CN111473797A - Motion state detection method and device - Google Patents
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Abstract
The invention provides a method for detecting a motion state, which comprises the following steps: acquiring motion amplitude information of an arm; in order to obtain the motion amplitude information of the arm, the user may be required to wear a watch on which a sensor is arranged. Filtering the motion amplitude information of the arm to obtain effective motion characteristic information; and detecting motion state data according to the effective motion characteristic information. And filtering the motion amplitude information of the arm, so that abnormal data can be removed, and the accuracy and effectiveness of the motion characteristic information are ensured. After the motion characteristics are determined to be effective motion characteristics, the motion state of the user is detected, and accordingly more targeted motion data are obtained. Therefore, the motion state of the user is detected in a targeted manner. Thereby facilitating the next operation.
Description
Technical Field
The present invention relates to a device for monitoring exercise performance, and more particularly, to a method for detecting exercise status and a portable device.
Background
Currently, a watch for monitoring sports performance can record sports information such as sports time, distance, pace, lap and the like. But the motion performance monitoring capability is poor, and the recording of the motion is not accurate. After the exercise data is recorded, the exercise watch is not helpful for the user to make a next exercise plan, but may cause the user to make a misjudgment on the own body state due to wrong information, so that the situation of excessive planned exercise amount or insufficient planned exercise amount is caused, and the exercise watch becomes one of sources for hurting the body of the user.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: a method for detecting motion state and a portable mobile device are provided to more accurately obtain the motion state of a sporter.
In order to solve the technical problems, the invention adopts the technical scheme that: a method of motion state detection, comprising the steps of:
acquiring motion amplitude information of an arm;
filtering the motion amplitude information of the arm to obtain effective motion characteristic information;
and detecting motion state data according to the effective motion characteristic information.
Further, the method specifically comprises the following steps:
acquiring motion amplitude information of an arm;
filtering the motion amplitude information of the arm to obtain effective motion characteristic information;
and detecting motion state data according to the effective motion characteristic information.
Optionally, the step of obtaining the motion amplitude information of the arm specifically includes:
acquiring the vertical motion amplitude of an arm;
obtaining a range of effective motion thresholds;
and confirming that the vertical motion amplitude of the arm is in the range of the effective motion threshold value, and extracting the vertical motion amplitude of the arm.
Further, in the step of performing filtering processing on the motion characteristic information to obtain effective motion characteristic information, if the exercise is running, the step of performing filtering processing on the vertical motion amplitude of the arm specifically includes:
performing median filtering on the vertical motion amplitude of the arm to generate first filtering data;
and carrying out amplitude limiting filtering on the first filtering data to generate effective motion characteristic information.
Specifically, the step of performing amplitude limiting filtering on the first filtered data specifically includes:
acquiring an amplitude minimum value of the first filtering data, an amplitude threshold of the first filtering data and an amplitude value of the first filtering data;
and confirming that the difference value between the amplitude value of the first filtering data and the amplitude minimum value of the first filtering data is smaller than the amplitude threshold value of the first filtering data, and removing the corresponding first filtering data.
Specifically, the step of performing clipping filtering on the first filtered data further includes:
acquiring a dense threshold and amplitude frequency;
and confirming that the amplitude frequency is smaller than the dense threshold value, and removing the corresponding first filtering data.
Further, the step of detecting the motion state data specifically includes:
acquiring a user motion grade;
acquiring a corresponding heart rate interval threshold according to the user motion grade;
acquiring first heart rate data;
and confirming that the first heart rate data exceeds the corresponding heart rate interval threshold value, and sending heart rate prompt information to the user.
Specifically, after the step of sending the heart rate prompt to the user, the method further includes:
acquiring a time interval;
obtaining second heart rate data after the time interval;
and confirming that the second heart rate data exceeds the maximum heart rate of the exercise grade, and sending help seeking information to a third party.
Further, after the step of acquiring the first heart rate data, the method further includes:
and forming and displaying a heart rate graph according to the first heart rate data.
Specifically, the step of detecting the motion state data further includes:
detecting and outputting motion information and displacement information;
wherein the exercise information includes one or more of stride information, stride frequency information, calorie consumption information, maximum speed, average speed, or average pace, and the displacement information includes one or more of movement distance information, altitude change information, and altitude change information.
A second aspect of the present application provides a system for motion state detection, comprising:
the acquisition module is used for acquiring the motion amplitude information of the arm;
the extraction module is used for extracting motion characteristic information;
the filtering module is used for carrying out filtering processing on the motion characteristic information to obtain effective motion characteristic information;
and the detection module is used for detecting motion state data according to the effective motion characteristic information.
The invention has the beneficial effects that: in order to obtain the motion amplitude information of the arm, the user may be required to wear a watch on which a sensor is arranged. And filtering the motion amplitude information of the arm, so that abnormal data can be removed, and the accuracy and effectiveness of the motion characteristic information are ensured. After the motion characteristics are determined to be effective motion characteristics, the motion state of the user is detected, and accordingly more targeted motion data are obtained. Therefore, the motion state of the user is detected in a targeted manner. Thereby facilitating the next operation.
Drawings
The detailed structure of the invention is described in detail below with reference to the accompanying drawings
FIG. 1 is a flow chart of a first embodiment of a method of motion state detection of the present invention;
FIG. 2 is a flow chart of a second embodiment of the method of motion state detection of the present invention;
FIG. 3 is a flow chart of a method of motion state detection according to a third embodiment of the present invention;
FIG. 4 is a flow chart of a fourth embodiment of the method of motion state detection of the present invention;
fig. 5 is a block diagram of a first embodiment of the system for detecting a motion state according to the present invention.
Detailed Description
In order to explain technical contents, structural features, and objects and effects of the present invention in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for detecting a motion state according to a first embodiment of the present invention. A first aspect of the present application provides a method for detecting a motion state, the method comprising the steps of:
s100, acquiring motion amplitude information of an arm; in order to obtain the motion amplitude information of the arm, the user may be required to wear a watch on which a sensor is arranged.
S200, filtering the motion amplitude information of the arm to obtain effective motion characteristic information;
and step S300, detecting motion state data according to the effective motion characteristic information.
And filtering the motion amplitude information of the arm, so that abnormal data can be removed, and the accuracy and effectiveness of the motion characteristic information are ensured. After the motion characteristics are determined to be effective motion characteristics, the motion state of the user is detected, and accordingly more targeted motion data are obtained. Therefore, the motion state of the user is detected in a targeted manner. Thereby facilitating the next operation.
The portable mobile device for detecting the motion state can be an intelligent watch, an intelligent bracelet and other equipment; or other devices which can not be worn but can be placed in a pocket or a bag and can realize detection on the user. In this embodiment, the device is a smart watch.
Specifically, please refer to fig. 2. Fig. 2 is a flowchart of a method for detecting a motion state according to a second embodiment of the present invention. In step S100, the step of obtaining the motion amplitude information of the arm specifically includes:
step S110, acquiring the vertical direction movement amplitude of the arm;
wherein, the motion state of the arm of the user can be measured only by collecting the vertical motion amplitude of the arm. Therefore, the motion state of the user can be judged integrally only by lower computing resources. The motion amplitude of the arm is generally proportional to the speed of the user, and the motion speed is faster when the vertical motion amplitude of the arm is larger.
Step S120, obtaining the range of the effective motion threshold value;
it is to be understood that since the person is in motion, the arms may have interfering motion. The disturbing motion may be a hand swing, a shoulder clap by a person, or the like. If these actions are calculated into the motion, a large amount of redundant data may be generated, which may cause the overall data to be inaccurate, and consume a large amount of computing resources, so that it is difficult to ensure the accuracy of the measurement. Therefore, it is necessary to set a range of effective motion thresholds.
And S130, confirming that the vertical motion amplitude of the arm is in the range of the effective motion threshold value, and extracting the vertical motion amplitude of the arm.
In the human action, the change range of actions such as hand throwing and shaking is small, so that after the lowest threshold value is set, the relevant actions can be filtered. However, since the movement such as waving or waving has a large variation range and is not accompanied by a specific movement, a maximum threshold value needs to be set to filter out the related movement.
Further, in the step S200 of performing filtering processing on the motion characteristic information to obtain effective motion characteristic information, if the exercise is running, the step of performing filtering processing on the vertical motion amplitude of the arm specifically includes:
step S210, performing median filtering on the vertical motion amplitude of the arm to generate first filtering data.
The median filtering is originally a nonlinear smoothing technology, and the gray value of each pixel point is set as the median of the gray values of all pixel points in a certain neighborhood window of the point. In this embodiment, this technique is used to filter the vertical amplitude curve of the arm. It will be appreciated that each time the arm moves from the lowest point to the highest point of the vertical amplitude movement, it is a minimum movement period. In the application, the vertical amplitude of the arm movement is taken as the gray value of one pixel point; each minimum motion period is equivalent to a window; the median of the amplitude of the minimum motion period is equivalent to the median of the gray values of all the pixel points in a certain neighborhood window.
It is understood that the minimum period in the present embodiment is a relatively precise value, and if a plurality of minimum periods are combined, a larger period can be formed. The longer the period is, more computing resources can be saved, and the fluency of the system is guaranteed. And the smaller the period is, the accuracy of detection can be guaranteed.
Step S220, performing amplitude limiting filtering on the first filtered data to generate effective motion characteristic information.
The amplitude limiting filtering is performed for the first filtered data, and the amplitude of the minimum period can be effectively attenuated. In general, the clipping filtering is to determine the maximum deviation value allowed twice according to the empirical judgment. Every time a new value is detected, it is judged: if the difference between the current value and the previous value is smaller than the maximum deviation value allowed by the two times of sampling, the current value is invalid, the current value is abandoned, and the previous value is used for replacing the current value.
Further, in step S220, the step of performing amplitude limiting filtering on the first filtered data specifically includes:
step S221, an amplitude minimum value of the first filtered data, an amplitude threshold of the first filtered data, and an amplitude value of the first filtered data are obtained.
Step S222, confirming that the difference between the amplitude value of the first filtered data and the amplitude minimum value of the first filtered data is smaller than the amplitude threshold of the first filtered data, and removing the corresponding first filtered data.
In the embodiment, the selected first sampling value is the amplitude minimum value of the first filtering data, the sampling is not performed for the second time, but a threshold value is directly set, and by applying the filtering in such a way, the accuracy of the filtering affected by the outside is reduced, which is beneficial to improving the overall filtering speed and efficiency.
Further, in step S220, the step of performing clipping filtering on the first filtered data further includes:
step S223, acquiring an intensive threshold and amplitude frequency;
step S224, confirming that the amplitude frequency is smaller than the dense threshold, and removing the corresponding first filtered data.
In this embodiment, since the processed data includes a large amount of interference arm movements, the simple processing using the effective movement threshold for limiting the movement amplitude cannot cover the complicated movement conditions such as hand shaking in mid-air and frequent arm shaking, which may cause the overall data to be disordered and redundant, resulting in calculation errors. When the amplitude frequency is introduced into the calculation, the above-mentioned complicated arm movements can be more effectively removed.
Referring to fig. 3, fig. 3 is a flowchart illustrating a method for detecting a motion state according to a third embodiment of the present invention;
further, in step S3, the step of detecting the motion state data specifically includes:
step S310, obtaining a user motion grade;
it will be appreciated that there are many ways in which the user's motion level may be divided. The first motion level can be divided into motion levels such as running, urban running, hiking and the like. By applying the first motion grade dividing mode, the motion effect of different motion states can be effectively detected.
It is understood that the second motion division manner is division performed for a certain motion state of the user. In this embodiment, the exercise level of the user is divided by using data of the heart rate. Heart rate was divided into five intervals: exercise warming, fat burning, heart and lung strengthening, muscle strength strengthening and anaerobic warning, wherein the intervals are respectively 50% -60%, 61% -70%, 71% -80%, 81% -90% and 91% -100% of the maximum heart rate. If the heart rate is below 50% of the maximum heart rate, "daily activity" is displayed.
Step S320, acquiring a heart rate interval threshold according to the motion level of the user;
based on the above, the second exercise classification method can be directly applied to classify the heart rate of the user, or the second grade classification method can be adopted on the basis of the first exercise classification method. If only the second motion partition is used, it may be the case that the data audit record may not be sufficiently accurate. For example, when a person is frightened, the heart rate may suddenly accelerate and a longer arrhythmia may be produced. If at this point the data is shown to be cardiopulmonary intensive, it is clearly inappropriate. If the motion is divided twice on the basis of the first motion division mode, the above situation can be avoided.
In this embodiment, the division of the heart rate interval has 2 modes of maximum heart rate percentage and resting heart rate combination calculation. And calculating each interval value of the exercise prompt according to the set division mode. When the special sports are carried out, the heart rate is not in the interval, namely, the heart rate reminding is carried out.
The maximum heart rate percentage is calculated as: maximum heart rate exercise intensity. Maximum heart rate is 220-age, and when the age is not set, the age is 30 by default;
the method for calculating the combined resting heart rate comprises the following steps: (max heart rate-resting heart rate) exercise intensity + resting heart rate, resting heart rate measured by heart rate test, not measured by default 65.
Step S330, acquiring first heart rate data;
the first heart rate data is the heart rate data of the current user. Further, a heart rate map is formed and presented based on the first heart rate data. In this embodiment, the ring is divided into 5 equal parts, and five intervals of the heart rate are displayed corresponding to the second motion division mode. If the heart rate is lower than the maximum heart rate by 50%, daily activities are displayed, and the ring is empty.
And step S340, confirming that the first heart rate data exceeds the heart rate interval threshold value, and sending heart rate prompt information to the user.
Therefore, the state of the user can be reminded, and the situation that the user is off-duty due to excessive exercise caused by overexcitation or overstrain of the user is avoided.
It is understood that the heart rate interval threshold is two values that are not fixed. Below the lower limit of the interval indicates: "exercise Heart Rate lower than the fat burning Range, speed Up! "higher than interval upper limit indicates: "exercise Heart Rate above the fat burning Range, deceleration! "
In this implementation, the interval of heart rate is judged 1 minute after the opening exercise. If the heart rate is not within the interval within 1 minute after the starting exercise, the alarm cannot be given. And (5) immediately reminding when the temperature is lower than the interval for the first time or higher than the interval. If the heart rate is lower than the lower limit of the interval after the start exercise is carried out for 1 minute, the alarm is given. And changing the interval from being lower to being higher or changing the interval from being higher to being lower, and immediately reminding. If the reminding is carried out within 3 minutes from being lower than the interval and the judgment is carried out within 3 minutes from being higher than the interval, or the reminding is carried out within 3 minutes from being higher than the interval and the judgment is carried out within being lower than the interval, the reminding can be immediately carried out
The multiple occurrences in the same interval need to be reminded at intervals of 3 minutes. If the reminding is performed after the interval is lower, the reminding needs to wait for 3 minutes for reminding again after the interval is continuously lower, or the reminding is performed after the interval is lower, the heart rate is recovered to the interval and then is changed to be lower, and the reminding needs to be performed again after the interval is more than 3 minutes.
When the heart rate exceeds the maximum heart rate and 5 consecutive detections exceed the maximum heart rate, the watch shakes and pops up an alert. If the response information is not obtained, the method further comprises the following steps:
further, referring to fig. 4, fig. 4 is a flowchart illustrating a method for detecting a motion state according to a fourth embodiment of the present invention. After step S340, the following steps are also included:
step S350, acquiring a time interval;
step S360, after the time interval, acquiring second heart rate data;
and step S370, confirming that the second heart rate data exceeds the maximum heart rate of the exercise grade, and sending help seeking information to a third party.
In this embodiment, the time interval is 5 seconds, and the user does not operate after 5 seconds, and the heart rate that detects is not between rest heart rate and maximum heart rate, dials the SOS number automatically. If the user clicks the button within 5 seconds, executing the operation of clicking by the user; if the user does not click, the detected heart rate is between the maximum heart rate and the resting heart rate, and then the user does not dial. Wherein the SOS number is preset.
Further, in step S3, the step of detecting the motion state data further includes:
step S380, detecting and outputting motion information and displacement information;
wherein the exercise information includes one or more of stride information, stride frequency information, calorie consumption information, maximum speed, average speed, or average pace, and the displacement information includes one or more of movement distance information, altitude change information, and altitude change information.
The stride information and the step frequency information are helpful for counting the basic condition of the body doing running exercise; the calorie consumption information is very helpful for the weight-losing people; the maximum speed and the average matching speed can be used for analyzing the explosive force and endurance of the user and mastering the special state of the user.
The moving distance information, the height change information and the altitude change information are beneficial to the control of the whole state and the knowledge of the hiking distance and the mountain climbing distance of the travelers. Moreover, mountaineering officials are omitted, and labor cost is saved.
Referring to fig. 5, fig. 5 is a block diagram illustrating a motion state detection system according to a first embodiment of the present invention. The present application further provides a system for motion state detection, comprising:
the acquisition module is used for acquiring the motion amplitude information of the arm;
the extraction module is used for extracting motion characteristic information;
the filtering module is used for carrying out filtering processing on the motion characteristic information to obtain effective motion characteristic information;
and the detection module is used for detecting the motion state data according to the effective motion characteristic information.
Each functional module in the embodiments of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The module-integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may be stored in a computer-readable storage medium.
Based on this, all or part of the flow in the method of the embodiments of the present invention may also be implemented by a computer program to instruct related hardware, and the computer program of the module may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the methods may be implemented. Where the modular computer program comprises computer program code, the modular computer program code may be in the form of source code, object code, an executable file or some intermediate form, or the like. The module computer readable medium may include: any entity or device capable of carrying modular computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like.
It should be noted that the modular computer-readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method of motion state detection, the method comprising the steps of:
acquiring motion amplitude information of an arm;
filtering the motion amplitude information of the arm to obtain effective motion characteristic information;
and detecting motion state data according to the effective motion characteristic information.
2. The method for detecting a motion state according to claim 1, wherein the step of obtaining the motion amplitude information of the arm specifically includes:
acquiring the vertical motion amplitude of an arm;
obtaining a range of effective motion thresholds;
and confirming that the vertical motion amplitude of the arm is in the range of the effective motion threshold value, and extracting the vertical motion amplitude of the arm.
3. The method according to claim 2, wherein the step of performing filtering processing on the motion characteristic information to obtain effective motion characteristic information, and the step of performing filtering processing on the vertical motion amplitude of the arm when the exercise is running specifically includes:
performing median filtering on the vertical motion amplitude of the arm to generate first filtering data;
and carrying out amplitude limiting filtering on the first filtering data to generate effective motion characteristic information.
4. The method according to claim 3, wherein the step of performing the clipping filtering on the first filtered data specifically includes:
acquiring an amplitude minimum value of the first filtering data, an amplitude threshold of the first filtering data and an amplitude value of the first filtering data;
and confirming that the difference value between the amplitude value of the first filtering data and the amplitude minimum value of the first filtering data is smaller than the amplitude threshold value of the first filtering data, and removing the corresponding first filtering data.
5. The method of motion state detection according to claim 4, wherein said step of performing clipping filtering on said first filtered data further comprises:
acquiring a dense threshold and amplitude frequency;
and confirming that the amplitude frequency is smaller than the dense threshold value, and removing the corresponding first filtering data.
6. The method for detecting a motion state according to claim 1, wherein the step of detecting the motion state data specifically includes:
acquiring a user motion grade;
acquiring a corresponding heart rate interval threshold according to the user motion grade;
acquiring first heart rate data;
and confirming that the first heart rate data exceeds the corresponding heart rate interval threshold value, and sending heart rate prompt information to the user.
7. The method of motion state detection according to claim 6, wherein the step of issuing a heart rate alert to the user is followed by further comprising:
acquiring a time interval;
obtaining second heart rate data after the time interval;
and confirming that the second heart rate data exceeds the maximum heart rate of the exercise grade, and sending help seeking information to a third party.
8. The method of motion state detection according to claim 6, wherein the step of acquiring the first heart rate data is followed by further comprising:
and forming and displaying a heart rate graph according to the first heart rate data.
9. The method for detecting motion state according to any one of claims 1 to 7, wherein the step of detecting motion state data further comprises:
detecting and outputting motion information and displacement information;
wherein the exercise information includes one or more of stride information, stride frequency information, calorie consumption information, maximum speed, average speed, or average pace, and the displacement information includes one or more of movement distance information, altitude change information, and altitude change information.
10. A system for motion state detection, the system comprising:
the acquisition module is used for acquiring the motion amplitude information of the arm;
the extraction module is used for extracting motion characteristic information;
the filtering module is used for carrying out filtering processing on the motion characteristic information to obtain effective motion characteristic information;
and the detection module is used for detecting motion state data according to the effective motion characteristic information.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112057067A (en) * | 2020-09-03 | 2020-12-11 | 青岛歌尔智能传感器有限公司 | Heart rate detection method, wearable device and readable storage medium |
| CN114224329A (en) * | 2021-12-28 | 2022-03-25 | 北京启恒星科技有限公司 | Motion monitoring device, method, apparatus, electronic device, and computer-readable medium |
| WO2022257406A1 (en) * | 2021-06-10 | 2022-12-15 | 歌尔股份有限公司 | Intelligent display method, and device, computer program product and storage medium |
-
2020
- 2020-03-27 CN CN202010228266.7A patent/CN111473797A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112057067A (en) * | 2020-09-03 | 2020-12-11 | 青岛歌尔智能传感器有限公司 | Heart rate detection method, wearable device and readable storage medium |
| WO2022257406A1 (en) * | 2021-06-10 | 2022-12-15 | 歌尔股份有限公司 | Intelligent display method, and device, computer program product and storage medium |
| CN114224329A (en) * | 2021-12-28 | 2022-03-25 | 北京启恒星科技有限公司 | Motion monitoring device, method, apparatus, electronic device, and computer-readable medium |
| CN114224329B (en) * | 2021-12-28 | 2022-09-16 | 北京启恒星科技有限公司 | Motion monitoring device, method, apparatus, electronic device, and computer-readable medium |
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Application publication date: 20200731 |