CN116804893A - System for health analysis and suggestion based on intelligent wearing detection motion data - Google Patents
System for health analysis and suggestion based on intelligent wearing detection motion data Download PDFInfo
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Abstract
The application provides a system and a method for health analysis and suggestion based on intelligent wearing detection motion data, wherein the system comprises: the first acquisition module is used for acquiring a first electrocardiosignal measured by intelligent wearable equipment worn by a user; the filtering module is used for carrying out filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal; the second acquisition module is used for acquiring motion data sensed by a preset sensor in a measurement period; and the analysis suggestion module is used for acquiring the historical motion record of the user, carrying out health analysis on the user according to the second electrocardiosignal, the motion data and the historical motion record, and sending health suggestions. According to the system and the method for health analysis and suggestion based on intelligent wearing detection motion data, the filtering module is introduced to filter the first electrocardiosignal, so that the accuracy of acquiring the second electrocardiosignal is improved; and the historical exercise record is introduced to judge the exercise intensity of the user and carry out health analysis, so that the exercise machine is more suitable.
Description
Technical Field
The application relates to the technical field of intelligent wearing equipment, in particular to a system and a method for health analysis and suggestion based on intelligent wearing detection motion data.
Background
When people have a motion data detection requirement (for example, athletes need to record motion data), professional equipment (for example, heart rate belts, component analyzers and the like) and intelligent wearable equipment (for example, intelligent watches) are generally adopted for detection, and the professional equipment needs users to go to a special mechanism for detection, so that the detection is very inconvenient. The existing intelligent wearing equipment is convenient to wear and can detect in real time, but general intelligent wearing equipment directly acquires motion data of a user, noise (such as baseline drift and ambient light caused by power frequency interference, breathing jitter and the like) exists, and the situation that an obtained electrocardiogram signal is not clean easily occurs, so that obtained heart rate data is inaccurate. In addition, when analyzing the health condition of the user, no suitable judgment basis exists, and the analysis process is also unsuitable.
Thus, a solution is needed.
Disclosure of Invention
The application aims at providing a system for health analysis and suggestion based on intelligent wearing detection motion data, wherein a filtering module is introduced to carry out filtering processing on a first electrocardiosignal, so that the interference of noise on the electrocardiosignal is avoided, and the accuracy of acquiring a second electrocardiosignal is improved; and the historical exercise record is introduced to judge the exercise intensity of the user and carry out health analysis, so that the exercise machine is more suitable.
The system for health analysis and suggestion based on intelligent wearing detection motion data provided by the embodiment of the application comprises the following components:
the first acquisition module is used for acquiring a first electrocardiosignal measured by an intelligent wearable device worn by a preset user in a latest measurement period in real time;
the filtering module is used for carrying out filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal;
the second acquisition module is used for acquiring motion data sensed by a preset sensor in a measurement period;
and the analysis suggestion module is used for acquiring the historical motion record of the user, carrying out health analysis on the user according to the second electrocardiosignal, the motion data and the historical motion record, and sending corresponding health suggestions.
Preferably, the filtering module performs filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal, which includes:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
Preferably, the analysis suggestion module obtains a historical motion record of the user, performs health analysis on the user according to the second electrocardiograph signal, the motion data and the historical motion record, and sends corresponding health suggestions, including:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
Preferably, the calculating, based on the second electrocardiograph signal and the motion data, current data of the user in each preset unit time in the measurement period includes:
based on a preset first calculation rule, determining the dynamic heart rate of the user according to the second electrocardiosignal;
determining the unit wrist movement times of the user according to the motion data based on a preset second calculation rule;
determining the unit movement steps of the user according to the movement data based on a preset third calculation rule;
and integrating the dynamic heart rate, the unit wrist movement times and the unit movement steps to obtain current data.
Preferably, the analyzing the health of the user and sending the corresponding health advice according to the current exercise intensity includes: acquiring a historical exercise intensity record;
judging whether the user has high-intensity motion or not based on the historical motion intensity record;
if so, carrying out health analysis on the user and sending corresponding health advice.
Preferably, the determining whether the user has a high-intensity motion based on the historical motion intensity record includes:
determining a highest historical motion intensity based on the historical motion intensity record;
if the current motion intensity is greater than the highest historical motion intensity, corresponding users have high-intensity motions;
and/or the number of the groups of groups,
determining a longest duration corresponding to the same historical motion intensity based on the historical motion intensity record;
determining target historical motion intensity consistent with the current motion intensity from the historical motion intensities;
acquiring the longest duration of the target movement intensity and taking the longest duration as the target longest duration;
if the duration of the acquired current motion intensity is longer than the target maximum duration, the corresponding user has high-intensity motion.
Preferably, the analyzing the health of the user and sending the corresponding health advice includes:
generating a template based on a preset analysis result, generating an analysis result according to a second electrocardiosignal and motion data of a user corresponding to high-intensity motion, and simultaneously, acquiring a health suggestion corresponding to the analysis result;
determining an evaluation report extraction item in an analysis result based on a preset evaluation report extraction item comparison table;
filling the evaluation report extraction items into corresponding positions in a preset evaluation report template to obtain an evaluation report;
based on preset pushing rules, pushing the assessment report and the corresponding health advice to the corresponding user.
The method for health analysis and suggestion based on intelligent wearing detection motion data provided by the embodiment of the application comprises the following steps:
step 1: acquiring a first electrocardiosignal measured in a latest measuring period of intelligent wearing equipment worn by a preset user in real time;
step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal;
step 3: acquiring motion data sensed by a preset sensor in a measurement period;
step 4: and acquiring a historical motion record of the user, and carrying out health analysis on the user and sending corresponding health advice according to the second electrocardiosignal, the motion data and the historical motion record.
Preferably, step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal, which comprises the following steps:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
Preferably, the step 4: acquiring a historical motion record of the user, carrying out health analysis on the user and sending corresponding health suggestions according to the second electrocardiosignal, the motion data and the historical motion record, wherein the method comprises the following steps:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the application is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate the application and together with the embodiments of the application, serve to explain the application. In the drawings:
FIG. 1 is a schematic diagram of a system for health analysis and advice based on smart wearable detected motion data in an embodiment of the application;
fig. 2 is a schematic diagram of a method for health analysis and advice based on smart wearable detected motion data in an embodiment of the application.
Detailed Description
The preferred embodiments of the present application will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present application only, and are not intended to limit the present application.
The embodiment of the application provides a system for health analysis and suggestion based on intelligent wearing detection motion data, as shown in fig. 1, comprising:
the first acquisition module 1 is used for acquiring a first electrocardiosignal measured by an intelligent wearable device worn by a preset user in a latest measurement period in real time;
the filtering module 2 is used for carrying out filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal;
a second acquisition module 3, configured to acquire motion data sensed by a preset sensor in a measurement period;
and the analysis suggestion module 4 is used for acquiring the historical motion record of the user, carrying out health analysis on the user according to the second electrocardiosignal, the motion data and the historical motion record, and sending corresponding health suggestions.
The working principle and the beneficial effects of the technical scheme are as follows:
the preset user is a user using an intelligent wearable device (for example, an intelligent watch), the user wears the intelligent wearable device to measure motion data (for example, walking steps, heart rate and the like), and the first electrocardiosignal measured in the last measurement period is: the electrocardiographic signals of the monitored user are measured in real time, and the measurement period is, for example: 5 minutes. When the intelligent wearable equipment detects the first electrocardiosignal, the first electrocardiosignal can be subjected to baseline drift, ambient light and other noises caused by power frequency interference, breath jitter and the like, so that the first electrocardiosignal is subjected to filtering processing to obtain a processed second electrocardiosignal, for example: and removing the interference signals such as blood flow sound and the like by utilizing the self-adaptive filtering, so that a clean second electrocardiosignal can be obtained. The motion data sensed by the sensor is, for example: three-dimensional motion acceleration, the sensor is, for example: a three-axis sensor. Acquiring a historical motion record of the user, and carrying out health analysis on the user and sending corresponding health suggestions according to the second electrocardiosignal, the motion data and the historical motion record, for example: sending a notification message to a smart phone of a user: "you exercise intensity is too high, and it is recommended to slowly increase exercise intensity to strengthen physique", and when sending, the smart phone and the intelligent wearing detection exercise data are in communication docking with the recommended system for health analysis.
According to the application, the intelligent wearing equipment is introduced to filter the first electrocardiosignal, so that the interference of noise on the electrocardiosignal is avoided, and the accuracy of acquiring the second electrocardiosignal is improved; and the historical exercise record is introduced to judge the exercise intensity of the user and carry out health analysis, so that the exercise machine is more suitable.
In one embodiment, the filtering module performs filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal, which includes:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
The working principle and the beneficial effects of the technical scheme are as follows:
the preset first feature extraction template is as follows: a template for extracting signal characteristics of the first electrocardiograph signal, such as: the first set of eigenvalues are, for example: the degree to which the first electrocardiosignal is disturbed by noise, the bandwidth of the first electrocardiosignal, etc. The filter matching library stores a first filter and a second characteristic value set which are in one-to-one correspondence, and the second characteristic value set is as follows: the first filter is adapted to signal characteristics of the processed signal. And matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value (the larger the matching value is, the more suitable the corresponding first filter is for filtering the first electrocardiosignal). And if the matching value is greater than or equal to a matching value threshold value corresponding to the first filter (the matching value threshold value is preset by staff), taking the corresponding first filter as a second filter, and filtering the first electrocardiosignal through the second filter to finish the filtering process.
According to the application, the first characteristic extraction template is introduced, and the first characteristic value set of the first electrocardiosignal is determined, so that the accuracy of acquiring the first characteristic set is improved; the first characteristic value set and the second characteristic value set are matched one by one, and the second filter with the matched value larger than the threshold value of the corresponding matched value is determined to carry out filtering processing on the first electrocardiosignal, so that the suitability of the filtering processing is improved.
In one embodiment, the analysis suggestion module obtains a historical motion record of the user, and analyzes the current motion intensity of the user according to the second electrocardiographic signal, the motion data and the historical motion record, including:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
The working principle and the beneficial effects of the technical scheme are as follows:
the preset unit time is, for example: 1 minute, calculating current data based on the second electrocardiographic signal and the motion data, including: dynamic heart rate, number of beats per unit of wrist and number of steps per unit of exercise (e.g., 90 beats per minute at heart rate, 100 beats per minute at wrist swing, 120 steps per minute per step of exercise). Historical exercise records are parsed to obtain historical average measurement data for the user (e.g., when the user is exercising, the average number of steps is 100 steps/min, the heart rate is 88 beats/min, and the wrist is 90 beats/min). The current data and the average measurement data are calculated to correspond to the data difference (for example: 10 times/min) of the same data type (for example: heart rate data), the difference direction (for example: the difference is positive and for example: the difference is negative) of the data difference is obtained, and the type weights of the data types (the physical quality of the individuals is different, the standard of the exercise intensity is different, but the heart rate can directly reflect the bearing degree of the user on the ongoing exercise for themselves no matter the physical quality is good or poor), so that the heart rate data can more represent the exercise intensity of the user, and the type weights of the heart rate data are more important than the type weights of the exercise step number data). Based on the data difference value, the difference value direction and the type weight of the corresponding data type, the current motion intensity is calculated according to the following calculation formula:
wherein, the liquid crystal display device comprises a liquid crystal display device,gamma, the current exercise intensity i Type weight with the i-th difference direction being positive direction, d i For the data difference value with the ith difference value direction being the positive direction, n 1 The total number of data differences with the difference direction being the positive direction; gamma ray t Type weight with the t-th difference direction being negative, d ’ t For the data difference value with the t-th difference value direction being the negative direction, n 2 The total number of data differences whose difference direction is the negative direction. Based on the current exercise intensity, the user is analyzed for health and corresponding health advice is sent (e.g., exercise intensity is too high, suggesting that the user decrease exercise intensity).
The method and the device for determining the current motion intensity based on the calculated current data and the average data are more reasonable, meanwhile, the current motion intensity is calculated according to the type weights of different data types, and the accuracy of motion intensity determination is further improved.
In one embodiment, the calculating, based on the second electrocardiographic signal and the motion data, current data of the user in each preset unit time in the measurement period includes:
based on a preset first calculation rule, determining the dynamic heart rate of the user according to the second electrocardiosignal;
determining the unit wrist movement times of the user according to the motion data based on a preset second calculation rule;
determining the unit movement steps of the user according to the movement data based on a preset third calculation rule;
and integrating the dynamic heart rate, the unit wrist movement times and the unit movement steps to obtain current data.
The working principle and the beneficial effects of the technical scheme are as follows:
based on a preset first calculation rule, calculating the heart rate of the user (for example, 90 times/min) according to the second electrocardiosignal, wherein the preset first calculation rule is as follows: how to calculate the heart rate of the human body by electrocardiosignals. Determining the wrist movement times (for example, 100 times/min of wrist swinging) of the user according to the movement data based on a preset second calculation rule; the preset second calculation rule is as follows: how to calculate the wrist motion times of the human body through the three-dimensional motion acceleration measured by the intelligent wearable equipment. Based on a preset third calculation rule, calculating the number of exercise steps (for example, 120 steps/min) of the user according to the exercise data, wherein the preset third calculation rule is as follows: how to calculate the number of the motion steps of the human body through the three-dimensional motion acceleration measured by the intelligent wearable equipment. And integrating the data of the dynamic heart rate, the unit wrist movement times and the unit movement steps to obtain the current data.
According to the application, different calculation rules are introduced, and the heart rate, the wrist movement times and the exercise step number of the user are respectively determined, so that the accuracy of calculation data is improved, and the method is more reasonable.
In one embodiment, the analyzing the health of the user and sending the corresponding health advice according to the current exercise intensity includes:
acquiring a historical exercise intensity record;
judging whether the user has high-intensity motion or not based on the historical motion intensity record;
if so, carrying out health analysis on the user and sending corresponding health advice.
The working principle and the beneficial effects of the technical scheme are as follows:
while the user is exercising, exercise behavior of high intensity exercise may occur, however, judgment criteria of exercise intensity for each individual are inconsistent, for example: the exercise intensity evaluation criteria for the elderly are generally lower than for the young, and thus, it is necessary to alert the user according to individual differences. Because the physical quality of the same individual tends to be stable for a period of time, it is reasonable to judge the exercise intensity according to the historical exercise intensity record of the user. When the historical exercise intensity is acquired, the historical exercise intensity record in the last three months is acquired, and the historical exercise intensity record can be acquired from the local storage space of the intelligent wearable device worn by the user. Based on the historical exercise intensity record, whether the user moves at high intensity is judged, if so, the user is subjected to health analysis and corresponding health advice is sent (for example, you have an excessive heart rate, please reduce the pace/make a rest). And the historical exercise intensity record is introduced, the high-intensity exercise judgment is carried out, and the corresponding health analysis and suggestion are carried out, so that the method is more suitable.
In one embodiment, the determining whether the user has a high intensity motion based on the historical motion intensity record includes:
determining a highest historical motion intensity based on the historical motion intensity record;
if the current motion intensity is greater than the highest historical motion intensity;
there is a high intensity motion for the corresponding user;
and/or the number of the groups of groups,
determining a longest duration corresponding to the same historical motion intensity based on the historical motion intensity record;
determining target historical motion intensity consistent with the current motion intensity from the historical motion intensities;
acquiring the longest duration of the target movement intensity and taking the longest duration as the target longest duration;
if the duration of the acquired current motion intensity is longer than the target maximum duration, the corresponding user has high-intensity motion.
The working principle and the beneficial effects of the technical scheme are as follows:
there are two ways to determine if a user has high intensity motion. First kind: based on the historical exercise intensity record, the highest historical exercise intensity is determined (e.g., the historical highest heart rate is 120 beats/min). If the user's current exercise intensity (e.g., current heart rate of 125 beats/min), there is a high intensity exercise for the corresponding user; second kind: based on the historical exercise intensity record, the longest duration corresponding to the same historical exercise intensity is determined (e.g., heart rate is maintained for 30 seconds 125 times/min, heart rate is maintained for 1 minute 110 times/min), and the historical exercise intensity consistent with the current exercise intensity is determined as the target historical exercise intensity (e.g., heart rate is maintained for 110 times/min). The longest duration (e.g., 1 minute) for which the target historical motion intensity is obtained is the target longest duration. If the duration of the current motion intensity (e.g., 1 minute 10 seconds) is greater than the target maximum duration, there is a high intensity motion for the corresponding user.
According to the application, two modes are introduced to judge the high-intensity movement of the user, so that the comprehensiveness of the judgment of the movement intensity is improved.
In one embodiment, the system for health analysis and advice based on intelligent wearing detection motion data, the system for health analysis and sending corresponding health advice to a user, comprises:
generating a template based on a preset analysis result, generating an analysis result according to a second electrocardiosignal and motion data of a user corresponding to high-intensity motion, and simultaneously, acquiring a health suggestion corresponding to the analysis result;
determining an evaluation report extraction item in an analysis result based on a preset evaluation report extraction item comparison table;
filling the evaluation report extraction items into corresponding positions in a preset evaluation report template to obtain an evaluation report;
based on preset pushing rules, pushing the assessment report and the corresponding health advice to the corresponding user.
The working principle and the beneficial effects of the technical scheme are as follows:
generating a template based on a preset analysis result, and generating an analysis result according to a second electrocardiosignal and motion data of a user corresponding to high-intensity motion; the preset analysis result generation template is, for example: the motion intensity is …, the motion intensity is higher than that of the historical motion record, and the motion data is …. Determining an evaluation report extraction item in an analysis result based on a preset evaluation report extraction item comparison table; the preset evaluation report extraction item comparison table stores data items for generating an evaluation report, for example: data of heart rate variation and number of steps in a day, etc. And filling the evaluation report extraction item into a corresponding position in a preset evaluation report template to obtain an evaluation report. Pushing the evaluation report and the corresponding health advice to the corresponding user based on a preset pushing rule; the push rule is, for example: the intelligent wearable device is in butt joint with the intelligent terminal, and an assessment report and health advice are sent to the intelligent terminal every day 18:00.
The embodiment of the application provides a method for health analysis and suggestion based on intelligent wearing detection motion data, which is shown in fig. 2 and comprises the following steps:
step 1: acquiring a first electrocardiosignal measured in a latest measuring period of intelligent wearing equipment worn by a preset user in real time;
step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal;
step 3: acquiring motion data sensed by a preset sensor in a measurement period;
step 4: and acquiring a historical motion record of the user, and carrying out health analysis on the user and sending corresponding health advice according to the second electrocardiosignal, the motion data and the historical motion record.
In one embodiment, the step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal, which comprises the following steps:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
In one embodiment, the step 4: acquiring a historical motion record of the user, carrying out health analysis on the user and sending corresponding health suggestions according to the second electrocardiosignal, the motion data and the historical motion record, wherein the method comprises the following steps:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. System for health analysis and advice based on intelligent wearing detection motion data, characterized by comprising:
the first acquisition module is used for acquiring a first electrocardiosignal measured by an intelligent wearable device worn by a preset user in a latest measurement period in real time;
the filtering module is used for carrying out filtering processing on the first electrocardiosignal to obtain a processed second electrocardiosignal;
the second acquisition module is used for acquiring motion data sensed by a preset sensor in a measurement period;
and the analysis suggestion module is used for acquiring the historical motion record of the user, carrying out health analysis on the user according to the second electrocardiosignal, the motion data and the historical motion record, and sending corresponding health suggestions.
2. The system for health analysis and advice based on smart wearable detected motion data of claim 1, wherein the filtering module performs filtering processing on the first cardiac signal to obtain a processed second cardiac signal, comprising:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
3. The system for health analysis and advice based on intelligent wearable detected motion data of claim 1, wherein the analysis advice module obtains a historical motion profile of the user, performs health analysis on the user based on the second electrocardiographic signal, the motion data, and the historical motion profile, and transmits corresponding health advice, comprising:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
4. The system for health analysis and advice based on smart wearable detected motion data of claim 3, wherein the calculating the current data of the user for each preset unit time in the measurement period based on the second electrocardiographic signal and the motion data comprises:
based on a preset first calculation rule, determining the dynamic heart rate of the user according to the second electrocardiosignal;
determining the unit wrist movement times of the user according to the motion data based on a preset second calculation rule;
determining the unit movement steps of the user according to the movement data based on a preset third calculation rule;
and integrating the dynamic heart rate, the unit wrist movement times and the unit movement steps to obtain current data.
5. The system for health analysis and advice based on smart wearable detected motion data according to claim 3, wherein said analyzing the health of the user and sending corresponding health advice based on the current intensity of motion comprises:
acquiring a historical exercise intensity record;
judging whether the user has high-intensity motion or not based on the historical motion intensity record;
if so, carrying out health analysis on the user and sending corresponding health advice.
6. The system for health analysis and advice based on intelligent wearable detected motion data of claim 5, wherein the determining whether the user has high intensity motion based on the historical motion intensity record comprises:
determining a highest historical motion intensity based on the historical motion intensity record;
if the current motion intensity is greater than the highest historical motion intensity, corresponding users have high-intensity motions;
and/or the number of the groups of groups,
determining a longest duration corresponding to the same historical motion intensity based on the historical motion intensity record;
determining target historical motion intensity consistent with the current motion intensity from the historical motion intensities;
acquiring the longest duration of the target movement intensity and taking the longest duration as the target longest duration;
if the duration of the acquired current motion intensity is longer than the target maximum duration, the corresponding user has high-intensity motion.
7. The system for performing health analysis and advice based on smart wearable detected motion data according to claim 5, wherein the performing health analysis on the user and transmitting corresponding health advice comprises:
generating a template based on a preset analysis result, generating an analysis result according to a second electrocardiosignal and motion data of a user corresponding to high-intensity motion, and simultaneously, acquiring a health suggestion corresponding to the analysis result;
determining an evaluation report extraction item in an analysis result based on a preset evaluation report extraction item comparison table;
filling the evaluation report extraction items into corresponding positions in a preset evaluation report template to obtain an evaluation report;
based on preset pushing rules, pushing the assessment report and the corresponding health advice to the corresponding user.
8. The method for health analysis and suggestion based on intelligent wearing detection motion data is characterized by comprising the following steps:
step 1: acquiring a first electrocardiosignal measured in a latest measuring period of intelligent wearing equipment worn by a preset user in real time;
step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal;
step 3: acquiring motion data sensed by a preset sensor in a measurement period;
step 4: and acquiring a historical motion record of the user, and carrying out health analysis on the user and sending corresponding health advice according to the second electrocardiosignal, the motion data and the historical motion record.
9. The method for health analysis and advice based on smart wear detection athletic data of claim 8, wherein step 2: filtering the first electrocardiosignal to obtain a processed second electrocardiosignal, which comprises the following steps:
based on a preset first feature extraction template, carrying out feature extraction on the signal characteristics of the first electrocardiosignal to obtain a first feature value set;
obtaining a preset filter matching library, wherein the filter matching library comprises: a plurality of second filters corresponding to the first filters and the second characteristic value sets one by one;
matching the first characteristic value set with each second characteristic value set in the filter matching library to obtain a matching value;
if the matching value is greater than or equal to the matching value threshold value corresponding to the first filter, the corresponding first filter is used as a second filter;
and filtering the first electrocardiosignal through a second filter to obtain a processed second electrocardiosignal.
10. The method for health analysis and advice based on smart wear detection athletic data of claim 8, wherein the step 4: acquiring a historical motion record of the user, carrying out health analysis on the user and sending corresponding health suggestions according to the second electrocardiosignal, the motion data and the historical motion record, wherein the method comprises the following steps:
based on the second electrocardiosignal and the motion data, calculating current data of the user in each preset unit time in the measurement period, wherein the current data comprises: dynamic heart rate, number of unit wrist movements and number of unit exercise steps;
analyzing the historical motion record to obtain average measurement data of the user in each unit time in history;
calculating a data difference value of the current data and the average measurement data corresponding to the same data type, and simultaneously, acquiring a difference value direction of the data difference value and a type weight of the corresponding data type;
determining the current motion intensity based on the data difference value, the difference value direction and the type weight of the corresponding data type;
and according to the current exercise intensity, carrying out health analysis on the user and sending corresponding health advice.
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