A wearable multi-channel physiological parameter monitoring system

Abstract

This invention provides a wearable multi-channel physiological indicator monitoring system, comprising several sets of acquisition devices, a wireless concentrator, a processor, and a user terminal. The wireless concentrator receives physiological indicator information from the acquisition devices and sends several pieces of physiological indicator information to the processor. The processor processes the received physiological indicator information and sends the processing results to the user terminal. The acquisition devices include a headband, an acquisition mechanism, and a controller. This invention allows for convenient wearing and fixing by the user, and is also easy to disassemble and clean. Furthermore, it enables comprehensive analysis of physiological indicator information from multiple individuals to meet the monitoring needs of group training effects.

Description

Technical Field

[0001] This invention relates to the field of human body monitoring technology, and in particular to a wearable multi-channel physiological indicator monitoring system. Background Technology

[0002] With the application of smart wearable technology, people can collect physiological indicators of the human body through wearable devices, enabling real-time monitoring of the body's state and allowing people to promptly understand their vital signs. Existing wearable multi-channel physiological indicator monitoring systems are typically monitoring wristbands. When collecting brain signals, a head-mounted device is needed to collect physiological indicators. Because headbands and wristbands are used in different locations, headband devices are easily contaminated, and existing headband-mounted collection devices are inconvenient to disassemble and clean, have unreasonable settings, and are not convenient to use. Furthermore, in some group training activities, it is necessary to promptly understand the effectiveness of each training session; however, existing monitoring equipment is usually used for individual monitoring, and is insufficient for comprehensive analysis of multiple individuals. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a wearable multi-channel physiological indicator monitoring system that is convenient for users to wear and fix, and is also easy to disassemble and clean. At the same time, it can comprehensively analyze the physiological indicator information of multiple individuals to meet the monitoring needs of group training effects.

[0004] To solve the above problems, the present invention is achieved through the following technical solution: a wearable multi-channel physiological indicator monitoring system, comprising several sets of acquisition devices, a wireless concentrator, a processor, and a user terminal. The wireless concentrator is used to receive physiological indicator information sent by several sets of acquisition devices and send several physiological indicator information to the processor. The processor is used to process the received physiological indicator information and send the processing result to the user terminal. The data acquisition device includes a headband, a data acquisition mechanism, and a controller. The two ends of the headband are detachably connected to the data acquisition mechanism via a set of connectors. The headband and the data acquisition mechanism are connected to form a ring structure and are worn on the user's head. The controller is located on one side of the headband and is electrically connected to the data acquisition mechanism. The controller contains a wireless transceiver, which is used to send the physiological indicator information collected by the data acquisition mechanism to an external receiving end. The acquisition mechanism includes an acquisition plate and a heart rate sensor, an EEG sensor, a blood oxygen probe, and a temperature sensor installed within the acquisition plate. The heart rate sensor is used to acquire the user's heart rate value, the EEG sensor is used to acquire the user's brainwave signal, the blood oxygen probe is used to acquire the user's blood oxygen concentration, and the temperature sensor is used to acquire the user's body temperature value. The physiological indicators include heart rate, electroencephalogram (EEG) signal, blood oxygen concentration, and body temperature. The processor includes a training module, a processing module, and a storage module. The training module is used to send training instructions to several groups of acquisition devices through a wireless concentrator. The processing module is used to process physiological indicator information. The storage module stores the average heart rate, average blood oxygen concentration, and average body temperature of healthy individuals. The processing module includes an independent processing unit and a comprehensive processing unit. The independent processing unit is used to process each physiological indicator information independently, and the comprehensive processing unit is used to process several physiological indicator information in combination. The independent processing unit is configured with a first algorithm and a first processing strategy; The first algorithm calculates the user's health risk value based on heart rate, blood oxygen concentration, and body temperature. The first algorithm is configured as follows: Where H is the health risk value, HR is the heart rate value, HRa is the average heart rate, PaO2 is the blood oxygen concentration, PaO2a is the average blood oxygen, T is the body temperature value, Ta is the average body temperature, K1 is the first weight value, K2 is the second weight value, K3 is the third weight value, A1 is the first reference value, and C1 is the first balance value. The first processing strategy includes: comparing a health risk value with a first threshold; outputting a health risk signal when the health risk value is greater than the first threshold; and outputting a normal health signal when the health risk value is less than the first threshold. The integrated processing unit includes a transformation subunit, a truncation subunit, an individual evaluation subunit, and an overall evaluation subunit; The transformation subunit plots the EEG signals into an EEG, where the vertical axis of the EEG is set to potential amplitude and the horizontal axis of the EEG is set to time period. The interception subunit is used to acquire several heart rate values, potential amplitude, blood oxygen concentration and body temperature values ​​of several users from the start to the end of the training instruction. The individual assessment subunit is equipped with a second algorithm, a third algorithm, a fourth algorithm, a fifth algorithm, and a sixth algorithm. The second algorithm calculates the individual heart rate change value based on several heart rate values ​​of the user from the start to the end of the training instruction. The third algorithm calculates the individual brain electrical signal change value based on several potential amplitudes of the user from the start to the end of the training instruction. The fourth algorithm calculates the individual blood oxygen change value based on several blood oxygen concentrations of the user from the start to the end of the training instruction. The fifth algorithm calculates the individual body temperature change value based on several body temperature values ​​of the user from the start to the end of the training instruction. The sixth algorithm calculates an individual comprehensive change value based on the user's individual heart rate change value, individual electrical signal change value, individual blood oxygen change value, and individual body temperature change value. The sixth algorithm is configured as follows: Where Z is the individual comprehensive change value, HRi is the individual heart rate change value, PaO2i is the individual blood oxygen change value, fi is the individual electrical signal change value, Ti is the individual body temperature change value, A2 is the second reference value, A3 is the third reference value, A4 is the fourth reference value, and A5 is the fifth reference value. The overall evaluation subunit is equipped with a seventh algorithm, an eighth algorithm, a ninth algorithm, a tenth algorithm, and an eleventh algorithm. The seventh algorithm calculates the overall heart rate change value based on the individual heart rate change values ​​of several users. The eighth algorithm calculates the overall electrical signal change value based on the individual electrical signal change values ​​of several users. The ninth algorithm calculates the overall blood oxygen change value based on the individual blood oxygen change values ​​of several users. The tenth algorithm calculates the overall body temperature change value based on the individual body temperature change values ​​of several users. The eleventh algorithm calculates the overall comprehensive change value based on the overall heart rate change value, overall electrical signal change value, overall blood oxygen change value, and overall body temperature change value. The eleventh algorithm is configured as follows: Where Y is the overall comprehensive change value, HRj is the overall heart rate change value, PaO2j is the overall blood oxygen change value, fj is the overall electrical signal change value, Tj is the overall body temperature change value, A6 is the sixth reference value, A7 is the seventh reference value, A8 is the eighth reference value, and A9 is the ninth reference value.

[0005] Furthermore, the controller is also equipped with a display screen, a speaker, and a fingerprint reader. The controller receives external training instructions via a wireless transceiver and transmits them to the user via the speaker. The fingerprint reader is used for user login identification.

[0006] Furthermore, the controller is provided with a buckle and a breathable mesh pad on the side connected to the headband, and buckle strips matching the buckle are provided on both sides of the headband. The controller is detachably connected to the buckle strips of the headband through the buckle.

[0007] Furthermore, a first connection hole is provided at each end of the acquisition plate, and a second connection hole is provided at each end of the headband. The connector is connected to the adjacent first connection hole and second connection hole respectively.

[0008] Furthermore, the connector includes a snap fastener and a snap-fit ​​connector. The snap fastener has two sets of symmetrically arranged sleeves, and the snap-fit ​​connector has two sets of symmetrically arranged protrusions. The sleeves match the protrusions, and the snap fastener and the snap-fit ​​connector are detachably connected through the sleeves and protrusions.

[0009] Furthermore, a washer is provided on the protrusion, and a slot is provided inside the sleeve, with the washer matching the slot.

[0010] Furthermore, the headband includes a first connecting strap and a second connecting strap, wherein the first connecting strap and the second connecting strap are adhered together.

[0011] Furthermore, the second algorithm is configured as follows: The third algorithm is configured as follows: The fourth algorithm is configured as follows: The fifth algorithm is configured as follows: Where B1 is the first conversion value, B2 is the second conversion value, B3 is the third conversion value, B4 is the fourth conversion value, and n is the number of times data is acquired from the start to the end of each training instruction.

[0012] Furthermore, the seventh algorithm is configured as follows: The eighth algorithm is configured as follows: The ninth algorithm is configured as follows: The tenth algorithm is configured as follows: Where m is the number of users.

[0013] The beneficial effects of the present invention are as follows: In the collection device of the present invention, the headband is detachably connected to the collection mechanism through a connector. The headband includes a first connecting strap and a second connecting strap. The first connecting strap and the second connecting strap are respectively connected to the collection mechanism through a connector. The controller is detachably connected through a buckle and a buckle bar. This design makes it convenient for users to assemble and wear the whole device. It also makes it convenient to disassemble and clean the headband, thus improving the convenience and rationality of use. This invention uses a wireless concentrator to centrally transmit physiological indicator information collected by several sets of acquisition devices to a processor. The processor can independently and comprehensively process several physiological indicator information to obtain the health status of each individual. It can also comprehensively analyze the physiological state of the group during training to improve the rationality of the comprehensive evaluation of the group training effect. Furthermore, the processor can send the processing results to the user terminal, so that the manager or user can know the processing results through the user terminal. Attached Figure Description

[0014] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a connection diagram of the monitoring system; Figure 2 This is a schematic diagram of the data acquisition device; Figure 3 This is the first side view of the controller; Figure 4 This is the second side view of the controller; Figure 5 This is a partial structural diagram of the first connecting strip; Figure 6 This is a schematic diagram showing the connection between the first connecting strip and the acquisition board; Figure 7 This is a cross-sectional view showing the connection of the first connecting strip, the acquisition plate, and the connector; Figure 8 for Figure 7 Enlarged view of A in the middle; Figure 9 This is a block diagram of the processor.

[0015] In the diagram: 1. Data acquisition device; 11. Headband; 111. First connecting strap; 112. Second connecting strap; 1121. Second connecting hole; 12. Connector; 13. Buckle; 121. Buckle; 122. Snap-fit; 123. Sleeve; 1231. Slot; 124. Protrusion; 1241. Washer; 1300. Data acquisition mechanism; 131. Data acquisition plate; 1311. First connecting hole; 132. Heart rate sensor; 133. Electroencephalogram (EEG) sensor; 134. Blood oxygen probe; 35. Temperature sensor; 14. Controller; 141. Fingerprint reader; 142. Display screen; 143. Buckle; 144. Breathable mesh mat; 2. Wireless concentrator; 3. Processor; 31. Training module; 32. Processing module; 321. Independent processing unit; 322. Integrated processing unit; 3221. Transformation subunit; 3222. Interception subunit; 3223. Individual evaluation subunit; 3224. Overall evaluation subunit; 33. Storage module; 4. User terminal. Detailed Implementation

[0016] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0017] Please see Figure 1 and 2 A wearable multi-channel physiological indicator monitoring system includes several sets of acquisition devices 1, a wireless concentrator 2, a processor 3, and a user terminal 4. The wireless concentrator 2 is used to receive physiological indicator information sent by several sets of acquisition devices 1 and send several physiological indicator information to the processor 3. The processor 3 is used to process the received physiological indicator information and send the processing result to the user terminal 4.

[0018] The data acquisition mechanism 1300 includes a headband 11, the data acquisition mechanism 1300, and a controller 14. The two ends of the headband 11 are detachably connected to the data acquisition mechanism 1300 via a set of connectors 12. The headband 11 and the data acquisition mechanism 1300 are connected to form a ring structure and are worn on the user's head. The controller 14 is located on one side of the headband 11 and is electrically connected to the data acquisition mechanism 1300. The controller 14 contains a wireless transceiver, which is used to send the physiological indicator information collected by the data acquisition mechanism 1300 to an external receiving end. In use, the user fixes the data acquisition mechanism 1300 to the headband 11 with the connecting strap and points the data acquisition mechanism 1300 toward the user's forehead. The controller 14 is fixed to one side of the headband 11 and located near the user's ear.

[0019] The headband 11 includes a first connecting strap 111 and a second connecting strap 112. The first connecting strap 111 and the second connecting strap 112 are bonded together. The tightness of the headband can be adjusted when wearing the headband by bonding the first connecting strap 111 and the second connecting strap 112.

[0020] The data acquisition device 1300 includes a data acquisition board 131 and a heart rate sensor 132, an electroencephalogram (EEG) sensor 133, a blood oxygen probe 134, and a temperature sensor 135 disposed within the data acquisition board 131. The heart rate sensor 132 is used to acquire the user's heart rate value, the EEG sensor 133 is used to acquire the user's brainwave signals, the blood oxygen probe 134 is used to acquire the user's blood oxygen concentration, and the temperature sensor 135 is used to acquire the user's body temperature value. The heart rate sensor 132, EEG sensor 133, blood oxygen probe 134, and temperature sensor 135 on the data acquisition board 131 are in close contact with the forehead, which facilitates the acquisition of the human body's physiological indicators.

[0021] Please see Figures 3-5 The controller 14 is also equipped with a display screen 142, a speaker, and a fingerprint reader 141. The controller 14 receives external training instructions through a wireless transceiver and transmits them to the user through the speaker. The fingerprint reader 141 is used for user login identification. The display screen 142 can display the user's physiological indicator information for easy viewing. During group training, the speaker can play group training music or be used by the coach to send training instructions. The fingerprint reader 141 can identify the user's identity when the user uses the device.

[0022] The controller 14 is provided with a buckle 143 and a breathable mesh pad 144 on the side connected to the headband 11. The headband 11 is provided with buckle strips 13 on both sides that match the buckle 143. The controller 14 is detachably connected to the buckle strips 13 of the headband 11 through the buckle 143. The controller 14 can be easily installed by buckling the buckle 143 into the buckle strip 13. The breathable mesh pad 144 fits against the skin near the user's ears, which can improve the breathability and improve the comfort of use.

[0023] Please see Figures 6-8 The acquisition plate 131 has a first connection hole 1311 at each end, and the headband 11 has a second connection hole 1121 at each end. The connector 12 is connected to the adjacent first connection hole 1311 and second connection hole 1121 respectively.

[0024] The connector 12 includes a buckle 121 and a snap-fit ​​122. The buckle 121 has two sets of sleeves 123 symmetrically arranged on it, and the snap-fit ​​122 has two sets of protrusions 124 symmetrically arranged on it. The sleeves 123 match the protrusions 124. The buckle 121 and the snap-fit ​​122 are detachably connected through the sleeves 123 and the protrusions 124. During installation, the two sets of sleeves 123 of the buckle 121 are passed through the first connecting hole 1311 and the second connecting hole 1121 respectively, so that the two sets of protrusions 124 of the snap-fit ​​122 are connected to the two sets of sleeves 123 respectively, thereby realizing the installation and fixation of the acquisition board 131 and the headband 11.

[0025] A washer 1241 is provided on the protrusion 124, and a slot 1231 is provided inside the sleeve 123. The washer 1241 matches the slot 1231. The cooperation between the washer 1241 and the slot 1231 can improve the stability of the connection between the snap fastener 122 and the buckle 121.

[0026] Please see Figure 1 and Figure 8 Physiological indicators include heart rate, electroencephalogram (EEG) signal, blood oxygen concentration, and body temperature.

[0027] The processor 3 includes a training module 31, a processing module 32, and a storage module 33. The training module 31 is used to send training instructions to several groups of acquisition devices 1 through the wireless concentrator 2. The processing module 32 is used to process physiological index information. The storage module 33 stores the average heart rate, average blood oxygen concentration, and average body temperature of healthy people.

[0028] The processing module 32 includes an independent processing unit 321 and a comprehensive processing unit 322. The independent processing unit 321 is used to process each physiological indicator information independently, and the comprehensive processing unit 322 is used to process several physiological indicator information comprehensively.

[0029] The independent processing unit 321 is configured with a first algorithm and a first processing strategy.

[0030] The first algorithm calculates the user's health risk value based on heart rate, blood oxygen saturation, and body temperature. The first algorithm is configured as follows: Where H is the health risk value, HR is the heart rate value, HRa is the average heart rate, PaO2 is the blood oxygen concentration, PaO2a is the average blood oxygen, T is the body temperature value, Ta is the average body temperature, K1 is the first weight value, K2 is the second weight value, K3 is the third weight value, A1 is the first reference value, and C1 is the first balance value. In the first algorithm, the first reference value is the maximum value of heart rate fluctuation. When the heart rate fluctuation is less than the first reference value, the absolute value of the heart rate value minus the average heart rate value minus the cube of the first reference value is negative, which reduces the value calculated from the heart rate value. If the heart rate fluctuation exceeds the maximum value, the absolute value of the heart rate value minus the average heart rate value minus the cube of the first reference value increases sharply, and the value calculated from the heart rate value also increases, resulting in a higher health risk value. A higher health risk value indicates a greater likelihood of health risk. In the calculation of blood oxygen concentration, when the blood oxygen concentration is less than the average blood oxygen concentration, the calculated value is larger, and a first balance value is set for balancing. When the blood oxygen concentration is lower, the average blood oxygen concentration minus the cube of the blood oxygen concentration plus the first balance value increases sharply, resulting in a larger calculated value for blood oxygen concentration. Therefore, the final total health risk value is larger. In the calculation of body temperature, the higher the body temperature value, the higher the value calculated from the body temperature value, and the higher the final health risk value.

[0031] The first algorithm can reflect a user's health status by using their heart rate, blood oxygen concentration, and body temperature. When a user's heart rate, blood oxygen concentration, and body temperature deviate significantly from the average, it can be concluded that the user's health is at risk, thereby improving the accuracy of health monitoring.

[0032] The first processing strategy includes: comparing the health risk value with a first threshold; when the health risk value is greater than the first threshold, outputting a health risk signal; when the health risk value is less than the first threshold, outputting a normal health signal. The higher the health risk value, the greater the risk to the user's health.

[0033] The comprehensive processing unit 322 includes a transformation subunit 3221, a truncation subunit 3222, an individual evaluation subunit 3223, and an overall evaluation subunit 3224.

[0034] The transformation subunit 3221 plots the EEG signal into an EEG, with the vertical axis of the EEG set to potential amplitude and the horizontal axis of the EEG set to time period.

[0035] The interception subunit 3222 is used to acquire several heart rate values, potential amplitude, blood oxygen concentration and body temperature values ​​of several users from the start to the end of the training instruction.

[0036] The individual assessment subunit 3223 is equipped with a second algorithm, a third algorithm, a fourth algorithm, a fifth algorithm, and a sixth algorithm. The second algorithm calculates the individual heart rate change value based on several heart rate values ​​of the user from the start to the end of the training instruction; the third algorithm calculates the individual brain electrical signal change value based on several potential amplitudes of the user from the start to the end of the training instruction; the fourth algorithm calculates the individual blood oxygen change value based on several blood oxygen concentrations of the user from the start to the end of the training instruction; and the fifth algorithm calculates the individual body temperature change value based on several body temperature values ​​of the user from the start to the end of the training instruction.

[0037] The second algorithm is configured as follows: The third algorithm is configured as follows: The fourth algorithm is configured as follows: The fifth algorithm is configured as follows: Where B1 is the first conversion value, B2 is the second conversion value, B3 is the third conversion value, B4 is the fourth conversion value, and n is the number of times data is acquired from the beginning to the end of each training instruction. In the second, third, fourth and fifth algorithms, by calculating the difference between each set of data and the previous set of data and the difference between the last set of data and the first set of data, the change value of each individual's data can be obtained. By independently analyzing each data, the changes of each individual's physiological indicators during training can be obtained.

[0038] The second, third, fourth, and fifth algorithms can respectively derive individual heart rate changes, individual electrical signal changes, individual blood oxygen changes, and individual body temperature changes. By obtaining these changes, a detailed analysis of the changes in each individual's physiological indicators during the training process can be conducted. This allows for targeted training guidance when an individual has specific training needs for a particular physiological indicator, thereby improving the effectiveness of subsequent training.

[0039] The sixth algorithm calculates an individual comprehensive change value based on the user's individual heart rate change value, individual electrical signal change value, individual blood oxygen change value, and individual body temperature change value. The sixth algorithm is configured as follows: Where Z is the individual comprehensive change value, HRi is the individual heart rate change value, PaO2i is the individual blood oxygen change value, fi is the individual electrical signal change value, Ti is the individual body temperature change value, A2 is the second reference value, A3 is the third reference value, A4 is the fourth reference value, and A5 is the fifth reference value. In the sixth algorithm, the second, third, fourth, and fifth reference values ​​are the corresponding average change values ​​under normal conditions. The greater the change in individual heart rate, individual electrical signal, individual blood oxygen, and individual body temperature, the greater the resulting individual comprehensive change value.

[0040] The sixth algorithm yields an individual's comprehensive change value, which reflects the overall impact of each training exercise on an individual's physiological indicators. This comprehensive change value provides a more complete picture of the changes in an individual's physiological indicators during a particular training exercise, and is beneficial for providing training guidance to users who require comprehensive training.

[0041] The overall evaluation subunit 3224 is equipped with a seventh algorithm, an eighth algorithm, a ninth algorithm, a tenth algorithm, and an eleventh algorithm. The seventh algorithm calculates the overall heart rate change value based on the individual heart rate change values ​​of several users. The eighth algorithm calculates the overall electrical signal change value based on the individual electrical signal change values ​​of several users. The ninth algorithm calculates the overall blood oxygen change value based on the individual blood oxygen change values ​​of several users. The tenth algorithm calculates the overall body temperature change value based on the individual body temperature change values ​​of several users.

[0042] The seventh algorithm is configured as follows: The eighth algorithm is configured as follows: The ninth algorithm is configured as follows: The tenth algorithm is configured as follows: Where m is the number of users, in the seventh, eighth, ninth and tenth algorithms, the variance of each change value of several individuals is calculated to obtain the overall change in each physiological indicator.

[0043] The seventh, eighth, ninth, and tenth algorithms are used to obtain the overall heart rate change, overall electrical signal change, overall blood oxygen change, and overall body temperature change, respectively. By comprehensively analyzing each physiological indicator, and with a sufficient number of individuals, enough information is obtained for each physiological indicator. This allows us to remove the influence of extreme physiological changes in some individuals on the data, thus enabling a more accurate assessment of the impact of a particular training on a specific physiological indicator. This provides more precise guidance for subsequent training and improves the overall effectiveness of the training.

[0044] The eleventh algorithm calculates the overall comprehensive change value based on the overall heart rate change value, overall electrical signal change value, overall blood oxygen change value, and overall body temperature change value. The configuration of the eleventh algorithm is as follows: Where Y is the overall comprehensive change value, HRj is the overall heart rate change value, PaO2j is the overall blood oxygen change value, fj is the overall electrical signal change value, Tj is the overall body temperature change value, A6 is the sixth reference value, A7 is the seventh reference value, A8 is the eighth reference value, A9 is the ninth reference value, and in the eleventh algorithm, the sixth, seventh, eighth, and ninth reference values ​​are the corresponding average change values ​​under normal conditions. The greater the change in the overall heart rate, overall electrical signal, overall blood oxygen, and overall body temperature, the greater the overall comprehensive change value. The calculation of the overall comprehensive change value can reflect the overall training effect.

[0045] The eleventh algorithm comprehensively calculates and analyzes overall heart rate changes, overall electrical signal changes, overall blood oxygen changes, and overall body temperature changes. This allows for a comprehensive assessment of the overall impact of training on the individual, enabling trainees to obtain a more complete picture of the overall training effect and improving the accuracy of their judgment.

[0046] Working principle: In actual use, the user wears the data acquisition device 1300 on their head. The trainer can send training instructions to each user through the user terminal 4 and the wireless concentrator 2. During the training process, the data acquisition device 1300 can acquire the user's physiological indicators and send them to the processor 3 through the wireless concentrator 2. The processor 3 can process and analyze the received data. On the one hand, it can analyze the user's health status, and on the other hand, it can analyze the user's training status, so that the trainer can know the effect of each training and thus allow the user to make targeted changes to the training strategy to improve the effectiveness of the training.

[0047] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A wearable multi-channel physiological indicator monitoring system, characterized in that, It includes several sets of data acquisition devices (1), a wireless concentrator (2), a processor (3), and a user terminal (4). The wireless concentrator (2) is used to receive physiological indicator information sent by several sets of data acquisition devices (1) and send several physiological indicator information to the processor (3). The processor (3) is used to process the received physiological indicator information and send the processing result to the user terminal (4). The data acquisition device (1) includes a headband (11), a data acquisition mechanism (1300), and a controller (14). The two ends of the headband (11) are detachably connected to the data acquisition mechanism (1300) through a set of connectors (12). The headband (11) and the data acquisition mechanism (1300) are connected to form a ring structure and are worn on the user's head. The controller (14) is located on one side of the headband (11) and is electrically connected to the data acquisition mechanism (1300). The controller (14) is equipped with a wireless transceiver, which is used to send the physiological indicator information collected by the data acquisition mechanism (1300) to an external receiving end. The acquisition mechanism (1300) includes an acquisition plate (131) and a heart rate sensor (132), an electroencephalogram (EEG) sensor (133), a blood oxygen probe (134), and a temperature sensor (135) disposed in the acquisition plate (131). The heart rate sensor (132) is used to acquire the user's heart rate value, the EEG sensor (133) is used to acquire the user's EEG signal, the blood oxygen probe (134) is used to acquire the user's blood oxygen concentration, and the temperature sensor (135) is used to acquire the user's body temperature value. The physiological indicators include heart rate, electroencephalogram (EEG) signal, blood oxygen concentration, and body temperature. The processor (3) includes a training module (31), a processing module (32) and a storage module (33). The training module (31) is used to send training instructions to several sets of acquisition devices (1) through the wireless concentrator (2). The processing module (32) is used to process physiological index information. The storage module (33) stores the average heart rate, average blood oxygen concentration and average body temperature of healthy people. The processing module (32) includes an independent processing unit (321) and a comprehensive processing unit (322). The independent processing unit (321) is used to process each physiological indicator information independently, and the comprehensive processing unit (322) is used to process several physiological indicator information comprehensively. The independent processing unit (321) is configured with a first algorithm and a first processing strategy; The first algorithm calculates the user's health risk value based on heart rate, blood oxygen concentration, and body temperature. The first algorithm is configured as follows: Where H is the health risk value, HR is the heart rate value, HRa is the average heart rate, PaO2 is the blood oxygen concentration, PaO2a is the average blood oxygen, T is the body temperature value, Ta is the average body temperature, K1 is the first weight value, K2 is the second weight value, K3 is the third weight value, A1 is the first reference value, and C1 is the first balance value. The first processing strategy includes: comparing a health risk value with a first threshold; outputting a health risk signal when the health risk value is greater than the first threshold; and outputting a normal health signal when the health risk value is less than the first threshold. The integrated processing unit (322) includes a transformation subunit (3221), a truncation subunit (3222), an individual evaluation subunit (3223), and an overall evaluation subunit (3224); The transformation subunit (3221) plots the EEG signal into an EEG, wherein the vertical axis of the EEG is set as the potential amplitude and the horizontal axis of the EEG is set as the time period. The interception subunit (3222) is used to acquire several heart rate values, potential amplitude, blood oxygen concentration and body temperature values ​​of several users from the start to the end of the training instruction; The individual assessment subunit (3223) is equipped with a second algorithm, a third algorithm, a fourth algorithm, a fifth algorithm, and a sixth algorithm. The second algorithm calculates the individual heart rate change value based on several heart rate values ​​of the user from the start to the end of the training instruction. The third algorithm calculates the individual brain electrical signal change value based on several potential amplitudes of the user from the start to the end of the training instruction. The fourth algorithm calculates the individual blood oxygen change value based on several blood oxygen concentrations of the user from the start to the end of the training instruction. The fifth algorithm calculates the individual body temperature change value based on several body temperature values ​​of the user from the start to the end of the training instruction. The sixth algorithm calculates an individual comprehensive change value based on the user's individual heart rate change value, individual electrical signal change value, individual blood oxygen change value, and individual body temperature change value. The sixth algorithm is configured as follows: Where Z is the individual comprehensive change value, HRi is the individual heart rate change value, PaO2i is the individual blood oxygen change value, fi is the individual electrical signal change value, Ti is the individual body temperature change value, A2 is the second reference value, A3 is the third reference value, A4 is the fourth reference value, and A5 is the fifth reference value. The overall evaluation subunit (3224) is equipped with a seventh algorithm, an eighth algorithm, a ninth algorithm, a tenth algorithm, and an eleventh algorithm. The seventh algorithm calculates the overall heart rate change value based on the individual heart rate change values ​​of several users. The eighth algorithm calculates the overall electrical signal change value based on the individual electrical signal change values ​​of several users. The ninth algorithm calculates the overall blood oxygen change value based on the individual blood oxygen change values ​​of several users. The tenth algorithm calculates the overall body temperature change value based on the individual body temperature change values ​​of several users. The eleventh algorithm calculates the overall comprehensive change value based on the overall heart rate change value, overall electrical signal change value, overall blood oxygen change value, and overall body temperature change value. The eleventh algorithm is configured as follows: Where Y is the overall comprehensive change value, HRj is the overall heart rate change value, PaO2j is the overall blood oxygen change value, fj is the overall electrical signal change value, Tj is the overall body temperature change value, A6 is the sixth reference value, A7 is the seventh reference value, A8 is the eighth reference value, and A9 is the ninth reference value.

2. The wearable multi-channel physiological indicator monitoring system according to claim 1, characterized in that, The controller (14) is also equipped with a display screen (142), a speaker and a fingerprint reader (141). The controller (14) receives external training instructions through a wireless transceiver and transmits them to the user through the speaker. The fingerprint reader (141) is used for user login identification.

3. The wearable multi-channel physiological indicator monitoring system according to claim 2, characterized in that, The controller (14) is provided with a buckle (143) and a breathable mesh pad (144) on the side connected to the headband (11). The headband (11) is provided with buckle strips (13) that match the buckle (143) on both sides. The controller (14) is detachably connected to the buckle strips (13) of the headband (11) through the buckle (143).

4. The wearable multi-channel physiological indicator monitoring system according to claim 1, characterized in that, The acquisition plate (131) has a first connection hole (1311) at each end, and the headband (11) has a second connection hole (1121) at each end. The connector (12) is connected to the adjacent first connection hole (1311) and second connection hole (1121) respectively.

5. The wearable multi-channel physiological indicator monitoring system according to claim 4, characterized in that, The connector (12) includes a buckle (121) and a snap-fit ​​(122). The buckle (121) has two sets of symmetrically arranged sleeves (123), and the snap-fit ​​(122) has two sets of symmetrically arranged protrusions (124). The sleeves (123) match the protrusions (124), and the buckle (121) and the snap-fit ​​(122) are detachably connected through the sleeves (123) and the protrusions (124).

6. The wearable multi-channel physiological indicator monitoring system according to claim 5, characterized in that, A washer (1241) is provided on the protrusion (124), and a slot (1231) is provided in the sleeve (123), and the washer (1241) matches the slot (1231).

7. The wearable multi-channel physiological indicator monitoring system according to claim 1, characterized in that, The headband (11) includes a first connecting band (111) and a second connecting band (112), wherein the first connecting band (111) and the second connecting band (112) are bonded together.

8. The wearable multi-channel physiological indicator monitoring system according to claim 1, characterized in that, The second algorithm is configured as follows: The third algorithm is configured as follows: The fourth algorithm is configured as follows: The fifth algorithm is configured as follows: Where B1 is the first conversion value, B2 is the second conversion value, B3 is the third conversion value, B4 is the fourth conversion value, and n is the number of times data is acquired from the start to the end of each training instruction.

9. A wearable multi-channel physiological indicator monitoring system according to claim 1, characterized in that, The seventh algorithm is configured as follows: The eighth algorithm is configured as follows: The ninth algorithm is configured as follows: The tenth algorithm is configured as follows: Where m is the number of users.

Images