CN110495892B - Motion data detection method and intelligent wearable device - Google Patents
Motion data detection method and intelligent wearable device Download PDFInfo
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Abstract
The invention discloses a motion data detection method which is applied to intelligent wearable equipment comprising a motion sensor and a magnetic sensor. According to the method and the device, when the first motion data of the user, detected by the motion sensor currently, is not in the preset data detection range, the magnetic sensor with higher detection sensitivity is used for obtaining the current second motion data of the user, whether the current motion data of the user is actual motion data or not is judged based on the second motion data, if the current motion data is actual motion data, the difference between the current detection value of the motion sensor and the actual motion situation of the user is shown, and then the current motion data of the user is counted in the calculation of the subsequent motion steps. Therefore, the accuracy of the motion data is improved under the auxiliary detection of the magnetic sensor, and the accuracy of the step counting function of the intelligent wearable device is improved. The invention also discloses intelligent wearable equipment which has the same beneficial effects as the detection method.
Description
Technical Field
The invention relates to the field of sports pedometer, in particular to a sports data detection method and intelligent wearable equipment.
Background
At present, in an intelligent wearable device, a detection sensor meeting the requirement of detection sensitivity of the number of steps of exercise is generally arranged to detect the exercise data of a user, so that the exercise data of the user is combined with a related step counting algorithm to obtain the number of steps of the exercise of the user. However, when the user wears two same intelligent wearable devices to walk simultaneously, or different users wear the same intelligent wearable devices to walk in a synchronous number, the number of steps of the exercise detected by the two intelligent wearable devices is different under most conditions, and even the difference is large. The intelligent wearable device comprises a detection sensor, a detection module and a control module, wherein the detection sensor on the intelligent wearable device can generate different detection values according to different wearing positions and different motion amplitudes of a user, and the detection values are considered as actual motion data of the user when being within a preset detection range and can be used as a calculation basis for the number of subsequent motion steps; otherwise, the detection value is discarded and is not used as the calculation basis of the subsequent movement steps. However, the detection sensor is likely to cause the difference between the detection value and the actual motion condition of the user due to different wearing positions and different motion amplitudes of the user, so that the detection sensor is mistakenly discarded, the accuracy of motion data is reduced, and the accuracy of the step counting function of the intelligent wearable device is further reduced.
Therefore, how to provide a solution to the above technical problem is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a motion data detection method and intelligent wearable equipment, which improve the accuracy of motion data under the auxiliary detection of a magnetic sensor, and further improve the accuracy of a step counting function of the intelligent wearable equipment.
In order to solve the technical problem, the invention provides a motion data detection method, which is applied to an intelligent wearable device comprising a motion sensor and a magnetic sensor, and comprises the following steps:
acquiring first motion data of a user currently detected by the motion sensor;
judging whether the first motion data is in a preset data detection range or not;
if so, determining the first motion data as the current actual motion data of the user;
if not, the current second motion data of the user is obtained by using the magnetic sensor, and when the second motion data meets the walking characteristics of the human body, the second motion data is determined to be the current actual motion data of the user, so that the motion step number of the user is calculated based on the actual motion data.
Preferably, the process of acquiring the current second motion data of the user by using the magnetic sensor includes:
acquiring a Z-axis potential difference which is currently detected by the magnetic sensor and represents the motion state of a user in the Z-axis direction;
obtaining the current motion state data of the user in the Z-axis direction according to the Z-axis potential difference; correspondingly, when the second motion data meets the walking characteristics of the human body, the process of determining that the second motion data is the current actual motion data of the user includes:
and when the motion state data keeps periodic change, determining the motion state data as the current actual motion data of the user.
Preferably, after the motion state data keeps periodically changing, before determining that the motion state data is the current actual motion data of the user, the motion data detecting method further includes:
judging whether the data change frequency of the motion state data is within a preset motion frequency range or not;
if yes, executing the step of determining the motion state data to be the current actual motion data of the user;
and if not, discarding the motion state data.
Preferably, the magnetic sensor is a linear hall sensor.
Preferably, the motion data detection method further includes:
after the intelligent wearable device is started, the magnetic sensor is kept in a dormant state, and the magnetic sensor is not waken up until the first motion data is not in a preset data detection range.
Preferably, after waking up the magnetic sensor, the motion data detection method further includes:
and after the first motion data returns to the preset data detection range again and lasts for the preset time, sleeping the magnetic sensor.
In order to solve the above technical problem, the present invention further provides an intelligent wearable device, including:
a magnetic sensor;
the motion sensor is used for detecting current first motion data of a user;
the controller is used for acquiring the first motion data and judging whether the first motion data is in a preset data detection range; if so, determining the first motion data as the current actual motion data of the user; if not, the current second motion data of the user is obtained by using the magnetic sensor, and when the second motion data meets the walking characteristics of the human body, the second motion data is determined to be the current actual motion data of the user, so that the motion step number of the user is calculated based on the actual motion data.
Preferably, the motion sensor is an acceleration sensor, and the magnetic sensor is a linear hall sensor.
Preferably, the intelligent wearable device is a watch or a bracelet.
The invention provides a motion data detection method which is applied to intelligent wearable equipment comprising a motion sensor and a magnetic sensor. According to the method and the device, when the first motion data of the user, detected by the motion sensor currently, is not in the preset data detection range, the magnetic sensor with higher detection sensitivity is used for obtaining the current second motion data of the user, whether the current motion data of the user is actual motion data or not is judged based on the second motion data, if the current motion data is actual motion data, the difference between the current detection value of the motion sensor and the actual motion situation of the user is shown, and then the current motion data of the user is counted in the calculation of the subsequent motion steps. Therefore, the accuracy of the motion data is improved under the auxiliary detection of the magnetic sensor, and the accuracy of the step counting function of the intelligent wearable device is improved.
The invention also provides intelligent wearable equipment which has the same beneficial effects as the detection method.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed in the prior art and 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 to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a motion data detection method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an intelligent wearable device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an intelligent wearable device according to an embodiment of the present invention;
fig. 4 is a schematic external view of an intelligent wearable device according to an embodiment of the present invention.
Detailed Description
The core of the invention is to provide the motion data detection method and the intelligent wearable device, which improve the accuracy of the motion data under the auxiliary detection of the magnetic sensor, and further improve the accuracy of the step counting function of the intelligent wearable device.
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.
Referring to fig. 1, fig. 1 is a flowchart illustrating a motion data detection method according to an embodiment of the present invention.
The motion data detection method is applied to intelligent wearable equipment comprising a motion sensor and a magnetic sensor.
The motion data detection method comprises the following steps:
step S1: first motion data of a user currently detected by a motion sensor is acquired.
Specifically, the intelligent wearable device of the application adds a magnetic sensor with detection sensitivity higher than that of a motion sensor on the basis of setting the motion sensor meeting the requirement of the detection sensitivity of the number of steps of the motion, which considers that the motion sensor is likely to cause the difference between the motion data of the detected user and the actual motion situation (the motion data is wrongly discarded) due to different wearing positions and different motion amplitudes of the user, and the magnetic sensor can be utilized to more accurately acquire the current motion data of the user under the situation, so that the current actual motion situation of the user can be more accurately known.
Therefore, the motion sensor serves as a main detection sensor, the magnetic sensor serves as an auxiliary detection sensor, and the magnetic sensor is used for making up for the influence of the motion sensor on the motion data detection result under the condition that the motion data detected by the motion sensor is discarded by mistake.
Based on this, this application is when intelligent wearing equipment during operation, at first obtains the first motion data of the user of motion sensor current detection, for the application and the motion step number calculation of follow-up magnetic sensor lay the basis.
Step S2: judging whether the first motion data is in a preset data detection range or not; if yes, go to step S3; if not, step S4 is executed.
It should be noted that the preset of the present application is set in advance, and only needs to be set once, and the reset is not needed unless the modification is needed according to the actual situation.
Specifically, the application sets a data detection range in advance, and the setting principle is as follows: when the currently detected first motion data is in the set data detection range, considering the currently detected first motion data as the actual motion data of the user, and then adding the currently detected first motion data into the calculation of the subsequent motion steps; when the currently detected first motion data is not in the set data detection range, the currently detected first motion data is considered to be not the actual motion data of the user, and the currently detected first motion data is discarded and is not counted in the calculation of the subsequent motion steps.
Based on this, in the present application, after the first motion data currently detected by the motion sensor is obtained in step S1, the first motion data is compared with a preset data detection range (motion data upper limit + motion data lower limit), specifically, the first motion data is respectively compared with the preset motion data upper limit and the preset motion data lower limit, and when the first motion data is not less than the motion data lower limit and the first motion data is not greater than the motion data upper limit, it is determined that the first motion data is within the preset data detection range; otherwise, determining that the first motion data is not in the preset data detection range.
Step S3: and determining the first motion data as the current actual motion data of the user so as to execute the step of calculating the motion step number of the user based on the actual motion data.
Specifically, when the first motion data currently detected by the motion sensor is within the preset data detection range, the currently detected first motion data is determined to be the currently actual motion data of the user, and then the currently detected first motion data is counted in the calculation of the subsequent motion steps.
Step S4: and acquiring current second motion data of the user by using the magnetic sensor, and determining the second motion data as the current actual motion data of the user when the second motion data meets the walking characteristics of the human body so as to execute the step of calculating the number of motion steps of the user based on the actual motion data.
Specifically, when the first motion data currently detected by the motion sensor is not within the preset data detection range, it is determined that the currently detected first motion data is not the actual motion data of the user, and the currently detected first motion data is discarded. However, considering that the motion sensor has the situation that the motion data is discarded by mistake, in order to avoid that the motion data is discarded by mistake to affect the motion data detection result, the present application adopts the magnetic sensor to more accurately acquire the current second motion data of the user, so as to secondarily judge the current actual motion situation of the user based on the second motion data.
More specifically, after the current second motion data of the user is acquired by using the magnetic sensor, whether the second motion data meets the human walking characteristics is judged, if the second motion data meets the human walking characteristics, the first motion data detected by the motion sensor is discarded by mistake, the current second motion data is determined to be the current actual motion data of the user, and then the current second motion data is counted in the calculation of the subsequent motion steps, so that the current motion steps of the user are corrected to obtain more accurate motion steps (it can be understood that the current motion steps of the user are equal to the sum of the motion steps calculated based on the first motion data and the motion steps calculated based on the second motion data); if the walking characteristic of the human body is not satisfied, the first motion data detected by the motion sensor is not discarded by mistake, and the current motion step number of the user does not need to be corrected.
The invention provides a motion data detection method which is applied to intelligent wearable equipment comprising a motion sensor and a magnetic sensor. According to the method and the device, when the first motion data of the user, detected by the motion sensor currently, is not in the preset data detection range, the magnetic sensor with higher detection sensitivity is used for obtaining the current second motion data of the user, whether the current motion data of the user is actual motion data or not is judged based on the second motion data, if the current motion data is actual motion data, the difference between the current detection value of the motion sensor and the actual motion situation of the user is shown, and then the current motion data of the user is counted in the calculation of the subsequent motion steps. Therefore, the accuracy of the motion data is improved under the auxiliary detection of the magnetic sensor, and the accuracy of the step counting function of the intelligent wearable device is improved.
On the basis of the above-described embodiment:
as an alternative embodiment, the process of acquiring the current second motion data of the user by using the magnetic sensor includes:
acquiring a Z-axis potential difference which is currently detected by a magnetic sensor and represents the motion state of a user in the Z-axis direction;
obtaining the current motion state data of the user in the Z-axis direction according to the Z-axis potential difference; correspondingly, when the second motion data meets the walking characteristics of the human body, the process of determining that the second motion data is the current actual motion data of the user comprises the following steps:
and when the motion state data keeps periodic change, determining the motion state data as the current actual motion data of the user.
Further, knowing that the X-axis direction and the Y-axis direction are on the ground where the human body stands, and the Z-axis direction is perpendicular to the ground where the human body stands, the magnetic sensor can be used for acquiring motion state data of a user in the X-axis direction, motion state data in the Y-axis direction and motion state data in the Z-axis direction to jointly form second motion data. In consideration of the fact that the motion state data of the user in the Z-axis direction can represent the current motion condition of the user most, the motion state data of the user in the Z-axis direction is obtained mainly by using the magnetic sensor (the specific process comprises the steps of firstly obtaining the Z-axis potential difference which is currently detected by the magnetic sensor and represents the motion state of the user in the Z-axis direction, and then obtaining the motion state data of the user in the Z-axis direction according to the Z-axis potential difference (the corresponding relation between the Z-axis potential difference detected by the magnetic sensor and the motion state data of the user in the Z-axis direction can be set in advance according to a motion test, and then obtaining the motion state data of the user in the Z-axis direction corresponding to the Z-axis potential difference currently detected by the magnetic sensor based on the corresponding relation)).
In addition, considering that human walking is a repetitive motion, and the motion frequency of the same person in a unit time is basically kept constant (human walking characteristics), the motion state data of the user in the Z-axis direction acquired by the magnetic sensor should be kept periodically changed during the walking process of the user. Based on the above, after the motion state data of the user in the Z-axis direction is acquired by using the magnetic sensor, whether the motion state data keeps periodic variation (a certain deviation is allowed to exist) is judged, if yes, the motion state data meets the walking characteristics of the human body in the Z-axis direction, and the motion state data is determined to be the current actual motion data of the user; if not, the motion state data does not meet the walking characteristics of the human body in the Z-axis direction, and the motion state data is determined not to be the current actual motion data of the user.
As an optional embodiment, after the motion state data keeps periodically changing, before determining that the motion state data is the current actual motion data of the user, the motion data detecting method further comprises:
judging whether the data change frequency of the motion state data is within a preset motion frequency range or not;
if yes, executing the step of determining the motion state data as the current actual motion data of the user;
if not, the motion state data is discarded.
Further, generally, in the process of normal walking of the human body, the fastest speed 1s is not more than 5 steps, and the slowest speed 2s is not less than one step, namely, the motion frequency range of the human body is 50hz-100 hz. Since the human motion frequency is the data change frequency of the motion state data, the data change frequency of the motion state data should be within the human motion frequency range when the human body normally walks.
Based on this, the present application sets a motion frequency range (e.g., 50hz to 100hz, or sets other range values according to experience) in advance, so as to calculate a data change frequency of the motion state data after the motion state data keeps periodic change, and determine whether the data change frequency of the motion state data is within the set motion frequency range, if the data change frequency is within the set motion frequency range, which indicates that the user is walking normally, then execute a step of determining the motion state data as the current actual motion data of the user; if the user does not walk normally when the user is not in the set motion frequency range, the motion state data is discarded and is not counted in the calculation of the subsequent motion steps, so that the accuracy of the calculation of the motion steps is further improved.
As an alternative embodiment, the magnetic sensor is a linear hall sensor.
Specifically, the magnetic sensor of this application can select for use linear hall sensor, and its theory of operation is: when a current flows through a semiconductor of the linear Hall sensor, a current carrier deflects to generate an electric field perpendicular to the direction of the current or a magnetic field, and the electric field is applied to the semiconductor of the linear Hall sensor, so that a potential difference (Hall effect principle) is generated at two ends of the semiconductor, a magnetic signal changing around the linear Hall sensor is detected through the Hall effect principle, and the magnetic signal is converted into an electric signal, thereby facilitating subsequent data calculation.
The linear Hall sensor is electrified with constant current I when in workHWhen the motion data of the user changes, the magnetic field around the linear hall sensor also changes, and according to the hall effect principle, the linear hall sensor can generate a certain potential difference:
so that the movement data of the user can be obtained through the voltage signal. Wherein G isHIs a constant, which is determined by the actual material of the linear hall sensor; b is the magnetic induction intensity of the magnetic field; a is an offset angle (namely an included angle between a magnetic field and a normal line of a linear Hall sensor plane) in a motion state; and S is the area of a sensitive element of the linear Hall sensor.
It should be noted that the linear hall effect transistorThe sensor specifically detects the change of the magnetic field in the X-axis direction (corresponding to the potential difference of the X-axis)
) Change of magnetic field in Y-axis direction (corresponding to potential difference of Y-axis)
) And the change of the magnetic field in the Z-axis direction (corresponding to the potential difference of the Z-axis)
). Wherein, BX、BY、BZMagnetic induction of magnetic field in X, Y, Z axial directions, aX、aY、aZWhich are respectively the included angles between the magnetic field in the direction of the X, Y, Z axis and the normal line of the plane of the linear hall sensor.
Considering that the motion state data in the Z-axis direction can best represent the current motion condition of the user, the Z-axis potential difference V representing the motion state of the user in the Z-axis direction is extracted from the detection result of the linear Hall sensorHZAccording to a Z-axis potential difference VHZAnd acquiring motion state data of the user in the Z-axis direction. Then judging whether the data change frequency of the motion state data in the Z-axis direction is within a preset motion frequency range, if so, determining that the motion state data in the Z-axis direction is the actual motion data of the user when the motion state data in the Z-axis direction keeps periodic change, and counting the actual motion data into the calculation of the subsequent motion steps; if not, discarding the motion state data in the Z-axis direction, and not counting the number of subsequent motion steps.
As an optional embodiment, the motion data detecting method further comprises:
after the intelligent wearable device is started, the magnetic sensor is kept in a dormant state, and the magnetic sensor is not waken up until the first motion data is not in the preset data detection range.
Further, considering that the wearing habits and the exercise amplitude of most users are relatively standardized most of the time, the standardization is characterized in that: the actual motion condition of the user can be accurately detected only by the motion sensor without the assistance of a magnetic sensor; meanwhile, the magnetic sensor generates certain power consumption in a working mode, so that the motion sensor enters the working mode after the intelligent wearable device is started to detect the current first motion data of the user in real time; and the magnetic sensor is kept in a dormant state to save power consumption. Because when the first motion data detected by the motion sensor currently is not in the preset data detection range, the magnetic sensor is required to perform auxiliary detection, when the first motion data detected by the motion sensor is not in the preset data detection range, the magnetic sensor is awakened again to enter a working mode, and whether the current motion data of a user is actual motion data is detected.
As an optional embodiment, after waking up the magnetic sensor, the motion data detecting method further comprises:
and after the first motion data returns to the preset data detection range again and lasts for the preset time, the magnetic sensor is dormant.
Further, considering that the wearing habit and the exercise amplitude are relatively standardized, the user basically walks according to the original walking habit (in the stable walking phase) at ordinary times, but there may be a case: because some special factors cause the user to change the walking habit of the user (in the walking unstable stage) in a short time, the method starts timing from the time when the first motion data detected by the motion sensor returns to the preset data detection range again, and when the timing time reaches the preset time, if the first motion data detected by the motion sensor is still in the preset data detection range, the user is considered to be in the walking stable stage, the magnetic sensor is dormant until the first motion data detected by the next motion sensor is not in the preset data detection range, so that the situation that the magnetic sensor always consumes power when the user is in the walking stable stage for a long time is avoided.
Referring to fig. 2, fig. 2 is a schematic structural diagram of an intelligent wearable device according to an embodiment of the present invention.
This intelligence wearing equipment includes:
a magnetic sensor 2;
the motion sensor 1 is used for detecting current first motion data of a user;
the controller 3 is used for acquiring the first motion data and judging whether the first motion data is in a preset data detection range; if so, determining the first motion data as the current actual motion data of the user; if not, the current second motion data of the user is obtained by using the magnetic sensor 2, and when the second motion data meets the walking characteristics of the human body, the second motion data is determined to be the current actual motion data of the user, so that the motion step number of the user is calculated based on the actual motion data.
Specifically, the intelligent wearable device of the present application includes a motion sensor 1, a magnetic sensor 2, and a controller 3 connected to the motion sensor 1 and the magnetic sensor 2, and please refer to the above embodiment of the motion data detection method for describing the working principle of the intelligent wearable device, which is not described herein again.
As an alternative embodiment, the motion sensor 1 is an acceleration sensor, and the magnetic sensor 2 is a linear hall sensor.
Specifically, the motion sensor 1 of the present application may be an acceleration sensor, and its working principle is: in the process of user's walking, acceleration sensor detectable user wears the motion acceleration of the position of intelligent wearing equipment to through acceleration value representation user's motion data.
The magnetic sensor 2 of the present application can be a linear hall sensor, and the working principle thereof can be described with reference to the principle of the linear hall sensor in the above embodiments, which is not described herein again.
In addition, referring to fig. 3, fig. 3 is a schematic structural diagram of an intelligent wearable device according to an embodiment of the present invention.
The smart wearable device includes a third detection sensor (for example, a third detection sensor) for detecting wearing of the smart wearable device, in addition to a motion sensor 1 (for example, an acceleration sensor), a magnetic sensor 2 (for example, a linear hall sensor), and a controller 3 (optionally, an MCU (micro controller Unit))Such as an infrared sensor), a fourth detection sensor (e.g. a pulse sensor) for detecting the heart rate of the user, a power chip for supplying power to the controller 3, a display screen (e.g. an Organic Light-Emitting Diode (OLED) screen) for displaying each detection data, an indicator Light (e.g. an LED) for representing different functions by different Light-Emitting states, and a bluetooth 5.0 for real-time information interaction with a terminal device (e.g. a mobile phone), which are controlled by the controller 3, specifically, the controller 3, the acceleration sensor, the infrared sensor, and the pulse sensor are controlled by the controller 3 through I2C, the controller 3 communicates with other devices through GPIO (General-purpose input/output).
As an optional embodiment, the smart wearable device is a watch or a bracelet.
Specifically, the intelligent wearing equipment of this application can be wrist-watch or bracelet, as shown in fig. 4. The working principle of the watch or the bracelet comprising the acceleration sensor and the linear hall sensor is specifically as follows: acquiring an acceleration value currently detected by an acceleration sensor; judging whether the acceleration value is within a preset acceleration detection range or not; if yes, determining the acceleration value as the current actual motion data of the user, and counting the acceleration value in the calculation of the motion steps of the subsequent user; if not, acquiring the Z-axis potential difference currently detected by the linear Hall sensor, obtaining the motion state data of the user in the Z-axis direction according to the Z-axis potential difference, determining the motion state data in the Z-axis direction as the current actual motion data of the user when the motion state data in the Z-axis direction keeps periodic change, and counting the current actual motion data of the user in the calculation of the motion steps of the subsequent user.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A motion data detection method is applied to an intelligent wearable device comprising a motion sensor and a magnetic sensor, and comprises the following steps:
acquiring first motion data of a user currently detected by the motion sensor;
judging whether the first motion data is in a preset data detection range or not;
if so, determining the first motion data as the current actual motion data of the user;
if not, acquiring current second motion data of the user by using the magnetic sensor, and when the second motion data meets the walking characteristics of the human body, determining the second motion data as the current actual motion data of the user so as to calculate the motion steps of the user based on the actual motion data;
wherein the process of acquiring the current second motion data of the user by using the magnetic sensor comprises:
acquiring a Z-axis potential difference which is currently detected by the magnetic sensor and represents the motion state of a user in the Z-axis direction;
obtaining the current motion state data of the user in the Z-axis direction according to the Z-axis potential difference;
correspondingly, when the second motion data meets the walking characteristics of the human body, the process of determining that the second motion data is the current actual motion data of the user includes:
and when the motion state data keeps periodic change, determining the motion state data as the current actual motion data of the user.
2. The exercise data detection method according to claim 1, wherein after the exercise state data maintains the periodic variation, before determining that the exercise state data is the exercise data currently actually performed by the user, the exercise data detection method further comprises:
judging whether the data change frequency of the motion state data is within a preset motion frequency range or not;
if yes, executing the step of determining the motion state data to be the current actual motion data of the user;
and if not, discarding the motion state data.
3. The motion data detection method according to claim 1, wherein the magnetic sensor is a linear hall sensor.
4. The motion data detection method according to any one of claims 1 to 3, further comprising:
after the intelligent wearable device is started, the magnetic sensor is kept in a dormant state, and the magnetic sensor is not waken up until the first motion data is not in a preset data detection range.
5. The motion data detection method according to claim 4, wherein after waking up the magnetic sensor, the motion data detection method further comprises:
and after the first motion data returns to the preset data detection range again and lasts for the preset time, sleeping the magnetic sensor.
6. An intelligence wearing equipment which characterized in that includes:
a magnetic sensor;
the motion sensor is used for detecting current first motion data of a user;
the controller is used for acquiring the first motion data and judging whether the first motion data is in a preset data detection range; if so, determining the first motion data as the current actual motion data of the user; if not, acquiring current second motion data of the user by using the magnetic sensor, and when the second motion data meets the walking characteristics of the human body, determining the second motion data as the current actual motion data of the user so as to calculate the motion steps of the user based on the actual motion data;
wherein the process of acquiring the current second motion data of the user by using the magnetic sensor comprises:
acquiring a Z-axis potential difference which is currently detected by the magnetic sensor and represents the motion state of a user in the Z-axis direction;
obtaining the current motion state data of the user in the Z-axis direction according to the Z-axis potential difference;
correspondingly, when the second motion data meets the walking characteristics of the human body, the process of determining that the second motion data is the current actual motion data of the user includes:
and when the motion state data keeps periodic change, determining the motion state data as the current actual motion data of the user.
7. The intelligent wearable device of claim 6, wherein the motion sensor is an acceleration sensor and the magnetic sensor is a linear Hall sensor.
8. The intelligent wearable device of claim 6, wherein the intelligent wearable device is a watch or a bracelet.
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| CN112237427B (en) * | 2020-10-14 | 2024-05-28 | 北京爱笔科技有限公司 | Method, device, detection equipment and computer storage medium for detecting steps |
| CN112833908A (en) * | 2021-01-27 | 2021-05-25 | 捷开通讯(深圳)有限公司 | Step counting method, step counting device and computer readable storage medium |
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