (FPGA), application specific integrated circuit (ASIC).This
Outside, it can be stored in the memory 120 of meter step equipment 100 for enabling processor 110
Enough instruction and datas for performing the method according to the embodiment of the present disclosure.
, below will be to count step equipment as portable mobile apparatus or wearable for the simplicity of explanation
Described in detail exemplified by equipment (for example, smart phone or Intelligent bracelet), can possess add thereon
Speedometer transducer 130 and gyro sensor 140.
Fig. 2 shows the overall flow figure of the step-recording method 200 according to the first embodiment of the present disclosure.
As shown in Fig. 2 method 200 can include step S210~S232.According to some of the disclosure
Embodiment, some steps of method 200 individually can perform or combine execution, and can be simultaneously
Row is performed or order is performed, it is not limited to the concrete operations order shown in Fig. 2.For example, to the greatest extent
Pipe step S222 and S224 sequence number after step S210~S220, but actually it
The step of can perform parallel, or step S222 and S224 can be partly or entirely in steps
Performed before or after rapid S210~S220.In certain embodiments, method 200 can be by
The meter shown in meter step equipment 100 and/or Figure 10 shown in Fig. 1 walks equipment 1000 to perform.
As shown in Fig. 2 method 200 can be performed since step S210 or S222 or from this
The two starts simultaneously at execution.Generally, step S210~S220 is related to counts according to acceleration
According to counting the first step number;Step S222~S224 is related to according to gyro data to count
Two step numbers;And step S226~S232 is related to according to both statistics to obtain finally
Compound meter step data.
In step S210, meter step equipment 100 (more specifically, processor 110) can be from
Acceierometer sensor 130 obtains the accelerometer data of user.For example, when user wears
When meter step equipment 100 is moved, as it was previously stated, 3-axis acceleration sensor 130 can be exported
When sample rate is FsWhen three mutually perpendicular directions on acceleration (for example, x-axis/y-axis/z-axis)
Angle value.
In step S212, resulting 3-axis acceleration value can be pre-processed, with
Lower combination Fig. 3 specifically describes the pretreatment.Fig. 3 is shown in method 200 shown in Fig. 2
For the exemplary method 300 of the pretreatment of accelerometer data.The pretreatment 300 can include 3
Individual subprocess:Down-sampled 310, frequency domain interference suppresses 320 and sliding-window filtering 330.
In some embodiments, down-sampled process 310 is related to the acceleration of acceierometer sensor 130
The sample rate counted is down to such as 50Hz (disclosure not limited to this).
In addition, in frequency domain interference process of inhibition 320, by calculating three axle auto-correlation functions,
Interference frequency point ranges can be detected, and trap is carried out to it.More specifically, the method in Fig. 4
400 are shown in detail each step S410~S430 of frequency domain interference process of inhibition 320.In view of attached
The order of each step in figure, input and output are clear and definite, and each step is this area in itself
Detailed description thereof is omitted known to technical staff, therefore in the disclosure.
Fig. 3 is returned to, can be by (the warp of the data in the long scope of window in sliding-window filtering 330
Cross the data after for example foregoing frequency domain interference suppresses) average value exported as it.By above-mentioned
Preprocessing process, can effectively suppress the interference/noise in sensing data so that follow-up inspection
Survey more accurate, reliable.
Fig. 2 step S214 is returned to, in step S214, reference axis can be selected.For example,
In certain embodiments, by calculating the peak-to-peak value of sensing data, peak-to-peak value can be chosen most
Big axle is used as reference axis data.In an alternative embodiment, three number of axle can also be chosen according to mould to make
On the basis of number of axle evidence.
Next in step S216, dynamic accuracy filtering can be performed.Specifically, one
In a little embodiments, t-1 moment values are assigned to t-2 moment values first.Then, by current time most
Freshly harvested filtered result makes the difference with t-1 moment values, and judges the absolute value of difference
Whether predefined precision precision is more than.If it is greater, then current time is most freshly harvested
Filtered result is assigned to t-1 moment values, otherwise keeps t-1 moment values constant.Finally, can be with
It regard t-2 moment values as dynamic accuracy filter result.
In step S218, dynamic threshold calculating can be performed.Specifically, it will can filter
Output afterwards is filled into the window for calculating dynamic threshold (the long NN_th of sliding window of dynamic threshold),
And ask for the maximum max and minimum value min of numerical value in the long NN_th of window.Then real-time dynamic gate
Limit value is (max+min)/2.
In step S220, meter step Information Statistics are performed.Specifically, Fig. 5 can be combined
The meter step Information Statistics based on accelerometer data are described in detail.As shown in figure 5, meter step information
Statistical method 500 is since step S510.In step S510, dynamic accuracy is first determined whether
Whether the output result of filtering is more than dynamic threshold.If greater than thresholding, then judged result can be with
Assign 1;If less than thresholding, then judged result can assign -1.Then, in step S512,
The difference value of current time judged result and previous moment judged result is calculated, and in step S514
It is middle that rising edge judgement is carried out according to difference value., can be front and rear by calculating in step S516
Time difference between rising edge, which to arrive when calculating strides, to be consumed.More specifically, using current time
The time that the time of rising edge subtracts previous moment rising edge is consumed when being exactly current stride.Further
Ground, in step S518, consumption is poor when being striden before and after can calculating.Finally, in step S520
In, consume the limitation of difference to count effective paces according to the limitation consumed when striding and when striding.
So far, the meter step based on accelerometer data is described in detail with reference to Fig. 2 and Fig. 3~5
Process.Next, the meter based on gyro data is described in detail by Fig. 2 and Fig. 6~8 are combined
Step process.
Usually, when user, which wears upper meter step equipment 100, to be moved, its three-axis gyroscope
Sensor 140 can export when sample rate be Fs when three mutually perpendicular directions on (for example, x-axis
/ y-axis/z-axis) angular speed.Therefore, can be from top in the step S222 shown in Fig. 2
Spiral shell instrument sensor 140 receives the gyro data of its user collected.Then, in step S224
In, step count information can be counted based on gyro data.
More specifically, the step S224 shown in Fig. 2 can be described in detail with reference to Fig. 6.Fig. 6
Show according to the embodiment of the present disclosure for counting the side of step count information based on gyro data
Method 600.Method 600 starts from step S610, in step S610, equally first to top
Spiral shell instrument data are pre-processed, such as it is down-sampled and/or zero-suppress partially.Then, in step S612
In, it is possible to use complementary filter corrects gyro error.Specifically, Fig. 7 can be combined
The gyro error makeover process 700 is described in detail.
In Fig. 7 step S710, first with the data of three-axis gyroscope by pretreatment
Result afterwards is input, to calculate attitude matrix.Then, can be by weight in step S712
Power reference vector is transformed under carrier coordinate system.In step S714, gravity survey can be calculated
Error between value and reference value, and in step S716, top is carried out according to the error
Spiral shell instrument amendment.
In the step S614 for returning next to Fig. 6, sliding-window filtering can be performed.Specifically
Ground, can by the long scope of window data (data of the gyroscope after error correction) it is flat
Average is exported as it.Then in step S616, reference axis can be selected.Specifically,
The peak-to-peak value of preprocessed and amendment gyro data can be calculated, and it is maximum to choose peak-to-peak value
Axle be used as reference axis data.Then in step S618, meter step Information Statistics can be performed.
Specifically, Fig. 8 method 800 can be combined meter step Information Statistics process is described in detail.
In Fig. 8 step S810, zero passage detection can be carried out to reference axis data first,
Then in step S812, exceptional value can be picked out.Next in step S814 and S816
In, consumption can be calculated when striding and front and rear consumption when striding is poor.For example, in step S814,
It can subtract the time of previous zero point to obtain during current stride with the time of current zero point
Consumption.And then in step S816, the difference of consumption when being striden before and after can calculating accordingly.Finally,
In step S818, effective paces are counted according to the limitation of consumption difference when consuming and stride when striding.
So far, the meter based on gyro data is described in detail and walked with reference to Fig. 2 and Fig. 6~8
Journey.
Fig. 2 step S226 and S228 is returned to, accelerometer and gyro are directed to by calculating respectively
Instrument consumes standard deviation when striding.
In step S226, standard deviation is consumed when can be striden with accelerometer in the range of calculation window.
Consumed when can obtain striding when carrying out meter step Information Statistics according to the data of accelerometer, in time window
Obtained in the range of mouthful Ts n consumption step_len_a when striding (1), step_len_a (2) ...,
Step_len_a (n), if the n averages consumed when striding are step_len_aavg, then add in the range of Ts
Standard deviation is consumed when speedometer strides is:
Similarly, in step S228, consumed when can be striden with gyroscope in the range of calculation window
Standard deviation.Consumed when can obtain striding when carrying out meter step Information Statistics according to the data of gyroscope,
Obtained in the range of time window Ts consumption step_len_g (1) when m strides, step_len_g (2) ...,
Step_len_g (m), if the m averages consumed when striding are step_len_gavg, then in the range of Ts
Standard deviation is consumed when gyroscope strides is:
Then, in step S230, gyro instrument meter step letter in the range of calculation window can be distinguished
The confidence level and accelerometer meter of breath walk the confidence level of information.In principle, in time window scope
The standard deviation consumed when striding that some interior sensor is calculated is bigger, then its confidence level is lower.Cause
This, the confidence level of gyro instrument meter step information can be:
And correspondingly, the confidence level of accelerometer meter step information is:
After the corresponding confidence level of the sensor is obtained, step S232 can be carried out, wherein,
Meter step information from different sensors is merged.Meter after fusion walks information
" obtained according to gyroscope meter step information " be multiplied by " confidence level of gyroscope " add " according to
The meter step information that accelerometer is obtained " is multiplied by " confidence level of accelerometer ".More intuitively, may be used
To calculate final step number according to below equation:
In the range of time window merge after step number=
The confidence level of the step number * accelerometers calculated according to accelerometer
The confidence level of+step number * the gyroscopes calculated according to gyroscope
So, can be by a variety of meters by using the step number statistical method shown in Fig. 2~8
The fusion of step data (for example, accelerometer data and gyro data), improves meter step precision,
Enhancing meter step algorithm expands covering of the step counting system to different crowd to the adaptability of different crowd
Face.
Fig. 9 is shown according to the embodiment of the present disclosure in meter step equipment 100 and/or meter step equipment
The flow chart for being used to count the method 900 of step number performed in 1000.As shown in figure 9, method
900 can include step S910, S920 and S930.According to the embodiment of the present disclosure, method 900
Some steps individually can perform or combine execution, and can perform parallel or order is performed,
It is not limited to the concrete operations order shown in Fig. 9.In certain embodiments, method 900 can
Equipment 100 is walked in terms of as shown in Figure 1 and/or counts step equipment 1000 to perform shown in Figure 10.
Figure 10 is to show to walk equipment based on counting step number according to the embodiment of the present disclosure
1000 each illustrative functions unit.As shown in Figure 10, node 1000 can include:The first step
Number computing unit 1010, the second step number computing unit 1020 and final step number computing unit 1030.
First step number computing unit 1010 can be used for being based on from first sensor (for example, figure
Acceierometer sensor 130 or gyro sensor 140 shown in 1) data calculate first
Step number.First step number computing unit 1010 can be the CPU of meter step equipment 1000
(CPU), digital signal processor (DSP), microprocessor, microcontroller etc. (for example,
The processor 110 of meter step equipment 100), it can receive sensing data from first sensor,
And first step number corresponding with the sensing data is calculated with such as aforesaid way.
Second step number computing unit 1020 can be used for being based on from second sensor (for example, figure
Gyro sensor 140 or acceierometer sensor 130 shown in 1) data calculate second
Step number.Second step number computing unit 1020 equally can be the center processing of meter step equipment 1000
Unit (CPU), digital signal processor (DSP), microprocessor, microcontroller etc. (example
Such as, the processor 110 of meter step equipment 100), it can receive sensor number from second sensor
According to, and calculate with such as aforesaid way second step number corresponding with the sensing data.
Final step number computing unit 1030 can be used for according to first sensor and second sensor
Respective confidence level, final step number is calculated based on the first step number and the second step number.Final step number
Computing unit 1030 equally can be the CPU (CPU) of meter step equipment 1000, number
Word signal processor (DSP), microprocessor, microcontroller etc. are (for example, meter step equipment
100 processor 110), it can calculate the confidence level of each sensing data, and root first
Each step number respective weights ratio shared in final step number is adjusted according to corresponding confidence level, and
Obtain final step number.
In addition, meter step equipment 1000 in can also include accompanying drawing not shown in other hardware and/
Or software unit.In view of these units are well-known to those skilled in the art, therefore omission pair
Its detailed description.
Below with reference to Fig. 9 and Figure 10, to according to embodiments of the present invention in meter step equipment 100
And/or the method 900 for being used to count step number performed on 1000 is described in detail.
Method 900 starts from step S910, in step S910, can be by meter step equipment 1000
The first step number computing unit 1010 calculate the first step based on the data from first sensor
Number.
In step S920, the second step number computing unit 1020 of equipment 1000 can be walked by meter
The second step number is calculated based on the data from second sensor.
In step S930, the final step number computing unit 1030 of equipment 1000 can be walked by meter
According to first sensor and the respective confidence level of second sensor, based on the first step number and second step
Count to calculate final step number.
In certain embodiments, first sensor can be accelerometer, and second sensor
It can be gyroscope.In certain embodiments, confidence level can be according to respective sensor across
The standard deviation that is consumed during step is determined.In certain embodiments, the standard deviation consumed when striding is root
Determined according to below equation:
Wherein, step_len_std represents the standard deviation consumed when striding of respective sensor,
Step_len (i) represents being consumed when striding for the i-th step, step_lenavgWhat expression n consumed when striding is averaged
Value, and n is natural number.In certain embodiments, the confidence level of first sensor and the second sensing
The confidence level of device can be calculated according to below equation respectively:
Wherein, Cred1Represent the confidence level of first sensor, Cred2Represent second sensor
Confidence level, step_len_std1The standard deviation consumed when striding of first sensor is represented, and
step_len_std2Represent the standard deviation consumed when striding of second sensor.In certain embodiments,
Final step number can be calculated based on below equation:The step number of final step number=first ×
The confidence level of the step number of confidence level+the second × second sensor of first sensor.
So far the disclosure is described combined preferred embodiment.It should be understood that ability
Field technique personnel in the case where not departing from spirit and scope of the present disclosure, can carry out it is various its
Its change, replacement and addition.Therefore, the scope of the present disclosure is not limited to above-mentioned particular implementation
Example, and should be defined by the appended claims.
Claims (10)
1. a kind of method for counting step number, including:
(a) the first step number is calculated based on the data from first sensor;
(b) the second step number is calculated based on the data from second sensor;And
(c) according to the first sensor and the respective confidence level of the second sensor, it is based on
First step number and second step number calculate final step number.
2. according to the method described in claim 1, wherein, the first sensor is acceleration
Meter, and the second sensor is gyroscope.
3. according to the method described in claim 1, wherein, the confidence level is according to corresponding biography
The standard deviation consumed when striding of sensor is determined.
4. method according to claim 3, wherein, the standard deviation consumed when striding is basis
Below equation is determined:
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<mi>s</mi>
<mi>t</mi>
<mi>d</mi>
<mo>=</mo>
<msqrt>
<mfrac>
<mrow>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
<mo>-</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<msub>
<mi>len</mi>
<mrow>
<mi>a</mi>
<mi>v</mi>
<mi>g</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
<mi>n</mi>
</mfrac>
</msqrt>
</mrow>
Wherein, step_len_std represents the standard deviation consumed when striding of respective sensor,
Step_len (i) represents being consumed when striding for the i-th step, step_lenavgWhat expression n consumed when striding is averaged
Value, and n is natural number.
5. method according to claim 4, wherein, the confidence level of the first sensor
Calculated respectively according to below equation with the confidence level of the second sensor:
<mrow>
<msub>
<mi>Cred</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
</mrow>
<mrow>
<msub>
<mi>Cred</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
</mrow>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
</mrow>
Wherein, Cred1Represent the confidence level of the first sensor, Cred2Represent described second
The confidence level of sensor, step_len_std1The standard deviation consumed when striding of first sensor is represented,
And step_len_std2Represent the standard deviation consumed when striding of second sensor.
6. according to the method described in claim 1, wherein, the final step number is based on following
Formula is calculated:
The step number of confidence level+the second of final step number=first step number × first sensor ×
The confidence level of second sensor.
7. a kind of equipment for counting step number, including:
First step number computing unit, for calculating first based on the data from first sensor
Step number;
Second step number computing unit, for calculating second based on the data from second sensor
Step number;And
Final step number computing unit, for according to the first sensor and the second sensor
Respective confidence level, final step number is calculated based on first step number and second step number.
8. equipment according to claim 7, wherein, the confidence level is according to corresponding biography
The standard deviation consumed when striding of sensor is determined, and the standard deviation consumed when striding is according to following
Formula is determined:
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<mi>s</mi>
<mi>t</mi>
<mi>d</mi>
<mo>=</mo>
<msqrt>
<mfrac>
<mrow>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
<mo>-</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<msub>
<mi>len</mi>
<mrow>
<mi>a</mi>
<mi>v</mi>
<mi>g</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
<mi>n</mi>
</mfrac>
</msqrt>
</mrow>
Wherein, step_len_std represents the standard deviation consumed when striding of respective sensor,
Step_len (i) represents being consumed when striding for the i-th step, step_lenavgWhat expression n consumed when striding is averaged
Value, and n is natural number.
9. equipment according to claim 8, wherein, the confidence level of the first sensor
Calculated respectively according to below equation with the confidence level of the second sensor:
<mrow>
<msub>
<mi>Cred</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
</mrow>
<mrow>
<msub>
<mi>Cred</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
</mrow>
<mrow>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>s</mi>
<mi>t</mi>
<mi>e</mi>
<mi>p</mi>
<mo>_</mo>
<mi>l</mi>
<mi>e</mi>
<mi>n</mi>
<mo>_</mo>
<msub>
<mi>std</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
</mrow>
Wherein, Cred1Represent the confidence level of the first sensor, Cred2Represent described second
The confidence level of sensor, step_len_std1The standard deviation consumed when striding of first sensor is represented,
And step_len_std2Represent the standard deviation consumed when striding of second sensor.
10. equipment according to claim 7, wherein, the final step number is based on following
Formula is calculated:
The step number of confidence level+the second of final step number=first step number × first sensor ×
The confidence level of second sensor.
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