CN116784839A - Activity intensity detection method and device and wearable equipment - Google Patents
Activity intensity detection method and device and wearable equipment Download PDFInfo
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1118—Determining activity level
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
Abstract
The application discloses an activity intensity detection method, an activity intensity detection device and wearable equipment, wherein the method comprises the following steps: after the physiological data of the target object when participating in the target activity is obtained, a plurality of discrimination index scores corresponding to the target object are obtained based on the physiological data, the plurality of discrimination index scores represent index scores respectively corresponding to the target object under the activity amount discrimination indexes of different dimensions, and the activity intensity data of the target object in the target activity is obtained based on the plurality of discrimination index scores. According to the method, a plurality of judgment index scores are obtained based on physiological data, and the activity intensity data of the target object in the target activity is obtained according to the judgment index scores, so that the activity intensity of the target object can be comprehensively and efficiently judged under the activity quantity judgment indexes of different dimensions, the judgment process of the activity intensity is more targeted, simple and efficient, and the obtained activity intensity data is more comprehensive and accurate.
Description
Technical Field
The application relates to the technical field of health monitoring, in particular to an activity intensity detection method. The application also relates to an activity intensity detection device and a wearable device.
Background
When the user participates in the body-building training project such as physical training, the method has an important role in accurately judging the training intensity of the user, if the training intensity is too high, irreversible damage is easily caused to the body of the user, and if the training intensity is too low, the preset training effect cannot be achieved. The physical training intensity consists of load intensity and load quantity, wherein the load intensity refers to the depth of the load to the body stimulus, reflects the quality characteristics of the training load and is a core element of the physical training load; the load quantity is the measurement of the load to the body stimulus, which reflects the quantity characteristic of the training load, and the application and change of the load quantity are the basis of the change of the load intensity. The method is mainly based on the fact that the intensity of the physical training meets the standard, the intensity of the physical training is mainly based on the intensity of the load, the intensity of the physical training load can be evaluated by training indexes and biological indexes, the training indexes are mainly used for evaluating the intensity of the physical training through comparing the intensity of the load in the training with the competitive intensity in the standard, and the intensity of the physical training load is evaluated, such as percentage intensity evaluation or qualitative intensity level evaluation, and the method has the problems that the evaluation standard is different, the time consumption is long, the detection process is complex, and the execution standard in the physical training is inconsistent.
Therefore, how to efficiently, objectively and accurately detect the activity intensity of the user when participating in various activities is a problem to be solved in order to make the activity intensity of the user match with the physiological condition of the user.
Disclosure of Invention
The application aims to solve the technical problem of efficiently, objectively and accurately detecting the activity intensity of a user by providing an activity intensity detection method, an activity intensity detection device and wearable equipment.
To solve or improve the above technical problem to some extent, according to an aspect of the present application, there is provided an activity intensity detection method, including:
obtaining physiological data of a target object when participating in a target activity;
based on the physiological data, obtaining a plurality of discrimination index scores corresponding to the target object, wherein the discrimination index scores represent index scores respectively corresponding to the target object under the activity discrimination indexes of different dimensions;
and acquiring activity intensity data of the target object in the target activity based on the plurality of discrimination index scores.
In some embodiments, the obtaining activity intensity data of the target object corresponding to the target activity based on the plurality of discrimination indicator scores includes:
acquiring activity scores corresponding to the discrimination index scores based on a preset score corresponding relation;
and counting the activity amount scores corresponding to the discrimination index scores to obtain activity intensity data corresponding to the target object in the time interval of the target activity.
In some embodiments, the physiological data comprises: heart rate data;
the activity amount discrimination index includes at least two of:
a relative heart rate of the target subject in the target activity;
an absolute heart rate of the target subject in the target activity;
a maximum heart rate of the target subject in the target activity;
an average heart rate of the target subject in the target activity;
heart rate variability of the target subject in the target activity.
In some embodiments, the method further comprises:
and determining whether the activity amount of the target object meets the standard or not based on the activity intensity data.
In some embodiments, the target activity is a physical training program for a target group, the target object being any object in the target group; the method further comprises the steps of:
and determining whether the training intensity of the sports training item meets the standard or not based on the activity intensity data of each target object in the target group.
In some embodiments, the determining whether the training intensity of the sports training item meets the standard based on the activity intensity data of each target object in the target group includes:
determining that the training intensity of the target population does not reach the standard in response to the duty cycle of the target object, for which the activity intensity data does not reach the first activity intensity threshold, in the target population exceeding a first proportion threshold;
alternatively, in response to the duty cycle of the target object in the target population for which the activity intensity data exceeds a second activity intensity threshold exceeding a second proportion threshold, it is determined that the training intensity of the target population has exceeded.
In some embodiments, the target population is a minor population.
In some embodiments, the method further comprises:
in response to the training intensity of the physical training program not reaching the standard, increasing the training intensity of the target object; or, in response to the training intensity of the athletic training program having exceeded a criterion, decreasing the training intensity of the target object.
According to another aspect of the present application, there is provided an activity intensity detection apparatus including:
a physiological data obtaining unit for obtaining physiological data of the target object when participating in the target activity;
a discrimination index score obtaining unit, configured to obtain a plurality of discrimination index scores corresponding to the target object based on the physiological data, where the plurality of discrimination index scores represent index scores corresponding to the target object under activity discrimination indexes of different dimensions, respectively;
and the activity intensity data obtaining unit is used for obtaining the activity intensity data of the target object in the target activity based on the plurality of discrimination index scores.
According to another aspect of the application, a wearable device is provided, which may perform the method as described above.
Compared with the prior art, the application has the following advantages:
according to the activity intensity detection method provided by the application, after the physiological data of the target object when participating in the target activity is obtained, a plurality of discrimination index scores corresponding to the target object are obtained based on the physiological data, the plurality of discrimination index scores represent index scores corresponding to the target object under the activity amount discrimination indexes of different dimensions respectively, and the activity intensity data of the target object in the target activity is obtained based on the plurality of discrimination index scores. According to the method, a plurality of discrimination index scores are obtained based on physiological data, and the activity intensity data of the target object in the target activity is obtained according to the discrimination index scores, so that the activity intensity of the target object can be comprehensively and efficiently judged under the activity amount discrimination indexes of different dimensions, the detection process of the activity intensity is more targeted, simple and efficient, and the obtained activity intensity data is more comprehensive, objective and accurate.
Drawings
FIG. 1 is a flow chart of a method for detecting activity intensity according to an embodiment of the present application;
FIG. 2 is a block diagram of an activity intensity detection device according to an embodiment of the present application;
fig. 3 is a schematic logic structure diagram of a wearable device according to an embodiment of the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. The present application may be embodied in many other forms than those herein described, and those skilled in the art will readily appreciate that the present application may be similarly embodied without departing from the spirit or essential characteristics thereof, and therefore the present application is not limited to the specific embodiments disclosed below.
The physical training intensity consists of load intensity and load quantity, wherein the load intensity refers to the depth of the load to the body stimulus, reflects the quality characteristics of the training load and is a core element of the physical training load; the load quantity is the measurement of the load to the body stimulus, which reflects the quantity characteristic of the training load, and the application and change of the load quantity are the basis of the change of the load intensity. The method is mainly based on the fact that the intensity of the physical training meets the standard, the intensity of the physical training is mainly based on the intensity of the load, the intensity of the physical training load can be evaluated by training indexes and biological indexes, the training indexes are mainly used for evaluating the intensity of the physical training through comparing the intensity of the load in the training with the competitive intensity in the standard, and the intensity of the physical training load is evaluated, such as percentage intensity evaluation or qualitative intensity level evaluation, and the method has the problems that the evaluation standard is different, the time consumption is long, the detection process is complex, and the execution standard in the physical training is inconsistent.
The biological index can objectively judge the intensity of training load by monitoring the physiological and biochemical indexes such as urine protein, blood lactic acid and the like, and can accurately and conveniently detect the activity intensity, so that aiming at an activity intensity detection scene, the method provided by the application adopts heart rate as an index and comprehensively researches and judges heart rate indexes of multiple dimensions to obtain comprehensive, accurate and objective activity intensity detection results in order to enable the activity intensity detection process to be more targeted, simple and efficient and enable the obtained activity intensity data to be more comprehensive, objective and accurate.
The application also provides an activity intensity detection device and wearable equipment corresponding to the method. The following provides examples to describe the above method, apparatus, and wearable device in detail.
An embodiment of the present application provides an activity intensity detection method, where an application body of the method may be a computing device application for detecting activity intensity of a user, where the computing device application may be executed in a wearable device or in a server for activity intensity detection. Fig. 1 is a flowchart of an activity intensity detection method according to an embodiment of the present application, and the method according to the embodiment is described in detail below with reference to fig. 1. The embodiments referred to in the following description are intended to illustrate the method principles and not to limit the practical use.
As shown in fig. 1, the activity intensity detection method provided in this embodiment includes the following steps:
s101, obtaining physiological data of a target object when participating in a target activity.
The step is used for obtaining physiological data of a target object participating in target activities, the target object can be any individual or the physiological data can be one or more of respiratory rate, pulse wave signal data, heart rate data and the like of the target object, and the target activities can be any type of activities for enabling a user to generate activities, such as any type of sports training items.
In this embodiment, the physiological data of the target object when participating in the target activity can be obtained by: when a target object participates in target activities, multi-modal physiological data is acquired based on a wearable device worn by a target user, for example, a pulse wave sensor, a skin electric sensor, an acceleration sensor, an angular velocity sensor, a GPS sensor, a blood oxygen sensor, a blood pressure sensor, a voice sensor, a respiratory rate detector and other sensors used for acquiring the multi-modal physiological data such as a pulse wave sensor, a skin electric sensor, an acceleration sensor, an angular velocity sensor, a GPS sensor, a blood oxygen sensor, a blood pressure sensor, a voice sensor, a respiratory rate detector and other monitoring modules are used for acquiring the multi-modal physiological data such as PPG signals, heart rate data and respiratory rate of the user.
S102, obtaining a plurality of discrimination index scores corresponding to the target object based on the physiological data.
After the step of obtaining the physiological data of the target object when participating in the target activity, the step is used for obtaining a plurality of discrimination index scores corresponding to the target object according to the physiological data, wherein the discrimination index scores represent index scores corresponding to the target object under the activity amount discrimination indexes of different dimensions respectively. Specifically, data extraction can be performed on the basis of the multi-mode physiological data according to preset activity judgment indexes, so as to obtain judgment index scores of different dimensions and different modes.
The embodiment uses Heart Rate (HR) as the above physiological data to describe, where the Heart Rate refers to the number of Heart beats in unit time, that is, the frequency of Heart contraction beating, and the resting Heart Rate of a normal individual is generally 60 to 100 times per minute (60 to 100 bpm), and the Heart Rate can rise during exercise, and the height of the Heart Rate can intuitively reflect the fluctuation of the cardiovascular activity of the human body in a calm state as compared with a state in which the Heart Rate is calm, and can also reflect the phenomena of fatigue, exercise overload, exercise load and the like on the physiological system. The activity amount discrimination index may be at least two of data such as a maximum heart rate, an average heart rate, a relative heart rate, an absolute heart rate, and a heart rate variation rate of the target subject in the target activity. The maximum heart rate is the heart rate maximum value of the target object in the whole target activity interval, the average heart rate is the average value of the heart rate of the target object in the whole target activity interval, the relative heart rate represents the difference value between the average heart rate of the target object in the motion interval of the target activity and the average heart rate of the rest interval, the absolute heart rate represents the ratio between the relative heart rate and the difference heart rate (the difference value heart rate is the difference value between the maximum heart rate and the average heart rate of the target object in the rest interval of the target activity), and the heart rate change rate represents the difference value between the maximum heart rate and the average heart rate.
For example, the respiratory rate may be used as the physiological data, and the activity determination index may be at least two of data such as a maximum respiratory rate, an average respiratory rate, a relative respiratory rate, an absolute respiratory rate, and a respiratory rate change rate of the target subject in the target activity, and the meaning of the index is referred to as the maximum heart rate, the average heart rate, the relative heart rate, the absolute heart rate, and the heart rate change rate, which are not described herein.
S103, obtaining activity intensity data of the target object in the target activity based on the multiple discrimination index scores.
After the step of obtaining the plurality of discrimination indicator scores corresponding to the target object, the step is used for obtaining the activity intensity data of the target object corresponding to the target activity based on the plurality of discrimination indicator scores. The purpose of using a plurality of discrimination index scores is to comprehensively determine the activity intensity of the target object under the activity amount discrimination indexes of different dimensions, so that the obtained activity intensity data is more comprehensive and accurate. In this embodiment, the activity intensity data may be obtained specifically by:
firstly, obtaining activity scores corresponding to the scores of all discrimination indexes based on preset score correspondence; that is, for each activity amount discrimination index, a plurality of value intervals are preset, each value interval corresponds to an activity amount score, and if the index score corresponding to a certain activity amount discrimination index is within a certain value interval, the activity amount score corresponding to the index score is the activity amount score corresponding to the value interval.
And secondly, counting the activity amount scores corresponding to the discrimination index scores to obtain activity intensity data corresponding to the target object in the time interval of the target activity, for example, determining the sum value of the activity amount scores corresponding to the discrimination index scores as the activity intensity data corresponding to the target object in the time interval of the target activity.
After the activity intensity data of the target object in the target activity is obtained, it is also required to determine whether the activity amount of the target object meets the standard based on the activity intensity data. In this embodiment, the target activity is preferably a physical training program for a target group, and the target object is any object in the target group, for example, the target group is a minor group (for example, a group of middle and primary school students). In this case, it is also necessary to determine whether the training intensity of the sports training program meets the standard based on the activity intensity data of each target object in the target group. For example, if the activity intensity data does not reach the first activity intensity threshold (the first activity intensity threshold is used for determining whether the activity intensity of the individual meets the standard) the number of target objects, the ratio of the target group exceeds the first ratio threshold, the training intensity of the target group is determined to be not met, if the activity intensity data exceeds the second activity intensity threshold (the second activity intensity threshold is used for determining whether the activity intensity of the individual exceeds the standard) the number of target objects, the ratio of the target group exceeds the second ratio threshold, and the training intensity of the target group is determined to be exceeded. Correspondingly, when the training intensity of the physical training items does not reach the standard, the training intensity of the target object needs to be correspondingly increased, or when the training intensity of the physical training items exceeds the standard, the training intensity of the target object needs to be correspondingly reduced.
According to the activity intensity detection method provided by the embodiment, after the physiological data of the target object when participating in the target activity is obtained, a plurality of discrimination index scores corresponding to the target object are obtained based on the physiological data, the plurality of discrimination index scores represent index scores corresponding to the target object under the activity amount discrimination indexes of different dimensions respectively, and the activity intensity data of the target object in the target activity is obtained based on the plurality of discrimination index scores. According to the method, a plurality of discrimination index scores are obtained based on physiological data, and the activity intensity data of the target object in the target activity is obtained according to the discrimination index scores, so that the activity intensity of the target object can be comprehensively and efficiently judged under the activity amount discrimination indexes of different dimensions, the detection process of the activity intensity of the user is simple and efficient, and the obtained activity intensity data is more comprehensive, objective and accurate.
The first embodiment provides a method for detecting activity intensity, and correspondingly, another embodiment of the present application further provides an activity intensity detecting device, and since the device embodiment is substantially similar to the method embodiment, the description is relatively simple, and details of relevant technical features should be referred to the corresponding description of the method embodiment provided above, and the following description of the device embodiment is merely illustrative.
Referring to fig. 2 for understanding the embodiment, fig. 2 is a block diagram of a unit of an activity intensity detection apparatus according to the present embodiment, and as shown in fig. 2, the apparatus according to the present embodiment includes:
a physiological data obtaining unit 201 for obtaining physiological data of a target subject when participating in a target activity;
a discrimination indicator score obtaining unit 202, configured to obtain, based on the physiological data, a plurality of discrimination indicator scores corresponding to the target object, where the plurality of discrimination indicator scores represent indicator scores corresponding to the target object under activity amount discrimination indicators in different dimensions, respectively;
an activity intensity data obtaining unit 203, configured to obtain activity intensity data of the target object in the target activity based on the plurality of discrimination indicator scores.
In some embodiments, the obtaining activity intensity data of the target object corresponding to the target activity based on the plurality of discrimination indicator scores includes:
acquiring activity scores corresponding to the discrimination index scores based on a preset score corresponding relation;
and counting the activity amount scores corresponding to the discrimination index scores to obtain activity intensity data corresponding to the target object in the time interval of the target activity.
In some embodiments, the physiological data comprises: heart rate data;
the activity amount discrimination index includes at least two of:
a relative heart rate of the target subject in the target activity;
an absolute heart rate of the target subject in the target activity;
a maximum heart rate of the target subject in the target activity;
an average heart rate of the target subject in the target activity;
heart rate variability of the target subject in the target activity.
In some embodiments, the apparatus further comprises:
and the activity amount standard determining unit is used for determining whether the activity amount of the target object meets the standard or not based on the activity intensity data.
In some embodiments, the target activity is a physical training program for a target group, the target object being any object in the target group; the method further comprises the steps of:
and determining whether the training intensity of the sports training item meets the standard or not based on the activity intensity data of each target object in the target group.
In some embodiments, the determining whether the training intensity of the sports training item meets the standard based on the activity intensity data of each target object in the target group includes:
determining that the training intensity of the target population does not reach the standard in response to the duty cycle of the target object, for which the activity intensity data does not reach the first activity intensity threshold, in the target population exceeding a first proportion threshold;
alternatively, in response to the duty cycle of the target object in the target population for which the activity intensity data exceeds a second activity intensity threshold exceeding a second proportion threshold, it is determined that the training intensity of the target population has exceeded.
In some embodiments, the target population is a minor population.
In some embodiments, the apparatus further comprises:
the training intensity adjusting unit is used for increasing the training intensity of the target object in response to the training intensity of the sports training item not reaching the standard; or, in response to the training intensity of the athletic training program having exceeded a criterion, decreasing the training intensity of the target object.
According to the activity intensity detection device provided by the embodiment of the application, after the physiological data of the target object when participating in the target activity is obtained, a plurality of discrimination index scores corresponding to the target object are obtained based on the physiological data, the plurality of discrimination index scores represent index scores corresponding to the target object under the activity amount discrimination indexes of different dimensions respectively, and the activity intensity data of the target object in the target activity is obtained based on the plurality of discrimination index scores. The device obtains a plurality of discrimination index scores based on physiological data, and obtains the activity intensity data of the target object in the target activity according to the discrimination index scores, and can comprehensively and efficiently judge the activity intensity of the target object under the activity amount discrimination indexes of different dimensions, so that the judgment process of the activity intensity is simple and efficient, and the obtained activity intensity data is more comprehensive and accurate.
The above embodiment provides a method for detecting activity intensity and a device for detecting activity intensity, and in addition, another embodiment of the present application further provides a wearable device, which may be a wearable bracelet, a helmet, or the like, on which a sensor for acquiring multi-mode raw data, such as a pulse wave sensor, a skin sensor, an acceleration sensor, an angular velocity sensor, a GPS sensor, an oxygen sensor, a blood pressure sensor, a voice sensor, or the like, and other monitoring modules are mounted. Since the wearable device embodiment is substantially similar to the method embodiment, the description is relatively simple, and the details of the relevant technical features may be found in the corresponding description of the method embodiment provided above, and the following description of the wearable device embodiment is merely illustrative. The wearable device embodiment is as follows:
fig. 3 is a schematic diagram of the wearable device provided in the present embodiment.
As shown in fig. 3, the wearable device provided in this embodiment includes, in addition to various sensors and other monitoring modules for acquiring multi-mode raw data: a processor 301 and a memory 302;
the memory 302 is used to store computer instructions for data processing which, when read and executed by the processor 301, perform the following operations:
obtaining physiological data of a target object when participating in a target activity;
based on the physiological data, obtaining a plurality of discrimination index scores corresponding to the target object, wherein the discrimination index scores represent index scores respectively corresponding to the target object under the activity discrimination indexes of different dimensions;
and acquiring activity intensity data of the target object in the target activity based on the plurality of discrimination index scores.
In some embodiments, the obtaining activity intensity data of the target object corresponding to the target activity based on the plurality of discrimination indicator scores includes:
acquiring activity scores corresponding to the discrimination index scores based on a preset score corresponding relation;
and counting the activity amount scores corresponding to the discrimination index scores to obtain activity intensity data corresponding to the target object in the time interval of the target activity.
In some embodiments, the physiological data comprises: heart rate data;
the activity amount discrimination index includes at least two of:
a relative heart rate of the target subject in the target activity;
an absolute heart rate of the target subject in the target activity;
a maximum heart rate of the target subject in the target activity;
an average heart rate of the target subject in the target activity;
heart rate variability of the target subject in the target activity.
In some embodiments, further comprising:
and determining whether the activity amount of the target object meets the standard or not based on the activity intensity data.
In some embodiments, the target activity is a physical training program for a target group, the target object being any object in the target group; the method further comprises the steps of:
and determining whether the training intensity of the sports training item meets the standard or not based on the activity intensity data of each target object in the target group.
In some embodiments, the determining whether the training intensity of the sports training item meets the standard based on the activity intensity data of each target object in the target group includes:
determining that the training intensity of the target population does not reach the standard in response to the duty cycle of the target object, for which the activity intensity data does not reach the first activity intensity threshold, in the target population exceeding a first proportion threshold;
alternatively, in response to the duty cycle of the target object in the target population for which the activity intensity data exceeds a second activity intensity threshold exceeding a second proportion threshold, it is determined that the training intensity of the target population has exceeded.
In some embodiments, the target population is a minor population.
In some embodiments, further comprising:
in response to the training intensity of the physical training program not reaching the standard, increasing the training intensity of the target object; or, in response to the training intensity of the athletic training program having exceeded a criterion, decreasing the training intensity of the target object.
According to the wearable device provided by the embodiment, after the physiological data of the target object when participating in the target activity is obtained, a plurality of discrimination index scores corresponding to the target object are obtained based on the physiological data, the plurality of discrimination index scores represent index scores corresponding to the target object under the activity amount discrimination indexes of different dimensions respectively, and the activity intensity data of the target object in the target activity is obtained based on the plurality of discrimination index scores. The wearable device obtains a plurality of discrimination index scores based on physiological data, and obtains activity intensity data of the target object in the target activity according to the discrimination index scores, so that the activity intensity of the target object can be comprehensively judged under the activity quantity discrimination indexes of different dimensions, and the obtained activity intensity data is more comprehensive and accurate.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
1. Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer readable media, as defined herein, does not include non-transitory computer readable media (transmission media), such as modulated data signals and carrier waves.
2. It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
While the application has been described in terms of preferred embodiments, it is not intended to be limiting, but rather, it will be apparent to those skilled in the art that various changes and modifications can be made herein without departing from the spirit and scope of the application as defined by the appended claims.
Claims (10)
1. A method of activity intensity detection, the method comprising:
obtaining physiological data of a target object when participating in a target activity;
based on the physiological data, obtaining a plurality of discrimination index scores corresponding to the target object, wherein the discrimination index scores represent index scores respectively corresponding to the target object under the activity discrimination indexes of different dimensions;
and acquiring activity intensity data of the target object in the target activity based on the plurality of discrimination index scores.
2. The method of claim 1, wherein the obtaining activity intensity data of the target object corresponding to the target activity based on the plurality of discrimination indicator scores comprises:
acquiring activity scores corresponding to the discrimination index scores based on a preset score corresponding relation;
and counting the activity amount scores corresponding to the discrimination index scores to obtain activity intensity data corresponding to the target object in the time interval of the target activity.
3. The method of claim 1, wherein the physiological data comprises: heart rate data;
the activity amount discrimination index includes at least two of:
a relative heart rate of the target subject in the target activity;
an absolute heart rate of the target subject in the target activity;
a maximum heart rate of the target subject in the target activity;
an average heart rate of the target subject in the target activity;
heart rate variability of the target subject in the target activity.
4. The method according to claim 1, wherein the method further comprises:
and determining whether the activity amount of the target object meets the standard or not based on the activity intensity data.
5. The method of claim 1, wherein the target activity is a physical training program for a target group, the target object being any object in the target group; the method further comprises the steps of:
and determining whether the training intensity of the sports training item meets the standard or not based on the activity intensity data of each target object in the target group.
6. The method of claim 5, wherein determining whether the training intensity of the athletic training program meets the criteria based on activity intensity data of each target object in the target group comprises:
determining that the training intensity of the target population does not reach the standard in response to the duty cycle of the target object, for which the activity intensity data does not reach the first activity intensity threshold, in the target population exceeding a first proportion threshold;
alternatively, in response to the duty cycle of the target object in the target population for which the activity intensity data exceeds a second activity intensity threshold exceeding a second proportion threshold, it is determined that the training intensity of the target population has exceeded.
7. The method of claim 5 or 6, wherein the target population is a minor population.
8. The method of claim 6, wherein the method further comprises:
in response to the training intensity of the physical training program not reaching the standard, increasing the training intensity of the target object; or, in response to the training intensity of the athletic training program having exceeded a criterion, decreasing the training intensity of the target object.
9. An activity intensity detection device, the device comprising:
a physiological data obtaining unit for obtaining physiological data of the target object when participating in the target activity;
a discrimination index score obtaining unit, configured to obtain a plurality of discrimination index scores corresponding to the target object based on the physiological data, where the plurality of discrimination index scores represent index scores corresponding to the target object under activity discrimination indexes of different dimensions, respectively;
and the activity intensity data obtaining unit is used for obtaining the activity intensity data of the target object in the target activity based on the plurality of discrimination index scores.
10. A wearable device, characterized in that the wearable device is executable to perform the method of any of claims 1-8.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150327804A1 (en) * | 2012-02-16 | 2015-11-19 | Katholieke Universiteit Leuven | Exercise system and method |
| JP2017123898A (en) * | 2016-01-12 | 2017-07-20 | セイコーエプソン株式会社 | Biological information processing system, electronic instrument, program, and control method for biological information processing system |
| CN108551659A (en) * | 2018-04-19 | 2018-09-18 | 中科爱思（天津）科技有限公司 | A kind of method and system for group sports real time monitoring analysis |
| CN109126056A (en) * | 2018-09-21 | 2019-01-04 | 万赢体育科技（上海）有限公司 | Athletic training system |
| US20200261011A1 (en) * | 2019-02-19 | 2020-08-20 | Firstbeat Technologies Oy | Methods and apparatus for analyzing and providing feedback of training effects, primary exercise benefits, training status, balance between training intensities and an automatic feedback system and apparatus for guiding future training |
| CN112349413A (en) * | 2020-10-23 | 2021-02-09 | 湖南城市学院 | Long-distance exercise training load analysis system |
| CN114187996A (en) * | 2021-11-19 | 2022-03-15 | 逸群海豚信息科技(上海)有限公司 | Personalized exercise prescription management system |
| CN114550865A (en) * | 2022-02-18 | 2022-05-27 | 北京碧云数创科技有限公司 | Multidimensional data analysis method and device influencing student physical measurement |
| CN115040116A (en) * | 2022-08-01 | 2022-09-13 | 上海探寻信息技术有限公司 | Method and device for monitoring activity of wearable equipment |
| CN115191997A (en) * | 2021-04-09 | 2022-10-18 | 广东小天才科技有限公司 | Motion intensity detection method and wearable device |
| CN115462767A (en) * | 2022-08-16 | 2022-12-13 | 安克创新科技股份有限公司 | Motion monitoring method, motion guiding device, wearable equipment and terminal equipment |
-
2023
- 2023-08-29 CN CN202311098257.0A patent/CN116784839B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150327804A1 (en) * | 2012-02-16 | 2015-11-19 | Katholieke Universiteit Leuven | Exercise system and method |
| JP2017123898A (en) * | 2016-01-12 | 2017-07-20 | セイコーエプソン株式会社 | Biological information processing system, electronic instrument, program, and control method for biological information processing system |
| CN108551659A (en) * | 2018-04-19 | 2018-09-18 | 中科爱思（天津）科技有限公司 | A kind of method and system for group sports real time monitoring analysis |
| CN109126056A (en) * | 2018-09-21 | 2019-01-04 | 万赢体育科技（上海）有限公司 | Athletic training system |
| US20200261011A1 (en) * | 2019-02-19 | 2020-08-20 | Firstbeat Technologies Oy | Methods and apparatus for analyzing and providing feedback of training effects, primary exercise benefits, training status, balance between training intensities and an automatic feedback system and apparatus for guiding future training |
| CN112349413A (en) * | 2020-10-23 | 2021-02-09 | 湖南城市学院 | Long-distance exercise training load analysis system |
| CN115191997A (en) * | 2021-04-09 | 2022-10-18 | 广东小天才科技有限公司 | Motion intensity detection method and wearable device |
| CN114187996A (en) * | 2021-11-19 | 2022-03-15 | 逸群海豚信息科技(上海)有限公司 | Personalized exercise prescription management system |
| CN114550865A (en) * | 2022-02-18 | 2022-05-27 | 北京碧云数创科技有限公司 | Multidimensional data analysis method and device influencing student physical measurement |
| CN115040116A (en) * | 2022-08-01 | 2022-09-13 | 上海探寻信息技术有限公司 | Method and device for monitoring activity of wearable equipment |
| CN115462767A (en) * | 2022-08-16 | 2022-12-13 | 安克创新科技股份有限公司 | Motion monitoring method, motion guiding device, wearable equipment and terminal equipment |
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