CN115193009A

CN115193009A - Sit-up frequency calculation method and wearable device

Info

Publication number: CN115193009A
Application number: CN202110386404.9A
Authority: CN
Inventors: 周奎
Original assignee: Guangdong Genius Technology Co Ltd
Current assignee: Guangdong Genius Technology Co Ltd
Priority date: 2021-04-09
Filing date: 2021-04-09
Publication date: 2022-10-18

Abstract

The embodiment of the invention discloses a method for calculating the sit-up times and wearable equipment, which are applied to the technical field of wearable equipment and can solve the problem that in the prior art, detection equipment with a counting function is easily interfered by other equipment, so that the counting is inaccurate. The method comprises the following steps: acquiring M first accelerations of a user in a first time length through a six-axis sensor; if the M first accelerations meet the preset sit-up characteristic, N second accelerations which are smaller than a preset acceleration threshold value in the M first accelerations are obtained; if the target acceleration smaller than the adjacent acceleration exists in the N second accelerations, determining the number of the target accelerations as the sit-up times of the user within the first time period; wherein the adjacent accelerations are a preceding acceleration and a succeeding acceleration of the target acceleration.

Description

Sit-up frequency calculation method and wearable device

Technical Field

The embodiment of the invention relates to the technical field of wearable equipment, in particular to a sit-up frequency calculation method and wearable equipment.

Background

Sit-up is a simple but effective aerobic exercise that can consume the abdominal fat of the exerciser and improve cardiopulmonary function. At present, the mechanical counting method is generally adopted in the sit-up count, and the check out test set that has the tally function can judge whether to have carried out a complete sit-up according to the undulation action of user's health, but the check out test set volume that has the tally function is great, and the operation is complicated to receive the interference of other equipment easily, lead to the count inaccurate.

Disclosure of Invention

The embodiment of the invention provides a sit-up frequency calculation method and wearable equipment, which are used for solving the problem that in the prior art, detection equipment with a counting function is easily interfered by other equipment, so that the counting is inaccurate. In order to solve the above technical problem, the embodiment of the present invention is implemented as follows:

in a first aspect, a method for calculating the number of sit-ups is provided, the method comprising: acquiring M first accelerations of a user in a first time length through a six-axis sensor;

if the M first accelerations meet the preset sit-up characteristic, N second accelerations which are smaller than a preset acceleration threshold value in the M first accelerations are obtained;

if the target acceleration smaller than the adjacent acceleration exists in the N second accelerations, determining the number of the target accelerations as the sit-up times of the user within the first time period;

wherein the adjacent acceleration is a preceding acceleration and a succeeding acceleration of the target acceleration.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, if there is a target acceleration smaller than an adjacent acceleration in the N second accelerations, determining the number of target accelerations as before the number of sit-ups of the user in the first time period, further includes:

determining an acceleration curve according to the M first accelerations;

acquiring P acceleration peak values positioned at a peak and Q acceleration valley values positioned at a trough in the acceleration curve, wherein P and Q are integers smaller than M;

and if the P acceleration peak values are all located in a first preset interval, and the Q acceleration valley values are all located in a second preset interval, determining that the M first accelerations meet the preset sit-up characteristic.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, if the P acceleration peaks are all in a first preset interval, and the Q acceleration valleys are all in a second preset interval, the determining that the M first accelerations satisfy the preset sit-up characteristic includes:

if the P acceleration peak values are all located in the first preset interval, and the Q acceleration valley values are all located in the second preset interval, determining the difference value between each acceleration peak value and the adjacent acceleration valley value;

and if the difference value is within a preset difference value interval, determining that the M first acceleration values meet the preset sit-up characteristic.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, after acquiring P acceleration peak values located at a peak and Q acceleration valley values located at a valley in the acceleration curve, the method further includes:

acquiring a first average value of the P acceleration peak values and a second average value of the Q acceleration valley values;

and if the first average value is in the first preset interval and the second average value is in the second preset interval, determining that the M first accelerations meet the preset sit-up characteristic.

As an alternative implementation manner, in the first aspect of the embodiment of the present invention, the acquiring, by a six-axis sensor, M first accelerations of the user in the first time period includes:

continuously acquiring K target accelerations and K target gyroscope data at K moments through the six-axis sensor;

calculating target arm attitude angles at the K moments according to the K target accelerations and the K target gyroscope data;

if the target arm posture angles at the K moments are all in a preset sit-up posture interval and the K target accelerations are all in a third preset interval, acquiring the M first accelerations of the user within the first duration through the six-axis sensor;

the preset sit-up posture interval is an arm posture angle interval corresponding to pre-stored sit-up movement.

acquiring K third accelerations of the user within the first duration through the six-axis sensor, wherein K is an integer greater than or equal to M;

and deleting a third acceleration with the difference value larger than or equal to a preset difference value threshold value from the adjacent acceleration to obtain the M processed first accelerations.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, after determining the number of the target accelerations as the number of sit-ups of the user in the first time period, the method further includes:

calculating the motion amplitude of the user according to the M first accelerations and a target formula;

if the motion amplitude of the user is larger than a preset amplitude threshold value, outputting a first prompt message, wherein the first prompt message is used for prompting the user to pay attention to rest;

wherein the target formula is:

s is the amplitude of motion, A _i For the ith first acceleration among the M first accelerations,

is the average of the M first accelerations.

In a second aspect, there is provided a wearable device comprising: the acquisition module is used for acquiring M first accelerations of a user in a first time length through a six-axis sensor;

the obtaining module is further configured to obtain N second accelerations greater than a preset acceleration threshold from among the M first accelerations if the M first accelerations satisfy a preset sit-up characteristic;

the processing module is used for determining the number of the target accelerations as the number of times of sit-ups of the user in the first time period if the target accelerations larger than the adjacent accelerations exist in the N second accelerations;

wherein the adjacent accelerations are a preceding acceleration and a succeeding acceleration of the target acceleration.

In a third aspect, a wearable device is provided, comprising:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute the method for calculating the number of times of sit-ups in the first aspect of the embodiment of the present invention.

In a fourth aspect, there is provided a computer-readable storage medium storing a computer program for causing a computer to execute the method for calculating the number of sit-ups in the first aspect of the embodiment of the present invention. The computer readable storage medium includes a ROM/RAM, a magnetic or optical disk, or the like.

In a fifth aspect, there is provided a computer program product for causing a computer to perform some or all of the steps of any one of the methods of the first aspect when the computer program product is run on the computer.

A sixth aspect provides an application publishing platform for publishing a computer program product, wherein the computer program product, when run on a computer, causes the computer to perform some or all of the steps of any one of the methods of the first aspect.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, the wearable device can acquire M first accelerations of a user in a first time length through a six-axis sensor; if these M first accelerations satisfy and predetermine the sit up characteristic, then can explain that wearable equipment detects that the user is carrying out effectual sit up motion, then wearable equipment just can be less than in M first accelerations and predetermine the sit up number of times of user in first time duration for the number of the target acceleration of predetermineeing the acceleration threshold value and being less than adjacent acceleration. Because the sit-up is a motion that has periodicity, the user can repeat the sit-up motion many times in first duration, and wearable equipment can detect the periodic law of M acceleration to select the target acceleration that accords with the condition in every cycle from it, thereby according to the cycle quantity in the target acceleration quantity accuracy determination first duration of condition, the sit-up number of times of user in first duration promptly.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a first schematic flowchart of a method for calculating the number of sit-ups according to an embodiment of the present invention;

fig. 2 is a data processing schematic diagram of a method for calculating the number of sit-ups according to an embodiment of the present invention;

fig. 3 is a schematic flow chart of a method for calculating the number of sit-ups according to an embodiment of the present invention;

fig. 4 is a first schematic structural diagram of a wearable device according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a wearable device according to an embodiment of the present invention;

fig. 6 is a schematic hardware structure diagram of a wearable device according to an embodiment of the present invention.

Detailed Description

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, 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.

The terms "first" and "second," and the like, in the description and in the claims of the present invention are used for distinguishing between different objects and not for describing a particular order of the objects. For example, the first acceleration and the second acceleration, etc. are used to distinguish between different accelerations, and are not used to describe a particular sequence of accelerations.

The terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "such as" in an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

In the related art, the sit-up is a simple but effective aerobic exercise that can consume abdominal fat of a sporter and improve the cardiopulmonary function. At present, a mechanical counting method is generally adopted for the sit-up counting, and a detection device with a counting function can judge whether a complete sit-up is performed according to the fluctuation action of the body of a user, but the detection device with the counting function is large in size and complex to operate, is easily interfered by other devices, and causes inaccurate counting.

In order to solve the above problem, an embodiment of the present invention provides a method for calculating the number of sit-ups and a wearable device, where the wearable device may acquire M first accelerations of a user within a first time duration through a six-axis sensor; if these M first accelerations satisfy and predetermine the sit up characteristic, then can explain that wearable equipment detects that the user is carrying out effectual sit up motion, then wearable equipment just can be less than in M first accelerations and predetermine the sit up number of times of user in first time duration for the number of the target acceleration of predetermineeing the acceleration threshold value and being less than adjacent acceleration. Because the sit-up is a periodic movement, the user can repeat the sit-up movement for many times in the first duration, the wearable device can detect the periodic regularity of M accelerations, and screen out the target acceleration meeting the conditions in each period, thereby accurately determining the number of periods in the first duration according to the number of target accelerations meeting the conditions, namely the sit-up times of the user in the first duration.

The wearable device related to the embodiment of the invention can be an intelligent watch, an intelligent bracelet, a watch phone and the like, and the embodiment of the invention is not limited. The user can wear the wearable device to perform sit-up exercise, so that the wearable device can detect the sit-up times of the user according to the sit-up time calculation method provided by the embodiment of the invention.

The executing main body of the sit-up number calculating method provided by the embodiment of the present invention may be the wearable device, or may also be a functional module and/or a functional entity capable of implementing the sit-up number calculating method in the wearable device, which may be specifically determined according to actual use requirements, and the embodiment of the present invention is not limited. The following takes a wearable device as an example to exemplarily explain the method for calculating the number of sit-ups provided by the embodiment of the present invention.

Example one

As shown in fig. 1, an embodiment of the present invention provides a method for calculating the number of sit-ups, which may include the following steps:

101. m first accelerations of a user in a first time period are obtained.

In the embodiment of the invention, the wearable device can acquire the M first accelerations of the user in the first time period through the six-axis sensor.

The M first accelerations correspond to M moments in a first time length.

Optionally, the six-axis sensor includes a three-axis acceleration sensor and a three-axis gyroscope sensor.

It should be noted that, in the three-dimensional rectangular coordinate system, the three-axis acceleration sensor detects the accelerations of the X axis, the Y axis and the Z axis respectively to obtain three acceleration components; the three-axis gyroscope sensor respectively senses dynamic angle changes of the wearable device rotating around an X axis, a Y axis and a Z axis to obtain three gyroscope data components.

Optionally, in this embodiment of the present invention, the M first accelerations obtained by the wearable device through the six-axis sensor may be M first accelerations including three acceleration components, or may be M first accelerations obtained by calculating a modulus value according to the three acceleration components.

Wherein, the modulus of the acceleration can be calculated by a modulus formula

Wherein A is _x 、A _y And A _z Three acceleration components, respectively.

For example, assuming that the wearable device obtains 5 accelerations through the acceleration sensor, the 5 accelerations may be respectively represented as an acceleration a: (5 m/s) ² ，3m/s ² ，8m/s ² ) The acceleration B: (6 m/s) ² ，2m/s ² ，4m/s ² ) Acceleration C: (3 m/s) ² ，3m/s ² ，3m/s ² ) And the acceleration D: (6 m/s) ² ，1m/s ² ，2m/s ² ) The acceleration E: (6 m/s) ² ，6m/s ² ，3m/s ² ) (ii) a The 5 first accelerations may also be respectively expressed as an acceleration a:

acceleration B:

acceleration C:

acceleration D:

acceleration E:

optionally, the obtaining M first accelerations of the user in the first time period may specifically include: acquiring K third accelerations of the user in the first time duration through a six-axis sensor, wherein K is an integer greater than or equal to M; and deleting the third acceleration with the difference value larger than or equal to the preset difference value threshold value from the adjacent acceleration to obtain the processed M first accelerations.

In the embodiment of the invention, the wearable device can firstly acquire K third accelerations through a three-axis acceleration sensor in the six-axis sensor, then filter the K third accelerations, filter out the accelerations with larger errors, and obtain M processed first accelerations.

It should be noted that, when the wearable device filters the K third accelerations, a difference between each third acceleration and an adjacent acceleration may be obtained; if the difference value between a certain third acceleration and the adjacent acceleration is larger than or equal to the preset difference threshold value, it indicates that an error occurs when the wearable device measures the third acceleration, so that the third acceleration deviates from a normal value, and the wearable device may delete the third acceleration.

Wherein the adjacent acceleration may be a previous acceleration of the third acceleration, and/or a subsequent acceleration.

Illustratively, assume that the preset difference threshold is 1m/s ² The wearable device acquires 6 third accelerations, which are respectively an acceleration a:5.1m/s ² The acceleration B:5.2m/s ² And the acceleration C:5.5m/s ² The acceleration D:9.2m/s ² And the acceleration E:5.8m/s ² The acceleration F:6.0m/s ² . The wearable device may calculate a difference between each third acceleration and the adjacent acceleration, and obtain an acceleration D through calculation; 9.2m/s ² Adjacent acceleration C:5.5m/s ² And acceleration E:5.8m/s ² Respectively, are 3.7m/s ² And 3.4m/s ² Are all larger than a preset difference threshold value of 1m/s ² Then the wearable device may compare the acceleration D:9.2m/s ² Deleting to obtain the rest five accelerations, namely M first accelerations are respectively 5.1M/s ² ，5.2m/s ² ，5.5m/s ² ，5.8m/s ² And 6.0m/s ² 。

102. And acquiring N second accelerations which are smaller than a preset acceleration threshold value in the M first accelerations.

In this embodiment of the present invention, if the M first accelerations satisfy the preset sit-up characteristic, the wearable device may acquire N second accelerations, where the N second accelerations are accelerations smaller than a preset acceleration threshold value among the M first accelerations.

Wherein the preset acceleration threshold is set by the wearable device according to the accelerations acquired multiple times.

Illustratively, assume that the preset acceleration threshold is 6m/s ² The wearable device obtains 10 first accelerations, which are acceleration a:4.2m/s ² The acceleration B:5.0m/s ² And the acceleration C:5.3m/s ² The acceleration D:6.5m/s ² And the acceleration E:8.3m/s ² The acceleration F:9.1m/s ² Acceleration G:10.2m/s ² The acceleration H:9.6m/s ² The acceleration I:8.4m/s ² Acceleration J:7.6m/s ² . The wearable device may then select less than 6m/s of the 10 first accelerations ² Is determined as a second acceleration, i.e. the second acceleration comprises: acceleration A:4.2m/s ² The acceleration B:5.0m/s ² And acceleration C:5.3m/s ² 。

Optionally, the M first accelerations satisfy a preset sit-up feature, which may specifically include the following six optional implementation manners:

the implementation mode is as follows: determining an acceleration curve according to the M first accelerations; acquiring P acceleration peak values positioned at a peak in an acceleration curve; and if the P acceleration peak values are all located in a first preset interval, determining that the M first accelerations meet the preset sit-up characteristic.

In this optional implementation manner, the wearable device may represent the M first accelerations in a rectangular coordinate system according to a time sequence, so as to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time, and a ordinate of the rectangular coordinate system is a numerical value of the first acceleration; the wearable device can acquire P acceleration peak values located at the peak from the acceleration curve, wherein P is an integer greater than or equal to 1; if the P acceleration peaks are all in the first preset interval, it can be said that the M first accelerations satisfy the preset sit-up characteristics.

Alternatively, if the user is performing a sit-up exercise, each jump rope cycle in the acceleration curve may be first decreased to an increased curve, as shown in fig. 2, and during each cycle, there is one overshoot, the wearable device may detect the overshoot amount and determine the overshoot amount as the sit-up number.

In the acceleration curve, the peak is the maximum value of the amplitude in a cycle of the acceleration change.

For example, as shown in fig. 2, the wearable device detects the first acceleration during 0-45ms, and it can be seen from fig. 2 that point a is the peak of the acceleration curve, and the value represented by point a is the acceleration peak during 0-45 ms. Assume that the first predetermined interval is 9m/s ² -11m/s ² From FIG. 2, it can be seen that the value represented by the point A is 10.5m/s ² At 9m/s ² -11m/s ² It can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

The second implementation mode is as follows: determining an acceleration curve according to the M first accelerations; obtaining Q acceleration valley values positioned in a valley in an acceleration curve; and if the Q acceleration valleys are all in a second preset interval, determining that the M first accelerations meet the preset sit-up characteristic.

In this optional implementation manner, the wearable device may represent the M first accelerations in a rectangular coordinate system according to a time sequence, so as to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time, and a ordinate of the rectangular coordinate system is a numerical value of the first acceleration; the wearable device can acquire Q acceleration valleys located at the valleys from the acceleration curve, wherein Q is an integer greater than or equal to 1; if the Q acceleration valleys are all within the second predetermined interval, it can be said that the M first accelerations satisfy the predetermined sit-up characteristics.

In the acceleration curve, the trough is the minimum value of the amplitude in a period range of the acceleration change.

For example, as shown in fig. 2, the wearable device detects the first acceleration during 0-45ms, and it can be seen from fig. 2 that point B is the valley of the acceleration curve, and the value represented by point B is the acceleration valley during 0-45 ms. Assuming that the second predetermined interval is 0m/s ² -3m/s ² From FIG. 2, it can be seen that the value represented by the point B is 1.5m/s ² At 0m/s ² -3m/s ² It can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

The implementation mode is three: determining an acceleration curve according to the M first accelerations; acquiring P acceleration peak values positioned at wave crests and Q acceleration valley values positioned at wave troughs in an acceleration curve; determining a difference between each acceleration peak and an adjacent acceleration valley; and if the difference value is within the preset difference value interval, determining that the M first accelerations meet the preset sit-up characteristic.

In this optional implementation manner, the wearable device may represent the M first accelerations in a rectangular coordinate system according to a time sequence, so as to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time, and a ordinate of the rectangular coordinate system is a numerical value of the first acceleration; the wearable device can obtain P acceleration peak values located at a peak and Q acceleration valley values located at a trough from the acceleration curve, wherein P and Q are integers greater than or equal to 1; determining a difference between each acceleration peak and an acceleration valley adjacent to the acceleration peak; if the difference is within the preset difference interval, it can be said that the M first accelerations satisfy the preset sit-up characteristic.

Alternatively, if the user is performing a sit-up exercise, each jump rope cycle in the acceleration curve may be first decreased to an increased curve, as shown in fig. 2, and within each cycle, there is one overshoot, the wearable device may detect the overshoot amount and determine the overshoot amount as the number of sit-ups.

It should be noted that, in the acceleration curve, the peak is the maximum value of the amplitude within a period range of acceleration change; the trough is the minimum of the amplitude over a period of acceleration change.

For example, as shown in fig. 2, the wearable device detects a first acceleration during 0-45ms, and it can be seen from fig. 2 that point a is a peak of the acceleration curve, and then the value represented by point a is an acceleration peak during 0-45 ms; it can also be seen that point B is the valley of the acceleration curve, and the value represented by point B is the acceleration valley during 0-45 ms. Assuming that the preset difference interval is 7m/s ² -13m/s ² From FIG. 2, it can be seen that the value represented by the point A is 10.5m/s ² The value represented by point B is 1.5m/s ² Then the difference between point A and point B is 9m/s ² At 7m/s ² -13m/s ² Within the range, it can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

The implementation mode is four: determining an acceleration curve according to the M first accelerations; acquiring P acceleration peak values positioned at wave crests and Q acceleration valley values positioned at wave troughs in an acceleration curve; if P acceleration peak values are all located in a first preset interval, and Q acceleration valley values are all located in a second preset interval, determining that M first accelerations meet preset sit-up characteristics.

In this optional implementation manner, the wearable device may represent the M first accelerations in a rectangular coordinate system according to a time sequence, so as to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time, and a ordinate of the rectangular coordinate system is a numerical value of the first acceleration; the wearable device can obtain P acceleration peak values located at a peak and Q acceleration valley values located at a trough from the acceleration curve, wherein P and Q are integers greater than or equal to 1; if the P acceleration peaks are all in the first preset interval and the Q acceleration valleys are all in the second preset interval, it can be said that the M first accelerations satisfy the preset sit-up characteristics.

It should be noted that, in the acceleration curve, the peak is the maximum value of the amplitude in a period range of acceleration change; the trough is the minimum of the amplitude over a period of acceleration change.

For example, as shown in fig. 2, the wearable device detects a first acceleration during 0-45ms, and it can be seen from fig. 2 that point a is a peak of the acceleration curve, and then the value represented by point a is an acceleration peak during 0-45 ms; it can also be seen that point B is the valley of the acceleration curve, and the value represented by point B is the acceleration valley during 0-45 ms. Assume that the first predetermined interval is 9m/s ² -11m/s ² The second preset interval is 0m/s ² -3m/s ² From FIG. 2, it can be seen that the value represented by the point A is 10.5m/s ² At 9m/s ² -11m/s ² It can also be seen that the value represented by point B is 1.5m/s ² At 0m/s ² -3m/s ² It can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

The implementation mode is five: determining an acceleration curve according to the M first accelerations; acquiring P acceleration peak values positioned at wave crests and Q acceleration valley values positioned at wave troughs in an acceleration curve; acquiring a first average value of P acceleration peak values and a second average value of Q acceleration valley values; and if the first average value is in a first preset interval and the second average value is in a second preset interval, determining that the M first accelerations meet the preset sit-up characteristic.

In this optional implementation, the wearable device may represent the M first accelerations in a rectangular coordinate system according to a time sequence, to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time and a ordinate of the rectangular coordinate system is a value of the first acceleration; the wearable device can acquire P acceleration peak values located at wave crests and Q acceleration valley values located at wave troughs from an acceleration curve, wherein both P and Q are integers greater than or equal to 1; the wearable device can calculate a first average value of the P acceleration peak values according to the P acceleration peak values, and then calculate a second average value of the Q acceleration valley values according to the Q acceleration valley values; if the first average value is within a first preset interval and the second average value is within a second preset interval, it can be said that the M first accelerations satisfy the preset sit-up characteristics.

For example, as shown in fig. 2, the wearable device detects a first acceleration during 0-45ms, and it can be seen from fig. 2 that point a is a peak of the acceleration curve, and then the value represented by point a is an acceleration peak during 0-45 ms; it can also be seen that point B is the valley of the acceleration curve, and the value represented by point B is the acceleration valley during 0-45 ms. Assume that the first predetermined interval is 9m/s ² -11m/s ² The second preset interval is 0m/s ² -3m/s ² It can be seen from FIG. 2 that the peak value of the acceleration has only one point A, and the first average value is the value of the point A, i.e. the first average value is 10.5m/s ² At 9m/s ² -11m/s ² It can also be seen that the acceleration valley is only a point B, and the first average value is the value of the point B, i.e. the first average value is 1.5m/s ² At 0m/s ² -3m/s ² It can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

The implementation mode is six: determining an acceleration curve according to the M first accelerations; acquiring P acceleration peak values positioned at a wave crest and Q acceleration valley values positioned at a wave trough in an acceleration curve; if the P acceleration peak values are all located in a first preset interval, and the Q acceleration valley values are all located in a second preset interval, determining the difference value between each acceleration peak value and the adjacent acceleration valley value; and if the difference value is within the preset difference value interval, determining that the M first accelerations meet the preset sit-up characteristic.

In this optional implementation manner, the wearable device may represent M first accelerations in a rectangular coordinate system according to a time sequence, to obtain an acceleration curve, where an abscissa of the rectangular coordinate system is a time, and a ordinate of the rectangular coordinate system is a value of the first acceleration; the wearable device can acquire P acceleration peak values located at wave crests and Q acceleration valley values located at wave troughs from an acceleration curve, wherein both P and Q are integers greater than or equal to 1; if the P acceleration peaks are all within a first preset interval and the Q acceleration valleys are all within a second preset interval, the wearable device may determine a difference between each acceleration peak and an acceleration valley adjacent to the acceleration peak; if the difference is within the preset difference interval, it can be said that the M first accelerations satisfy the preset sit-up characteristic.

For example, as shown in fig. 2, the wearable device detects a first acceleration during 0-45ms, and it can be seen from fig. 2 that point a is a peak of the acceleration curve, and then the value represented by point a is an acceleration peak during 0-45 ms; it can also be seen that point B is the valley of the acceleration curve, and the value represented by point B is the acceleration valley during 0-45 ms. Assume that the first predetermined interval is 9m/s ² -11m/s ² The second preset interval is 0m/s ² -3m/s ² The preset difference interval is 7m/s ² -13m/s ² From FIG. 2, it can be seen that the value represented by the point A is 10.5m/s ² At 9m/s ² -11m/s ² It can also be seen that the value represented by point B is 1.5m/s ² At 0m/s ² -3m/s ² Then the difference between point A and point B is 9m/s ² At 7m/s ² -13m/s ² Within the range, it can be stated that the first acceleration during 0-45ms satisfies the preset sit-up characteristic.

103. And determining the number of the target acceleration as the sit-up times of the user in the first time length.

In this embodiment of the present invention, if there is a target acceleration smaller than the adjacent acceleration in the N second accelerations, the wearable device may determine the number of target accelerations as the number of sit-ups of the user in the first time period.

It should be noted that the target acceleration needs to be smaller than two accelerations adjacent to the target acceleration, so that the target acceleration may be a trough, and the target acceleration may be a sit-up number.

For example, assume that the wearable device acquires 10 second accelerations, which are acceleration a:2.6m/s ² The acceleration B:1.8m/s ² And the acceleration C:1.9m/s ² The acceleration D:1.9m/s ² The acceleration E:1.6m/s ² And the acceleration F:2.4m/s ² Acceleration G:2.6m/s ² The acceleration H:0.9m/s ² The acceleration I:1.1m/s ² And the acceleration J:1.3m/s ² . The wearable device can obtain the acceleration B through calculation: 1.8m/s ² Less than adjacent acceleration a:2.6m/s ² And acceleration C:1.9m/s ² The acceleration E:1.6m/s ² Smaller than adjacent acceleration D:1.9m/s ² And acceleration F:2.4m/s ² The acceleration I:1.1m/s ² Smaller than adjacent acceleration G:0.9m/s ² And acceleration J:1.3m/s ² (ii) a That is, the target acceleration includes: acceleration B:1.8m/s ² Acceleration E:1.6m/s ² And acceleration I:1.1m/s ² Then, the wearable device may determine the number of target accelerations as the number of sit-ups of the user within the first time period, i.e. the number of sit-ups of the user within the first time period is 3.

The embodiment of the invention provides a method for calculating the number of sit-ups, wherein wearable equipment can acquire M first accelerations of a user in a first time length through a six-axis sensor; if this M first acceleration satisfies predetermines sit up characteristic, then can explain that wearable equipment detects that the user is carrying out effectual sit up motion, then wearable equipment just can be greater than in M first acceleration and predetermine the sit up number of times of user in first time length for the number of the target acceleration of predetermineeing the acceleration threshold value and being greater than adjacent acceleration. Because the sit-up is a motion that has periodicity, the user can repeat the sit-up motion many times in first duration, and wearable equipment can detect the periodic law of M acceleration to select the target acceleration that accords with the condition in every cycle from it, thereby according to the cycle quantity in the target acceleration quantity accuracy determination first duration of condition, the sit-up number of times of user in first duration promptly.

Example two

As shown in fig. 3, an embodiment of the present invention provides a method for calculating the number of sit-ups, which may further include the following steps:

301. and continuously acquiring K target accelerations and K target gyroscope data at K moments.

In the embodiment of the invention, the wearable device can continuously acquire K target accelerations and K target gyroscope data at K moments through the six-axis sensor.

Wherein the K times may be times other than the first time length.

302. And calculating the target arm attitude angles at K moments.

In the embodiment of the invention, the wearable device can calculate the target arm attitude angles of the user at K moments according to the K target accelerations and the K target gyroscope data.

Wherein the target arm pose angle may be used to indicate an arm pose of the user.

Optionally, the wearable device may calculate the target arm attitude angle at K moments according to the K target accelerations and the K target gyroscope data through a Mahony algorithm.

The Mahony algorithm is a common attitude fusion algorithm, and six-axis data of an acceleration sensor and a gyroscope are fused and solved to calculate the quaternion of the body.

It should be noted that the target arm pose angle can generally have three description forms, which are: euler angles, direction cosine matrices, and quaternions.

Optionally, the target arm attitude angle may be obtained by performing three euler angle rotations around a rigid coordinate system in a z-x-z axis sequence, and the target arm attitude angle may also be determined by three basic rotation matrices, and the three matrices are multiplied to obtain a rotation matrix R, where the rotation matrix R may be represented as:

in the embodiment of the invention, the wearable device can obtain three gyroscope data components, namely alpha, beta and gamma, through the three-axis gyroscope to obtain a rotation matrix R formula, namely the rotation matrix R can be used for representing the target arm attitude angle.

303. M first accelerations of a user in a first time period are obtained.

In the embodiment of the present invention, if the target arm posture angles at the K moments are all in the preset sit-up posture interval, and the K target accelerations are all in the third preset interval, it may be indicated that the user is performing sit-up exercise, and then the wearable device may acquire M first accelerations of the user within the first time duration.

It should be noted that wearable device can set up preset sit-up posture interval and third preset interval according to historical data of the user during sit-up before, so that target arm posture angle at K moments is all in preset sit-up posture interval, and when K target acceleration is all in the third preset interval, wearable device can regard the user as sit-up, thereby acquiring M first accelerations of the user in the first time.

Optionally, since the user may place the arm in front of the chest or behind the ear when performing a sit-up, if the wearable device is worn on the wrist of the user, the wearable device may generate posture angles in three directions along with the fluctuation of the arm of the user, wherein the change range of the posture angle in at least one direction is small because the wrist does not rotate greatly when the user performs a sit-up; if the posture angle is within the preset sit-up posture interval, it can be interpreted that the user is sit-up.

Illustratively, assuming that K is 5, the preset sit-up posture interval is (30 °,40 °,25 °) - (60 °,80 °,35 °), and the third preset interval is 8m/s ² -13m/s ² . Wearable device can obtain 5 target acceleration at 5 moments respectively, be: 9.6m/s ² 、9.3m/s ² 、9.1m/s ² 、10.7m/s ² 、12.6m/s ² And 5 pieces of gyro data, the 5 target arm posture angles acquired to the user by the 5 pieces of target acceleration and the 5 pieces of gyro data are (47.2 °,61.0 °,29.8 °), (58.0 °,49.6 °,29.8 °), (47.2 °,53.1 °,34.7 °), (39.6 °,49.1 °,29.6 °), (58.7 °,78.3 °,31.0 °), respectively, and it can be seen that the 5 target arm posture angles are all in the (30 °,40 °,25 ° - (60 °,80 °,35 °) interval, and 9.6m/s ² 、9.3m/s ² 、9.1m/s ² 、10.7m/s ² 、12.6m/s ² Are all at 8m/s ² -13m/s ² In the interval, the wearable device may then assume that the user is sit-up, thereby acquiring M first accelerations of the user over the first time period.

304. And obtaining N second accelerations which are smaller than a preset acceleration threshold value in the M first accelerations.

305. And determining the number of the target acceleration as the sit-up times of the user in the first time length.

306. And calculating the motion amplitude of the user according to the M first accelerations and the target formula.

In the embodiment of the invention, the wearable device can calculate the motion amplitude of the user according to the M first accelerations through a target formula.

Alternatively, the target formula may be

Wherein S is the amplitude of motion, A _i For the ith first acceleration among the M first accelerations,

is the average of the M first accelerations.

For example, assume that the wearable device acquires 10 first accelerations, which are acceleration a:4.2m/s ² And the acceleration B:5.0m/s ² Acceleration C:5.3m/s ² And the acceleration D:6.5m/s ² The acceleration E:8.3m/s ² The acceleration F:9.1m/s ² Acceleration G:10.2m/s ² The acceleration H:9.6m/s ² The acceleration I:8.4m/s ² Acceleration J:7.6m/s ² . The wearable device may first average the 10 first accelerations to obtain

Then, the square of the difference between each first acceleration and the average is calculated to be 10.364 (m/s) ² ) ² 、5.8564(m/s ² ) ² 、4.4944(m/s ² ) ² 、0.8464(m/s ² ) ² 、0.7744(m/s ² ) ² 、2.8224(m/s ² ) ² 、7.7284(m/s ² ) ² 、4.7524(m/s ² ) ² 、0.9604(m/s ² ) ² 、0.0324(m/s ² ) ² (ii) a Then the wearable device sums the 10 values, averages and separates to obtain the motion amplitude S =1.96m/S of the user ² 。

Optionally, the wearable device may further average the M first accelerations, and represent the motion amplitude of the user with an average value.

307. And outputting the first prompt message.

In the embodiment of the present invention, if the motion amplitude of the user is greater than the preset amplitude threshold, it may be stated that the current motion amplitude of the user is large, and the wearable device may output a first prompt message, where the first prompt message is used to prompt the user to take a break.

It should be noted that the preset amplitude threshold may be determined by the user according to the self state, or may be determined by the wearable device according to historical motion data of the user, which is not limited in the embodiment of the present invention.

The embodiment of the invention provides a method for calculating the number of sit-ups, which is characterized in that a wearable device can acquire the acceleration and gyroscope data of a user at a first moment through a six-axis sensor, calculate the arm posture angle of the user according to the acceleration and the gyroscope data, determine that the user is doing sit-ups movement, and acquire M first accelerations of the user within a first time length, so that the situation that the wearable device also detects when the user is not doing sit-ups can be avoided, and the power consumption of the wearable device can be effectively reduced.

Further, if the M first accelerations satisfy the preset sit-up feature, it may be described that the wearable device detects that the user is performing effective sit-up exercise, and then the wearable device may determine, as the sit-up times of the user within the first duration, the number of target accelerations that are smaller than the preset acceleration threshold and that are smaller than the adjacent acceleration among the M first accelerations. Because the sit-up is a periodic movement, the user can repeat the sit-up movement for many times in the first duration, the wearable device can detect the periodic regularity of M accelerations, and screen out the target acceleration meeting the conditions in each period, thereby accurately determining the number of periods in the first duration according to the number of target accelerations meeting the conditions, namely the sit-up times of the user in the first duration.

As an alternative implementation, after the wearable device determines the number of target accelerations as the number of sit-ups of the user in the first time period, the method may further include: the wearable device calculates the average sit-up times per minute of the user according to the sit-up times of the user within the first time length; the wearable device determines a sit-up score corresponding to the average sit-up frequency of the user according to a corresponding relation between pre-stored sit-up frequencies and scores; the wearable device displays the sit-up score on a display screen of the wearable device and sends the sit-up score to other devices associated with the wearable device.

For example, it is assumed that the correspondence between the pre-stored sit-up times and scores of the wearable device is as follows: 100 minutes for more than 110 times per minute, 90 minutes for 90-109 times per minute, 80 minutes for 70-89 times per minute, 70 minutes for 50-69 times per minute, and 60 minutes for less than 50 times per minute. The wearable device calculates the average sit-up times per minute of the user to be 93 times according to the sit-up times of the user in the first time length, and then according to the corresponding relation, the 93 times are seen to be in an interval of 90-109 times, and then the current sit-up score of the user is 90 scores; the wearable device may display the 90 score on a display screen of the wearable device, and may also send the 90 score to a parent device associated with the wearable device.

As an optional implementation manner, a heart rate sensor may be configured in the wearable device, and the heart rate sensor is used to acquire N heart rate data within a first duration; the wearable device calculates the heart rate amplification parameters of the user according to the N heart rate data through a heart rate calculation formula; and if the heart rate amplification parameter is larger than the preset heart rate threshold value, outputting a second prompt message, wherein the second prompt message is used for prompting the user to pay attention to rest.

It should be noted that the preset heart rate threshold may be determined by the user according to the self state, or may be determined by the wearable device according to historical motion data of the user, which is not limited in the embodiment of the present invention.

Optionally, the heart rate calculation formula may be:

wherein B is a heart rate amplification parameter, B is a heart rate amplification parameter _r Median of N heart rate data, B ₁ To rest heart rate, B _max The maximum heart rate of the user.

It should be noted that the resting heart rate is a heart rate detected by the wearable device when the user is in a stationary state; the maximum heart rate of the user may be calculated from the age of the user.

Alternatively, the maximum heart rate may be: b _max =220-Age; the maximum heart rate may also be: b _max =206.3-0.711 × age; wherein Age is the Age of the user.

Further, the maximum heart rate may also be related to the age and gender of the user, and when the user is male, the maximum heart rate may be: b is _max =202-0.55 × age; when the user is female, the maximum heart rate may be: b is _max =216-1.09 × age; wherein Age is the Age of the user.

For example, assume that the wearable device acquires 9 heart rate data of the user in a first duration, which are 91, 93, 102, 88, 110, 79, 96, 100, 83, respectively, the rest heart rate is 60, and the user is 48 years old. The wearable device calculates that the median of the 9 heart rate data is 93, and the maximum heart rate can be 220-48=172, so that B =29% can be obtained according to the heart rate calculation formula.

Through this optional implementation, wearable equipment can confirm the current heart rate amplification of user according to user's heart rate data to when the heart rate amplification is greater than and predetermines the heart rate threshold value, remind the user, avoid appearing the user because the heart rate amplification is too big and the uncomfortable condition of health.

EXAMPLE III

As shown in fig. 4, an embodiment of the present invention provides a wearable device, including:

the acquisition module 401 is configured to control an acceleration sensor in a six-axis sensor, and acquire M first accelerations of a user in a first time period;

the obtaining module 401 is further configured to obtain N second accelerations greater than a preset acceleration threshold from among the M first accelerations if the M first accelerations satisfy a preset sit-up characteristic;

a processing module 402, configured to determine, if a target acceleration greater than an adjacent acceleration exists in the N second accelerations, the number of the target accelerations as the number of times of sit-ups of the user within the first time period;

Optionally, the processing module 402 is further configured to determine an acceleration curve according to the M first accelerations;

the obtaining module 401 is further configured to obtain P acceleration peak values located at a peak and Q acceleration valley values located at a trough in an acceleration curve, where P and Q are integers smaller than M;

the processing module 402 is further configured to determine that the M first accelerations satisfy the preset sit-up feature if the P acceleration peak values are all located in a first preset interval and the Q acceleration valley values are all located in a second preset interval.

Optionally, the processing module 402 is specifically configured to determine a difference between each acceleration peak and an adjacent acceleration valley if the P acceleration peaks are all in a first preset interval and the Q acceleration valleys are all in a second preset interval;

the processing module 402 is specifically configured to determine that the M first accelerations satisfy the preset sit-up characteristic if the difference is within the preset difference interval.

Optionally, the obtaining module 401 is further configured to obtain a first average value of P acceleration peak values and a second average value of Q acceleration valley values;

the processing module 402 is further configured to determine that the M first accelerations satisfy the preset sit-up feature if the first average value is within a first preset interval and the second average value is within a second preset interval.

Optionally, the obtaining module 401 is specifically configured to control an acceleration sensor and a gyroscope sensor in a six-axis sensor, and continuously obtain K target accelerations and K target gyroscope data at K times;

a processing module 402, configured to calculate target arm attitude angles at the K moments according to the K target accelerations and the K target gyroscope data;

an obtaining module 401, configured to obtain, through the six-axis sensor, the M first accelerations of the user within the first duration if the target arm posture angles at the K times are all in a preset sit-up posture interval and the K target accelerations are all in a third preset interval;

wherein the preset sit-up posture interval is a pre-stored arm posture angle interval corresponding to the sit-up movement.

Optionally, the obtaining module 401 is specifically configured to control an acceleration sensor in the six-axis sensor, and obtain K third accelerations of the user in the first time period, where K is an integer greater than or equal to M;

the processing module 402 is specifically configured to delete the third acceleration whose difference from the adjacent acceleration is greater than or equal to a preset difference threshold, so as to obtain the processed M first accelerations.

Optionally, the processing module 402 is further configured to calculate a motion amplitude of the user according to the M first accelerations and the target formula;

the processing module 402 is further configured to output a first prompt message if the motion amplitude of the user is greater than a preset amplitude threshold, where the first prompt message is used to prompt the user to take a rest;

wherein the target formula is:

is the average of the M first accelerations.

In the embodiment of the present invention, each module may implement the method for calculating the number of sit-ups provided in the above method embodiment, and may achieve the same technical effect, and for avoiding repetition, details are not described here again.

As shown in fig. 5, an embodiment of the present invention further provides a wearable device, where the wearable device may include:

a memory 501 in which executable program codes are stored;

a processor 502 coupled to a memory 501;

the processor 502 calls the executable program code stored in the memory 501 to execute the method for calculating the number of sit-ups performed by the wearable device in the above embodiments of the methods.

As shown in fig. 6, an embodiment of the present invention further provides a wearable device, which includes but is not limited to: a Radio Frequency (RF) circuit 601, a memory 602, an input unit 603, a display unit 604, a sensor 605, an audio circuit 606, a WiFi (wireless communication) module 607, a processor 608, a power supply 609, and a camera 610. The rf circuit 601 includes a receiver 6011 and a transmitter 6012. Those skilled in the art will appreciate that the wearable device structure shown in fig. 6 does not constitute a limitation of the wearable device, and may include more or fewer components than shown, or combine certain components, or a different arrangement of components.

The RF circuit 601 may be used for receiving and transmitting signals during a message transmission or call, and in particular, for receiving downlink messages from a base station and then processing the received downlink messages to the processor 608. The RF circuitry 601 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol, including but not limited to global system for mobile communication (GSM), general Packet Radio Service (GPRS), code Division Multiple Access (CDMA), wideband Code Division Multiple Access (WCDMA), long Term Evolution (LTE), email, short Message Service (SMS), etc.

The memory 602 may be used to store software programs and modules, and the processor 608 executes various functional applications and data processing of the wearable device by running the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phone book, etc.) created according to the use of the wearable device, and the like.

The input unit 603 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the wearable device. Specifically, the input unit 603 may include a touch panel 6031 and other input devices 6032. The touch panel 6031, also referred to as a touch screen, may collect touch operations of a user on or near the touch panel 6031 (e.g., operations of a user on or near the touch panel 6031 using any suitable object or accessory such as a finger, a stylus, etc.) and drive corresponding connection devices according to a preset program.

The display unit 604 may be used to display information input by or provided to the user and various menus of the wearable device. The display unit 604 may include a display panel 6041, and optionally, the display panel 6041 may be configured in the form of a Liquid Crystal Display (LCD), an organic light-Emitting diode (OLED), or the like.

The wearable device may also include at least one sensor 605, such as light sensors, motion sensors, and other sensors. In the embodiment of the present invention, the wearable device may include an acceleration sensor 6051 and a gyroscope sensor 6052, where the acceleration sensor may be used to detect a current acceleration value of the wearable device, and the gyroscope sensor may be used to detect a current rotation angle value of the wearable device.

Audio circuitry 606, speaker 6061, microphone 6062 may provide an audio interface between the user and the wearable device. The audio circuit 606 may transmit the electrical signal converted from the received audio data to the speaker 6061, and convert the electrical signal into a sound signal by the speaker 6061 and output the sound signal; on the other hand, the microphone 6062 converts the collected sound signal into an electrical signal, which is received by the audio circuit 606 and converted into audio data, and then the audio data is processed by the audio data output processor 608, and then the audio data is sent to another wearable device through the RF circuit 601, or the audio data is output to the memory 602 for further processing.

WiFi belongs to short-range wireless transmission technology, and the wearable device can help the user send and receive e-mail, browse web pages, access streaming media, etc. through the WiFi module 607, it provides wireless broadband internet access for the user.

The processor 608 is a control center of the wearable device, and is connected to various parts of the entire wearable device through various interfaces and lines, and performs various functions of the wearable device and processes data by running or executing software programs and/or modules stored in the memory 602 and calling up the data stored in the memory 602, thereby performing overall monitoring of the wearable device.

The wearable device also includes a power source 609 (e.g., a battery) that provides power to various components, preferably, the power source may be logically connected to the processor 608 via a power management system, such that functions such as managing charging, discharging, and power consumption are performed via the power management system. Although not shown, the wearable device may further include a bluetooth module or the like, which is not described herein.

Embodiments of the present invention provide a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute some or all of the steps of the method as in the above method embodiments.

Embodiments of the present invention also provide a computer program product, wherein the computer program product, when run on a computer, causes the computer to perform some or all of the steps of the method as in the above method embodiments.

Embodiments of the present invention further provide an application publishing platform, where the application publishing platform is configured to publish a computer program product, where the computer program product, when running on a computer, causes the computer to perform some or all of the steps of the method in the above method embodiments.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art should also appreciate that the embodiments described in this specification are exemplary and alternative embodiments, and that the acts and modules illustrated are not required in order to practice the invention.

In various embodiments of the present invention, it should be understood that the sequence numbers of the above-mentioned processes do not imply a necessary order of execution, and the order of execution of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.

The integrated units, if implemented as software functional units and sold or used as a stand-alone product, may be stored in a computer accessible memory. Based on such understanding, the technical solution of the present invention, which is a part of or contributes to the prior art in essence, or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several requests for causing a computer device (which may be a personal computer, a server, a network device, or the like, and may specifically be a processor in the computer device) to execute part or all of the steps of the above-described method of each embodiment of the present invention.

It will be understood by those skilled in the art that all or part of the steps of the methods of the embodiments described above may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, including Read-Only Memory (ROM), random Access Memory (RAM), programmable Read-Only Memory (PROM), erasable Programmable Read-Only Memory (EPROM), one-time Programmable Read-Only Memory (OTPROM), electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM) or other Memory capable of storing data, a magnetic tape, or any other computer-readable medium capable of storing data.

Claims

1. A method for calculating the number of sit-ups is applied to a wearable device, and comprises the following steps:

acquiring M first accelerations of a user in a first time length through a six-axis sensor;

2. The method according to claim 1, wherein if there is a target acceleration smaller than an adjacent acceleration among the N second accelerations, determining the number of target accelerations as the number of sit-ups of the user within the first time period, further comprises:

determining an acceleration curve according to the M first accelerations;

3. The method of claim 2, wherein determining that the M first accelerations satisfy the predetermined sit-up characteristic if the P acceleration peaks are all within a first predetermined interval and the Q acceleration valleys are all within a second predetermined interval comprises:

and if the difference is within a preset difference interval, determining that the M first accelerations meet the preset sit-up characteristic.

4. The method of claim 2, wherein after obtaining P acceleration peaks at a peak and Q acceleration valleys at a valley in the acceleration curve, the method further comprises:

5. The method of claim 1, wherein said obtaining M first accelerations of the user over the first duration via a six-axis sensor comprises:

the preset sit-up posture interval is an arm posture angle interval corresponding to the pre-stored sit-up movement.

6. The method of claim 1, wherein said obtaining M first accelerations of the user over the first duration via a six-axis sensor comprises:

7. The method of claim 1, wherein after determining the number of target accelerations as the number of sit-ups of the user over the first length of time, the method further comprises:

wherein the target formula is:

is the average of the M first accelerations.

8. A wearable device, comprising:

the acquisition module is used for acquiring M first accelerations of a user in a first time length through a six-axis sensor;

the processing module is used for determining the number of the target accelerations as the sit-up times of the user within the first time period if the target accelerations larger than the adjacent accelerations exist in the N second accelerations;

9. A wearable device, comprising:

a memory storing executable program code;

and a processor coupled to the memory;

the processor calls the executable program code stored in the memory for performing the sit-up times calculation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, comprising: the computer readable storage medium stores thereon computer instructions which, when executed by a processor, implement the method of calculating the number of sit-ups of any one of claims 1 to 7.