CN108253992A - Step-recording method based on walking states - Google Patents
Step-recording method based on walking states Download PDFInfo
- Publication number
- CN108253992A CN108253992A CN201711493923.5A CN201711493923A CN108253992A CN 108253992 A CN108253992 A CN 108253992A CN 201711493923 A CN201711493923 A CN 201711493923A CN 108253992 A CN108253992 A CN 108253992A
- Authority
- CN
- China
- Prior art keywords
- acc
- axis
- acceleration
- curve
- walking
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Measurement Of Distances Traversed On The Ground (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The present invention provides the step-recording methods based on walking states, include the following steps：Acceleration information is continuously acquired from acceleration transducer；Calculate global acceleration；The linear acceleration ACC on three axis is calculated againx, ACCyAnd ACCz；Judge ACCx, ACCyAnd ACCzWhether it is more than given threshold, this group of data is marked if being more than given threshold as abnormal data, and be purged；Component of the linear acceleration on gravity direction is calculated, obtains ACCg；By ACCgThe first curve is depicted as, by ACCyThe second curve is depicted as, and the first curve and the second curve are overlapped into overlapping image；Assert condition according to the walking of walking feature-set, assert condition analysis overlapping image using walking, judge whether that walking occurs；When judging to occur walking, by the ACC at walking momentgIt is worth material calculation and calculates cadence, obtains walking data.Compared with the prior art, the present invention can exclude most equipment and shake interference, can provide Stride length and frequency data, effectively improve meter step precision.
Description
Technical field
The present invention relates to meter step technical field more particularly to step-recording methods based on walking states.
Background technology
Various smart mobile phones and wearable device are more and more universal in recent years, in such devices, especially wearable to set
It is standby, there are movement and the relevant application of health.One of core algorithm of these applications is exactly meter step algorithm.Existing meter step
Algorithm all using fairly simple threshold detection method, only provides step function, can not provide gait information.
Prior art main method is：Before starting between the first shortest time between one acceleration rate threshold of setting and two
Every；Read accelerometer data；Acceleration caused by user walks about is isolated from accelerometer data on gravity direction
This data is denoted as V by component；Whether two continuous V numerical value of detection cross over given threshold from low to high.As long as meet first
A numerical value V1 is less than threshold value, and second numerical value V2 is more than threshold value, then judges that two continuous V numerical value span setting from low to high
Threshold value；If it is more than setting duration that step time interval was counted with last time at this time simultaneously, meter step is carried out.
But there are following shortcomings for the prior art：
Meter step is not usually very accurate, cannot exclude some common interference, the random rocking apparatus of user can all cause
Meter step；Although these meter step algorithms can be applied in some applications not high to required precision, such as one day institute of counting user
The step number walked, if but it applies in the application similar to PDR (pedestrian's reckoning), influence meeting of this error to result
It is very big.
The information provided is very little；Most basic step function is only provided, more gait informations can not be provided；If energy
Know the information more about user's gait, just can thus extrapolate with mostly about the data of user movement.Such as in healthy class
In, if it is known that the substantially step-length of each step of user and the frequency of walking, it is possible to more accurately estimate that user disappears
The energy of consumption and the distance walked in total.
It is therefore necessary to these shortcomings are solved.
Invention content
The object of the present invention is to provide a kind of step-recording method based on walking states, the technical problem to be solved is that：Meter
Step is not usually very accurate, and the information provided is very little.
Then, the present invention provides the step-recording method based on walking states, include the following steps：
Step 1：Acceleration information is continuously acquired from acceleration transducer；It is calculated entirely by multigroup raw acceleration data
Office's acceleration；The linear acceleration ACC on three axis is calculated by raw acceleration data and global acceleration informationx, ACCy
And ACCz；
Step 2：Judge the linear acceleration ACC on three axisx, ACCyAnd ACCzWhether it is more than given threshold, if more than setting
Determine threshold value and then mark this group of data as abnormal data, and be purged；Component of the linear acceleration on gravity direction is calculated, and
Smothing filtering is carried out, obtains ACCg；
Step 3：By ACCgThe first curve is depicted as, by ACCyIt is depicted as the second curve, and by the first curve and the second curve
Overlapping forms overlapping image；
Step 4：Assert condition, and walking assert condition by ACC according to the walking of walking feature-setgAnd ACCyFeature point group
Into, using walking assert condition analysis overlapping image, judge whether occur walking；
Step 5：When judging to occur walking, by the ACC at walking momentgIt is worth material calculation, by the timestamp at walking moment
With a upper ACCgThe timestamp of valley value calculates cadence, obtains walking data.
Further, one group of raw acceleration data of acceleration transducer acquisition is specially in step 1：Utilize acceleration sensing
Device measures the acceleration on X-axis, Y-axis and Z axis, obtains the acceleration value on X-axis, Y-axis and Z axis, respectively RAW_ACCX, RAW_
ACCYAnd RAW_ACCZ。
Further, component of the linear acceleration after filtering on gravity direction is calculated in step, and carries out parallel filtering
Specially：Multiple DATA REASONING is carried out using acceleration transducer, obtains the acceleration value on multigroup X-axis, Y-axis and Z axis；It calculates
The average value of acceleration value on multigroup X-axis, Y-axis and Z axis obtains the component on global acceleration X-axis, Y-axis and Z axis, remembers respectively
For ACCworldx、ACCworldyAnd ACCworldz, specially：
Wherein RAW_ACCX, RAW_ACCY and RAW_ACCZ are respectively survey of the acceleration transducer on X-axis, Y-axis and Z axis
Magnitude.
Further, step 2 is specially：Component on linear acceleration X-axis, Y-axis and Z axis, is denoted as ACC respectivelyx、ACCyWith
ACCz, specially：
ACCx=RAW_ACCxk-ACCworldx
ACCy=RAW_ACCyk-ACCworldy
ACCz=RAW_ACCzk-ACCworldz；
Wherein ACCworldx、ACCworldyAnd ACCworldzComponent on respectively global acceleration X-axis, Y-axis and Z axis；RAW_
ACCX, RAW_ACCY and RAW_ACCZ are respectively measured value of the acceleration transducer on X-axis, Y-axis and Z axis.
Further, step 2 is specially：
Wherein ACCx、ACCyAnd ACCzRespectively component of the linear acceleration on X-axis, Y-axis and Z axis；
Global acceleration is normalized, specially：
The measured value of acceleration transducer：
RAW_ACC=[RAW_ACCx RAW_ACCy RAW_ACCz]
By the measurement value matrix transposition of acceleration transducer, it is multiplied with global acceleration normalization numerical value, obtains two
The dot product of a space vector, then the mould of global acceleration is subtracted, the linear acceleration value on gravity direction is obtained, add up n weight
Linear acceleration value on force direction, obtains ACCg；
Wherein, the value of n is 10.
Further, by multiple ACCgThe first curve is depicted as, by multiple ACCyIt is depicted as the second curve, and by the first curve
It is overlapped with the second curve, forms overlapping image；
Wherein walking feature is specially：Between the trough and first wave crest later of the first curve, corresponding second
Curve is there are wave crest, and its value is more than zero；When the first curve is in wave crest, the ACC in wave crestg, the of corresponding position
ACC on two curvesyFor negative value；When the trough that the wave crest on the second curve is adjacent to is in the time threshold of setting；
Assert that condition is specially according to the walking of walking feature-set：
ACC in the first curvegDuring in wave crest, the ACC in the second curveyFor negative value；ACC in second curve simultaneouslyy
Peak time stamp be more than the first curve in ACCgDecrease amount stamp；ACC in second curve simultaneouslyyWave crest adjacent first
ACC in curvegTime interval between wave crest is less than given threshold；ACC in first curve simultaneouslygThe adjacent ACC of troughg
Time interval between wave crest is more than the threshold value of setting；Furthermore ACC in the first curvegWave crest and a upper invalid data when
Between interval more than setting threshold value.
Further, material calculation and cadence, wherein step-length LestFor：
Wherein ACCgAccumulated value for linear acceleration value on n gravity direction；
To LestIt is constrained, obtains final step-length L：
Cadence F can be obtained according to the following formula:
Wherein, TpeakRepresent ACCgThe timestamp of wave crest, TtroughRepresent corresponding A CCgOn wave crest ACCg trough when
Between stab.
The advantageous effect of said program：Can exclude most equipment and shake interference, detection user whether really in walking,
The mistake meter step under some abnormal conditions is eliminated, and the information such as Stride length and frequency are provided；Meter step precision can be effectively improved.
Description of the drawings
Fig. 1 is the flow chart of the step-recording method the present invention is based on walking states；
Fig. 2 is the schematic diagram of the first curve of the invention；
Fig. 3 is the schematic diagram of overlapping image that the first curve and the second curve of the invention are formed；
Fig. 4 implements meter step schematic diagram for the present invention；
Fig. 5 is implements meter step effect diagram under the abnormal interference of the present invention.
Specific embodiment
In the following, with reference to attached drawing, the present invention will be described in detail.
As shown in Figures 1 to 5, the step-recording method based on walking states, includes the following steps：
Step 1：Acceleration information is continuously acquired from acceleration transducer；It is calculated entirely by multigroup raw acceleration data
Office's acceleration；The linear acceleration ACC on three axis is calculated by raw acceleration data and global acceleration informationx, ACCy
And ACCz；
Step 2：Judge the linear acceleration ACC on three axisx, ACCyAnd ACCzWhether it is more than given threshold, if more than setting
Determine threshold value and then mark this group of data as abnormal data, and be purged；Component of the linear acceleration on gravity direction is calculated, and
Smothing filtering is carried out, obtains ACCg；
Step 3：By ACCgThe first curve is depicted as, by ACCyIt is depicted as the second curve, and by the first curve and the second curve
Overlapping forms overlapping image；
Step 4：Assert condition, and walking assert condition by ACC according to the walking of walking feature-setgAnd ACCyFeature point group
Into, using walking assert condition analysis overlapping image, judge whether occur walking；
Step 5：When judging to occur walking, by the ACC at walking momentgIt is worth material calculation, by the timestamp at walking moment
With a upper ACCgThe timestamp of valley value calculates cadence, obtains walking data.
In above-described embodiment, one group of raw acceleration data of acceleration transducer acquisition is specially in step 1：Utilize acceleration
The acceleration on sensor measurement X-axis, Y-axis and Z axis is spent, obtains the acceleration value on X-axis, Y-axis and Z axis, respectively RAW_
ACCX, RAW_ACCYAnd RAW_ACCZ。
Component of the linear acceleration after filtering on gravity direction is calculated in above-described embodiment, in step, and is put down
Row filters：Multiple DATA REASONING is carried out using acceleration transducer, obtains the acceleration on multigroup X-axis, Y-axis and Z axis
Value；The average value of the acceleration value on multigroup X-axis, Y-axis and Z axis is calculated, obtains the component on global acceleration X-axis, Y-axis and Z axis,
It is denoted as ACC respectivelyworldx、ACCworldyAnd ACCworldz, specially：
Wherein RAW_ACCX, RAW_ACCY and RAW_ACCZ are respectively survey of the acceleration transducer on X-axis, Y-axis and Z axis
Magnitude.
In above-described embodiment, step 2 is specially：Component on linear acceleration X-axis, Y-axis and Z axis, is denoted as ACC respectivelyx、
ACCyAnd ACCz, specially：
ACCx=RAW_ACCxk-ACCworldx
ACCy=RAW_ACCyk-ACCworldy
ACCz=RAW_ACCzk-ACCworldz；
Wherein ACCworldx、ACCworldyAnd ACCworldzComponent on respectively global acceleration X-axis, Y-axis and Z axis；RAW_
ACCX, RAW_ACCY and RAW_ACCZ are respectively measured value of the acceleration transducer on X-axis, Y-axis and Z axis.
In above-described embodiment, step 2 is specially：
Wherein ACCx、ACCyAnd ACCzRespectively component of the linear acceleration on X-axis, Y-axis and Z axis；
Global acceleration is normalized, specially：
The measured value of acceleration transducer：
RAW_ACC=[RAW_ACCx RAW_ACCy RAW_ACCz]
By the measurement value matrix transposition of acceleration transducer, it is multiplied with global acceleration normalization numerical value, obtains two
The dot product of a space vector, then the mould of global acceleration is subtracted, the linear acceleration value on gravity direction is obtained, add up n weight
Linear acceleration value on force direction, obtains ACCg；
Wherein, the value of n is 10.
In above-described embodiment,
By multiple ACCgThe first curve is depicted as, by multiple ACCyThe second curve is depicted as, and the first curve and second is bent
Line overlap forms overlapping image；
Wherein walking feature is specially：Between the trough and first wave crest later of the first curve, corresponding second
Curve is there are wave crest, and its value is more than zero；When the first curve is in wave crest, the ACC in wave crestg, the of corresponding position
ACC on two curvesyFor negative value；When the trough that the wave crest on the second curve is adjacent to is in the time threshold of setting；
Assert that condition is specially according to the walking of walking feature-set：
ACC in the first curvegDuring in wave crest, the ACC in corresponding second curveyFor negative value；Simultaneously in the second curve
ACCyPeak time stamp be more than the first curve in ACCgDecrease amount stamp；ACC in second curve simultaneouslyyWave crest is adjacent
ACC in first curvegTime interval between wave crest is less than given threshold；ACC in first curve simultaneouslygTrough is adjacent
ACCgTime interval between wave crest is more than the threshold value of setting；Furthermore ACC in the first curvegWave crest and a upper invalid data
Time interval is more than the threshold value of setting；
Wherein, linear acceleration maximum value:6.8；
ACCgWave crest range:3.3~45；
ACCgTrough range:- 45~-3.3；
ACCgMaximum time interval between wave crest and a upper ACCy wave crest:350ms；
ACCgMinimum interval between the adjacent ACCg wave crests of trough:200ms；
ACCgMaximum time interval between wave crest and a upper invalid data:850ms.
ACC in the first curvegDuring in wave crest, the ACC in the second curveyFor negative value, shaken extremely for filter plant
The mistake meter step of movable property life.
In above-described embodiment, material calculation and cadence, wherein step-length LestFor：
Wherein ACCgAccumulated value for linear acceleration value on n gravity direction；
To LestIt is constrained, obtains final step-length L：
Cadence F can be obtained according to the following formula:
Wherein, TpeakRepresent ACCgThe timestamp of wave crest, TtroughRepresent an ACC on corresponding A CCg wave crestsgTrough when
Between stab.
Fig. 4 is implements meter step schematic diagram；Each vertical line represents primary meter step, lower section text importing step-length and step in curve graph
The information such as frequency；Fig. 5 is to implement meter step effect diagram in the case where interfering extremely, this figure is the image generated by artificial whipping equipment,
It can be seen that having, the oscillogram generated under abnormal disturbed condition and the oscillogram generated in the case of normal walk are similar, but not
It can cause meter step (schematic diagram comparison can be walked with the implementation meter under normal condition)；The technical program energy material calculation size and paces
Frequency can exclude most equipment and shake interference, and whether user is really in walking for detection, eliminates the mistake under some abnormal conditions
Error count walks, and provides the information such as Stride length and frequency；Meter step precision can be effectively improved.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
With within principle, any modification, equivalent replacement, improvement and so on should all be included in the protection scope of the present invention god.
Claims (7)
1. the step-recording method based on walking states, which is characterized in that include the following steps：
Step 1：Acceleration information is continuously acquired from acceleration transducer；Global add, is calculated by multigroup raw acceleration data
Speed；The linear acceleration ACC on three axis is calculated by raw acceleration data and global acceleration informationx, ACCyWith
ACCz；
Step 2：Judge the linear acceleration ACC on three axisx, ACCyAnd ACCzWhether it is more than given threshold, if more than setting threshold
Value then marks this group of data as abnormal data, and is purged；Component of the linear acceleration on gravity direction is calculated, and is carried out
Smothing filtering obtains ACCg；
Step 3：By ACCgThe first curve is depicted as, by ACCyIt is depicted as the second curve, and by the first curve and the second curve weight
It is folded, form overlapping image；
Step 4：Assert condition, and walking assert condition by ACC according to the walking of walking feature-setgAnd ACCyFeature point group into, profit
Assert condition analysis overlapping image with walking, judge whether that walking occurs；
Step 5：When judging to occur walking, by the ACC at walking momentgIt is worth material calculation, by the timestamp at walking moment and upper one
A ACCgThe timestamp of valley value calculates cadence, obtains walking data.
2. the step-recording method according to claim 1 based on walking states, which is characterized in that acceleration sensing in step 1
Device obtains one group of raw acceleration data：The acceleration on X-axis, Y-axis and Z axis is measured using acceleration transducer, is obtained
Obtain the acceleration value on X-axis, Y-axis and Z axis, respectively RAW_ACCX, RAW_ACCYAnd RAW_ACCZ。
3. the step-recording method according to claim 2 based on walking states, which is characterized in that after calculating filtering in step
Component of the linear acceleration on gravity direction, and carry out parallel filtering and be specially：It is repeatedly counted using acceleration transducer
According to measurement, the acceleration value on multigroup X-axis, Y-axis and Z axis is obtained；Calculate the flat of the acceleration value on multigroup X-axis, Y-axis and Z axis
Mean value obtains the component on global acceleration X-axis, Y-axis and Z axis, is denoted as ACC respectivelyworldx、ACCworldyAnd ACCworldz, specifically
For：
Wherein RAW_ACCX, RAW_ACCY and RAW_ACCZ are respectively measurement of the acceleration transducer on X-axis, Y-axis and Z axis
Value.
4. the step-recording method according to claim 3 based on walking states, which is characterized in that step 2 is specially：It is linear to add
Component on speed X-axis, Y-axis and Z axis, is denoted as ACC respectivelyx、ACCyAnd ACCz, specially：
ACCx=RAW_ACCxk-ACCworldx
ACCy=RAW_ACCyk-ACCworldy
ACCz=RAW_ACCzk-ACCworldz；
Wherein ACCworldx、ACCworldyAnd ACCworldzComponent on respectively global acceleration X-axis, Y-axis and Z axis；RAW_
ACCX, RAW_ACCY and RAW_ACCZ are respectively measured value of the acceleration transducer on X-axis, Y-axis and Z axis.
5. the step-recording method according to claim 4 based on walking states, which is characterized in that step 2 is specially：
Wherein ACCx、ACCyAnd ACCzRespectively component of the linear acceleration on X-axis, Y-axis and Z axis；
Global acceleration is normalized, specially：
The measured value of acceleration transducer：
RAW_ACC=[RAW_ACCx RAW_ACCy RAW_ACCz]
By the measurement value matrix transposition of acceleration transducer, it is multiplied with global acceleration normalization numerical value, obtains two skies
Between vectorial dot product, then subtract the mould of global acceleration, obtain the linear acceleration value on gravity direction, add up n gravity side
Upward linear acceleration value, obtains ACCg；
Wherein, the value of n is 10.
6. the step-recording method according to claim 5 based on walking states, which is characterized in that by multiple ACCgIt is depicted as
One curve, by multiple ACCyThe second curve is depicted as, and the first curve and the second curve are overlapped, forms overlapping image；
Wherein walking feature is specially：Between the trough and first wave crest later of the first curve, corresponding second curve
There are wave crest, and its value is more than zero；When the first curve is in wave crest, the ACC in wave crestg, the second song of corresponding position
ACC on lineyFor negative value；When the trough that the wave crest on the second curve is adjacent to is in the time threshold of setting；
Assert that condition is specially according to the walking of walking feature-set：
ACC in the first curvegDuring in wave crest, the ACC in the second curveyFor negative value；ACC in second curve simultaneouslyyWave
Peak time stamp is more than ACC in the first curvegDecrease amount stamp；ACC in second curve simultaneouslyyAdjacent first curve of wave crest
Middle ACCgTime interval between wave crest is less than given threshold；ACC in first curve simultaneouslygThe adjacent ACC of troughgWave crest
Between time interval be more than setting threshold value；Furthermore ACC in the first curvegBetween the time of wave crest and a upper invalid data
Every the threshold value more than setting.
7. the step-recording method according to claim 6 based on walking states, which is characterized in that material calculation and cadence,
Middle step-length LestFor：
Wherein ACCgAccumulated value for linear acceleration value on n gravity direction；
To LestIt is constrained, obtains final step-length L：
Cadence F can be obtained according to the following formula:
Wherein, TpeakRepresent ACCgThe timestamp of wave crest, TtroughRepresent corresponding A CCgThe timestamp of an ACCg trough on wave crest.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711493923.5A CN108253992B (en) | 2017-12-31 | 2017-12-31 | Step counting method based on walking state |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711493923.5A CN108253992B (en) | 2017-12-31 | 2017-12-31 | Step counting method based on walking state |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108253992A true CN108253992A (en) | 2018-07-06 |
| CN108253992B CN108253992B (en) | 2021-07-02 |
Family
ID=62725604
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711493923.5A Active CN108253992B (en) | 2017-12-31 | 2017-12-31 | Step counting method based on walking state |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108253992B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109212260A (en) * | 2018-09-07 | 2019-01-15 | 青岛迈金智能科技有限公司 | A kind of motion frequency calculation method and device |
| CN109870172A (en) * | 2019-02-25 | 2019-06-11 | 广州市香港科大霍英东研究院 | Step counting detection method, device, equipment and storage medium |
| CN109883531A (en) * | 2019-03-05 | 2019-06-14 | 广州亚美信息科技有限公司 | Vehicle vibration kind identification method and system based on acceleration transducer |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1271099A2 (en) * | 2001-06-29 | 2003-01-02 | Nokia Corporation | Method and arrangement for determining movement |
| US20030191582A1 (en) * | 2002-04-08 | 2003-10-09 | Casio Computer Co., Ltd. | Moving direction detection method, moving direction detection apparatus, and program code |
| WO2006073219A1 (en) * | 2005-01-04 | 2006-07-13 | Healthpia Co., Ltd. | Mobile communication terminal having exercise quantity measurement function and method of measuring exercise quantity using the same |
| CN101694499A (en) * | 2009-10-22 | 2010-04-14 | 浙江大学 | Pedestrian gait detection-based system and method of walking speed measurement and transmission |
| CN101750096A (en) * | 2008-11-28 | 2010-06-23 | 佛山市顺德区顺达电脑厂有限公司 | Step-counting processing system and method |
| CN102564449A (en) * | 2010-11-17 | 2012-07-11 | 索尼公司 | Walking situation detection device, walking situation detection method, and walking situation detection program |
| CN103792386A (en) * | 2013-11-21 | 2014-05-14 | 清华大学 | Walking direction detection method and device |
| CN103997572A (en) * | 2014-06-03 | 2014-08-20 | 深圳市爱康伟达智能医疗科技有限公司 | Step counting method and device based on data of acceleration sensor of mobile phone |
| CN106123897A (en) * | 2016-06-14 | 2016-11-16 | 中山大学 | Indoor fusion and positioning method based on multiple features |
| CN107250727A (en) * | 2014-09-15 | 2017-10-13 | 牛津大学创新有限公司 | Determine position of the mobile device in geographic area |
-
2017
- 2017-12-31 CN CN201711493923.5A patent/CN108253992B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1271099A2 (en) * | 2001-06-29 | 2003-01-02 | Nokia Corporation | Method and arrangement for determining movement |
| US20030191582A1 (en) * | 2002-04-08 | 2003-10-09 | Casio Computer Co., Ltd. | Moving direction detection method, moving direction detection apparatus, and program code |
| WO2006073219A1 (en) * | 2005-01-04 | 2006-07-13 | Healthpia Co., Ltd. | Mobile communication terminal having exercise quantity measurement function and method of measuring exercise quantity using the same |
| CN101750096A (en) * | 2008-11-28 | 2010-06-23 | 佛山市顺德区顺达电脑厂有限公司 | Step-counting processing system and method |
| CN101694499A (en) * | 2009-10-22 | 2010-04-14 | 浙江大学 | Pedestrian gait detection-based system and method of walking speed measurement and transmission |
| CN102564449A (en) * | 2010-11-17 | 2012-07-11 | 索尼公司 | Walking situation detection device, walking situation detection method, and walking situation detection program |
| CN103792386A (en) * | 2013-11-21 | 2014-05-14 | 清华大学 | Walking direction detection method and device |
| CN103997572A (en) * | 2014-06-03 | 2014-08-20 | 深圳市爱康伟达智能医疗科技有限公司 | Step counting method and device based on data of acceleration sensor of mobile phone |
| CN107250727A (en) * | 2014-09-15 | 2017-10-13 | 牛津大学创新有限公司 | Determine position of the mobile device in geographic area |
| CN106123897A (en) * | 2016-06-14 | 2016-11-16 | 中山大学 | Indoor fusion and positioning method based on multiple features |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109212260A (en) * | 2018-09-07 | 2019-01-15 | 青岛迈金智能科技有限公司 | A kind of motion frequency calculation method and device |
| CN109212260B (en) * | 2018-09-07 | 2021-06-25 | 青岛迈金智能科技有限公司 | Motion frequency calculation method and device |
| CN109870172A (en) * | 2019-02-25 | 2019-06-11 | 广州市香港科大霍英东研究院 | Step counting detection method, device, equipment and storage medium |
| CN109870172B (en) * | 2019-02-25 | 2020-12-18 | 广州市香港科大霍英东研究院 | Step counting detection method, device, equipment and storage medium |
| CN109883531A (en) * | 2019-03-05 | 2019-06-14 | 广州亚美信息科技有限公司 | Vehicle vibration kind identification method and system based on acceleration transducer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108253992B (en) | 2021-07-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108253992A (en) | Step-recording method based on walking states | |
| TWI518304B (en) | A step counting method and pedometer based on 3-axis accelerometer | |
| EP2748093B1 (en) | Method and apparatus for elevator motion detection | |
| CN102944240B (en) | A kind of inertial navigation system based on smart mobile phone and method | |
| FI124343B (en) | Apparatus and method for monitoring swimming performance | |
| US10520330B2 (en) | Estimation of direction of motion of users on mobile devices | |
| CN104567912B (en) | Method for realizing pedometer on Android mobile phone | |
| KR101920306B1 (en) | Apparatus and method of measuring amount of exercise using mobile device | |
| CN106256396A (en) | Motion assisting system and motion support method | |
| US20150241243A1 (en) | Method for counting steps and electronic apparatus using the same | |
| CN106017502A (en) | Step counting method and electronic device | |
| CN109844460A (en) | A kind of stride calibration method, relevant device and system | |
| CN104660779A (en) | Method and device for computing amount of exercise and cellphone | |
| KR20230084446A (en) | System and Method for improving measurement accuracy of the momentum in a health care system | |
| CN104089625A (en) | Step counting method with self-learning capability | |
| KR101609813B1 (en) | Apparatus and method for counting step in smartphone | |
| CN110916673A (en) | Gait monitoring method and intelligent equipment | |
| CN105953794A (en) | Step counting navigation method based on MEMS sensor | |
| JP2013022090A (en) | Energy consumption amount presentation device and energy consumption amount estimation method | |
| Uddin et al. | SmartSpaghetti: Accurate and robust tracking of Human's location | |
| CN110595501B (en) | Running distance correction method based on three-axis sensor | |
| JP2020101849A (en) | Measurement apparatus, measurement method and measurement program | |
| CN111337050B (en) | Zero-speed judgment condition and step counting method based on multi-condition fusion | |
| TWI579530B (en) | Mobile device pedometer system and gait analysis method thereof | |
| CN209500722U (en) | Exercise intensity evaluation device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |