CN110680293A - Motion monitoring method, motion monitoring device and terminal equipment - Google Patents
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Abstract
The application is applicable to the technical field of health monitoring, and provides an exercise monitoring method, an exercise monitoring device and terminal equipment, which comprise: acquiring a target motion mode of a user, and determining standard motion data corresponding to the target motion mode; and monitoring the actual motion data of the user, and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data. By the method, the user can be effectively monitored.
Description
Technical Field
The present application belongs to the technical field of health monitoring, and in particular, to an exercise monitoring method, an exercise monitoring device, and a terminal device.
Background
With the development of society, people pay more and more attention to their health, and more people join the line of sports and fitness. Not all exercisers understand scientific fitness. For example: sometimes, overload exercise is performed, which causes muscle strain; sometimes, the exercise action is not standard, and the exercise effect cannot be achieved.
Existing athletic monitoring devices, such as athletic bracelets, typically only monitor actual athletic data (e.g., heart rate) of a user. For most amateur exercisers, it is still impossible to distinguish whether the exercise method is scientific or not based on the monitored actual exercise data. Therefore, the existing exercise monitoring devices cannot effectively monitor the exercise of the user.
Disclosure of Invention
The embodiment of the application provides a motion monitoring method, a motion monitoring device and a terminal device, which can solve the problem that the existing motion monitoring device cannot effectively monitor the motion of a user.
In a first aspect, an embodiment of the present application provides an exercise monitoring method, including:
acquiring a target motion mode of a user, and determining standard motion data corresponding to the target motion mode;
and monitoring the actual motion data of the user, and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
In one possible implementation form of the first aspect, the standard athletic data includes a standard heart rate range, and the actual athletic data includes an actual heart rate;
the acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode includes:
acquiring a target motion mode of a user, acquiring sign information of the user corresponding to the target motion mode, and determining standard motion data corresponding to the target motion mode according to the sign information;
the monitoring of the actual motion data of the user and the prompting of the user to adjust the motion state when the actual motion data is not matched with the standard motion data comprises:
monitoring an actual heart rate of the user;
when the actual heart rate is larger than the maximum value of the standard heart rate range, prompting the user to reduce exercise intensity;
and when the actual heart rate is smaller than the minimum value of the standard heart rate range, prompting the user to improve the exercise intensity.
In a possible implementation manner of the first aspect, when the target motion mode is an anaerobic motion, the acquiring sign information of the user corresponding to the target motion mode includes:
acquiring the age of a user;
the determining of the standard motion data corresponding to the target motion mode according to the sign information includes:
calculating a maximum heart rate from the age;
calculating an anaerobic exercise heart rate from the maximum heart rate and the age;
and acquiring a preset difference value, and determining a standard heart rate range corresponding to the target exercise mode according to the preset difference value and the anaerobic exercise heart rate.
In a possible implementation manner of the first aspect, when the target exercise mode is aerobic exercise, the obtaining sign information of the user corresponding to the target exercise mode includes:
acquiring the average values of height, weight, age and sleep heart rate of a user;
the determining of the standard motion data corresponding to the target motion mode according to the sign information includes:
calculating a resting heart rate according to the height, the weight, the age and the average value of the sleep heart rate, and calculating a maximum heart rate according to the age;
calculating a heart rate reserve from the resting heart rate and the maximum heart rate;
and acquiring a maximum heart rate percentage range corresponding to the target movement mode, and calculating a standard heart rate range corresponding to the target movement mode according to the heart rate reserve and the maximum heart rate percentage range.
In one possible implementation manner of the first aspect, the standard motion data includes a standard swing trajectory and a standard motion trajectory, and the actual motion data includes an actual swing trajectory and an actual motion trajectory;
the acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode includes:
acquiring a target motion mode of a user, and determining a standard swing track and a standard motion track corresponding to the target motion mode;
the monitoring of the actual motion data of the user and the prompting of the user to adjust the motion state when the actual motion data is not matched with the standard motion data comprises:
monitoring an actual swing track and an actual motion track of a user;
and when the actual swing track is not matched with the standard swing track and/or when the actual motion track is not matched with the standard motion track, prompting a user to change the action posture.
In a possible implementation manner of the first aspect, the monitoring an actual swing track and an actual motion track of the user includes:
monitoring a real-time acceleration signal and a real-time angular velocity signal of wearable equipment worn by a user, and acquiring static attitude data of the wearable equipment;
and determining an actual swing track and an actual motion track according to the static attitude data, the real-time acceleration signal and the real-time angular velocity signal.
In a possible implementation manner of the first aspect, the static posture data includes preset initial coordinates and an initial acceleration signal when the wearable device is in a static state when worn by a user;
determining an actual swing track and an actual motion track according to the static attitude data, the actual acceleration signal and the actual angular velocity signal, including:
respectively calculating the space position variable quantity and the path variable quantity corresponding to each historical monitoring moment according to the real-time acceleration signal and the real-time angular velocity signal;
calculating the actual swing track of the current monitoring moment according to the space position variation corresponding to each historical monitoring moment and the initial acceleration signal;
and calculating the actual motion track of the current monitoring moment according to the path variable quantity corresponding to each historical monitoring moment and the initial coordinate.
In a second aspect, an embodiment of the present application provides an exercise monitoring apparatus, including:
the information acquisition unit is used for acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode;
and the motion monitoring unit is used for monitoring the actual motion data of the user and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the exercise monitoring method according to any one of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, where the computer program is executed by a processor to implement the method for monitoring exercise according to any one of the first aspect.
In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on a terminal device, causes the terminal device to execute the exercise monitoring method according to any one of the first aspect.
It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.
Compared with the prior art, the embodiment of the application has the advantages that:
according to the embodiment of the application, the standard motion data suitable for the current user can be obtained by acquiring the target motion mode of the user and determining the standard motion data corresponding to the target motion mode, so that a reference basis is provided for subsequent motion monitoring; and then monitoring the actual movement data of the user, and prompting the user to move when the actual movement data is not matched with the standard movement data. By the method, the determined standard exercise data is used as a reference basis, and the user can be effectively monitored.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic diagram of a wearable device provided by an embodiment of the present application;
FIG. 2 is a flow chart illustrating a method for monitoring exercise according to an embodiment of the present application;
FIG. 3 is a flow chart illustrating a method for monitoring exercise according to another embodiment of the present application;
FIG. 4 is a table of the maximum heart rate percentage range for aerobic exercise provided by an embodiment of the present application;
fig. 5 is a schematic flow chart of an exercise monitoring method according to another embodiment of the present application;
FIG. 6 is a block diagram of an embodiment of an athletic monitoring device;
fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise.
An application scenario of the exercise monitoring method in the embodiment of the present application is described first. The user wears wearable equipment when moving, and this wearable equipment can be motion bracelet, motion armband, intelligent wrist-watch, intelligent glasses etc.. Referring to fig. 1, a schematic diagram of a wearable device provided in an embodiment of the present application is shown. As shown, a heart rate collector 101, an accelerometer 102, a gyroscope 103, a processor 104, an input device 105, and a prompting device 106 may be included in the wearable device. Wearable equipment can acquire the motion information of user's input through input device, through heart rate collector real-time supervision user's actual rhythm of the heart, through accelerometer monitoring acceleration signal to through gyroscope monitoring angular velocity signal. The processor is respectively connected with the input device, the heart rate collector, the accelerometer, the gyroscope and the prompting device, the processor receives the motion information sent by the input device, receives the actual heart rate sent by the heart rate collector, acquires the acceleration signal of the accelerometer and the angular velocity signal of the gyroscope, the motion monitoring method in the embodiment of the application is utilized to process the monitoring data, after the processing, when the motion prompt is needed to the user, the processor sends a prompting instruction to the prompting device, and the prompting device sends a prompting signal (the prompting signal can be a text signal, an acoustic signal, an optical signal, a vibration signal and the like) to the user according to the prompting instruction.
Of course, the wearable device may also be in communication connection with other terminal devices (the communication mode may be a wired or wireless mode, and the wireless mode may be wifi, bluetooth, etc.). The terminal equipment can be a mobile phone, a computer and the like. The user can also input a target motion mode in the terminal equipment, and the terminal equipment sends the target motion mode to the processor of the wearable equipment; the processor of the wearable device obtains heart rate, acceleration signals, angular velocity signals and the like, and processes the collected data according to the received target motion mode. When the user needs to be prompted for movement, the processor in the wearable device can also send a prompt instruction to the terminal device, and the terminal device sends a prompt signal to the user according to the prompt instruction. By using the method, the monitoring of the movement of others can be realized. For example, when a child wears a bracelet to go out for sports, parents can monitor the sports situation of the child through a mobile phone. The motion monitoring device and the terminal device can increase the adaptability of the motion monitoring method in the embodiment of the application.
In another application scenario of the embodiment of the application, a user inputs a target motion mode into terminal equipment, and obtains data such as heart rate, acceleration signals, angular velocity signals and the like by wearing wearable equipment; the wearable device sends the data to the terminal device in a communication mode; the terminal device processes the data to obtain standard motion data corresponding to the target motion mode and monitored actual motion data of the user, monitors the motion state of the user according to the actual motion data and the standard motion data, and sends a prompt signal to the user through a prompt device of the terminal device when the user needs to be prompted. In this application scenario, the wearable device is only used for acquiring data such as heart rate, acceleration signals, and angular velocity signals, and is not used for processing the data, and the step of processing the data is executed by the terminal device.
Fig. 2 is a schematic flow chart of an athletic monitoring method provided in an embodiment of the present application, which may include the following steps, by way of example and not limitation:
s201, acquiring a target motion mode of a user, and determining standard motion data corresponding to the target motion mode.
S202, monitoring actual motion data of the user, and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
In one embodiment, the standard motion data includes a standard heart rate range and the actual motion data includes an actual heart rate. Referring to fig. 3, a schematic flow chart of an athletic monitoring method according to another embodiment of the present application is provided, which may include, by way of example and not limitation, the following steps:
s301, acquiring a target motion mode of a user, acquiring sign information of the user corresponding to the target motion mode, and determining standard motion data corresponding to the target motion mode according to the sign information.
The target motion pattern may include, among other types of motion, walking, running, swimming, skipping, etc. The vital sign information may include name, height, weight, age, sleep heart rate average, and the like.
In practical application, a user can establish an account number on the exercise monitoring application software, and input physical sign information of the user (the physical sign information can be stored in the cloud server) when the user uses the exercise monitoring application software for the first time, so that the account number and the physical sign information can be bound. When the mobile monitoring system is used again, the terminal equipment logging in the motion monitoring application software can acquire the physical sign information of the user from the cloud server as long as the user inputs the account of the user. Before performing the exercise, the user only needs to select the target exercise mode.
Optionally, when the target motion mode is anaerobic motion, the obtaining of the physical sign information of the user corresponding to the target motion mode includes: the age of the user is obtained.
Correspondingly, the step S301 of determining the standard motion data corresponding to the target motion mode according to the physical sign information may include:
A. the maximum heart rate is calculated according to age.
The maximum heart rate may be calculated using FCmax 220-AGE, where FCmax represents the maximum heart rate and AGE represents AGE. For example, assume age 30, FCmax 220-30 190.
B. The anaerobic exercise heart rate was calculated from the maximum heart rate and age.
The anaerobic exercise heart rate may be calculated using the anaerobic exercise heart rate FCmax-AGE. For example, assuming FCmax is 190, the anaerobic exercise heart rate is 190-30 is 160.
C. And acquiring a preset difference value, and determining a standard heart rate range corresponding to the target exercise mode according to the preset difference value and the anaerobic exercise heart rate.
In practical application, the upper limit value of the standard heart rate range can be obtained by adding the preset difference value to the anaerobic exercise heart rate, and the lower limit value of the standard heart rate range can be obtained by subtracting the preset difference value from the anaerobic exercise heart rate.
For example, assuming the preset difference value is 20 and the anaerobic exercise heart rate is 160, the standard heart rate range is 140-180.
Optionally, when the target movement mode is aerobic movement, the obtaining of the physical sign information of the user corresponding to the target movement mode includes: and acquiring the height, weight, age and sleep heart rate average value of the user.
Correspondingly, the step S301 of determining the standard motion data corresponding to the target motion mode according to the physical sign information may include:
D. the resting heart rate is calculated from the height, weight, age and average value of the sleep heart rate, and the maximum heart rate is calculated from the age.
The resting heart rate can be calculated using fcrespose ═ k HR1, where fcrespose represents resting heart rate, HR1 represents average value of sleeping heart rate, k is individual coefficient calculated from height, weight and AGE, k ═ 1+ weight/(light × AGE) × 0.9, weight represents weight, and height represents height.
The maximum heart rate can be calculated using FCmax 220-AGE.
For example, assume height 160cm, weight 60kg, age 30, sleep heart rate average 60. Then the resting heart rate ≈ 1+60/(160 × 160 × 30) × 0.9) × 60. FCmax 220-30 190.
E. Heart rate reserve is calculated from the resting heart rate and the maximum heart rate.
The heart rate reserve may be calculated using FCmax-fcrespose.
Illustratively, as in the data in the above example, heart rate reserve 190-60-130 may be calculated.
F. And acquiring a maximum heart rate percentage range corresponding to the target movement mode, and calculating a standard heart rate range corresponding to the target movement mode according to the heart rate reserve and the maximum heart rate percentage range.
In practical applications, the maximum heart rate percentage ranges corresponding to aerobic exercises with different intensities are different, and refer to fig. 4, which is a table of the maximum heart rate percentage ranges of the aerobic exercises provided in the embodiment of the present application. As shown in the table, the maximum heart rate percentage range corresponding to the aerobic exercise of the small exercise amount is 50% to 60%, the maximum heart rate percentage range corresponding to the aerobic exercise of the medium exercise amount is 70% to 80%, and the maximum heart rate percentage range corresponding to the aerobic exercise of the large exercise amount is 80% to 90%.
When the target exercise pattern is aerobic exercise of a small exercise amount, it can be calculated using a standard heart rate range (heart rate reserve-AGE) × Q1, where Q1 takes a value of 50% to 60%.
When the target exercise pattern is aerobic exercise of a middle exercise amount, it can be calculated using a standard heart rate range (heart rate reserve-AGE) × Q2, where Q2 takes a value of 70% to 80%.
When the target exercise pattern is aerobic exercise of a large exercise amount, it can be calculated using a standard heart rate range (heart rate reserve-AGE) × Q3, where Q3 takes a value of 80% -90%.
Illustratively, assume that the calculated heart rate reserve is 130, age 30, and the target movement pattern is walking. The target exercise pattern may be determined as aerobic exercise of a small exercise amount, and the calculated standard heart rate range is (130-30) × (50% -60%) [50,60 ].
S302, monitoring the actual heart rate of the user.
And S303, when the actual heart rate is larger than the maximum value of the standard heart rate range, prompting the user to reduce the exercise intensity.
And S304, when the actual heart rate is smaller than the minimum value of the standard heart rate range, prompting the user to improve the exercise intensity.
In one embodiment, the standard motion data may further include a standard swing trajectory and a standard motion trajectory, and the actual motion data includes an actual swing trajectory and an actual motion trajectory. Referring to fig. 5, a schematic flow chart of an athletic monitoring method according to another embodiment of the present application is provided, which may include, by way of example and not limitation, the following steps:
s501, acquiring a target motion mode of a user, and determining a standard swing track and a standard motion track corresponding to the target motion mode.
A swing trajectory can be understood as a swing trajectory of a body part of a stationary motion monitoring device. For example, when the user performs running exercise, the exercise monitoring device may be fixed on the thigh, and the swing track at this time is the swing track of the thigh; when a user carries out rope skipping movement, the movement monitoring device can be fixed on the arm part, and the swinging track at the moment is the swinging track of the arm part.
The motion trajectory refers to a position movement trajectory of the user. For example, when the user performs a running exercise, the motion trajectory may be a straight line in the horizontal direction; when the user performs a rope skipping movement, the movement locus may be a round trip line in the vertical direction.
And S502, monitoring the actual swing track and the actual motion track of the user.
Optionally, step S502 may include the following steps;
s5021, monitoring real-time acceleration signals and real-time angular velocity signals of the wearable device worn by the user, and acquiring static attitude data of the wearable device.
And S5022, determining an actual swing track and an actual motion track according to the static attitude data, the real-time acceleration signal and the real-time angular velocity signal.
The static attitude data may include preset initial coordinates and an initial acceleration signal when the wearable device worn by the user is in a static state. In practical application, before moving, the acceleration signal in a period of time can be collected in advance, and if the acceleration signal in the period of time has almost no change, the acceleration signal can be considered to be in a static state. Because the acceleration is only acted on by the gravity in the static state, the vector sum of the acceleration signals is about 1g (g is approximately equal to 9.8 m/s)2). The acceleration signals are typically three-axis acceleration signals, i.e., x, y, z axes. Therefore, the triaxial acceleration signal at a vector sum of about 1g can be taken as the initial acceleration signal.
Correspondingly, step S5022 may further include the steps of:
I. and respectively calculating the space position variable quantity and the path variable quantity corresponding to each historical monitoring moment according to the real-time acceleration signal and the real-time angular velocity signal.
The monitoring time refers to a sampling time when the actual motion data of the user is monitored, and in this embodiment, refers to a sampling time when the acceleration signal and the angular velocity signal of the motion monitoring device are monitored.
For example, assuming that the current nth monitoring time is, to calculate the current actual motion trajectory and the current actual swing trajectory, first, the spatial position variation and the path variation corresponding to the 1 st monitoring time, and the spatial position variation and the path variation corresponding to the 2 nd monitoring time need to be calculated … ….
The spatial position variation corresponding to the nth monitoring moment can be obtained by comparing the acceleration signal of the nth monitoring moment with the acceleration signal of the (n-1) th monitoring moment, and by comparing the angular velocity signal of the nth monitoring moment with the angular velocity signal of the (n-1) th monitoring moment.
The path variation corresponding to the nth monitoring time can be calculated by the following formula:
wherein (S)x(n)，Sy(n)，Sz(n)) represents the amount of path change at the nth monitoring instant,
the speed of the nth monitoring time is shown, and t (n) t (n-1) represents the interval time between the nth monitoring time and the n-1 th monitoring time.
Can be calculated by the following formula:
wherein,
the acceleration signal at the nth monitoring moment. In practical applications, the acceleration signal at the nth monitoring time generally needs to be corrected by using the angular velocity signal at the nth monitoring time, and then the corrected acceleration signal is used to calculate the velocity.
II. And calculating the actual swing track of the current monitoring moment according to the space position variation and the initial acceleration signal corresponding to each historical monitoring moment.
The actual swing track of the 1 st monitoring moment after the static state can be obtained by determining according to the initial acceleration signal and the spatial position variation corresponding to the 1 st monitoring moment; the actual swing track of the 2 nd monitoring moment can be obtained by determining according to the actual swing track of the 1 st monitoring moment and the spatial position variation corresponding to the 2 nd monitoring moment; by analogy, the actual swing track of the nth monitoring moment can be determined according to the actual swing track of the (n-1) th monitoring moment and the spatial position variation corresponding to the nth monitoring moment.
And III, calculating the actual motion track of the current monitoring moment according to the path variable quantity and the initial coordinates corresponding to each historical monitoring moment.
The actual motion trajectory may be calculated by:
wherein (X)n，Yn，Zn) Indicating the coordinates of the nth monitoring moment. The coordinates of the 1 st monitoring moment can be calculated from the initial coordinates as follows:
(X0，Y0，Z0) Representing the initial coordinates. And then the analogy is carried out until the coordinate of the nth monitoring moment is calculated. And obtaining the actual motion track of the current monitoring moment according to the coordinates of each monitoring moment.
And S503, when the actual swing track is not matched with the standard swing track and/or when the actual motion track is not matched with the standard motion track, prompting the user to change the action posture.
Whether there is a match in step S503 may be determined by comparing the similarity between the two trajectories. For example, an image of the actual motion trajectory and an image of the standard motion trajectory may be acquired, and an image processing method may be used to determine whether the two trajectories are similar. For another example, a linear fit may be performed on the two tracks by using a data processing method, and then the degree of fitting may be calculated. The specific method is not limited herein.
In addition, in practical application, the actual swing track can be directly compared with the standard swing track, and the actual motion track can be directly compared with the standard motion track; and determining an actual motion mode according to the monitored actual motion track and the actual swing track, and then judging whether the actual motion mode is consistent with the target motion mode.
In one embodiment, the target exercise pattern of the user may further include an anaerobic exercise and an aerobic exercise, and accordingly, the standard exercise data may include a target exercise type and the actual exercise data may include an actual exercise type. The types of sports may include swimming, running, walking, skipping ropes, and the like.
Exemplarily, a target exercise mode input by a user is obtained, and if aerobic exercise is assumed, a target exercise type is recommended for the user according to the target exercise mode (that is, a target exercise type corresponding to the target exercise mode is determined), and two target exercise types of running and swimming are assumed to be recommended; the actual type of movement of the user is monitored. If the actual swing track is back-and-forth swinging relative to the initial coordinate and the actual motion track is a line segment relative to the initial coordinate, it can be determined that the actual motion type is running, i.e. the actual motion type is any one of the target motion types, and other motion data (such as heart rate) of the user is continuously monitored. If the actual swing track is monitored to be up-and-down reciprocating swing relative to the initial coordinate and the actual motion track is monitored to be up-and-down reciprocating broken lines relative to the initial coordinate, the actual motion type can be determined to be rope skipping, namely the actual motion type is not consistent with the target motion type, and a user needs to be prompted at the moment.
It should be noted that the above example is only an explanation of how to determine the actual motion mode according to the monitored actual swing trajectory and actual motion trajectory, and does not specifically limit the relationship between the swing trajectory, the motion trajectory, and the motion type, that is, does not limit the situations of the swing trajectory and the motion trajectory corresponding to a certain motion type.
In one embodiment, the target exercise pattern of the user may further include a target calorie and a target exercise type, and accordingly, the standard exercise data is a target exercise time and the actual exercise data is an actual exercise time. Illustratively, a target calorie and a target movement type input by a user are obtained, and a target movement time can be calculated according to the target calorie and the target movement type; monitoring the actual movement time of the user; when the actual movement time is longer than the target movement time, prompting the user to stop moving; and when the actual movement time is less than the target movement time, prompting the user of the residual movement time.
According to the embodiment of the application, the standard motion data suitable for the current user can be obtained by acquiring the target motion mode of the user and determining the standard motion data corresponding to the target motion mode, so that a reference basis is provided for subsequent motion monitoring; and then monitoring the actual movement data of the user, and prompting the user to move when the actual movement data is not matched with the standard movement data. By the method, the determined standard exercise data is used as a reference basis, and the user can be effectively monitored.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence 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 application.
Fig. 6 shows a block diagram of an exercise monitoring device provided in the embodiment of the present application, which corresponds to the exercise monitoring method described in the above embodiment, and only the relevant parts of the embodiment of the present application are shown for convenience of illustration.
Referring to fig. 6, the apparatus includes:
the information acquisition unit 61 is configured to acquire a target motion pattern of a user and determine standard motion data corresponding to the target motion pattern.
And the motion monitoring unit 62 is used for monitoring the actual motion data of the user and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
Optionally, the standard motion data comprises a standard heart rate range and the actual motion data comprises an actual heart rate.
Optionally, the information obtaining unit 61 is further configured to obtain a target motion mode of the user, obtain sign information of the user corresponding to the target motion mode, and determine standard motion data corresponding to the target motion mode according to the sign information.
Optionally, the motion monitoring unit 62 is further configured to monitor an actual heart rate of the user; when the actual heart rate is larger than the maximum value of the standard heart rate range, prompting the user to reduce the exercise intensity; when the actual heart rate is less than the minimum value of the standard heart rate range, the user is prompted to increase the exercise intensity.
Optionally, when the target exercise mode is anaerobic exercise, the information obtaining unit 61 is further configured to obtain the age of the user.
Optionally, the information obtaining unit 61 includes:
and the maximum heart rate calculation module is used for calculating the maximum heart rate according to the age.
And the anaerobic heart rate calculation module is used for calculating the anaerobic exercise heart rate according to the maximum heart rate and the age.
And the standard heart rate range acquisition module is used for acquiring a preset difference range and determining a standard heart rate range corresponding to the target exercise mode according to the difference range and the anaerobic exercise heart rate.
Optionally, when the target exercise mode is aerobic exercise, the information obtaining unit 61 is further configured to obtain height, weight, age, and average value of sleep heart rate of the user.
Optionally, the information obtaining unit 61 further includes:
and the maximum heart rate calculation module is also used for calculating the resting heart rate according to the height, the weight, the age and the average value of the sleep heart rate, and calculating the maximum heart rate according to the age.
And the heart rate reserve calculation module is used for calculating heart rate reserve according to the resting heart rate and the maximum heart rate.
And the standard heart rate range acquisition module is also used for acquiring the maximum heart rate percentage range corresponding to the target motion mode and calculating the standard heart rate range corresponding to the target motion mode according to the heart rate reserve and the maximum heart rate percentage range.
Optionally, the standard motion data includes a standard swing trajectory and a standard motion trajectory, and the actual motion data includes an actual swing trajectory and an actual motion trajectory.
Optionally, the information obtaining unit 61 is further configured to obtain a target motion mode of the user, and determine a standard swing trajectory and a standard motion trajectory corresponding to the target motion mode.
Optionally, the motion monitoring unit 62 comprises:
and the monitoring data module is used for monitoring the actual swing track and the actual motion track of the user.
And the judging module is used for prompting the user to change the action posture when the actual swing track is not matched with the standard swing track and/or when the actual motion track is not matched with the standard motion track.
Optionally, the monitoring data module is further configured to monitor a real-time acceleration signal and a real-time angular velocity signal of the wearable device worn by the user, and acquire stationary posture data of the user; and determining an actual swing track and an actual motion track according to the static attitude data, the real-time acceleration signal and the real-time angular velocity signal.
Optionally, the static posture data includes preset initial coordinates and an initial acceleration signal when the wearable device is worn by the user and is in a static state.
Optionally, the monitoring data module includes:
and the variable quantity calculation submodule is used for respectively calculating the space position variable quantity and the path variable quantity corresponding to each historical monitoring moment according to the real-time acceleration signal and the real-time angular velocity signal.
And the actual swing track calculating submodule is used for calculating the actual swing track of the current monitoring moment according to the space position variation and the initial acceleration signal corresponding to each historical monitoring moment.
And the actual motion track calculation submodule is used for calculating the actual motion track of the current monitoring moment according to the path variable quantity and the initial coordinate corresponding to each historical monitoring moment.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
In addition, the exercise monitoring device shown in fig. 6 may be a software unit, a hardware unit, or a combination of software and hardware unit that is built in the existing terminal device, or may be integrated into the terminal device as an independent pendant, or may exist as an independent terminal device.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 7, the terminal device 7 of this embodiment includes: at least one processor 70 (only one shown in fig. 7), a memory 71, and a computer program 72 stored in the memory 71 and executable on the at least one processor 70, the processor 70 implementing the steps in any of the various embodiments of the athletic monitoring method described above when executing the computer program 72.
The terminal device can be a desktop computer, a notebook, a palm computer and other computing devices. The terminal device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that fig. 7 is only an example of the terminal device 7, and does not constitute a limitation to the terminal device 7, and may include more or less components than those shown, or combine some components, or different components, for example, and may further include input/output devices, network access devices, and the like.
The Processor 70 may be a Central Processing Unit (CPU), and the Processor 70 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 71 may in some embodiments be an internal storage unit of the terminal device 7, such as a hard disk or a memory of the terminal device 7. In other embodiments, the memory 71 may also be an external storage device of the terminal device 7, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used for storing an operating system, an application program, a Boot Loader (Boot Loader), data, and other programs, such as program codes of the computer programs. The memory 71 may also be used to temporarily store data that has been output or is to be output.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.
The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), random-access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
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 a plurality of 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.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. An exercise monitoring method, comprising:
acquiring a target motion mode of a user, and determining standard motion data corresponding to the target motion mode;
and monitoring the actual motion data of the user, and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
2. The athletic monitoring method of claim 1, wherein the standard athletic data includes a standard heart rate range, and the actual athletic data includes an actual heart rate;
the acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode includes:
acquiring a target motion mode of a user, acquiring sign information of the user corresponding to the target motion mode, and determining standard motion data corresponding to the target motion mode according to the sign information;
the monitoring of the actual motion data of the user and the prompting of the user to adjust the motion state when the actual motion data is not matched with the standard motion data comprises:
monitoring an actual heart rate of the user;
when the actual heart rate is larger than the maximum value of the standard heart rate range, prompting the user to reduce exercise intensity;
and when the actual heart rate is smaller than the minimum value of the standard heart rate range, prompting the user to improve the exercise intensity.
3. The exercise monitoring method as claimed in claim 2, wherein when the target exercise mode is an anaerobic exercise, the obtaining of the physical sign information of the user corresponding to the target exercise mode includes:
acquiring the age of a user;
the determining of the standard motion data corresponding to the target motion mode according to the sign information includes:
calculating a maximum heart rate from the age;
calculating an anaerobic exercise heart rate from the maximum heart rate and the age;
and acquiring a preset difference value, and determining a standard heart rate range corresponding to the target exercise mode according to the preset difference value and the anaerobic exercise heart rate.
4. The exercise monitoring method according to claim 2, wherein when the target exercise mode is aerobic exercise, the obtaining of the physical sign information of the user corresponding to the target exercise mode includes:
acquiring the average values of height, weight, age and sleep heart rate of a user;
the determining of the standard motion data corresponding to the target motion mode according to the sign information includes:
calculating a resting heart rate according to the height, the weight, the age and the average value of the sleep heart rate, and calculating a maximum heart rate according to the age;
calculating a heart rate reserve from the resting heart rate and the maximum heart rate;
and acquiring a maximum heart rate percentage range corresponding to the target movement mode, and calculating a standard heart rate range corresponding to the target movement mode according to the heart rate reserve and the maximum heart rate percentage range.
5. The method for monitoring exercise of claim 1, wherein the standard exercise data comprises a standard swing trajectory and a standard exercise trajectory, and the actual exercise data comprises an actual swing trajectory and an actual exercise trajectory;
the acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode includes:
acquiring a target motion mode of a user, and determining a standard swing track and a standard motion track corresponding to the target motion mode;
the monitoring of the actual motion data of the user and the prompting of the user to adjust the motion state when the actual motion data is not matched with the standard motion data comprises:
monitoring an actual swing track and an actual motion track of a user;
and when the actual swing track is not matched with the standard swing track and/or when the actual motion track is not matched with the standard motion track, prompting a user to change the action posture.
6. The method for monitoring exercise monitoring of claim 5, wherein the monitoring of the actual swing trajectory and the actual exercise trajectory of the user comprises:
monitoring a real-time acceleration signal and a real-time angular velocity signal of wearable equipment worn by a user, and acquiring static attitude data of the wearable equipment;
and determining an actual swing track and an actual motion track according to the static attitude data, the real-time acceleration signal and the real-time angular velocity signal.
7. The athletic monitoring method of claim 6, wherein the static posture data includes preset initial coordinates and an initial acceleration signal when the wearable device is worn by the user in a static state;
determining an actual swing track and an actual motion track according to the static attitude data, the actual acceleration signal and the actual angular velocity signal, including:
respectively calculating the space position variable quantity and the path variable quantity corresponding to each historical monitoring moment according to the real-time acceleration signal and the real-time angular velocity signal;
calculating the actual swing track of the current monitoring moment according to the space position variation corresponding to each historical monitoring moment and the initial acceleration signal;
and calculating the actual motion track of the current monitoring moment according to the path variable quantity corresponding to each historical monitoring moment and the initial coordinate.
8. An athletic monitoring device, comprising:
the information acquisition unit is used for acquiring a target motion mode of a user and determining standard motion data corresponding to the target motion mode;
and the motion monitoring unit is used for monitoring the actual motion data of the user and prompting the user to adjust the motion state when the actual motion data is not matched with the standard motion data.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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