CN110720891A - Deep learning body management system and method based on smart band - Google Patents
Deep learning body management system and method based on smart band Download PDFInfo
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Abstract
The invention provides a deep learning body management system based on an intelligent bracelet, which comprises the intelligent bracelet, an APP mobile terminal and a cloud server, wherein the intelligent bracelet transmits collected body information data of a wearing user to the APP mobile terminal, the APP mobile terminal uses a deep learning neural network algorithm, synthesizes real-time data of each module, and calls the cloud server to intelligently synthesize daily reasonable arrangement of self-service doctor plans, nutrition plans, exercise plans and work plans. The invention monitors the physical condition of the wearing user in real time, effectively solves the problem of neglected physical health of people due to busy affairs, effectively prevents various diseases, and can also give an emergency alarm to transmit position information to a nearby hospital.
Description
Technical Field
The invention relates to the technical field of intelligent terminals, in particular to a deep learning body management system and method based on an intelligent bracelet.
Background
There are all kinds of bracelets in the market at present, and traditional intelligent bracelet is a wear-type smart machine. Through traditional intelligent bracelet, wear the user and can take notes real-time data such as exercise, sleep, part in addition diet among the daily life to with these data and cell-phone APP end synchronization, play the effect of guiding healthy life through data. However, these effects are relatively limited, and with the continuous development of cities, the physical quality of people is mostly in sub-health, and the simple data accumulation of the traditional smart bracelet is no longer satisfied, and the physical health of people has no actual improvement trend.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent bracelet system based on a big data deep learning technology, body information data of a wearing user are collected through the intelligent bracelet, and after an APP mobile terminal deeply learns according to the body information data of the wearing user, a cloud server is called to be matched to a plan scheme for improving body health for the wearing user to select.
In order to achieve the purpose, the invention adopts the technical scheme that:
a deep learning body management system based on a smart bracelet comprises the smart bracelet, an APP (Application smartphone third party Application) mobile terminal and a cloud server, wherein the smart bracelet is used for collecting body information data of a wearing user and sending the body information data of the wearing user to the APP mobile terminal; the APP mobile terminal is connected with the cloud server in an internet communication mode, collects body disease big data of disease crowds through the cloud server and establishes a model, then conducts deep learning on body information data of a wearing user and conducts model matching, and finally makes a health plan for the wearing user according to a result of the model matching.
Further, intelligence bracelet includes power module, human information acquisition module, MCU module, flash memory module and bluetooth module, power module is used for the intelligence bracelet supplies power, human information acquisition module is used for gathering the health information data of wearing the user, the MCU module is used for collecting the analysis wear user's health information data, flash memory module is used for storing the health information data of wearing the user, bluetooth module is used for intelligence bracelet removes end communication connection with APP.
Furthermore, the power supply module comprises a solar cell module, a standby power supply module, a charging management module, a battery protection module and a DC voltage reduction module, wherein the solar cell module adopts a solar energy collection screen to convert solar energy into electric energy to supply power to the intelligent bracelet; the standby power supply module is charged by adopting a data line and is matched with the solar cell module to provide power supply; the charging management module is used for adjusting loop current and voltage and displaying a charging state; the battery protection module is used for protecting the battery and avoiding damage to the battery due to overlarge battery load; the DC voltage reduction module is used for converting power provided by the solar cell module and the standby power module into safe voltage required by the intelligent bracelet in working.
Furthermore, the human body information acquisition module comprises an acceleration sensor module, a human body component detection module and a heart rate detection module, wherein the acceleration sensor module is used for acquiring the acceleration of the real-time arm swing of the wearing user so as to judge the movement transition state and the sleep transition state of the wearing user; the human body component detection module is used for detecting the proportion of each component of human body fat, skeletal muscle, inorganic salt, body age and protein of a wearing user; the heart rate detection module is used for detecting the real-time heart rate condition of a wearing user.
Furthermore, the intelligent bracelet further comprises a GPS positioning module, a vibrator module and an LED driving module, wherein the GPS positioning module is electrically connected with the MCU module and is used for collecting the position information of a wearing user, and the APP mobile terminal is in contact with a nearby hospital through a cloud server in an emergency; the vibrator module is electrically connected with the power supply module and the MCU module and is used for message reminding; the LED driving module is used as a display screen of the intelligent bracelet to display time and heart rate information.
The invention provides a method for deeply learning a body management system based on an intelligent bracelet, which specifically comprises the following steps:
s1: collecting body information data of disease people as a sample by using an APP mobile terminal through a cloud server, and establishing a reference database with disease hidden danger labels in the cloud server;
s2: the APP mobile terminal performs deep learning on the sample in the step S1, the sample is used as training data, a deep convolutional neural network model is trained, then the characteristics of the training data are extracted, and a classification model is trained by using the trained characteristics;
s3: the method comprises the steps that body information data of a wearing user are collected through an intelligent bracelet, and the collected body information data are sent to an APP mobile terminal and stored in a cloud server through the intelligent bracelet;
s4: the APP mobile terminal acquires body information data of the wearing user acquired by the smart band, and the body information data is matched with the classification model in the step S2 to predict the disease hidden danger of the wearing user;
s5: the APP mobile terminal searches a corresponding plan scheme in the network according to the disease hidden danger of the wearing user in the step S4 and provides the plan scheme for the wearing user to select.
Further, the body information data includes acceleration of arm swing of the wearing user, fat, skeletal muscle, inorganic salt, body age, composition ratio of protein, and heart rate.
The invention has the beneficial effects that: the invention relates to a method for deeply learning a fire explosion, which is based on deep learning, can be used for analyzing various body data of a wearing user detected by a hand ring end and intelligently calculating and pushing corresponding plan module information. In the information era, people are busy in work and study, often neglect to manage bodies, the intelligent bracelet provided by the invention can carry out all-around conjecture on the bodies of wearing users only by wearing the corresponding APP installed by the users, and more importantly, the system can carry out simulated human brain analysis and study on various data of the bodies of wearing users, provide a reasonable recommendation plan and improve the lives of the people.
Drawings
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is a schematic diagram of the smart bracelet of the present invention;
FIG. 3 is a schematic diagram of the mobile end of the present invention;
FIG. 4 is an algorithm diagram of deep learning of the present invention.
Reference numerals: 1-smart bracelet; 11-a power supply module; 111-solar cell module; 112-a standby power supply module; 113-a charge management module; 114-a battery protection module; a 115-DC voltage reduction module; 12-a human body information acquisition module; 121-an acceleration sensor module; 122-human body composition detection module; 123-heart rate detection module; 13-MCU module; 14-a flash memory module; 15-a bluetooth module; 16-a GPS positioning module; 17-a driver module; 18-an LED driver module; 2-APP mobile terminal; 3-a cloud server;
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
As shown in fig. 1, the invention provides a deep learning body management system based on an intelligent bracelet, which comprises an intelligent bracelet 1, an APP mobile terminal 2 and a cloud server 3, wherein the intelligent bracelet 1 is worn on a wrist of a user, can collect body information data of the user and sends the body information data of the user to the APP mobile terminal 2; wear the user and remove end 2 downloads and install corresponding APP software at APP, APP removes end 2 and establishes internet communication connection with cloud ware 3, and APP removes end 2 and utilizes cloud ware 3 to collect the body disease big data of disease crowd and establish the model, carries out the deep study to wearing user's body information data again and carries out the model matching, makes exercise or diet plan to wearing the user at last.
As an embodiment, the APP mobile terminal 2 may be a smart phone or a tablet computer.
As shown in fig. 2, the smart bracelet 1 includes a power module 11, a human body information collection module 12, an MCU module 13, a flash memory module 14 and a bluetooth module 15, the power module 11 provides working power for the smart bracelet 1, specifically, the power module 11 includes a solar cell module 111, a standby power module 112, a charging management module 113, a battery protection module 114 and a DC voltage reduction module 115, the solar cell module 111 adopts a solar energy collection screen to convert solar energy into electric energy to supply power to the smart bracelet 1; the standby power supply module 112 is charged by adopting a data line and supplies power to the smart bracelet 1 by matching with the solar cell module 111; the charging management module 113 employs a charger BQ24045 that fully integrates the charger power stage and charging current sensing functions and has the functions of high precision current and voltage regulation loops, charging status display, and charging termination; the battery protection module 114 adopts a battery composite IC SS71A, the SS71A has small volume which is less than half of the split packaging size of an IC + MOS (Futune Dw01+ MS8205), and the battery protection module is particularly suitable for the application occasions with smaller size, and SS71A has mature technology, saves cost and has reasonable price; the power supply provided by the solar cell module 111 and the standby power supply module 112 is converted into the working power supply of the smart bracelet 1 by the DC voltage reduction module 115, the DC voltage reduction module 115 uses a DC voltage reduction chip TPS62736, the energy loss is small in the voltage reduction process, the heat generation of the chip is not obvious, and the chip packaging ratio is small, so that the PWM digital control can be realized.
The human body information acquisition module 12 is used for acquiring body information data of a wearing user, and specifically comprises an acceleration sensor module 121, a human body component detection module 122 and a heart rate detection module 123, wherein the acceleration sensor module 121 acquires real-time acceleration of arm swing of the wearing user and judges motion transition state, sleep transition state and the like of the wearing user, the acceleration sensor module 121 adopts ADXL362, the power consumption of the sensor ADXL362 is low, a 3-axis MEMS accelerometer is adopted, the output data rate is 100Hz, the time power consumption is lower than 2 muA and is more than 5 times of that of a similar chip, the power consumption of the ADXL362 is only 1/25 of other sensors, even 1/50, and therefore, the service life of a product can be obviously prolonged; the human body composition detection module 122 is used for detecting the proportion of each component of human body fat, skeletal muscle, inorganic salt, body age, protein and the like of the wearing user, the human body composition detection module 122 adopts a bioelectrical impedance method for measurement, mainly detects the proportion of each component of human body fat, skeletal muscle, inorganic salt, body age, protein and the like of the wearing user, and the method refers to the most defensive human body shape health aesthetic method for judging the physical condition of the wearing user, and is relatively cheap, easy to operate, accurate in result and repeatable; the heart rate detection module 123 is used for detecting heart rate data of a wearing user, through heart rate measurement, by combining with other module data, calories consumed by exercise of the wearing user can be judged, whether the wearing user is in a shock state or not can be judged, sleep conditions of the wearing user and the like can be judged, and meanwhile, detection frequency can be set through an APP terminal.
The MCU module 13 is used for transferring sensor measurement wearing user data of each module, the MCU module 13 adopts a chip DA14580, the chip DA14580 is small in size, low in power consumption and low in cost, and the MCU module is suitable for being used on peripheries of mobile phones and PCs and remote controllers. The flash memory module 14 is mainly used as a data interaction storage unit, namely, stores the body information data of the wearing user collected by the sensor modules, the flash memory module 14 adopts a chip W25X20CL, the chip has the advantages of fast access, low error rate, no noise and small heat dissipation, and is very suitable for being used as a data storage unit of the smart bracelet 1. Bluetooth module 15 is used for intelligent bracelet 1 and APP to remove end communication connection, and Bluetooth module 15 includes bluetooth antenna pottery SMT, and this antenna is used for establishing intelligent bracelet 1 and APP and removes the medium that holds 2 data transmission, and transmission speed is fast, the output is stable.
The intelligent bracelet 1 further comprises a GPS positioning module 16, a vibrator module 17 and an LED driving module 18, wherein the GPS positioning module 16 collects detailed position information of a wearing user, judges the position of the wearing user, further judges that the wearing user is in a transition state of working, learning and entertainment, and provides an emergency contact position for a nearby hospital; the vibrator module 17 is used for calling the vibrator module 17 to generate vibration when a message is transmitted or other reminding messages exist, so as to achieve the reminding effect, as an embodiment, the vibrator module 17 adopts a crystal oscillator, the oscillator has precise geometric dimension, stable physical performance, very small thermal expansion coefficient and very stable oscillation frequency; LED drive module 18 mainly provides screen display for intelligent bracelet 1, and LED drive module 18 adopts chip LP5562, and this chip light efficiency is high, power consumptive few, and long-lived, easy control, non-maintaining, safety ring protects.
As shown in fig. 3 and 4, the MCU module 13 sends the body information data of the wearing user collected by each sensor to the APP mobile terminal 2 through the bluetooth module 15, and the APP mobile terminal 2 deeply learns and analyzes the body information data of the wearing user and calls the cloud server 3 to make a health plan for the wearing user.
The embodiment of the invention provides a method for deeply learning a body management system based on an intelligent bracelet, which comprises the following specific steps:
s1: the APP mobile terminal 2 is in communication connection with the cloud server 3 through the Internet, the APP mobile terminal 2 collects body information data of people with diseases as samples, and a reference database with disease hidden danger labels is established in the cloud server 3 according to the samples;
s2: the APP mobile terminal 2 deeply learns the samples in the step S1, trains a deep convolutional neural network model by taking the samples as training data, extracts the characteristics of the training data, and trains a classification model by using the trained characteristics;
s3: the intelligent bracelet 1 collects body information data of a certain wearing user, sends the body information data of the wearing user to the APP mobile terminal 2 through the Bluetooth module 15, and the APP mobile terminal 2 stores the body information data of the wearing user in the cloud server 3 through the Internet;
s4: the APP mobile terminal 2 inputs the body information data of the wearing user collected by the smart bracelet 1 into the deep convolutional neural network model in the step S2, extracts the characteristics of the body information data of the wearing user, and then predicts the disease hidden danger of the wearing user by using the classification model in the step S2;
s5: for the disease hidden trouble in step S4, the APP mobile terminal 2 searches the network for a corresponding planning scheme to provide for the wearing user to select.
As an embodiment, the data of the user measured in step S3 is transmitted through each sensor of the smart bracelet 1, and the sensor is the most popular and suitable type in the current market, so that the method has the characteristics of high precision, sufficient data, strong real-time performance, convenience, rapidness and the like, and is sufficient for supporting the prediction of the neural network; the data measured in the step S3 can be updated in real time, and the parameters of the deep convolutional neural network model are continuously optimized, so that the characteristics in the step S4 are more accurate, and the prediction is more reliable; the body data types measured in the step S3 are most of the types that the smart bracelet can measure in the market, which is beneficial to function transplantation of other mainstream bracelets in the future, provides a good platform for later development and development, and is beneficial to continuous development and innovation.
As an embodiment, the body information data of the wearing user in step S3 includes the acceleration of arm swing of the wearing user, fat, skeletal muscle, inorganic salt, body age, component proportion of protein, and heart rate, according to these body information data, the APP mobile terminal 2 makes a self-service doctor plan, a nutrition plan, an exercise plan, and a work plan, and the self-service doctor plan judges the body condition of the wearing user and provides a plan scheme for the appointment check of a nearby hospital for the APP mobile terminal according to the heart rate and body component information of the wearing user acquired by the smart band; the nutrition plan provides a plan scheme of a nutrition meal for the APP mobile terminal according to the arm shaking acceleration, the heart rate and the body composition information of the wearing user acquired by the smart band; the exercise plan is an exercise plan scheme provided by the APP mobile terminal according to the arm swing acceleration, the heart rate, the body composition information and the peripheral fitness facility information of the wearing user collected by the intelligent bracelet; the working plan is that the APP mobile terminal judges the working time of the wearing user according to the arm swing acceleration, the heart rate and the position information collected by the intelligent bracelet and reminds the wearing user to exercise.
Finally, it should be noted that: the above examples are only for illustrating the technical solutions of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the above embodiments may be modified, or some or all of the technical features may be equivalently replaced, and the modifications or the replacements do not make the essence of the corresponding technical solutions beyond the technical solutions of the embodiments of the present invention, and are all covered by the claims and the specification of the present invention.
Claims (7)
1. A deep learning body management system based on an intelligent bracelet is characterized by comprising the intelligent bracelet, an APP mobile terminal and a cloud server, wherein the intelligent bracelet is used for collecting body information data of a wearing user and sending the body information data of the wearing user to the APP mobile terminal; the APP mobile terminal is connected with the cloud server in an internet communication mode, collects body disease big data of disease crowds through the cloud server and establishes a model, then conducts deep learning on body information data of a wearing user and conducts model matching, and finally makes a health plan for the wearing user according to a result of the model matching.
2. The deep learning body management system based on smart band of claim 1, wherein the smart band comprises a power module, a human body information collection module, an MCU module, a flash memory module and a Bluetooth module, the power module is used for supplying power to the smart band, the human body information collection module is used for collecting body information data of a wearing user, the MCU module is used for collecting and analyzing the body information data of the wearing user, the flash memory module is used for storing the body information data of the wearing user, and the Bluetooth module is used for the smart band to be connected with APP mobile terminal communication.
3. The deep learning body management system based on the smart band of claim 2, wherein the power module comprises a solar cell module, a standby power module, a charging management module, a battery protection module and a DC voltage reduction module, the solar cell module adopts a solar collection screen to convert solar energy into electric energy to supply power to the smart band; the standby power supply module is charged by adopting a data line and is matched with the solar cell module to provide power supply; the charging management module is used for adjusting loop current and voltage and displaying a charging state; the battery protection module is used for protecting the battery and avoiding damage to the battery due to overlarge battery load; the DC voltage reduction module is used for converting power provided by the solar cell module and the standby power module into safe voltage required by the intelligent bracelet in working.
4. The deep learning body management system based on the smart band of claim 2, wherein the human body information collection module comprises an acceleration sensor module, a human body component detection module and a heart rate detection module, and the acceleration sensor module is used for collecting the acceleration of real-time arm swing of a wearing user so as to judge the movement state and the sleep state of the wearing user; the human body component detection module is used for detecting the proportion of each component of human body fat, skeletal muscle, inorganic salt, body age and protein of a wearing user; the heart rate detection module is used for detecting the real-time heart rate condition of a wearing user.
5. The intelligent life housekeeper bracelet based on deep learning of claim 2, further comprising a GPS positioning module, a vibrator module and an LED driving module, wherein the GPS positioning module is electrically connected with the MCU module and is used for collecting position information of a wearing user, and the APP mobile terminal is in contact with a hospital at a nearby position through a cloud server in case of emergency; the vibrator module is electrically connected with the power supply module and the MCU module and is used for message reminding; the LED driving module is used as a display screen of the intelligent bracelet to display time and heart rate information.
6. A method for deeply learning a body management system based on an intelligent bracelet is characterized by comprising the following steps:
s1: collecting body information data of disease people as a sample by using an APP mobile terminal through a cloud server, and establishing a reference database with disease hidden danger labels at the APP mobile terminal;
s2: the APP mobile terminal performs deep learning on the sample in the step S1, the sample is used as training data, a deep convolutional neural network model is trained, then the characteristics of the training data are extracted, and a classification model is trained by using the trained characteristics;
s3: the method comprises the steps that body information data of a wearing user are collected through an intelligent bracelet, and the collected body information data are sent to an APP mobile terminal and stored in a cloud server through the intelligent bracelet;
s4: the APP mobile terminal acquires body information data of the wearing user acquired by the smart band, and the body information data is matched with the classification model in the step S2 to predict the disease hidden danger of the wearing user;
s5: the APP mobile terminal searches a corresponding plan scheme in the network according to the disease hidden danger of the wearing user in the step S4 and provides the plan scheme for the wearing user to select.
7. The method for deep learning body management system based on smart band of claim 6, wherein the body information data comprises acceleration of arm swing of wearing user, fat, skeletal muscle, inorganic salt, body age, component ratio of protein and heart rate.
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| CN201910994894.3A CN110720891A (en) | 2019-10-18 | 2019-10-18 | Deep learning body management system and method based on smart band |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111798949A (en) * | 2020-07-02 | 2020-10-20 | 江苏蔷盛文化传媒有限公司 | Internet of things personal health care management system |
| CN112869721A (en) * | 2021-02-25 | 2021-06-01 | 江苏康力源体育科技股份有限公司 | Body measuring instrument capable of automatically generating exercise prescription |
| CN114296516A (en) * | 2021-12-30 | 2022-04-08 | 重庆芳甸智慧科技有限公司 | Learning management and control system based on wrist type wearable equipment |
| TWI790728B (en) * | 2021-08-27 | 2023-01-21 | 李宗諺 | Portable device for circulatory shock monitoring |
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2019
- 2019-10-18 CN CN201910994894.3A patent/CN110720891A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111798949A (en) * | 2020-07-02 | 2020-10-20 | 江苏蔷盛文化传媒有限公司 | Internet of things personal health care management system |
| CN112869721A (en) * | 2021-02-25 | 2021-06-01 | 江苏康力源体育科技股份有限公司 | Body measuring instrument capable of automatically generating exercise prescription |
| TWI790728B (en) * | 2021-08-27 | 2023-01-21 | 李宗諺 | Portable device for circulatory shock monitoring |
| CN114296516A (en) * | 2021-12-30 | 2022-04-08 | 重庆芳甸智慧科技有限公司 | Learning management and control system based on wrist type wearable equipment |
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