CN107747950B - Step recording method and device - Google Patents
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- CN107747950B CN107747950B CN201710893671.9A CN201710893671A CN107747950B CN 107747950 B CN107747950 B CN 107747950B CN 201710893671 A CN201710893671 A CN 201710893671A CN 107747950 B CN107747950 B CN 107747950B
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Abstract
The embodiment of the invention provides a step recording method and a step recording device, wherein the method comprises the following steps: acquiring triaxial acceleration data of equipment carried by a user; respectively carrying out periodic matching on the acceleration data of each coordinate axis, and taking the coordinate axis with the maximum periodicity as a target step recording axis; and determining the step number of the user according to the acceleration data corresponding to the target step recording shaft. According to the method and the device, the periodicity of the user in the motion process is considered, the coordinate axis with the largest periodicity is used as the target step recording axis, the step number of the user is accurately obtained based on the acceleration data of the target step recording axis, and then the step is accurately recorded for the user.
Description
Technical Field
The embodiment of the invention relates to a terminal technology, in particular to a step recording method and device.
Background
Wearable equipment such as current intelligent bracelet, intelligent wrist-watch generally have that of note step function, use the human motion of product integrated motion sensor perception, and then realize note step to according to user's step number, estimate user's walking distance, consume parameters such as calorie.
The current wearable device usually obtains three-axis acceleration data of the device when a user moves, namely acceleration in an X coordinate axis direction, acceleration in a Y coordinate axis direction, and acceleration in a Z coordinate axis direction. And obtaining a coordinate axis with the maximum integral amplitude value from the acceleration data of the three axes as a target coordinate axis, such as an X coordinate axis. And then, drawing an acceleration waveform diagram in the X coordinate axis direction, and counting the number of wave troughs or wave crests in the acceleration waveform diagram to realize step recording, wherein one wave crest represents one step.
However, the walking habits of the users are different, or when the users walk slowly, the coordinate axis with the maximum amplitude value cannot accurately reflect the actual motion state of the users, so that the problem of inaccurate step recording is caused.
Disclosure of Invention
The embodiment of the invention provides a step recording method and device, aiming at solving the problem that the prior art cannot accurately record steps for a user.
In a first aspect, an embodiment of the present invention provides an evaluation method for a step-counting method, including:
acquiring triaxial acceleration data of equipment carried by a user;
respectively carrying out periodic matching on the acceleration data of each coordinate axis, and taking the coordinate axis with the maximum periodicity as a target step recording axis;
and determining the step number of the user according to the acceleration data corresponding to the target step recording shaft.
In a possible implementation manner of the first aspect, before the periodically matching the acceleration data of each coordinate axis, the method further includes:
filtering the triaxial acceleration data using a filter bank, wherein the filter bank includes different types of filters having different cutoff frequencies.
In another possible implementation manner of the first aspect, the periodically matching the acceleration data of each coordinate axis, and taking the coordinate axis with the largest periodicity as the target step-recording axis specifically includes:
and respectively carrying out periodic matching on the filtered acceleration data of each coordinate axis, and taking the coordinate axis with the maximum periodicity as a target step recording axis.
In another possible implementation manner of the first aspect, the periodically matching the filtered acceleration data of each coordinate axis specifically includes:
respectively acquiring turning points in the filtered acceleration data corresponding to each coordinate axis;
for each turning point on each coordinate axis, acquiring a first amplitude difference and a first time difference between the turning point and the next turning point, acquiring a first turning point corresponding to the turning point in an adjacent period, and acquiring a second amplitude difference and a second time difference between the first turning point and the next turning point;
judging whether the first amplitude difference is equal to the second amplitude difference or not, and judging whether the first time difference is equal to the second time difference or not;
if so, determining that the turning point is successfully matched periodically.
In another possible implementation manner of the first aspect, after the first amplitude difference is equal to the second amplitude difference and the first time difference is equal to the second time difference, the method further includes:
judging whether the first amplitude difference is within a preset amplitude interval or not and judging whether the first time difference is within a preset period interval or not;
if so, determining that the turning point is successfully matched periodically.
In another possible implementation manner of the first aspect, the taking the coordinate axis with the largest periodicity as the target step-recording axis specifically includes:
and obtaining the number of first turning points which are successfully matched periodically in each turning point corresponding to each coordinate axis, and taking the coordinate axis corresponding to the maximum number of the first turning points as a target step recording axis.
In another possible implementation manner of the first aspect, the determining the step number of the user according to the acceleration data corresponding to the target step recording axis specifically includes:
judging whether a third time difference between the turning point which is periodically matched at present and the turning point which is periodically matched at the previous time is larger than or equal to a first threshold value or not for each turning point in the acceleration data corresponding to the target step recording axis;
if so, determining the step number of the user according to the third time difference and the periodic value of the acceleration data corresponding to the target step recording axis;
if not, determining the step number of the user according to the number of turning points of the acceleration data corresponding to the target step recording axis.
In another possible implementation manner of the first aspect, the method further includes:
determining first energy of the acceleration data according to the maximum value and the minimum value of each acceleration data amplitude corresponding to the target step recording axis;
determining a motion profile of the user from the first energy.
In another possible implementation manner of the first aspect, when it is determined that the user has at least two forms of motion according to the first energy, the method further includes:
determining second energy of the acceleration data according to the sum of absolute values of amplitude differences of two adjacent acceleration data in the acceleration data corresponding to the target step recording axis;
determining a motion profile of the user from the first energy and the second energy.
In another possible implementation manner of the first aspect, the determining the motion form of the user according to the first energy specifically includes:
acquiring first intervals of targets intersected with the first energy, wherein the first intervals corresponding to different motion forms are different;
and if the target first interval is one, determining that the motion form of the user is the motion form corresponding to the target first interval.
In another possible implementation manner of the first aspect, if the target first interval is at least two, the determining the motion form of the user according to the first energy and the second energy specifically includes:
acquiring a first operation form set corresponding to each target first interval;
acquiring second target intervals intersected with the second energy, and acquiring a second operation form set corresponding to the second target intervals, wherein the second intervals corresponding to different motion forms are different;
and taking the same operation form in the first operation form set and the second operation form set as the motion form of the user.
In a second aspect, an embodiment of the present invention provides a step recording device, including:
the acquisition module is used for acquiring triaxial acceleration data of equipment carried by a user;
the periodic matching module is used for periodically matching the acceleration data of each coordinate axis and taking the coordinate axis with the maximum periodicity as a target step recording axis;
and the determining module is used for determining the step number of the user according to the acceleration data corresponding to the target step recording shaft.
In a possible implementation manner of the second aspect, the apparatus further includes:
and the filtering module is used for filtering the triaxial acceleration data by using a filter bank, wherein the filter bank comprises different types of filters, and the cut-off frequencies corresponding to the different types of filters are different.
The periodic matching module is specifically configured to perform periodic matching on the filtered acceleration data of each coordinate axis respectively, and use the coordinate axis with the largest periodicity as a target step-recording axis.
In another possible implementation manner of the second aspect, the apparatus further includes a determining module:
the obtaining module is further configured to obtain turning points in the filtered acceleration data corresponding to each coordinate axis, and for each turning point on each coordinate axis, obtain a first amplitude difference and a first time difference between the turning point and a subsequent turning point, obtain a first turning point corresponding to the turning point in an adjacent period, and obtain a second amplitude difference and a second time difference between the first turning point and the subsequent turning point.
The judging module is configured to judge whether the first amplitude difference is equal to the second amplitude difference, and judge whether the first time difference is equal to the second time difference.
The determining module is configured to determine that the turning point is successfully matched periodically when the determining module 50 determines that the first amplitude difference is equal to the second amplitude difference and determines that the first time difference is equal to the second time difference.
In another possible implementation manner of the second aspect, the determining module is further configured to determine whether the first amplitude difference is within a preset amplitude interval and determine whether the first time difference is within a preset period interval after determining that the first amplitude difference is equal to the second amplitude difference and the first time difference is equal to the second time difference.
The determining module is configured to determine that the turning point is successfully matched periodically when the determining module determines that the first amplitude difference is within a preset amplitude interval and determines that the first time difference is within a preset period interval.
In another possible implementation manner of the second aspect, the obtaining module is further configured to obtain the number of first turning points, which are successfully matched periodically, in each turning point corresponding to each coordinate axis.
The determining module is further configured to use the coordinate axis corresponding to the maximum number of the first turning points as a target step-recording axis.
In another possible implementation manner of the second aspect, the determining module is further configured to determine, for each turning point in the acceleration data corresponding to the target step-recording axis, whether a third time difference between a turning point of a current periodic matching and a turning point of a previous periodic matching is greater than or equal to a first threshold.
The determining module is further configured to determine the step count of the user according to a period value of the acceleration data corresponding to the target step recording axis and the third time difference when the determining module determines that the third time difference between the turning point of the current periodic matching and the turning point of the previous periodic matching is greater than or equal to a first threshold.
The determining module is further configured to determine the number of steps of the user according to the number of turning points of the acceleration data corresponding to the target step recording axis when the determining module determines that a third time difference between a turning point of the current periodic matching and a turning point of the previous periodic matching is smaller than a first threshold.
In another possible implementation manner of the second aspect, the determining module is further configured to determine a first energy of the acceleration data according to a maximum value and a minimum value of each acceleration data amplitude corresponding to the target step-recording axis; and determining a motion pattern of the user based on the first energy.
In another possible implementation manner of the second aspect, the determining module is further configured to determine, when it is determined that the user has at least two motion forms according to the first energy, a second energy of the acceleration data according to a sum of absolute values of amplitude differences between two adjacent acceleration data in the acceleration data corresponding to the target step-recording axis; and determining a motion profile of the user based on the first energy and the second energy.
In another possible implementation manner of the second aspect, the obtaining module is further configured to obtain first target intervals intersecting the first energy, where the first intervals corresponding to different motion forms are different.
The determining module is configured to determine, when the target first interval is one, that the motion form of the user is the motion form corresponding to the target first interval.
In another possible implementation manner of the second aspect, the obtaining module is further configured to obtain, when the number of the target first intervals is at least two, a first operation form set corresponding to each target first interval; and acquiring second target intervals intersected with the second energy, and acquiring a second operation form set corresponding to the second target intervals, wherein the second intervals corresponding to different motion forms are different.
The determining module is configured to use the same operation form in the first operation form set and the second operation form set as the motion form of the user.
According to the step recording method and device provided by the embodiment of the invention, the three-axis acceleration data of the equipment carried by the user is acquired, the periodic matching is respectively carried out on the acceleration data of each coordinate axis, the coordinate axis with the largest periodicity is used as a target step recording axis, and the step number of the user is determined according to the acceleration data corresponding to the target step recording axis. That is, in the embodiment, because the periodicity of the user in the motion process is considered, the coordinate axis with the largest periodicity is used as the target step recording axis, and the step number of the user is accurately obtained based on the acceleration data of the target step recording axis, so that the step recording of the user is accurately realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart of a step-counting method according to an embodiment of the present invention;
FIG. 2 is an acceleration waveform diagram of acceleration data of a coordinate axis;
FIG. 3 is a flowchart of a step-counting method according to a second embodiment of the present invention;
FIG. 4 is a flowchart of a step-counting method according to a third embodiment of the present invention;
FIG. 5 is a signaling flow diagram of the pacing method described in FIG. 4;
FIG. 6 is a flowchart of a step-counting method according to a fourth embodiment of the present invention;
FIG. 7 is a waveform of acceleration for different motion profiles;
FIG. 8 is a block diagram of a step counter according to an embodiment of the present invention;
FIG. 9 is a block diagram of a step counter according to a second embodiment of the present invention;
fig. 10 is a structural diagram of a step counter according to a third embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
According to the method provided by the embodiment of the invention, the user has periodicity during movement, so that the coordinate axis with the maximum periodicity in the triaxial acceleration data is taken as the target step recording axis, and step recording is carried out based on the acceleration data of the target step recording axis, and the problem of inaccurate step recording caused by the fact that the coordinate axis with the maximum amplitude is taken as the target step recording axis in the prior art is solved.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a flowchart of a step recording method according to an embodiment of the present invention. The main execution body of this embodiment is a step counting device with step number calculation capability, and the step counting device may be a certain device in a device carried by a user or may be a separate device. The embodiment relates to a specific process of determining the step number of the user by the step recording device according to the acceleration data corresponding to the target step recording axis. As shown in fig. 1, the method of this embodiment may include:
s101, acquiring triaxial acceleration data of equipment carried by a user.
The device carried by the user can be wearable device, such as a wearable bracelet, a wearable watch and the like. The device comprises various sensing devices for collecting user data, for example, a sensing device for measuring acceleration during movement of a user, a sensing device for measuring heartbeat of the user and the like.
The coordinate system of the three-axis acceleration data may be an X, Y, Z coordinate system, and the corresponding three-axis acceleration data are X-axis acceleration data on an X-axis component, Y-axis acceleration data on a Y-axis component, and Z-axis acceleration data on a Z-axis component, respectively, when the user is moving. Optionally, the coordinate system of the triaxial acceleration data may also be a world coordinate system U, V, W coordinate system, and the corresponding triaxial acceleration data are U coordinate axis acceleration data on a U coordinate axis component, V coordinate axis acceleration data on a V coordinate axis component, and W coordinate axis acceleration data on a W coordinate axis component when the user moves. Optionally, the coordinate system of the triaxial acceleration data may also be a coordinate system in other forms, which is not limited in this embodiment.
The three-axis acceleration data of this embodiment can be decomposed according to a combined acceleration, for example, a sensing device is used to measure a combined acceleration a, and the combined acceleration a is decomposed along the X, Y, Z direction to obtain the acceleration data a of the X coordinate axisXY coordinate axis acceleration data aYAnd Z coordinate axis acceleration data aZ. Optionally, the present embodiment is a three-axis machiningThe speed data can also be acceleration data in three coordinate axis directions directly acquired by a triaxial acceleration sensing device.
When the device of this embodiment is located on the wrist of the user, the acceleration data is acceleration data when the arm of the user swings, and when the device is located on the leg or the foot of the user, the acceleration data is acceleration data when the leg or the foot of the user moves.
And S102, periodically matching the acceleration data of each coordinate axis, and taking the coordinate axis with the maximum periodicity as a target step recording axis.
And after the acceleration data of each coordinate axis is obtained, periodically matching the acceleration data of each coordinate axis. For example, an acceleration curve for each coordinate axis is plotted for the acceleration data for each coordinate axis, and whether the acceleration curve has periodicity or not is determined. As shown in fig. 2, taking the X coordinate axis as an example, assuming that the acceleration curve of the X coordinate axis is composed of 20 pieces of acceleration data, where 18 points satisfy the periodicity rule, and two points have poor periodicity, then 18 may be used as the periodicity matching value of the X coordinate axis. Similarly, of the 20 pieces of acceleration data, a value of the periodicity matching property of the Y coordinate axis, which is assumed to be 15, and a value of the periodicity matching property of the Z coordinate axis, which is assumed to be 16, can be obtained. Then, the coordinate axis with the largest periodic matching value is used as the target step-recording axis, i.e., the X coordinate axis is used as the target step-recording axis.
Optionally, the period similarity between the acceleration data on each coordinate axis may be calculated, and the period similarity is used as the periodicity. For example, a reference period is selected from an acceleration curve of an X coordinate axis, a period similarity between each acceleration data and a corresponding point on the reference period is determined, for example, an acceleration data point r and an acceleration data point s corresponding to the periodicity in the reference period are determined, an amplitude difference and a time difference between r and s are calculated, and when the amplitudes between the two points are the same and the time difference is a period duration T of the reference period, the similarity between the two points can be determined to be 100%. By referring to the method, the period similarity of each acceleration data on each coordinate axis can be obtained, and the coordinate axis with the maximum period similarity sum is used as a target step recording axis.
Optionally, the periodicity value may be determined according to the periodicity of the inflection points by determining the inflection points in the acceleration data corresponding to each coordinate axis. For example, it is determined whether the amplitude of a certain turning point of a certain coordinate axis is the same as the amplitude of the corresponding turning point in the preceding and following periods, and whether the time duration therebetween is a period, and if so, it is determined that the turning point has periodicity. According to the method, the periodicity of each turning point on each coordinate axis can be judged, and then the coordinate axis with the largest number of turning points matched periodically is used as a target step recording axis. The specific process refers to the following detailed description of the embodiments, which is not repeated herein.
And S103, determining the step number of the user according to the acceleration data corresponding to the target step recording shaft.
After the target pacing axis is determined, the number of steps of the user is determined based on the acceleration data on the target pacing axis based on the target pacing axis.
For example, according to the acceleration data corresponding to the target step-recording axis, an acceleration curve of the target step-recording axis is drawn, and the step number of the user is determined according to the number of troughs and/or peaks in the acceleration curve, wherein one trough or one peak represents one step. Assume that the acceleration curve has 8 peaks and 7 valleys, i.e. the user has 15 steps.
Alternatively, the number of steps of the user may also be determined by calculating the number of turning points. Specifically, for each acceleration data corresponding to the target step recording axis, one acceleration data is selected as a research object, the acceleration data is compared with two adjacent acceleration data, and when the acceleration data is larger than the two adjacent acceleration data or the acceleration data is smaller than the two adjacent acceleration data, the acceleration data is determined to be a turning point. According to the method, the turning points of the target step-recording axis can be determined, and the number of the turning points is determined as the number of steps of the user.
Optionally, the step recording device may also determine the number of steps of the user based on acceleration data corresponding to the target step recording axis according to other methods.
According to the step recording method provided by the embodiment of the invention, the three-axis acceleration data of the equipment carried by the user is acquired, the periodic matching is respectively carried out on the acceleration data of each coordinate axis, the coordinate axis with the largest periodicity is used as a target step recording axis, and the step number of the user is determined according to the acceleration data corresponding to the target step recording axis. That is, in the embodiment, because the periodicity of the user in the motion process is considered, the coordinate axis with the largest periodicity is used as the target step recording axis, and the step number of the user is accurately obtained based on the acceleration data of the target step recording axis, so that the step recording of the user is accurately realized.
In a possible implementation manner of the embodiment of the present invention, before the step S102 performs periodic matching on the acceleration data of each coordinate axis, the method of the embodiment may further include:
s100, filtering the triaxial acceleration data by using a filter bank, wherein the filter bank comprises different types of filters, and the cut-off frequencies corresponding to the different types of filters are different.
In the prior art, a low-pass digital filter is arranged in a human step frequency range, the passband of the low-pass digital filter is generally 0-4Hz, and the maximum frequency in an acceleration signal waveform which can obviously present the human step frequency is far more than 4Hz in the actual situation, so that the digital filter is designed in such a way that the low-pass digital filter is not suitable for a step recording mode according to wave crests or wave troughs. In the embodiment, when the same user is in different motion forms or the motion habits of different users are different, different filters can be adopted to adapt to the asynchronous walking mode, so that the accuracy of the step recording precision under different walking modes is ensured. That is, the filter bank of the present embodiment may be applied to the extreme high-low frequency walking mode (e.g., slow walking, fast walking, running) to improve the step-recording accuracy in the extreme high-low frequency walking mode.
The filter bank of the embodiment comprises different types of filters, and the different types of filters have different corresponding cut-off frequencies, so that acceleration data of asynchronous frequencies can be filtered.
For example, when the user is walking slowly, the frequency of the acceleration data is low, and the acceleration data may be filtered by using a low-pass filter to obtain filtered acceleration data. When the user runs, the frequency of the acceleration data is high, and the acceleration data can be filtered by using a high-pass filter at the moment to obtain the filtered acceleration data.
Optionally, the embodiment may use a moving average filtering method to perform filtering, specifically, consider N sampling values obtained continuously as a queue, where the length of the queue is N, and each time a new data is obtained by sampling, the new data is put into the head of the queue, and a data at the tail of the original queue is discarded (first in first out). And carrying out arithmetic mean operation on the N data in the queue to obtain a new filtering result. Finally, the moving average filtering method can be regarded as a window with a fixed width of N, which slides on the time axis and outputs a filtering value once per sliding.
After S100, S103 may specifically include: and respectively carrying out periodic matching on the filtered acceleration data of each coordinate axis, and taking the coordinate axis with the maximum periodicity as a target step recording axis.
In the embodiment, the filter banks with different cut-off frequencies are set according to different step frequencies when the user moves, so that the accuracy of step recording precision under different running modes is ensured, and the accuracy of step recording of the user is further improved.
Fig. 3 is a flowchart of a step recording method according to a second embodiment of the present invention, and on the basis of the second embodiment, the present embodiment relates to a specific process in which a step recording device performs periodic matching on the filtered acceleration data of each coordinate axis. As shown in fig. 3, the S102 may specifically include:
s201, respectively obtaining turning points in the filtered acceleration data corresponding to each coordinate axis.
In this embodiment, a three-point comparison method may be used to determine each turning point in the filtered acceleration data corresponding to each coordinate axis. Specifically, for filtered acceleration data of a certain coordinate axis, acquiring an acceleration number as target acceleration data, and when the target acceleration data is greater than the acceleration data at a previous moment and greater than the acceleration data at a next moment, determining that the target acceleration data is a turning point, and the turning point is a maximum value; or when the target acceleration data is smaller than the acceleration data at the previous moment and smaller than the acceleration data at the next moment, determining that the target acceleration data is a turning point, and the turning point is a minimum value.
For example, as shown in fig. 2, it is assumed that fig. 2 is an acceleration waveform diagram of the acceleration data of the X coordinate axis after passing through the filter 1. As can be seen from fig. 2, two steps are a period, the waveform exhibits strong periodicity, and the periodic determination can avoid multiple steps being mistakenly recorded in non-periodic actions. The specific implementation is as follows: assume in FIG. 2 that sample point 0 has a magnitude of AMP0, sample point 1 has a magnitude of AMP1, sample point 2 has a magnitude of AMP2, sample point 6 has a magnitude of AMP6, sample point 7 has a magnitude of AMP7, and sample point 8 has a magnitude of AMP 8. Since AMP1< AMP0 and AMP1< AMP2, sample point 1 is the inflection point, and since AMP7> AMP6 and AMP7> AMP8, sample point 7 is also the inflection point, according to the above method, each inflection point corresponding to each coordinate axis can be obtained.
S202, for each turning point on each coordinate axis, acquiring a first amplitude difference and a first time difference between the turning point and the next turning point, acquiring a first turning point corresponding to the turning point in an adjacent period, and acquiring a second amplitude difference and a second time difference between the first turning point and the next turning point.
S203, judging whether the first amplitude difference is equal to the second amplitude difference, and judging whether the first time difference is equal to the second time difference.
With continued reference to fig. 2, sample point 1 is the previous inflection point of sample point 7, the magnitude difference Δ AMP1 between sample point 1 and sample 7 is obtained, Δ AMP1 is taken as the first magnitude difference, and the TIME difference Δ TIME1 between sample point 1 and sample 7 is obtained, Δ TIME1 is taken as the first TIME difference. Sample point 3 is the first inflection point of sample point 1 corresponding to the next adjacent cycle, the next inflection point of sample point 3 is sample 4, according to the above method, the amplitude difference Δ AMP2 between sample point 3 and sample 4 is obtained, Δ AMP2 is used as the second amplitude difference, and the TIME difference Δ TIME2 between sample point 3 and sample 4 is obtained, and Δ TIME2 is used as the second TIME difference. Then, whether the first amplitude difference is equal to the second amplitude difference and whether the first time difference is equal to the second time difference are determined. If the two are equal, the periodic matching of the turning point is determined to be successful. It should be noted that, in this embodiment, equality is not completely equal, but a difference between the first amplitude difference and the second amplitude difference, and a difference between the first time difference and the second time difference may satisfy a small value.
Optionally, the first amplitude difference and the first time difference in this embodiment may also be an amplitude difference and a time difference between the turning point and a previous turning point, and the corresponding second amplitude difference and the corresponding second time difference may also be an amplitude difference and a time difference between the first turning point and the previous turning point.
For example, by using a first-in first-out principle, taking a first amplitude difference and a first time difference corresponding to 4 rising edges and 4 falling edges of a, b, c, and d buffered at the current time, and a second amplitude difference and a second time difference corresponding to 4 rising edges and 4 falling edges of e, f, g, and h as examples, if the periodicity is satisfied, the following condition (1) should be satisfied:
however, during the actual walking, the acquired acceleration waveform is a waveform that is approximately periodic, and therefore, the condition (1) is slightly modified in the periodic determination, as the condition (2):
wherein α and β are preset constants, which are specifically set according to actual needs, and this embodiment does not limit this.
Furthermore, in order to improve the accuracy of the periodic matching, it is further required to determine that the first amplitude difference and the second amplitude corresponding to the turning point cannot exceed the limit values corresponding to the human motion states. Specifically, after the first amplitude difference is equal to the second amplitude difference and the first time difference is equal to the second time difference according to the above determination, the steps of S204 and S205 need to be executed.
S204, judging whether the first amplitude difference is within a preset amplitude interval or not, and judging whether the first time difference is within a preset period interval or not.
S205, if yes, determining that the turning point is successfully matched periodically.
The preset amplitude interval is an extreme value of a corresponding motion amplitude of a human under a motion state, and specifically comprises a maximum value and a minimum value. Similarly, the preset period interval is a limit value of a motion period corresponding to the human being in the motion state, and specifically includes a maximum value and a minimum value. After determining that the first amplitude difference and the first time difference satisfy the condition (2), it is further determined whether the first amplitude difference satisfies a preset amplitude interval and the first time difference satisfies a preset period interval, and if the first amplitude difference corresponding to the turning point falls within the preset amplitude interval and the first time difference falls within the preset period interval, it is determined that the periodic matching of the turning point is successful. And when any one of the first amplitude difference and the first time difference does not meet the condition, determining that the turning point is not matched periodically.
S206, obtaining the number of first turning points which are successfully matched periodically in each turning point corresponding to each coordinate axis, and taking the coordinate axis corresponding to the maximum number of the first turning points as a target step recording axis.
With reference to the above method, it can be determined whether each turning point corresponding to each coordinate axis is periodically matched, and the periodically matched turning point in each coordinate axis is obtained and is recorded as the first turning point. Therefore, the number of the first turning points corresponding to each coordinate axis can be obtained, and the coordinate axis with the largest number of the first turning points is used as the target step recording axis.
For example, the buffered acceleration data of each coordinate axis at the current moment includes 20 turning points, and according to the above method, the turning points corresponding to each coordinate axis are periodically matched. It is assumed that 18 turning points are successfully matched periodically in the X coordinate axis, 15 turning points are successfully matched periodically in the Y coordinate axis, and 10 turning points are successfully matched periodically in the Z coordinate axis. At this time, the X coordinate axis with the largest number of successful periodic matching is used as the target step-recording axis, and the acceleration data corresponding to the X coordinate axis is used to determine the step number of the user.
The step recording method provided by the embodiment of the invention acquires the turning point in the acceleration data corresponding to each coordinate axis, acquires the first amplitude difference and the first time difference between the turning point and the next turning point, and the second amplitude difference and the second time difference between the first turning point corresponding to the turning point and the next turning point in the adjacent period, matches the first amplitude difference and the second amplitude difference, and matches the first time difference and the second time difference, when the first amplitude difference is equal to the second amplitude difference and the first time difference is equal to the second time difference, determines that the periodic matching of the turning point is successful, and uses the coordinate axis corresponding to the turning point with the most periodic matching as the target step recording axis, and accurately records the step of the user based on the acceleration data of the target step recording axis.
Fig. 4 is a flowchart of a step recording method according to a third embodiment of the present invention, and fig. 5 is a signaling flowchart of the step recording method shown in fig. 4. On the basis of the above embodiments, the present embodiment relates to a specific process in which the step counting device determines the number of steps of the user according to the acceleration data corresponding to the target step counting axis. As shown in fig. 4 and 5, the S103 may specifically include:
s301, judging whether a third time difference between the turning point of the current periodic matching and the turning point of the previous periodic matching is larger than or equal to a first threshold value or not for each turning point in the acceleration data corresponding to the target step recording axis.
As shown in fig. 4 and 5, after the target pace making axis is determined according to the above steps, the user is paced using the acceleration data corresponding to the target pace making axis. Specifically, according to the method of the above embodiment, it is first determined whether the acceleration data corresponding to the target pace-making axis is a turning point, and if so, the number of peaks and valleys formed at the turning point is recorded by waveform [ i ] + +. Then, whether the turning point meets the periodicity or not and whether the period corresponding to the turning point meets the period value T of the acceleration data corresponding to the target step-recording axis or not are judged. If the turning point satisfies the periodicity, a third time difference between the turning point and a turning point that is periodically matched with the previous turning point is obtained, and it is determined whether the third time difference is greater than or equal to a preset first threshold, where the first threshold is based on a motion limit value of the user in different motion forms, for example, when the user walks, a maximum value of the time difference between two steps, and a size of the first threshold is set according to a time condition, which is not limited in this embodiment.
And S302, if so, determining the step number of the user according to the third time difference and the periodic value of the acceleration data corresponding to the target step recording axis.
And S303, if not, determining the step number of the user according to the number of turning points of the acceleration data corresponding to the target step recording axis.
If the third time difference between the turning point and the turning point successfully matched with the previous periodicity is greater than the first threshold, it indicates that the turning point is successfully matched with the periodicity at this time, but the periodicity is poor, for example, the turning point periodicity is poor when the user has irregular movements of the hand during the walking process (for example, the movements of answering a call, eating things, etc. are inserted into the walking process). At this time, the number of steps of the user may be determined according to a period value of the acceleration data corresponding to the target step recording axis and the third time difference. For example, according to stepreturn ═ 2timeB [ i ]/T, where stepreturn is the step number compensation, timeB [ i ] is the third time difference, the total step number of the user is the previously calculated step number plus the step number compensation, e.g., the turning point is the 9 th turning point, the total step number of the user is 2+2timeB [ i ]/T. Then setting timeB [ i ] as 0, setting waveform [ i ] as 0, and continuing to judge the next turning point.
If the third time difference between the turning point and the turning point which is matched with the previous periodicity is smaller than the first threshold, the periodicity of the turning point is strong, and the step number of the user can be determined according to the number of the turning points of the acceleration data corresponding to the target step recording axis. For example, the step number compensation of the user is obtained according to the formula Steps Return ═ waveform [ i ]/2, where waveform [ i ]/2 is 0.5 step when waveform [ i ] ≦ 1. And the total step number of the user is the previously calculated step number plus the compensation step number, for example, the turning point is the 9 th turning point, and the total step number of the user is 2+ wave [ i ]/2. Then setting timeB [ i ] as 0, setting waveform [ i ] as 0, and continuing to judge the next turning point.
It should be noted that, as shown in fig. 5, the present embodiment determines the period of the acceleration data corresponding to the target step-recording axis according to the first 8 turning points. Specifically, the first 4 turning points are used to determine the waveform of a period, and then the 4 turning points corresponding to the second period are used to detect whether the period determined by the first 4 turning points is established, that is, whether the period Count [ i ] between the last 4 turning points and the corresponding 4 turning points in the previous period is equal to 1 is determined, wherein the period Count is an index of real-time periodicity strength. If the two are equal to 1, determining that each turning point on the next period is matched with the period of each turning point on the previous period, and when the waveform [ i ] is 8, the user walks for 2 steps. After the period is determined, starting from the 9 th turning point, whether the periodicity between the turning point and the turning point corresponding to the previous two periods is matched is determined according to the method, and the specific process refers to the description of the above embodiment, which is not described herein again.
In the step recording method provided by the embodiment of the invention, whether a third time difference between a current turning point which is periodically matched and a previous turning point which is periodically matched is greater than or equal to a first threshold value or not is judged through each turning point in acceleration data corresponding to the target step recording axis; if so, determining the step number of the user according to the third time difference and the periodic value of the acceleration data corresponding to the target step recording axis; if not, determining the step number of the user according to the number of turning points of the acceleration data corresponding to the target step recording axis, so that accurate step recording of the user is realized, and the user experience is improved.
Fig. 6 is a flowchart of a step recording method according to a fourth embodiment of the present invention, and fig. 7 is an acceleration waveform diagram corresponding to different motion patterns. On the basis of the above embodiments, the present embodiment relates to a specific process in which the step recording device determines the motion form of the user. As shown in fig. 6, the present embodiment may include:
s401, determining first energy of the acceleration data according to the maximum value and the minimum value of the acceleration data amplitude corresponding to the target step recording axis.
As shown in FIG. 7, the acceleration waveforms formed by the user under different motion patterns are different, wherein the amplitude of the slow walking is different<Amplitude of normal walking<Amplitude of fast walk<Amplitude of jogging<Amplitude of normal running<Amplitude of sprint. Thus, the first energy of the acceleration data corresponding to the target pacing axis may be determined based on the acceleration data corresponding to the target pacing axis and the maximum and minimum values of the amplitude, e.g., according to equation P1＝max([acc1,acc2,…accn])-min([acc1,acc2,…accn]) Obtaining a first energy P of the acceleration data1And the acc is the amplitude of the acceleration data, and the n is the number of the acceleration data corresponding to the target step-recording axis.
Then, the P is added1Comparing with preset threshold corresponding to each motion form, if the P is1And when the current movement form is matched with the preset threshold of a certain movement form, determining that the movement form corresponding to the preset threshold is the current movement form of the user. Specifically, a target first interval intersecting with the first energy is obtained, and if the number of the target first intervals is one, the motion form of the user is determined to be the motion form corresponding to the target first interval. Wherein, the first intervals corresponding to different motion forms are different.
As shown in fig. 7, for the same part of the same person, running can be distinguished by the first energy of the acceleration fluctuation. The target first intervals which are needed to be set by different people may be slightly different, the default target first interval can be distinguished for most people to walk, but misjudgment may occur in the processes of fast walking, slow walking and going upstairs and downstairs. That is, when the number of the target first intervals intersected with the first energy is at least two, the following steps need to be further executed in this embodiment:
s402, determining second energy of the acceleration data according to the sum of absolute values of amplitude differences of two adjacent acceleration data in the acceleration data corresponding to the target step recording axis.
This embodiment is to the motion form that can't confirm according to first energy, if the product is bracelet or wrist-watch, can increase the judgement of the second energy when swinging perpendicularly to the arm and lifting up the swing, judges the wrist promptly and is in the perpendicular arm-swinging when walking or the arm-swinging of carrying when running, and then has improved the accuracy of walking and running discernment.
In particular, according to the formula
Calculating a second energy P of the acceleration data2Wherein acciIs the magnitude of the ith acceleration data.
And S403, determining the motion form of the user according to the first energy and the second energy.
Specifically, when the number of the target first intervals intersected with the first energy is at least two, the first operation form set corresponding to each target first interval is obtained. And then, acquiring a target second interval intersected with the second energy, and acquiring a second operation form set corresponding to the target second interval. Then, the same operation form in the first operation form set and the second operation form set is used as the motion form of the user. Wherein the second intervals corresponding to different movement patterns are different.
For example, the first energy P of the acceleration data corresponding to the target step-recording axis at the current moment is determined according to the method1And a second energy P2. Assuming a first energy P1The intersected target first interval is a target first interval A and a target first interval B, wherein the motion form corresponding to the target first interval A is fast walking, and the motion form corresponding to the target first interval B is slow running. Determined according to the above method and the second energy P2The intersected target second interval is a target second interval C and a target second interval D, wherein the target second interval C corresponds to movementThe form is jogging, and the motion form corresponding to the target second interval D is going upstairs and downstairs. At the moment according to the first energy P1And a second energy P2The same motion pattern in the determined motion pattern is jogging, i.e. the motion pattern of the user at the current moment is jogging.
According to the step recording method provided by the embodiment of the invention, the first energy of the acceleration data is determined according to the maximum value and the minimum value of each acceleration data amplitude corresponding to the target step recording shaft; and determining a motion pattern of the user based on the first energy. When a plurality of motion forms of the user are determined according to the first energy, determining second energy of the acceleration data according to the sum of absolute values of amplitude differences of two adjacent acceleration data in the acceleration data corresponding to the target step recording axis; and determining the motion form of the user according to the first energy and the second energy, thereby improving the accuracy of the walking and running recognition.
Fig. 8 is a structural diagram of a step counter according to an embodiment of the present invention. The step-counting device of the present embodiment may be a wearable device, and the step-counting device may be software, hardware, or a combination of software and hardware. As shown in fig. 8, the step recording apparatus of the present embodiment includes:
the acquisition module 10 is configured to acquire triaxial acceleration data of a device carried by a user;
the periodicity matching module 20 is used for performing periodicity matching on the acceleration data of each coordinate axis respectively, and taking the coordinate axis with the largest periodicity as a target step recording axis;
and the determining module 30 is configured to determine the step number of the user according to the acceleration data corresponding to the target step recording axis.
The step recording device shown in the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
Fig. 9 is a structural diagram of a step counter according to a second embodiment of the present invention. On the basis of the above embodiment, the apparatus of this embodiment further includes:
and a filtering module 40, configured to filter the triaxial acceleration data by using a filter bank, where the filter bank includes different types of filters, and cut-off frequencies of the different types of filters are different.
The periodicity matching module 20 is specifically configured to perform periodicity matching on the filtered acceleration data of each coordinate axis, and use the coordinate axis with the largest periodicity as the target step-recording axis.
The step recording device shown in the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
Fig. 10 is a structural diagram of a step counter according to a third embodiment of the present invention. On the basis of the above embodiment, the apparatus of this embodiment further includes a determining module 50:
the obtaining module 10 is further configured to obtain turning points in the filtered acceleration data corresponding to each coordinate axis, and for each turning point on each coordinate axis, obtain a first amplitude difference and a first time difference between the turning point and a subsequent turning point, obtain a first turning point corresponding to the turning point in an adjacent period, and obtain a second amplitude difference and a second time difference between the first turning point and the subsequent turning point.
The determining module 50 is configured to determine whether the first amplitude difference is equal to the second amplitude difference, and determine whether the first time difference is equal to the second time difference.
The determining module 30 is configured to determine that the turning point is successfully matched periodically when the determining module 50 determines that the first amplitude difference is equal to the second amplitude difference and determines that the first time difference is equal to the second time difference.
In a possible implementation manner of this embodiment, the determining module 50 is further configured to determine whether the first amplitude difference is within a preset amplitude interval and determine whether the first time difference is within a preset period interval after determining that the first amplitude difference is equal to the second amplitude difference and the first time difference is equal to the second time difference.
The determining module 30 is configured to determine that the turning point is successfully matched periodically when the determining module 50 determines that the first amplitude difference is within a preset amplitude interval and determines that the first time difference is within a preset period interval.
The step recording device shown in the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
In a possible implementation manner of this embodiment, the obtaining module 10 is further configured to obtain the number of first turning points that are successfully matched periodically in each turning point corresponding to each coordinate axis.
The determining module 30 is further configured to use the coordinate axis corresponding to the maximum number of the first turning points as the target step-recording axis.
In another possible implementation manner of this embodiment, the determining module 50 is further configured to determine, for each turning point in the acceleration data corresponding to the target step-recording axis, whether a third time difference between a turning point of a current periodic matching and a turning point of a previous periodic matching is greater than or equal to a first threshold.
The determining module 30 is further configured to determine the step number of the user according to the third time difference and the period value of the acceleration data corresponding to the target step recording axis when the determining module 50 determines that the third time difference between the turning point of the current periodic matching and the turning point of the previous periodic matching is greater than or equal to the first threshold.
The determining module 30 is further configured to determine the number of steps of the user according to the number of turning points of the acceleration data corresponding to the target step-recording axis when the determining module 50 determines that the third time difference between the turning point of the current periodic matching and the turning point of the previous periodic matching is smaller than the first threshold.
The step recording device shown in the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
In another possible implementation manner of this embodiment, the determining module 30 is further configured to determine the first energy of the acceleration data according to a maximum value and a minimum value of each acceleration data amplitude corresponding to the target step-recording axis; and determining a motion pattern of the user based on the first energy.
In another possible implementation manner of this embodiment, the determining module 30 is further configured to, when it is determined that the user has at least two motion forms according to the first energy, determine a second energy of the acceleration data according to a sum of absolute values of amplitude differences between two adjacent acceleration data in the acceleration data corresponding to the target step-recording axis; and determining a motion profile of the user based on the first energy and the second energy.
In another possible implementation manner of this embodiment, the obtaining module 10 is further configured to obtain first target intervals intersecting with the first energy, where the first intervals corresponding to different motion forms are different.
The determining module 30 is configured to determine, when the target first interval is one, that the motion form of the user is the motion form corresponding to the target first interval.
In another possible implementation manner of this embodiment, the obtaining module 10 is further configured to obtain, when the number of the target first intervals is at least two, a first operation form set corresponding to each target first interval; and acquiring second target intervals intersected with the second energy, and acquiring a second operation form set corresponding to the second target intervals, wherein the second intervals corresponding to different motion forms are different.
The determining module 30 is configured to use the same operation form in the first operation form set and the second operation form set as the motion form of the user.
The step recording device shown in the embodiment of the present invention may implement the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A step recording method, comprising:
acquiring triaxial acceleration data of equipment carried by a user;
filtering the triaxial acceleration data by using a filter bank, wherein the filter bank comprises different types of filters, and the cut-off frequencies of the different types of filters are different;
respectively acquiring turning points in the filtered acceleration data corresponding to each coordinate axis, wherein the turning points comprise maximum values and minimum values in the acceleration data;
for each turning point on each coordinate axis, acquiring a first amplitude difference and a first time difference between the turning point and the next turning point, acquiring a first turning point corresponding to the turning point in an adjacent period, and acquiring a second amplitude difference and a second time difference between the first turning point and the next turning point;
judging whether the first amplitude difference is equal to the second amplitude difference or not, and judging whether the first time difference is equal to the second time difference or not;
if so, determining that the turning point is successfully matched periodically;
obtaining the number of first turning points which are successfully matched periodically in each turning point corresponding to each coordinate axis, and taking the coordinate axis corresponding to the maximum number of the first turning points as a target step recording axis;
and determining the step number of the user according to the acceleration data corresponding to the target step recording shaft.
2. The method of claim 1, wherein after the first and second magnitude differences are equal and the first and second time differences are equal, the method further comprises:
judging whether the first amplitude difference is within a preset amplitude interval or not and judging whether the first time difference is within a preset period interval or not;
if so, determining that the turning point is successfully matched periodically.
3. The method according to claim 1, wherein the determining the number of steps of the user according to the acceleration data corresponding to the target step-recording axis specifically comprises:
judging whether a third time difference between the turning point which is periodically matched at present and the turning point which is periodically matched at the previous time is larger than or equal to a first threshold value or not for each turning point in the acceleration data corresponding to the target step recording axis;
if so, determining the step number of the user according to the third time difference and the periodic value of the acceleration data corresponding to the target step recording axis;
if not, determining the step number of the user according to the number of turning points of the acceleration data corresponding to the target step recording axis.
4. The method according to any one of claims 1-3, further comprising:
determining first energy of the acceleration data according to the maximum value and the minimum value of each acceleration data amplitude corresponding to the target step recording axis;
determining a motion profile of the user from the first energy.
5. The method of claim 4, wherein when it is determined from the first energy that the user has at least two forms of motion, the method further comprises:
determining second energy of the acceleration data according to the sum of absolute values of amplitude differences of two adjacent acceleration data in the acceleration data corresponding to the target step recording axis;
determining a motion profile of the user from the first energy and the second energy.
6. The method according to claim 5, wherein the determining the motion profile of the user from the first energy comprises:
acquiring first intervals of targets intersected with the first energy, wherein the first intervals corresponding to different motion forms are different;
and if the target first interval is one, determining that the motion form of the user is the motion form corresponding to the target first interval.
7. The method according to claim 6, wherein if the target first interval is at least two, the determining the motion form of the user according to the first energy and the second energy specifically comprises:
acquiring a first operation form set corresponding to each target first interval;
acquiring second target intervals intersected with the second energy, and acquiring a second operation form set corresponding to the second target intervals, wherein the second intervals corresponding to different motion forms are different;
and taking the same operation form in the first operation form set and the second operation form set as the motion form of the user.
8. A step recording device, comprising:
the acquisition module is used for acquiring triaxial acceleration data of equipment carried by a user;
the filtering module is used for filtering the triaxial acceleration data by using a filter bank, wherein the filter bank comprises different types of filters, and the cut-off frequencies corresponding to the different types of filters are different;
the obtaining module is further configured to obtain turning points in the filtered acceleration data corresponding to each coordinate axis, and for each turning point on each coordinate axis, obtain a first amplitude difference and a first time difference between the turning point and a subsequent turning point, obtain a first turning point corresponding to the turning point in an adjacent period, and obtain a second amplitude difference and a second time difference between the first turning point and the subsequent turning point, where the turning point includes a maximum value and a minimum value in the acceleration data;
the judging module is used for judging whether the first amplitude difference is equal to the second amplitude difference or not and judging whether the first time difference is equal to the second time difference or not;
the determining module is configured to determine that the turning point is successfully matched periodically when the determining module determines that the first amplitude difference is equal to the second amplitude difference and determines that the first time difference is equal to the second time difference;
the acquisition module is further configured to acquire the number of first turning points, which are successfully matched periodically, in each turning point corresponding to each coordinate axis;
the determining module is further configured to determine the number of steps of the user according to acceleration data corresponding to a target step-recording axis, where the coordinate axis corresponding to the maximum number of the first turning points is used as the target step-recording axis.
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