CN107080933B - A kind of motion detection towards obese patient and feedback interventions system and method - Google Patents

A kind of motion detection towards obese patient and feedback interventions system and method Download PDF

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CN107080933B
CN107080933B CN201710345083.1A CN201710345083A CN107080933B CN 107080933 B CN107080933 B CN 107080933B CN 201710345083 A CN201710345083 A CN 201710345083A CN 107080933 B CN107080933 B CN 107080933B
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obese patient
grade
data
arm processor
sensor
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CN107080933A (en
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孙文方
张毅
李冠亚
胡杨
赵继政
秦国栋
孟倩倩
刘丽
金庆超
刘磊
袁凯
刘继欣
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Xidian University
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    • A63B71/00Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06Indicating or scoring devices for games or players, or for other sports activities
    • A63B71/0619Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
    • AHUMAN NECESSITIES
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Abstract

The present invention relates to a kind of motion detections towards obese patient and feedback interventions system and method.System includes arm processor, heart rate sensor, motion sensor, optical sensor, temperature sensor, digital dock chip, FLASH memory, LED attention device, micro buzzer-phone, Bluetooth antenna, power management chip and battery.Method includes (1), the age for inputting wearer and current time information, then acquires moving acceleration data, heart rate data, the temperature data of surrounding and the intensity of illumination data of obese patient;(2), adding window smothing filtering noise reduction, sampling and correction process are carried out to data;(3), weighting processing moving acceleration data and heart rate data, exercise intensity grade assessed value is obtained, fusional movement strength grade assessed value, sendible temperature grade assessed value, body-sensing brightness degree assessed value and usage time interval obtain the feedback interventions grade to obese patient;(4) intervention processing is implemented to obese patient.

Description

A kind of motion detection towards obese patient and feedback interventions system and method
Technical field
The present invention relates to motion detections and motor behavior feedback interventions technical field, in particular to one kind is towards obese patient Motion detection and feedback interventions system and method.
Background technique
2016 Britain famous medical journal " lancet " deliver global adult human body weight's survey report: the whole world is adult fat Population alreadys exceed regular severe one, wherein China is with 90,000,000 populations of being obese, (male 43,200,000, ten thousand) women 4649 is more than beauty The 87000000 of state become the most country of global population of being obese.Therefore the fat situation very severe that China faces.
Currently, countries in the world all suffer from this fat global problem, it is defined as disease by the World Health Organization (WHO) Disease is most threatening to human health the third-largest factor after cardiovascular disease and cancer.Obesity not only causes various metabolism Class disease (such as type-2 diabetes mellitus), and multiple complications can be caused, not such as coronary heart disease, hypertension, liver and gallbladder lesion, lung function Good, arthropathy etc..In addition, obesity has an effect on pretty figure, inconvenience in the majority is brought to people's life.
Research shows that causing fat reason very much, but principal element is excessive intake, the movement due to high heat food The reduction of amount leads to the imbalance between taking in and consuming, and then causes obesity.
It is current with the development of society, the change of dietary structure and living habit, the excessive intake of high heat food, and People are increasingly dependent on convenient and fast traffic, and the series of factors such as high-intensitive work result in us and take between consumption in addition Imbalance.How aspect is intervened in subordinate act, is regulated and controled life style, is increased amount of exercise and energy consumption, is to control and adjust One important link of weight.
Summary of the invention
Goal of the invention: the present invention has made improvements in view of the above-mentioned problems of the prior art, i.e., first mesh of the invention Be a kind of motion detection towards obese patient and feedback interventions system are disclosed, system is worn on human body wrist position, uses To help obesity controlling patient motion and sleep habit.Second object of the present invention is to disclose a kind of towards obese patient's Motion detection and feedback interventions method.
Technical solution: a kind of motion detection towards obese patient and feedback interventions system, comprising:
Arm processor is assessed, comprehensive is sentenced with merging for data acquisition and the pretreatment of Multiple Source Sensor, data analysis Certainly, intervene control;
Heart rate sensor is connected, for monitoring the heart rate of wearer by I2C bus with arm processor;
Motion sensor is connected with arm processor by I2C bus, and three axis by obtaining wearer's wrist movement add Speed and three axis angular rates monitor the movement of wearer;
Optical sensor is connected with arm processor by I2C bus, and the illumination for monitoring wearer's ambient enviroment is strong Degree;
Temperature sensor is connected, for monitoring the temperature of wearer's ambient enviroment by I2C bus with arm processor;
Digital dock chip is connected with arm processor by I2C bus, and accurate clock data are generated, and is sensed for multi-source The data time of device is synchronous and provides time standard for obese patient's therapeutic intervention;
FLASH memory is connected with arm processor by spi bus, for storing the pretreated number of Multiple Source Sensor According to;
LED attention device, input terminal are connected with the output end of arm processor, by issue different colours flash light to Wearer, which warns, to be intervened;
Micro buzzer-phone, input terminal are connected with the output end of arm processor, are warned by issuing tweeting sound to wearer Intervene,
Bluetooth antenna communicates interconnection with arm processor, carries out for the smart machine of system and surrounding short distance wireless blue Tooth communication;
Micro USB interface is connected with arm processor universal asynchronous receiving-transmitting transmitter, for host computer to system processing Device program debugging and program downloading, and higher level's power interface as battery charging;
Power management chip, respectively with battery, the power pin of heart rate sensor, the power pin of motion sensor, light According to the power pin of sensor, the power pin of temperature sensor, the power pin of digital dock chip, FLASH memory Power pin be connected, be managed for the charging voltage to battery, be also used to battery to heart rate sensor, motion sensor, Optical sensor, temperature sensor, digital dock chip, the supply voltage of FLASH memory and supply current are managed;
Battery is connected with power management chip;
Key is connected with the input terminal of arm processor, be respectively used to control arm processor carry out data storage operations and Stop intervention operation.
Further, the smart machine includes smart phone.
Further, key includes storage dedicated button and stops intervening dedicated button, and storage dedicated button and ARM are handled The input terminal of device is connected, and carries out data storage operations for controlling arm processor;Stop intervening dedicated button and arm processor Input terminal be connected, carry out stopping intervention operation for controlling arm processor.
A kind of motion detection towards obese patient and feedback interventions method, obese patient is by above-mentioned towards obese patient's Motion detection and feedback interventions system are worn at wrist, comprising the following steps:
(1), towards obese patient motion detection and feedback interventions system in input wearer age and it is current when Between information, then pass through the motion detection towards obese patient being worn at wrist and feedback interventions system acquisition obese patient Moving acceleration data, heart rate data, around temperature data and intensity of illumination data;
(2), adding window smothing filtering noise reduction, sampling and correction process are carried out to the collected data of step (1), reduced subsequent Handle data volume and memory space requirements;
(3), moving acceleration data and heart rate data that weighting processing step (2) obtains, obtain exercise intensity grade and comment Valuation, zonal quantization vitro temperature, external light intensity, obtain sendible temperature grade assessed value and body-sensing brightness etc. respectively Grade assessed value, fusional movement strength grade assessed value, sendible temperature grade assessed value, body-sensing brightness degree assessed value and use when Between section obtain to the feedback interventions grade of obese patient;
(4) intervention processing is implemented to obese patient according to the feedback interventions grade that step (3) obtains.
Further, step (3) the following steps are included:
(31) exercise intensity grade assessed value is calculated
(311) average value for calculating the acceleration of motion vector sum in time window, is denoted as A, it is very light according to movement, light, in Deng, again, very heavy interval range the assessment of exercise intensity grade is carried out to the value of A, assessed value is denoted as P1
As A < 0.1, indicate to move very light, P1=1;
As 0.1≤A < 0.2, indicate that movement is light, P1=2;
It indicates to move medium, P as 0.2≤A < 0.31=3;
As 0.4≤A < 0.5, movement weight, P are indicated1=4;
As A >=0.5, indicate to move very heavy, P1=5;
(312) calculate time window in obese patient heart rate average value, be denoted as B, according to move it is very light, light, medium, again, Very heavy interval range carries out the assessment of exercise intensity grade to B value, and assessed value is denoted as P2
When the B < 140- age, indicate to move very light, P2=1;
When 140- age≤B < 160- age, indicate that movement is light, P2=2;
When 160- age≤B < 180- age, indicate to move medium, P2=3;
When 180- age≤B < 200- age, movement weight, P are indicated2=4;
When B >=200- age, indicate to move very heavy, P2=5;
(313) processing is weighted to two kinds of exercise intensity hierarchical estimation values and obtains exercise intensity grade assessed value P1-2, P1-2=0.7P1+0.3P2
(32) average value for calculating vitro temperature in time window, is denoted as C, terribly cold according to body-sensing, cold, cool, warm, The temperature interval ranges such as hot, awfully hot, overheat carry out the assessment of sendible temperature grade to C value, and sendible temperature grade assessed value is denoted as P3
When 0 DEG C of C <, terribly cold, P is indicated3=1;
When 5 DEG C of 0 DEG C≤C <, cold, P is indicated3=2;
When 15 DEG C of 5 DEG C≤C <, cool, P is indicated3=3;
When 22 DEG C of 15 DEG C≤C <, warm, P is indicated3=4;
Heat, P are indicated when 27 DEG C of 22 DEG C≤C <3=5;
When 32 DEG C of 27 DEG C≤C <, awfully hot, P is indicated3=6;
When C > 32 DEG C, overheat, P are indicated3=7;
(33) average value for calculating the intensity of illumination in time window, is denoted as D, dark, glimmer very dark according to body-sensing, bright, very bright Etc. brightness sections range brightness degree assessment is carried out to D value, body-sensing brightness degree assessed value is denoted as P4
When 0 lux≤0.5 lux < D, very dark, P is indicated4=1;
When 0.5 lux≤20 lux < D, indicate dark, P4=2;
When 20 luxs≤50 lux < D, glimmer, P are indicated4=3;
When 50 luxs≤300 lux < D, bright, P is indicated4=4;
When D > 300 lux, very bright, P is indicated4=5;
(34) note usage time interval be T, according to morning, morning, the morning, noon, afternoon, the dusk, at night to the T value amount of progress Change, quantized value is denoted as P5
When 0 point≤T < 5, it is expressed as morning, P5=1;
When 5 points≤T < 8, it is expressed as morning, P5=2;
When 8 points≤T < 12, it is expressed as the morning, P5=3;
When 12 points≤T < 14, it is expressed as noon, P5=4;
When 14 points≤T < 17, it is expressed as afternoon, P5=5;
It is expressed as when 17 points≤T < 20 at dusk, P5=6;
It is expressed as when 20 points≤T < 24 at night, P5=7;
(35) the feedback interventions grade of obese patient is calculated
Building fusion assessment models calculate feedback interventions the grade P, P=w of obese patient1p1-2+w3p3+w4p4+w5p5, In
w1、w3、w4And w5For weighted value, weighted value is obtained using SVM method off-line training;
P is assessed as three feedback interventions grades, and respectively II grades, I grades and normal, wherein
As P >=0.7, P is II grades, and II grades of expression patient body situations serious problems occur and need alarm intervention;
As 0.4≤P < 0.7, P is I grades, and I grades of expression patients need to move or diet control warning is intervened;
When P < 0.4, P be it is normal, without intervening when normal condition.
Further, in step (4), when the feedback interventions grade P of obese patient is evaluated as II grades, micro buzzer-phone and LED attention device issues audible and visible alarm, and buzzer pipes for a long time, and LED attention device issues flashing feux rouges, while passing through Bluetooth antenna Connection short distance smart machine simultaneously sends warning information.
Further, in step (4), when the feedback interventions grade P of obese patient is evaluated as I grades, micro buzzer-phone and LED attention device issues audible and visible alarm, and micro buzzer-phone short time interval pipes, and LED attention device issues flash green, and warning is fat Patients' rights diet increases movement, reduces sleep.
Further, it in step (4), when the feedback interventions grade P of obese patient is evaluated as normal, does not take at intervention Reason.
Further, in step (4), when LED attention device issues the alternately red-green glow of flashing, the storage of system for prompting is empty Between it is full fastly, patient connects short distance smart machine by Bluetooth antenna by storage dedicated button, system, uploads and stores data into intelligence Energy device end backup, then removes the data in FLASH memory.
Further, in step (4), when micro buzzer-phone sounding and LED attention device shine, obese patient is special by stopping With key, cancel this acousto-optic intervention.
The utility model has the advantages that a kind of motion detection towards obese patient disclosed by the invention and feedback interventions system and method have Have it is following the utility model has the advantages that
1, comprehensive multiple sensors data, can accurately reflect physiology of exercise state, mechanics and the surrounding of obese patient Environment, and implement effective feedback interventions measure, facilitate patient and form good diet, movement, sleep habit, for obesity The treatment of patient's long-acting physical plays a significant role;
2, the complexity and system of calculating is effectively reduced in the processing such as data adding window, sampling, linear weighted function fusion simplified model Power consumption, extend the system standby time.
Detailed description of the invention
Fig. 1 is the structural representation of a kind of motion detection towards obese patient disclosed by the invention Yu feedback interventions system Figure.
Specific embodiment:
Detailed description of specific embodiments of the present invention below.
A kind of motion detection towards obese patient and feedback interventions system, comprising:
Arm processor, for Multiple Source Sensor, (including heart rate sensor, motion sensor, optical sensor and temperature are passed Sensor) data acquisition and pretreatment, data analysis with merge assessment, it is comprehensive adjudicate, intervention control;
Heart rate sensor (model MAX30100 or MAX30102), is connected by I2C bus with arm processor, is used for Monitor the heart rate of wearer;
Motion sensor is connected with arm processor by I2C bus, and three axis by obtaining wearer's wrist movement add Speed and three axis angular rates monitor the movement of wearer;
Optical sensor is connected with arm processor by I2C bus, and the illumination for monitoring wearer's ambient enviroment is strong Degree;
Temperature sensor is connected, for monitoring the temperature of wearer's ambient enviroment by I2C bus with arm processor;
Digital dock chip is connected with arm processor by I2C bus, and accurate clock data are generated, and is sensed for multi-source The data time of device is synchronous and provides time standard for obese patient's therapeutic intervention;
FLASH memory is connected with arm processor by spi bus, for storing the pretreated number of Multiple Source Sensor According to;
LED attention device, input terminal are connected with the output end of arm processor, by issue different colours flash light to Wearer, which warns, to be intervened;
Micro buzzer-phone, input terminal are connected with the output end of arm processor, are warned by issuing tweeting sound to wearer Intervene,
Bluetooth antenna communicates interconnection with arm processor, carries out for the smart machine of system and surrounding short distance wireless blue Tooth communication;
Micro USB interface is connected with arm processor universal asynchronous receiving-transmitting transmitter, for host computer to system processing Device program debugging and program downloading, and higher level's power interface as battery charging;
Power management chip, respectively with battery, the power pin of heart rate sensor, the power pin of motion sensor, light According to the power pin of sensor, the power pin of temperature sensor, the power pin of digital dock chip, FLASH memory Power pin be connected, be managed for the charging voltage to battery, be also used to battery to heart rate sensor, motion sensor, Optical sensor, temperature sensor, digital dock chip, the supply voltage of FLASH memory and supply current are managed;
Battery is connected with power management chip;
Key is connected with the input terminal of arm processor, be respectively used to control arm processor carry out data storage operations and Stop intervention operation.
Further, smart machine includes smart phone.
Further, key includes storage dedicated button and stops intervening dedicated button, and storage dedicated button and ARM are handled The input terminal of device is connected, and carries out data storage operations for controlling arm processor;Stop intervening dedicated button and arm processor Input terminal be connected, carry out stopping intervention operation for controlling arm processor.
A kind of motion detection towards obese patient and feedback interventions method, obese patient is by above-mentioned towards obese patient's Motion detection and feedback interventions system are worn at wrist, comprising the following steps:
(1), towards obese patient motion detection and feedback interventions system in input wearer age and it is current when Between information, then pass through the motion detection towards obese patient being worn at wrist and feedback interventions system acquisition obese patient Moving acceleration data, heart rate data, around temperature data and intensity of illumination data;
(2), adding window smothing filtering noise reduction, sampling and correction process are carried out to the collected data of step (1), reduced subsequent Handle data volume and memory space requirements;
(3), moving acceleration data and heart rate data that weighting processing step (2) obtains, obtain exercise intensity grade and comment Valuation, zonal quantization vitro temperature, external light intensity, obtain sendible temperature grade assessed value and body-sensing brightness etc. respectively Grade assessed value, fusional movement strength grade assessed value, sendible temperature grade assessed value, body-sensing brightness degree assessed value and use when Between section obtain to the feedback interventions grade of obese patient;
(4) intervention processing is implemented to obese patient according to the feedback interventions grade that step (3) obtains.
Further, step (3) the following steps are included:
(31) exercise intensity grade assessed value is calculated
(311) average value for calculating the acceleration of motion vector sum in time window, is denoted as A, it is very light according to movement, light, in Deng, again, very heavy interval range the assessment of exercise intensity grade is carried out to the value of A, assessed value is denoted as P1
As A < 0.1, indicate to move very light, P1=1;
As 0.1≤A < 0.2, indicate that movement is light, P1=2;
It indicates to move medium, P as 0.2≤A < 0.31=3;
As 0.4≤A < 0.5, movement weight, P are indicated1=4;
As A >=0.5, indicate to move very heavy, P1=5;
(312) calculate time window in obese patient heart rate average value, be denoted as B, according to move it is very light, light, medium, again, Very heavy interval range carries out the assessment of exercise intensity grade to B value, and assessed value is denoted as P2
When the B < 140- age, indicate to move very light, P2=1;
When 140- age≤B < 160- age, indicate that movement is light, P2=2;
When 160- age≤B < 180- age, indicate to move medium, P2=3;
When 180- age≤B < 200- age, movement weight, P are indicated2=4;
When B >=200- age, indicate to move very heavy, P2=5;
(313) processing is weighted to two kinds of exercise intensity hierarchical estimation values and obtains exercise intensity grade assessed value P1-2, P1-2=0.7P1+0.3P2
(32) average value for calculating vitro temperature in time window, is denoted as C, terribly cold according to body-sensing, cold, cool, warm, The temperature interval ranges such as hot, awfully hot, overheat carry out the assessment of sendible temperature grade to C value, and sendible temperature grade assessed value is denoted as P3
When 0 DEG C of C <, terribly cold, P is indicated3=1;
When 5 DEG C of 0 DEG C≤C <, cold, P is indicated3=2;
When 15 DEG C of 5 DEG C≤C <, cool, P is indicated3=3;
When 22 DEG C of 15 DEG C≤C <, warm, P is indicated3=4;
Heat, P are indicated when 27 DEG C of 22 DEG C≤C <3=5;
When 32 DEG C of 27 DEG C≤C <, awfully hot, P is indicated3=6;
When C > 32 DEG C, overheat, P are indicated3=7;
(33) average value for calculating the intensity of illumination in time window, is denoted as D, dark, glimmer very dark according to body-sensing, bright, very bright Etc. brightness sections range brightness degree assessment is carried out to D value, body-sensing brightness degree assessed value is denoted as P4
When 0 lux≤0.5 lux < D, very dark, P is indicated4=1;
When 0.5 lux≤20 lux < D, indicate dark, P4=2;
When 20 luxs≤50 lux < D, glimmer, P are indicated4=3;
When 50 luxs≤300 lux < D, bright, P is indicated4=4;
When D > 300 lux, very bright, P is indicated4=5;
(34) note usage time interval be T, according to morning, morning, the morning, noon, afternoon, the dusk, at night to the T value amount of progress Change, quantized value is denoted as P5
When 0 point≤T < 5, it is expressed as morning, P5=1;
When 5 points≤T < 8, it is expressed as morning, P5=2;
When 8 points≤T < 12, it is expressed as the morning, P5=3;
When 12 points≤T < 14, it is expressed as noon, P5=4;
When 14 points≤T < 17, it is expressed as afternoon, P5=5;
It is expressed as when 17 points≤T < 20 at dusk, P5=6;
It is expressed as when 20 points≤T < 24 at night, P5=7;
(35) the feedback interventions grade of obese patient is calculated
Building fusion assessment models calculate feedback interventions the grade P, P=w of obese patient1p1-2+w3p3+w4p4+w5p5, In
w1、w3、w4And w5For weighted value, weighted value is obtained using SVM method off-line training;
P is assessed as three feedback interventions grades, and respectively II grades, I grades and normal, wherein
As P >=0.7, P is II grades, and II grades of expression patient body situations serious problems occur and need alarm intervention;
As 0.4≤P < 0.7, P is I grades, and I grades of expression patients need to move or diet control warning is intervened;
When P < 0.4, P be it is normal, without intervening when normal condition.
Further, in step (4), when the feedback interventions grade P of obese patient is evaluated as II grades, micro buzzer-phone and LED attention device issues audible and visible alarm, and buzzer pipes for a long time, and LED attention device issues flashing feux rouges, while passing through Bluetooth antenna Connection short distance smart machine simultaneously sends warning information.
Further, in step (4), when the feedback interventions grade P of obese patient is evaluated as I grades, micro buzzer-phone and LED attention device issues audible and visible alarm, and micro buzzer-phone short time interval pipes, and LED attention device issues flash green, and warning is fat Patients' rights diet increases movement, reduces sleep.
Further, it in step (4), when the feedback interventions grade P of obese patient is evaluated as normal, does not take at intervention Reason.
Further, in step (4), when LED attention device issues the alternately red-green glow of flashing, the storage of system for prompting is empty Between it is full fastly, patient connects short distance smart machine by Bluetooth antenna by storage dedicated button, system, uploads and stores data into intelligence Energy device end backup, then removes the data in FLASH memory.
Further, in step (4), when micro buzzer-phone sounding and LED attention device shine, obese patient is special by stopping With key, cancel this acousto-optic intervention.
Embodiments of the present invention are elaborated above.But present invention is not limited to the embodiments described above, Technical field those of ordinary skill within the scope of knowledge, can also do without departing from the purpose of the present invention Various change out.

Claims (10)

1. a kind of motion detection towards obese patient and feedback interventions method, obese patient examines the movement towards obese patient It surveys and is worn at wrist with feedback interventions system, which comprises the following steps:
(1), the age of wearer is inputted in the motion detection and feedback interventions system towards obese patient and current time is believed It ceases, then the motion detection and the fortune of feedback interventions system acquisition obese patient towards obese patient by being worn at wrist Dynamic acceleration information, heart rate data, the temperature data of surrounding and intensity of illumination data;
(2), adding window smothing filtering noise reduction, sampling and correction process are carried out to the collected data of step (1), reduces subsequent processing Data volume and memory space requirements;
(3), moving acceleration data and heart rate data that weighting processing step (2) obtains, obtain exercise intensity grade assessed value, Zonal quantization vitro temperature, external light intensity respectively, obtain sendible temperature grade assessed value and body-sensing brightness degree are commented Valuation, fusional movement strength grade assessed value, sendible temperature grade assessed value, body-sensing brightness degree assessed value and usage time interval Obtain the feedback interventions grade to obese patient;
(4) intervention processing is implemented to obese patient according to the feedback interventions grade that step (3) obtains, in which:
Motion detection and feedback interventions system towards obese patient, comprising:
Arm processor, the data for Multiple Source Sensor acquire and analyze and merge assessment with pretreatment, data, synthesis is adjudicated, dry Pre-control;
Heart rate sensor is connected, for monitoring the heart rate of wearer by I2C bus with arm processor;
Motion sensor is connected with arm processor by I2C bus, by the 3-axis acceleration for obtaining wearer's wrist movement The movement of wearer is monitored with three axis angular rates;
Optical sensor is connected, for monitoring the intensity of illumination of wearer's ambient enviroment by I2C bus with arm processor;
Temperature sensor is connected, for monitoring the temperature of wearer's ambient enviroment by I2C bus with arm processor;
Digital dock chip is connected with arm processor by I2C bus, accurate clock data is generated, for Multiple Source Sensor Data time is synchronous and provides time standard for obese patient's therapeutic intervention;
FLASH memory is connected with arm processor by spi bus, for storing the pretreated data of Multiple Source Sensor;
LED attention device, input terminal are connected with the output end of arm processor, flash light to wearing by issuing different colours Person, which warns, to be intervened;
Micro buzzer-phone, input terminal are connected with the output end of arm processor, dry to wearer's warning by issuing tweeting sound In advance,
Bluetooth antenna communicates interconnection with arm processor, and it is logical to carry out wireless blue tooth for the smart machine of system and surrounding short distance Letter;
Micro USB interface is connected with arm processor universal asynchronous receiving-transmitting transmitter, for host computer to system processor journey Sequence debugging and program downloading, and higher level's power interface as battery charging;
Power management chip is passed with battery, the power pin of heart rate sensor, the power pin of motion sensor, illumination respectively The power supply of the power pin of sensor, the power pin of temperature sensor, the power pin of digital dock chip, FLASH memory Pin is connected, and is managed for the charging voltage to battery, is also used to battery to heart rate sensor, motion sensor, illumination Sensor, temperature sensor, digital dock chip, the supply voltage of FLASH memory and supply current are managed;
Battery is connected with power management chip;
Key is connected with the input terminal of arm processor, is respectively used to control arm processor and carries out data storage operations and stopping Intervention operation.
2. a kind of motion detection towards obese patient according to claim 1 and feedback interventions method, which is characterized in that The smart machine includes smart phone.
3. a kind of motion detection towards obese patient according to claim 1 and feedback interventions method, which is characterized in that Key includes storage dedicated button and stops intervening dedicated button, and storage dedicated button is connected with the input terminal of arm processor, uses Data storage operations are carried out in control arm processor;Stop intervention dedicated button to be connected with the input terminal of arm processor, be used for Control arm processor carries out stopping intervention operation.
4. a kind of motion detection towards obese patient according to claim 1 or 2 or 3 and feedback interventions method, step (3) the following steps are included:
(31) exercise intensity grade assessed value is calculated
(311) average value for calculating the acceleration of motion vector sum in time window, is denoted as A, very light, light, medium according to movement, Weight, very heavy interval range carry out the assessment of exercise intensity grade to the value of A, and assessed value is denoted as P1
As A < 0.1, indicate to move very light, P1=1;
As 0.1≤A < 0.2, indicate that movement is light, P1=2;
It indicates to move medium, P as 0.2≤A < 0.31=3;
As 0.4≤A < 0.5, movement weight, P are indicated1=4;
As A >=0.5, indicate to move very heavy, P1=5;
(312) calculate time window in obese patient heart rate average value, be denoted as B, according to move it is very light, light, medium, again, it is very heavy Interval range carries out the assessment of exercise intensity grade to B value, and assessed value is denoted as P2
When the B < 140- age, indicate to move very light, P2=1;
When 140- age≤B < 160- age, indicate that movement is light, P2=2;
When 160- age≤B < 180- age, indicate to move medium, P2=3;
When 180- age≤B < 200- age, movement weight, P are indicated2=4;
When B >=200- age, indicate to move very heavy, P2=5;
(313) processing is weighted to two kinds of exercise intensity hierarchical estimation values and obtains exercise intensity grade assessed value P1-2, P1-2= 0.7P1+0.3P2
(32) average value for calculating vitro temperature in time window, is denoted as C, terribly cold according to body-sensing, cold, cool, warm, hot, very The temperature interval ranges such as heat, overheat carry out the assessment of sendible temperature grade to C value, and sendible temperature grade assessed value is denoted as P3
When 0 DEG C of C <, terribly cold, P is indicated3=1;
When 5 DEG C of 0 DEG C≤C <, cold, P is indicated3=2;
When 15 DEG C of 5 DEG C≤C <, cool, P is indicated3=3;
When 22 DEG C of 15 DEG C≤C <, warm, P is indicated3=4;
Heat, P are indicated when 27 DEG C of 22 DEG C≤C <3=5;
When 32 DEG C of 27 DEG C≤C <, awfully hot, P is indicated3=6;
When C > 32 DEG C, overheat, P are indicated3=7;
(33) average value for calculating the intensity of illumination in time window, is denoted as D, dark, glimmer very dark according to body-sensing, bright, very bright etc. bright It spends interval range and brightness degree assessment is carried out to D value, body-sensing brightness degree assessed value is denoted as P4
When 0 lux≤0.5 lux < D, very dark, P is indicated4=1;
When 0.5 lux≤20 lux < D, indicate dark, P4=2;
When 20 luxs≤50 lux < D, glimmer, P are indicated4=3;
When 50 luxs≤300 lux < D, bright, P is indicated4=4;
When D > 300 lux, very bright, P is indicated4=5;
(34) note usage time interval is T, according to morning, morning, the morning, noon, afternoon, the dusk, is at night quantified to T value, Quantized value is denoted as P5
When 0 point≤T < 5, it is expressed as morning, P5=1;
When 5 points≤T < 8, it is expressed as morning, P5=2;
When 8 points≤T < 12, it is expressed as the morning, P5=3;
When 12 points≤T < 14, it is expressed as noon, P5=4;
When 14 points≤T < 17, it is expressed as afternoon, P5=5;
It is expressed as when 17 points≤T < 20 at dusk, P5=6;
It is expressed as when 20 points≤T < 24 at night, P5=7;
(35) the feedback interventions grade of obese patient is calculated
Building fusion assessment models calculate feedback interventions the grade P, P=w of obese patient1p1-2+w3p3+w4p4+w5p5, wherein
w1、w3、w4And w5For weighted value, weighted value is obtained using SVM method off-line training;
P is assessed as three feedback interventions grades, and respectively II grades, I grades and normal, wherein
As P >=0.7, P is II grades, and II grades of expression patient body situations serious problems occur and need alarm intervention;
As 0.4≤P < 0.7, P is I grades, and I grades of expression patients need to move or diet control warning is intervened;
When P < 0.4, P be it is normal, without intervening when normal condition.
5. a kind of motion detection towards obese patient according to claim 1 or 2 or 3 and feedback interventions method, step (4) in, when the feedback interventions grade P of obese patient is evaluated as II grades, micro buzzer-phone and LED attention device issue acousto-optic police Report, buzzer pipe for a long time, and LED attention device issues flashing feux rouges, while connecting short distance smart machine by Bluetooth antenna And send warning information.
6. a kind of motion detection towards obese patient according to claim 1 or 2 or 3 and feedback interventions method, step (4) in, when the feedback interventions grade P of obese patient is evaluated as I grades, micro buzzer-phone and LED attention device issue audible and visible alarm, The micro buzzer-phone short time interval pipe, LED attention device issue flash green, warning obese patient keep on a diet, increase movement, Reduce sleep.
7. a kind of motion detection towards obese patient according to claim 1 or 2 or 3 and feedback interventions method, step (4) in, when the feedback interventions grade P of obese patient is evaluated as normal, intervention is not taken to handle.
8. a kind of motion detection towards obese patient according to claim 1 or 2 or 3 and feedback interventions method, step (4) in, when LED attention device issues the alternately red-green glow of flashing, the memory space of system for prompting is full fastly, and patient is dedicated by storing Key, system connect short distance smart machine by Bluetooth antenna, and upload stores data into smart machine terminal backup, then clearly Except the data in FLASH memory.
9. a kind of motion detection towards obese patient according to claim 5 and feedback interventions method, in step (4), When micro buzzer-phone sounding and LED attention device shine, obese patient cancels this acousto-optic intervention by dedicated button is stopped.
10. a kind of motion detection towards obese patient according to claim 6 and feedback interventions method, in step (4), When micro buzzer-phone sounding and LED attention device shine, obese patient cancels this acousto-optic intervention by dedicated button is stopped.
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