CN114098686A - Wearable physiological sensing system for team activities - Google Patents
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Abstract
The present invention provides a wearable physiological sensing system for team activities, comprising: the wearable devices are respectively worn on a plurality of users and used for measuring heart rate data and physiological data of each user and calculating a heart rate variation characteristic value by Fourier transformation according to the physiological data; the main control platform is wirelessly connected with the plurality of wearing devices and is used for receiving each heart rate data, each physiological data and the heart rate variation characteristic value of each user; the main control platform calculates the current physical power consumption of each user during exercise and the physical power consumption of each user after exercise according to the heart rate variation characteristic value; the invention comprises a plurality of wearing devices which can respectively measure a plurality of users, and calculates the current physical power consumption and the physical power consumption after sports so as to monitor the physical power state of each user in a team.
Description
Technical Field
A physiological sensing system, in particular to a wearable physiological sensing system which comprises a plurality of wearable devices and can monitor team activities of physiological and physical states of all users in a team.
Background
Currently, wearable devices are still focused on personal physiological sensing, such as smart watches, smart wristbands, smart glasses, heart rate chest belts, smart clothes and the like, and can record various personal actions or physiological signals, such as heartbeat, blood oxygen, speed, time, distance and the like, and transmit the signals to an action device (such as a mobile phone) through bluetooth, so that a user can know the physiological state of the user during movement, and the wearable devices are suitable for monitoring general personal physiology.
However, for team activities or competition type sports, the leaders or coaches of the team cannot integrate and utilize the instant information of the team members to achieve the purposes of physiological supervision, safety care and the like of the team members, and especially under the competitive sports state of a large-scale space activity or sports field, the leaders or coaches can immediately grasp the physiological, physical and position states of the team members, so that the on-site performance of the team and the protection of the safety of the team members can be directly influenced. However, the current conception and design of all wearable physiological monitoring devices also lack the consideration of remote communication, multipoint data integration and group coordination communication, for example, when considering fierce sports competitions such as basketball and football, team members cannot use the mobile phone to collect and process data and coordinate communication at any time when playing in a sports field, and the wearable devices themselves often lack the communication capability of a long distance, so that the wearable devices cannot transmit data to the mobile phone APP by using a common short-range communication technology (such as bluetooth) and then collect and process the data. In addition, for many other outdoor activities, such as mountain climbing and water area activities, the activity area is far away, and the base station cannot cover the activity area, so that even if a team member carries a mobile phone, the team member cannot immediately transmit the physical ability status of the team member to other members through the device to know if the team member encounters an emergency accident, such as injury or loss.
Disclosure of Invention
In order to collect the physiological and physical ability data of a plurality of users before, during and after exercise, the invention provides a wearable physiological sensing system for team activities, which measures various physiological data of the users by means of a wearable device worn on the plurality of users to achieve the effect of monitoring the physical ability of the plurality of users.
To achieve the above objects, the present invention provides a wearable physiological sensing system for team activities, comprising:
the wearable devices are respectively worn on a plurality of users and used for measuring heart rate data and physiological data of each user and further calculating a heart rate variation characteristic value by Fourier transformation according to the physiological data;
the main control platform is wirelessly connected with the plurality of wearing devices and is used for receiving each heart rate data, each physiological data and the heart rate variation characteristic value of each user;
the cloud server is wirelessly connected with the main control platform and used for receiving and storing the heart rate data, the physiological data and the heart rate variation characteristic value of each user; the main control platform calculates the current physical power consumption of each user during exercise and the physical power consumption of each user after exercise according to the heart rate variation characteristic value.
The invention aims at group activities or competition type sports, a team leader or a coach can integrate and utilize wearable equipment of team members to collect instant physiological and physical performance information so as to achieve the purposes of physiological supervision, safe care and the like of the team members, and particularly, under the competitive sports state in an activity space or a sports field in a large range, the leader/coach can immediately grasp the physiological, physical performance and position states of the team members, so that the on-site performance of the team and the safety protection of the team members can be directly influenced. Meanwhile, the whole system operation is completed cooperatively by the wearing devices, the main control platform and the cloud server, so that the whole system not only has the function of a personal physical ability monitoring system, but also can be applied to group activities such as team activity/competition training and the like.
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FIG. 1: the system block diagram of the present invention.
FIG. 2: the appearance schematic diagram of the main control platform plane interface is provided.
Detailed Description
The present invention discloses a wearable physiological sensing system for team activities, as shown in fig. 1, comprising: a plurality of wearable devices 10A, 10B, 10C, a main control platform 20 and a cloud server 30.
The plurality of wearing devices 10A, 10B, 10C are worn on a plurality of users, respectively. Each of the wearable devices 10A, 10B, 10C is used for measuring a heart rate data and a physiological data of each user, and further calculating a heart rate variation characteristic value by fourier transform according to the physiological data. Each of the wearable devices 10A, 10B, 10C has a wireless transmission function, wherein the physiological data can be obtained by Photoplethysmography (PPG), and the physiological data detected by PPG can include heartbeat and blood flow inside blood vessels; the heart rate data may be obtained by detecting user activity with a motion sensor (MEMS) disposed within each of the wearable devices 10A, 10B, 10C. Each of the wearable devices 10A, 10B, 10C further collects a position data of each user, and the position data records a coordinate position of each user.
The main control platform 20 is wirelessly connected to the plurality of wearable devices 10A, 10B, and 10C, and is configured to receive the heart rate data, the physiological data, the heart rate variation characteristic value, and the position data of each user. The main control platform 20 can be a mobile device, a tablet or a pen-phone, and can be held by a leader or a coach of a team, so that the leader or the coach of the team can master the physiological status of each user for a long time.
The cloud server 30 is wirelessly connected to the main control platform 20 for receiving and storing the heart rate data, the physiological data, the heart rate variation characteristic value and the position data of each user for a long time.
Specifically, the present invention may employ low power wide area network (LoRa) as an example of the wireless communication application. The wearable devices 10, the host platform 20, and the cloud server 30 can all be connected using low power wan communication technology.
By receiving the heart rate variability characteristic value of each user, the main control platform 20 of the present invention can further calculate the fatigue level of each user during exercise.
The fourier transform is to calculate a continuous peak-to-peak interval, and divide the peak-to-peak interval into different frequency bands according to different frequency characteristics, so as to obtain a power spectrum diagram with frequency as horizontal coordinate and power spectrum density as vertical coordinate. The total area under the power spectrum curve is Total Power (TP); the area in the high frequency region is high frequency power (HF), and the area in the low frequency region is low frequency power (LF). After the above values are calculated, further definition can be made: the ratio of high frequency power to total power (HF/TP) is a quantitative indicator of parasympathetic activity, the ratio of low frequency power to total power (LF/TP) is a quantitative indicator of sympathetic activity, and the ratio of low frequency power to high frequency power (LF/HF) is an indicator of sympathetic-parasympathetic activity balance.
Based on the total power TP, the high-frequency power HP and the low-frequency power LF, the heart rate variability characteristic value (including the total power TP, the high-frequency power HP and the low-frequency power LF) of a tested person at ordinary times is used as a personal physical strength reference index, the highest value of the history is defined to be 100%, the lowest value is defined to be 10% or other set values, and the set value is not limited to 10%, so that the physical strength state of the user at the time can be evaluated according to the tested value of the user at the time in the non-exercise period. When the user is doing exercise, in addition to fatigue, the physical performance of the user may be affected by other factors (e.g., adrenalin and mood factors), which may cause the variation of the Heart Rate Variability (HRV) characteristic value to be too different from the heart rate variability characteristic value before doing exercise, and thus, the user is not suitable for determining the heart rate variability characteristic value. The heart rate variability characteristic value difference between the before-exercise state and the after-exercise state is small, and no significant factor influence other than fatigue exists after the exercise state, so that the fatigue degree of the user can be judged according to the heart rate variability characteristic value difference between the before-exercise state and the after-exercise state.
The fatigue degree after exercise is calculated by the difference of the heart rate variability characteristic values before and after exercise, and the exercise intensity is analyzed by the instantaneous heart rate at present, so that the exercise fatigue degree is further calculated. In a preferred embodiment of the invention, the american society of sports medicine ACSM rating recommendation is referenced in terms of maximum heart rate rating per minute for each age, as shown in table 1 below:
TABLE 1 comparison table of heart rate data and exercise intensity
Factors affecting the degree of fatigue include exercise intensity and time, for example, in the same time period, when the exercise intensity is maintained for high intensity exercise, the exercise intensity is relatively more fatigue than the exercise intensity for light intensity, so that the degree of exercise fatigue can be analyzed according to the current exercise intensity and the variation degree of the heart rate variability characteristic value, and the effect of exercise fatigue of different athletes can be further analyzed. Since exercise is not currently suitable for determining fatigue degree by using the heart rate variability characteristic value difference, the exercise fatigue degree analyzed by the heart rate variability characteristic value difference can be given by the following formula:
when exercising, the consumption of physical strength is alpha x th+β×tm+γ×tl+δ
Wherein α × tnTo evaluate the degree of fatigue caused by high intensity exercise, α is the fatigue coefficient of high intensity exercise, tnTotal time for performing high intensity exercises; beta is the fatigue coefficient of moderate-intensity exercise, tmTotal time to perform the medium intensity exercise; gamma is the fatigue coefficient of low intensity motion, tlTotal time to perform low intensity exercises; by analogy, β × tmTo assess the degree of fatigue caused by moderate exercise, γ × tlThen to assess the degree of fatigue caused by low intensity exercise, δ is the individual's physical difference; the coefficients α, β, γ, etc. vary depending on individual factors such as age, height, weight, etc., and are obtained by referring to the basic physiological data of the subject.
Since the fatigue coefficients α, β, γ, δ of each user are different, in order to obtain the fatigue coefficients, it is necessary to further calculate the physical power consumption after exercise, and the physical power consumption after exercise is estimated as follows:
wherein TPafterAfter exerciseTotal Power (TP), TPbeforeFor the total power before the movement,
the difference value of the low-frequency power ratio and the high-frequency power ratio before the movement is subtracted from the low-frequency power ratio and the high-frequency power ratio after the movement,
is at the same time
And will be the maximum difference in the history of
The tired state of the user is defined, so that the physical consumption after exercise is obtained.
The total time of a plurality of exercises with different strengths and the physical power consumption after the exercises are obtained through a plurality of times of training, and then the fatigue coefficients alpha, beta, gamma and delta of the user are obtained, the invention adopts multiple regression analysis, and the regression calculation model is as follows:
y＝b0+b1×x1+b2×x2+b3×x3
wherein the total time t of each intensity movementn、tm、tlIs an independent variable x in a multiple regression analysis1、x2、x3The body force consumption after exercise is the strain number y in the multiple regression analysis, and the individual fatigue coefficients α, β, γ, δ are the parameters b to be obtained in the multiple regression analysis0、b1、b2、b3Solving by a least square method to obtain personal fatigue coefficients alpha, beta, gamma and delta; wherein b is0＝δ、b1＝α、b2＝β、b3＝γ。
Determining the user's parameter b0、b1、b2、b3Then, in the later exercise process, the physical strength can be brought into exercise when the physical strength is consumed according to various exercise time with different degrees at the momentThe formula of the amount can instantly evaluate the physical consumption of the user in the process of sports (competition) and match the Total Power (TP) measured before the competition before the sportbefore) The physical consumption is deducted to derive the current physical activity value of the user, and the physical activity value is further displayed on the motion mode of the main control platform 20 for the coach or the leader to refer to. Wherein the physical activity value represents the physical power remaining while the user is exercising.
The present invention further includes a plurality of user devices 40A, 40B, and 40C, wherein the plurality of user devices 40A, 40B, and 40C are respectively wirelessly connected to the cloud server 30 and the corresponding plurality of wearable devices 10A, 10B, and 10C, that is, the user device 40A is wirelessly connected to the wearable device 10A, and the user device 40A and the wearable device 10A are generally held by the same user, and so on; the user device 40B is wirelessly connected to the wearable device 10B, and the user device 40C is wirelessly connected to the wearable device 10C. The plurality of user devices 40A, 40B, and 40C may receive the heart rate data, the physiological data, and the heart rate variability feature value of each corresponding user, as well as the physical power consumption and physical power value after exercise, so that the user can self-evaluate his/her exercise performance.
Referring to fig. 2, by calculating the physical ability and fatigue status of the user, the main control platform 20 has three recording modes, which are a general mode, a training mode and a sport mode. The three modes can be displayed through an operation interface 31 on the main control platform 20, and the leader or coach of the team can select the corresponding mode according to the activity intensity of the user. In other words, in a normal state, the host platform 20 executes the normal mode to record the normal data of the user; when the user is performing the training, the main control platform 20 executes the training mode; the master control platform 20 executes the sport mode when the user actually performs the sport (or competition). The data and functions recorded in the general mode, the training mode and the exercise mode are described below.
The general mode will be described first, and a single wearable device 10A (i.e., a single user) will be taken as an example. In a normal state, the non-exercise state belongs to the general mode, and the main control platform 20 periodically sends a command to the wearable device 10A to calculate the heart rate variability characteristic value of the user. The wearable device 10A calculates the heart rate variability characteristic value of the user and then transmits the heart rate variability characteristic value back to the main control platform 20 for displaying and storing. The main objective is to monitor the user's personal physical performance changes over a long period of time.
This training mode will be described next, and a single wearable device 10A will be taken as an example as well. The user will perform more than three mixed intensity exercises, each training process will be timed by the main control platform 20, during the training process, the main control platform 20 calculates the intensity of the received heartbeat in each time according to the table 1 and the heartbeat data, and calculates the time occupied by each intensity exercise in each training. After the third training, the fatigue coefficient of the individual high, medium and light intensity sports can be calculated, the historical data can be calculated after each training, the updating of the algorithm is continuously carried out, and the individual physical ability state of the user can be conveniently evaluated in the training mode.
This movement pattern will be described next, and the single wearing device 10A will be taken as an example as well. It is important to note that the master platform 20 will not initiate the exercise mode until the user has completed the exercise mode. After entering the exercise mode, the main control platform 20 is divided into two sections, namely, a section before the upper stage and a section after the lower stage, and the main control platform 20 first obtains a total power before exercise (i.e., TP) from the wearable device 10Abefore) As the basis for later recovery of physical energy. Total power before motion is taken (i.e., TP)before) The user can then go to the field for competition. When the user is performing a match, the main control platform 20 calculates the next physical power consumption of the user by using the fatigue coefficient calculated by the training mode and matching the heartbeat of the user, and then matches the Total Power (TP) before the user's exercise measured before the match, because the heart rate variability eigenvalue measured during the exercise is not suitable for determining the physical performance statusbefore) Deducing the current physical power consumption, the physical power value can be deduced, and the physical power value can be deducedThe remaining physical strength of the user during the exercise is digitalized, so that a coach in a team can master the physical strength change of each user during the exercise. After the user finishes the game, the user will start measuring the total power after the sport (TP)after) And substituting into a formula for calculating physical consumption after exercise so as to correct the fatigue coefficients alpha, beta, gamma and delta in the training mode in the future.
Claims (10)
1. A wearable physiological sensing system for team activities, comprising:
the wearable devices are respectively worn on a plurality of users and used for measuring heart rate data and physiological data of each user and further calculating a heart rate variation characteristic value by Fourier transformation according to the physiological data;
the main control platform is wirelessly connected with the plurality of wearing devices and is used for receiving each heart rate data, each physiological data and the heart rate variation characteristic value of each user;
the cloud server is wirelessly connected with the main control platform and used for receiving and storing the heart rate data, the physiological data and the heart rate variation characteristic value of each user; the main control platform calculates the current physical power consumption of each user during exercise and the physical power consumption of each user after exercise according to the heart rate variation characteristic value.
2. The wearable physiological sensing system for team activities of claim 1, wherein the athletic current physical consumption is calculated by:
when exercising, the consumption of physical strength is alpha x th+β×tm+γ×tl+δ；
Wherein α × tnTo evaluate the degree of fatigue caused by high intensity exercise, α is the fatigue coefficient of high intensity exercise, tnTotal time for performing high intensity exercises; beta is the fatigue coefficient of moderate-intensity exercise, tmTotal time to perform the medium intensity exercise; gamma is the fatigue coefficient of low intensity motion, tlTotal time to perform low intensity exercises; delta is the individual's physical difference.
3. The wearable physiological sensing system for team activities of claim 2, wherein the post-exercise physical consumption is calculated by:
wherein TPafterIs the total power after exercise (TP), TPbeforeFor the total power before the movement,
the difference value of the low-frequency power ratio and the high-frequency power ratio before the movement is subtracted from the low-frequency power ratio and the high-frequency power ratio after the movement,
is at the same time
The maximum difference in the history of (a).
4. The wearable physiological sensing system for team activities of claim 3, wherein the fatigue coefficients α, β, γ, δ of the user are calculated by the following equations:
y＝b0+b1×x1+b2×x2+b3×x3；
wherein the total time t of each intensity movementn、tm、tlIs an independent variable x1、x2、x3The body force consumption after movement is a strain number y, and fatigue coefficients alpha, beta, gamma and delta are solved by a least square method; wherein b is0＝δ、b1＝α、b2＝β、b3＝γ。
5. The wearable physiological sensing system for team activities of claim 4, further comprising a plurality of user devices wirelessly connected to the cloud server for receiving the heart rate data, physiological data and the heart rate variability characteristic of each user.
6. The wearable physiological sensing system for team activities of any one of claims 1-5, wherein each wearable device further collects a location data of each user and reports the location data to the host platform.
7. The wearable physiological sensing system for team activities of claim 6, wherein the main control platform has three recording modes, which are a general mode, a training mode and a sport mode, respectively, and an operation interface on the main control platform can display the three recording modes.
8. The wearable physiological sensing system for team activities of claim 7, wherein in the general mode, the host platform periodically sends a command to the wearable device to calculate the heart rate variability characteristic of the user; the wearable device calculates the heart rate variation characteristic value of the user and then transmits the heart rate variation characteristic value back to the main control platform for displaying and storing.
9. The wearable physiological sensing system for team activities of claim 8, wherein in the training mode, the main control platform is used to time each mixed intensity exercise performed by the user, determine the intensity of the heartbeat when the user performs the mixed intensity exercise, calculate the time occupied by each intensity exercise during each training, and calculate the fatigue coefficient of the user in the high, medium and light intensity exercises.
10. The wearable physiological sensing system for team activities of claim 9, wherein in the exercise mode, the master platform obtains a total pre-exercise power of the user from the wearable device prior to the user's exercise; when the user moves, the main control platform calculates the current physical consumption of the user during the movement; and finally, subtracting the current physical power consumption of the user from the total power before the user moves to obtain a current physical power value of the user moving.
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