CN117061551B - Health data monitoring system and method based on cloud computing - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 76
- 230000036541 health Effects 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 31
- 210000000707 wrist Anatomy 0.000 claims abstract description 132
- 210000003462 vein Anatomy 0.000 claims abstract description 123
- 238000004458 analytical method Methods 0.000 claims abstract description 39
- 239000013598 vector Substances 0.000 claims description 102
- 230000008859 change Effects 0.000 claims description 15
- 238000007726 management method Methods 0.000 claims description 15
- 238000012216 screening Methods 0.000 claims description 14
- 230000036772 blood pressure Effects 0.000 claims description 9
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 8
- 239000008280 blood Substances 0.000 claims description 8
- 210000004369 blood Anatomy 0.000 claims description 8
- 238000013500 data storage Methods 0.000 claims description 8
- 230000008451 emotion Effects 0.000 claims description 8
- 210000000811 metacarpophalangeal joint Anatomy 0.000 claims description 8
- 229910052760 oxygen Inorganic materials 0.000 claims description 8
- 239000001301 oxygen Substances 0.000 claims description 8
- 230000001815 facial effect Effects 0.000 claims description 7
- 238000004140 cleaning Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 6
- 210000000623 ulna Anatomy 0.000 claims description 5
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000009323 psychological health Effects 0.000 abstract description 5
- 230000009977 dual effect Effects 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 10
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- 238000000691 measurement method Methods 0.000 description 2
- 230000004630 mental health Effects 0.000 description 2
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- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000000149 penetrating effect Effects 0.000 description 2
- 206010027951 Mood swings Diseases 0.000 description 1
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/681—Wristwatch-type devices
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
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Abstract
The invention discloses a health data monitoring system and method based on cloud computing, and belongs to the field of health data monitoring. According to the invention, the wrist vein image of the user is analyzed, the identity of the user is judged, the shared information content is analyzed by using the face recognition and the wrist vein analysis dual identity recognition, and the information with small negative influence on the user is screened out for display, so that the physical health and psychological health of the user are ensured, and the use experience of the user is improved.
Description
Technical Field
The invention relates to the field of health data monitoring, in particular to a health data monitoring system and method based on cloud computing.
Background
Along with development of science and technology, intelligent equipment provides convenience for people's life gradually increases, and intelligent wrist-watch has been combined multiple intelligent function and has been worn small-size electronic equipment on the wrist, not only can easily receive the message, look over weather and remote control and shoot etc. convenience of customers's daily life can also monitor user's health condition, like rhythm of the heart, blood pressure, sleep quality etc. help the user to manage oneself healthy better.
In the use process of the intelligent watch, the old and the teenagers utilize the intelligent watch to carry out information sharing without using a mobile phone. However, the smart watch has the situation that other people use the smart watch, and in the process of information sharing, negative information often exists, and due to the privacy of guarantee information, guardians often cannot know that the situation that the negative information affects the physical and mental health of the old people and teenagers and even causes economic loss exists, and other words are used for replacing the negative information, so that sensitive words are avoided, and the old people and teenagers are difficult to distinguish.
It is necessary to reduce the negative impact of information on users how to ensure that users of the smart watch are binding users and how to screen and display shared information. Accordingly, there is a need for a cloud computing-based health data monitoring system and method.
Disclosure of Invention
The invention aims to provide a health data monitoring system and method based on cloud computing, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a health data monitoring method based on cloud computing comprises the following steps:
s1, acquiring watch information, inputting face information of a target user when the watch is started for use, and binding the watch with the target user;
s2, when the watch is in a wearing and using state, acquiring wrist vein information of a user in real time, comparing and analyzing wrist vein image information of the user in two adjacent times, and determining user identity information of the user using the watch;
s3, analyzing the information content which is transmitted and shared by a user through a watch according to the user identity condition analyzed in the step S2, shielding negative information, monitoring and analyzing the human health condition when the user views the information, analyzing the information causing heart rate variation, and screening related information for temporary shielding;
s4, shielding the information according to the analysis result in the step S3, and reminding and notifying related users.
Further, in step S1, when the wristwatch is turned on, the face information of the target user is recorded by the camera on the wristwatch, and meanwhile, the data information of the target user is recorded, and the wristwatch information, the target user information and the guardian information are associated with each other.
Further, in step S2, the following steps are included:
s201, monitoring the state of the watch, and analyzing the acquired data by utilizing cloud computing when the watch is in a wearing and using state; cloud computing is a distributed computing technology, in which huge data computing and analyzing programs are decomposed into numerous small programs by distributing a large amount of computing resources such as servers, storage devices and application programs on a network, the small programs are processed and analyzed through a system consisting of a plurality of servers, and finally the results are returned to users; the cloud computing enables a user to achieve a computing task by only accessing the cloud server through a network without installing an application program on a local device, so that the user can use any device to access the cloud service anytime and anywhere.
The wrist vein of the target user is identified through an ultrasonic sensor, the ultrasonic sensor is a sensor for converting ultrasonic signals into other energy signals, usually electric signals, and the ultrasonic is a mechanical wave with the vibration frequency higher than 20kHz, and has the characteristics of high frequency, short wave length, small diffraction phenomenon, good directivity, capability of being converted into rays to directionally propagate, and the like. The ultrasonic wave has great penetrating power on liquid and solid, particularly in the solid with opaque sunlight, the ultrasonic wave can generate obvious reflection to form reflection echo when touching impurities or interfaces, the ultrasonic wave can generate Doppler effect when touching living bodies, and the ultrasonic sensor is widely applied to the aspects of industry, national defense, biomedicine and the like; when a target user starts to use the watch, acquiring image information of wrist veins in real time through ultrasonic waves, acquiring wrist vein feature points of the user, presetting a time interval as t, and forming a vector set A= { a 1 ，a 2 ，...，a m Wherein m is the number of vector sets formed by acquiring images of the vein of the wrist, a m A vector set formed for the wrist vein image acquired for the mth time; through ultrasonic wave monitoring wrist vein image, compare with the infrared monitoring of generally using, receive the influence of light less, the monitoring result is more accurate.
S202, calculating the similarity k between vector sets through the following formula:
wherein i is E (1, m)]，a i-1 A vector set formed for the i-1 st acquired wrist vein image,represented as vector set a i-1 The%>Elements, a i Vector set formed for wrist vein image expressed as ith acquisition, +.>Represented as vector set a i The%>Element(s)>Represented as vector set a i-1 Middle->The module of the individual element->Represented as vector set a i Middle->Modulo, delta, of the individual elements, expressed as a set of vectors a i Element number, vector set a i-1 Vector set a i The number of elements in (a) is equal, < >>
Setting a threshold k for similarity Threshold value When k is greater than or equal to k Threshold value When the wrist vein of the target user acquired twice is representedIf the images are similar, starting a normal use mode of the watch; when k is<k Threshold value When the wrist vein images of the target users acquired in two adjacent times are dissimilar, locking the watch;
When the watch is started, the face information of the user and the wrist vein information are correlated, so that whether the user using the watch is the target user or not can be effectively determined, meanwhile, wrist vein information is collected when the user wears the watch for use, the situation that the watch is held by other people and the watch operation interface is opened in face of the target user is avoided, the situation that the health data of other people are monitored and the analysis of the health data of the target user is influenced is avoided, only the target user can use the watch, and the data safety and property safety of the target user are guaranteed.
Further, in step S2,
s203, acquiring the shape of a user ' S hand using a watch through an ultrasonic sensor, placing the shape in a coordinate system, presetting the coordinate system by a relevant technician, obtaining real-time coordinate phi (x, y) of the metacarpophalangeal joint position point of the middle finger connected with the palm, obtaining omega (x ', y ') of the radius and ulna connection position point of the wrist, and presetting standard coordinate phi ' (x ') of the metacarpophalangeal joint position point of the middle finger connected with the palm Label (C) ，y Label (C) ) Then the included angle theta is rotated Rotation The method comprises the following steps:
the monitored wrist-to-finger part of the wrist vein diagram takes a point omega (x ', y') as a circle center, and the angle is theta Rotation Performing rotation treatment until the rotation included angle is 0, so that the vectors formed by the metacarpophalangeal joint position point of the middle finger connected with the palm and the radius and ulna connection position point of the wrist are consistent all the time no matter how the wrist rotates;
the adjacent wrist vein images are correspondingly matched through a characteristic point matching algorithm, wherein the characteristic point matching algorithm is a common technology in computer vision and image processingThe method is mainly used for finding out similar parts in two or more pictures, and the technology is widely applied to scenes such as image stitching, 3D reconstruction, target tracking, gesture estimation and the like to obtain change vectors of the same characteristic so as to form a setWherein (1)>The vector formed between the wrist vein image acquired for the mth time and the same characteristic point position of the wrist vein image acquired for the mth-1 time is represented, and the included angle set is that Wherein (1)>Denoted as->And->The included angle between the two images is the characteristic point change vector of +.>The included angle is->In the case of the wrist vein image acquired at the i-1 th time, the feature point variation vector is obtained as +.>The included angle is->In the case of the wrist vein image acquired the i-th time, the feature point change vector is +. >The associated distance L' of the wrist vein image acquired at the i-1 th time is calculated by the following formula:
wherein L' represents the associated distance of the wrist vein image acquired for the i-2 th time,the association angle is expressed as the association angle at the characteristic point of the wrist vein image acquired in the i-1 th time, according to the wrist vein images acquired in the first time, the second time and the third time, the association distance and the association angle of the wrist vein image acquired in the third time can be obtained, and the association distance of the wrist vein image is obtained through iterative operation in sequence;
then the angle is correlatedThe association included angle is the included angle between the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the first time and the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the i-2 th time;
s204, calculating the association distance L in the ith acquired wrist vein image through the following formula:
the position of the characteristic point of the first wrist vein image is acquired as (x) 1 ，y 1 ) Taking the point as the center of a circle, the radius r sets the error range as follows: (x-x) 1 ) 2 +(y-y 1 ) 2 ＝r 2 When the limiting distance L is less than or equal to r, the characteristic points of the wrist vein meet the requirements, and a normal use mode of the watch is started; when limiting the distance L >r, if the wrist vein image is abnormal, locking the watch; the situation that errors are gradually enlarged due to the comparison of adjacent images is avoided, the accuracy of data analysis is guaranteed, meanwhile, the change of the adjacent images along with time can be reduced, and the influence of the skin and fat changes of a user is large;
s205, repeating the steps S203-S204 on all the characteristic points acquired on the wrist vein image, judging the identity of the user, locking the system when the user using the watch is inconsistent with the facial recognition binding user, and deleting the acquired data.
Further, in step S3, the following steps are included:
s301, according to the analysis result in the step S2, when the user of the current watch is judged to be the target user, word enabling algorithm is utilized to map the word information which is monitored to be shared by the target user through the watch in a numerical vector space, the monitored word information and the information in a pre-input sensitive word database are identified and screened, negative information containing sensitive words is shielded, information which does not contain the sensitive words is displayed for the user, the sensitive word identification technology is the prior art, and redundant description is omitted;
S302, when the target user views the shared information, the watch monitors the human health data of the target user, the method for monitoring the human health data of the user by the watch is the prior art, and the value of the heart rate of the user monitored when the jth user views the shared information is marked as P j The blood pressure value is recorded as Q j The blood oxygen value is recorded as R j ；
Mood-fluctuation index W for target user by the following formula j And (3) performing calculation:
obtaining according to the historical human health monitoring dataStandard mood swings indexWherein (1)>Expressed as average heart rate value of the target user, +.>Expressed as mean blood pressure value of the target user, +.>The average blood oxygen value, the average heart rate value, the average blood pressure value and the average blood oxygen value of the target user are preset by related technicians; when W is j >W Label (C) When the target user views the shared information, the emotion is influenced, the viewed shared information is marked, and the keyword information in the shared information is extracted to form a vector set E j ；
S303, when the target user views the shared information, repeating the steps S301-S302 to obtain a set E= { E 1 ，E 2 ，…，E n N is represented as the number of marked shared information, E n A set of vectors formed for keywords in the shared information represented as the nth tag;
The shared correlation index α is calculated by the following formula:
wherein E is c Vector set formed by keywords in shared information represented as the c-th tag, c.epsilon.1, n]，E d Vector set formed by keywords in shared information represented as the d-th tag, dε [1, n]Mu is expressed as a super parameter, which is preset by the relevant technician, |E c ∩E d The I is represented as a vector set E c Sum vector set E d Is a central office of intersection ofWith the number of elements, E c ∪E d The I is represented as a vector set E c Sum vector set E d The number of all elements in the union, |E c -E d The I is represented as a vector set E c Removing and vector set E d The number of elements remaining after all elements that are the same, |E d -E c The I is represented as a vector set E d Medium removal and vector set E c The number of the remaining elements after the same all elements in the list is set as alpha by the sharing association index threshold value Threshold value When alpha is greater than or equal to alpha Threshold value When the content representing two vector sets is similar, the shared information is marked as the same type for two times, when alpha<α Threshold value When the contents of the two vector sets are dissimilar, marking the two sharing information as different types;
computing and analyzing shared association indexes among all vector sets in the set E to obtain a set F= { (F) 1 ，f 1 )，(F 2 ，f 2 )，…，(F v ，f v ) V is expressed as the number of types of marks, F v Denoted as type v, (F) v ，f v ) The number of shared information denoted as v-th type has f v A plurality of;
s304, calculating the influence degree beta through the following formula:
wherein f u Indicated as the amount of shared information marked as the u-th type, z as a variable, a threshold value is set as beta Threshold value When beta is greater than or equal to beta Threshold value When the influence of the sharing information on the emotion of the target user is large, temporary storage is carried out on the sharing information at the cloud, namely, the target user is temporarily shielded; when beta is<β Threshold value When the influence of the shared information on the emotion of the target user is small, the shared information is displayed on the target user;
s305, repeating the steps S301-S304 for monitoring the shared data information in real time, and analyzing and judging the influence degree of the shared data information.
Further, in step S4, according to the analysis result in step S3, the sharing information monitored in real time is screened, temporary storage is performed on the sharing information with a large influence degree in the cloud, a guardian of the target user is reminded and notified, and after checking, the guardian selects whether to display the target user, so that the situation that the information affecting the health of the user avoids the sensitive word to display the user is avoided, the negative influence of the sharing information on the user is reduced, the user is prevented from being stimulated by the negative information, the physical health of the user is guaranteed, the psychological health of the user is also guaranteed, and the use experience of the user is improved.
A health data monitoring system based on cloud computing is characterized in that: the data monitoring system includes: a health analysis module;
the health analysis module is used for judging the user identity of the watch, analyzing the shared information on the watch, and comprises an identity identification unit and an information screening unit, wherein the identity identification unit is used for identifying the user identity of the watch through cloud computing in the use state of the watch, comparing the user identities of the watch used for two times adjacently, and the information screening unit is used for analyzing the real-time shared information when judging that the user used is the watch binding user, analyzing the type of the shared information and screening out the information with small influence on the user.
Further, the data monitoring system further comprises: an information monitoring module;
the output end of the information monitoring module is connected with the input end of the health analysis module;
the information monitoring module is used for monitoring the identity and the shared information of a user in real time and comprises a data binding unit, an identity acquisition unit and an information monitoring unit, wherein the data binding unit is used for recording facial information of a target user through a camera on the watch when the watch is started, recording basic data information of the target user, correlating watch information, target user information and guardian information, the identity acquisition unit is used for identifying wrist veins of the target user through an ultrasonic sensor to acquire wrist vein images, and the information monitoring unit is used for monitoring data information shared by the user in real time by using the watch.
Further, the data monitoring system further comprises: the cloud management module;
the input end of the cloud management module is connected with the output end of the information monitoring module, the output end of the cloud management module is connected with the input end of the health analysis module, and the output end of the health analysis module is connected with the input end of the cloud management module;
the cloud management module is used for safely storing acquired watch user information and analysis results, and comprises a data storage unit, a cloud temporary storage unit and a data cleaning unit, wherein the data storage unit is used for safely storing acquired data information and analyzed shared information type data, the cloud temporary storage unit is used for temporarily storing information which does not contain insensitive words but has large influence on users, and the data cleaning unit is used for deleting wrist vein images of users acquired in a historical mode, only the last wrist vein image is reserved, cloud storage space is saved, and data storage resources are saved.
Further, the data monitoring system further comprises: a user display module;
the input end of the user display module is connected with the output end of the health analysis module;
The user display unit is used for displaying shared information of a user according to an analysis result and comprises a first display unit and a second display unit, wherein the first display unit is used for locking a watch when the watch end judges that the user is not bound, shielding negative information containing sensitive words for the user when the watch end judges that the user is bound, displaying shared information with small influence, and the second display unit is used for displaying shared information which does not contain sensitive words for a guardian and has large influence on the user, and the guardian selects whether to display the user at the watch end. Whether the user using the watch is the target user can be effectively determined, the watch is prevented from being held by other people, the situation that the watch operation interface is opened in face of the target user is avoided, the health data of other people are prevented from being monitored, the situation that the analysis of the health data of the target user is influenced is avoided, only the target user can use the watch, the data safety and property safety of the target user are guaranteed, the situation that the information influencing the health of the user avoids sensitive words to display the user is avoided, the negative influence of shared information on the user is reduced, the user is prevented from being stimulated by the negative information, the physical health of the user is guaranteed, the psychological health of the user is also guaranteed, and the use experience of the user is improved.
Compared with the prior art, the invention has the following beneficial effects:
according to the wrist vein identification method and device, the wrist vein of the target user is identified through the ultrasonic sensor, the wrist vein image of the user is obtained, the wrist vein images of the wrist watch used by the user for two adjacent times are analyzed, the identity of the user is judged, the influence of the skin and fat changes of the user along with the change of time is reduced, the face identification and the wrist vein analysis dual identity identification are used, and the accuracy of the identity identification is ensured. The method comprises the steps of analyzing the content of shared information, screening out information with small negative influence on a user, displaying the information, marking the type of the shared information, temporarily storing the information in a cloud end when the information which does not contain sensitive words and has large negative influence on the user appears, displaying a guardian, selecting whether to display a watch end user or not by the guardian, ensuring that only a target user can use a watch, guaranteeing the data safety and property safety of the target user, avoiding the display of the sensitive words on the user when the information which affects the health of the user appears, reducing the negative influence of the shared information on the user, avoiding the stimulation of the user by the negative information, guaranteeing the physical health and psychological health of the user, and improving the use experience of the user.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of steps of a method for monitoring health data based on cloud computing according to the present invention;
FIG. 2 is a schematic diagram of the module composition of a cloud computing-based health data monitoring system of the present invention;
FIG. 3 is a schematic view of feature point correlation distances of the present invention;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides the technical scheme that: fig. 1 is a flowchart of the steps of a health data monitoring method based on cloud computing, including the following steps:
s1, acquiring watch information, inputting face information of a target user when the watch is started for use, and binding the watch with the target user;
In step S1, when the wristwatch is turned on, the face information of the target user is recorded through the camera on the wristwatch, and meanwhile, the data information of the target user, such as the guardian mobile phone account number of the target user, the identity information and the body information of the target user, is recorded, and the wristwatch information, the target user information and the guardian information are related to each other.
S2, when the watch is in a wearing and using state, acquiring wrist vein information of a user in real time, comparing and analyzing wrist vein image information of the user in two adjacent times, and determining user identity information of the user using the watch;
in step S2, the following steps are included:
s201, monitoring the state of the watch, and analyzing the acquired data by utilizing cloud computing when the watch is in a wearing and using state; cloud computing is a distributed computing technology, in which huge data computing and analyzing programs are decomposed into numerous small programs by distributing a large amount of computing resources such as servers, storage devices and application programs on a network, the small programs are processed and analyzed through a system consisting of a plurality of servers, and finally the results are returned to users; the cloud computing enables a user to achieve a computing task by only accessing the cloud server through a network without installing an application program on a local device, so that the user can use any device to access the cloud service anytime and anywhere.
The wrist vein of the target user is identified through an ultrasonic sensor, the ultrasonic sensor is a sensor for converting ultrasonic signals into other energy signals, usually electric signals, and the ultrasonic is a mechanical wave with the vibration frequency higher than 20kHz, and has the characteristics of high frequency, short wave length, small diffraction phenomenon, good directivity, capability of being converted into rays to directionally propagate, and the like. The ultrasonic wave has great penetrating power on liquid and solid, particularly in the solid with opaque sunlight, the ultrasonic wave can generate obvious reflection to form reflection echo when touching impurities or interfaces, the ultrasonic wave can generate Doppler effect when touching living bodies, and the ultrasonic sensor is widely applied to the aspects of industry, national defense, biomedicine and the like; when a target user starts to use the watch, acquiring image information of wrist veins in real time through ultrasonic waves, acquiring wrist vein feature points of the user, presetting a time interval as t, and forming a vector set A= { a 1 ，a 2 ，...，a m Wherein m is the number of vector sets formed by acquiring images of the vein of the wrist, a m A vector set formed for the wrist vein image acquired for the mth time; through ultrasonic wave monitoring wrist vein image, compare with the infrared monitoring of generally using, receive the influence of light less, the monitoring result is more accurate.
S202, calculating the similarity k between vector sets through the following formula:
wherein i is E (1, m)]，a i-1 A vector set formed for the i-1 st acquired wrist vein image,represented as vector set a i-1 The%>Elements, a i Vector set formed for wrist vein image expressed as ith acquisition, +.>Represented as vector set a i The%>Element(s)>Represented as vector set a i-1 Middle->The module of the individual element->Represented as vector set a i Middle->Modulo, delta, of the individual elements, expressed as a set of vectors a i Element number, vector set a i-1 Vector set a i The number of elements in (a) is equal, < >>
Setting a threshold k for similarity Threshold value When k is greater than or equal to k Threshold value When the wrist vein images of the target users acquired twice are similar, starting a normal use mode of the watch; when k is<k Threshold value When the wrist vein images of the target users acquired in two adjacent times are dissimilar, locking the watch;
when the watch is started, the face information of the user and the wrist vein information are correlated, so that whether the user using the watch is the target user or not can be effectively determined, meanwhile, wrist vein information is collected when the user wears the watch for use, the situation that the watch is held by other people and the watch operation interface is opened in face of the target user is avoided, the situation that the health data of other people are monitored and the analysis of the health data of the target user is influenced is avoided, only the target user can use the watch, and the data safety and property safety of the target user are guaranteed.
In the step S2 of the process of the present invention,
s203, acquiring the shape of the user 'S hand using the watch through an ultrasonic sensor, placing the shape in a coordinate system, setting the coordinate system in advance by a related technician, for example, establishing a rectangular coordinate system by taking an elbow joint position point as an origin, obtaining real-time coordinate of a metacarpophalangeal joint position point connected with the palm of the middle finger as phi (x, y), obtaining coordinate of a radius and ulna connecting position point at the wrist as omega (x', y '), and pre-inputting standard coordinate of the metacarpophalangeal joint position point connected with the palm of the middle finger as phi' (x) Label (C) ，y Label (C) ) Then the included angle theta is rotated Rotation The method comprises the following steps:
the monitored wrist-to-finger part of the wrist vein diagram takes a point omega (x ', y') as a circle center, and the angle is theta Rotation Performing rotation treatment until the rotation included angle is 0, so that the vectors formed by the metacarpophalangeal joint position point of the middle finger connected with the palm and the radius and ulna connection position point of the wrist are consistent all the time no matter how the wrist rotates;
the adjacent wrist vein images are correspondingly matched through a characteristic point matching algorithm, wherein the characteristic point matching algorithm is a common technology in computer vision and image processing, and is mainly used for finding out similar parts in two or more pictures, and the technology is used for image splicing, 3D reconstruction, target tracking, gesture estimation and the like The method has wide application in scenes, and the characteristic point matching algorithm comprises violent matching, FLANN matching, LMEDS matching and the like, so that the change vector of the same characteristic is obtained, and a set is formed Wherein (1)>The vector formed between the wrist vein image acquired for the mth time and the same characteristic point position of the wrist vein image acquired for the mth-1 time is represented, and the included angle set is ∈ ->Wherein (1)>Denoted as->And->The included angle between the two images is the characteristic point change vector of +.>The included angle is->In the case of the wrist vein image acquired at the i-1 th time, the feature point variation vector is obtained as +.>The included angle is->Wrist vein collected at the ith timeIn the case of an image, the feature point change vector is +.>The associated distance L' of the wrist vein image acquired at the i-1 th time is calculated by the following formula:
wherein L' represents the associated distance of the wrist vein image acquired for the i-2 th time,the association angle is expressed as the association angle at the characteristic point of the wrist vein image acquired in the i-1 th time, according to the wrist vein images acquired in the first time, the second time and the third time, the association distance and the association angle of the wrist vein image acquired in the third time can be obtained, and the association distance of the wrist vein image is obtained through iterative operation in sequence;
Then the angle is correlatedThe association included angle is the included angle between the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the first time and the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the i-2 th time;
s204, calculating the association distance L in the ith acquired wrist vein image through the following formula:
the position of the characteristic point of the first wrist vein image is acquired as (x) 1 ，y 1 ) Taking the point as the center of a circle, the radius r sets the error range as follows: (x-x) 1 ) 2 +(y-y 1 ) 2 ＝r 2 When the limiting distance L is less than or equal to r, the characteristic point character representing the vein of the wrist is representedIf the requirements are met, starting a normal use mode of the watch; when limiting the distance L>r, if the wrist vein image is abnormal, locking the watch; the situation that errors are gradually enlarged due to the comparison of adjacent images is avoided, the accuracy of data analysis is guaranteed, meanwhile, the change of the adjacent images along with time can be reduced, and the influence of the skin and fat changes of a user is large; FIG. 3 is a schematic diagram of feature point correlation distances;
s205, repeating the steps S203-S204 on all the characteristic points acquired on the wrist vein image, judging the identity of the user, locking the system when the user using the watch is inconsistent with the facial recognition binding user, and deleting the acquired data.
S3, analyzing the information content which is transmitted and shared by a user through a watch according to the user identity condition analyzed in the step S2, shielding negative information, monitoring and analyzing the human health condition when the user views the information, analyzing the information causing heart rate variation, and screening related information for temporary shielding;
in step S3, the following steps are included:
s301, according to the analysis result in the step S2, when the user of the current watch is judged to be the target user, word enabling algorithm is utilized to map the word information which is monitored to be shared by the target user through the watch in a numerical vector space, the monitored word information and the information in a pre-input sensitive word database are identified and screened, negative information containing sensitive words is shielded, information which does not contain the sensitive words is displayed for the user, the sensitive word identification technology is the prior art, redundant description is omitted, for example, a dictionary-based matching method, a naive Bayesian-based matching method and the like are utilized, and the negative information comprises advertisement information, child health information, fraud information requiring transfer and the like;
s302, when the target user views the shared information, the watch monitors the human health data of the target user, and the method for monitoring the human health data of the watch is the prior art, such as a photoelectric measurement method, an electrocardio signal method, an oscillation measurement method and the like, and the jth user views the shared information The heart rate value of the user monitored during information is marked as P j The blood pressure value is recorded as Q j The blood oxygen value is recorded as R j ；
Mood-fluctuation index W for target user by the following formula j And (3) performing calculation:
obtaining a standard emotion fluctuation index according to the historical human health monitoring dataWherein (1)>Expressed as average heart rate value of the target user, +.>Expressed as mean blood pressure value of the target user, +.>The average blood oxygen value, the average heart rate value, the average blood pressure value and the average blood oxygen value of the target user are preset by related technicians, for example, the human health data is monitored when the target user is in a resting state; when W is j >W Label (C) When the target user views the shared information, the emotion is influenced, the viewed shared information is marked, and the keyword information in the shared information is extracted to form a vector set E j ；
S303, when the target user views the shared information, repeating the steps S301-S302 to obtain a set E= { E 1 ，E 2 ，…，E n N is represented as the number of marked shared information, E n A set of vectors formed for keywords in the shared information represented as the nth tag;
the shared correlation index α is calculated by the following formula:
wherein E is c Vector set formed by keywords in shared information represented as the c-th tag, c.epsilon.1, n ]，E d Vector set formed by keywords in shared information represented as the d-th tag, dε [1, n]Mu is expressed as a super parameter, which is preset by the relevant technician, |E c ∩E d The I is represented as a vector set E c Sum vector set E d The number of all elements in the intersection of (E) c ∪E d The I is represented as a vector set E c Sum vector set E d The number of all elements in the union, |E c -E d The I is represented as a vector set E c Removing and vector set E d The number of elements remaining after all elements that are the same, |E d -E c The I is represented as a vector set E d Medium removal and vector set E c The number of the remaining elements after the same all elements in the list is set as alpha by the sharing association index threshold value Threshold value When alpha is greater than or equal to alpha Threshold value When the content representing two vector sets is similar, the shared information is marked as the same type for two times, when alpha<α Threshold value When the contents of the two vector sets are dissimilar, marking the two sharing information as different types;
computing and analyzing shared association indexes among all vector sets in the set E to obtain a set F= { (F) 1 ，f 1 )，(F 2 ，f 2 )，…，(F v ，f v ) V is expressed as the number of types of marks, F v Denoted as type v, (F) v ，f v ) The number of shared information denoted as v-th type has f v A plurality of;
s304, calculating the influence degree beta through the following formula:
Wherein f u Indicated as the amount of shared information marked as the u-th type, z as a variable, a threshold value is set as beta Threshold value When beta is greater than or equal to beta Threshold value When the influence of the sharing information on the emotion of the target user is large, temporary storage is carried out on the sharing information at the cloud, namely, the target user is temporarily shielded; when beta is<β Threshold value When the influence of the shared information on the emotion of the target user is small, the shared information is displayed on the target user;
s305, repeating the steps S301-S304 for monitoring the shared data information in real time, and analyzing and judging the influence degree of the shared data information.
S4, shielding the information according to the analysis result in the step S3, and reminding and notifying related users.
In step S4, according to the analysis result in step S3, the sharing information monitored in real time is screened, the sharing information with a large influence degree is temporarily stored in the cloud, the guardian of the target user is reminded and notified, and selects whether to display the target user after checking, so that the situation that the information affecting the health of the user avoids the sensitive word to display the user is avoided, the negative influence of the sharing information on the user is reduced, the user is prevented from being stimulated by the negative information, the physical health of the user is ensured, the mental health of the user is also ensured, and the use experience of the user is improved.
Fig. 2 is a schematic diagram of module composition of a health data monitoring system based on cloud computing, the data monitoring system comprising: a health analysis module;
the health analysis module is used for judging the user identity of the watch, analyzing the shared information on the watch, and comprises an identity identification unit and an information screening unit, wherein the identity identification unit is used for identifying the user identity of the watch through cloud computing in the use state of the watch, comparing the user identities of the watch used for two times adjacently, and the information screening unit is used for analyzing the real-time shared information when judging that the user used is the watch binding user, analyzing the type of the shared information and screening out the information with small influence on the user.
The data monitoring system further comprises: an information monitoring module;
the output end of the information monitoring module is connected with the input end of the health analysis module;
the information monitoring module is used for monitoring the identity and the shared information of a user in real time and comprises a data binding unit, an identity acquisition unit and an information monitoring unit, wherein the data binding unit is used for recording facial information of a target user through a camera on the watch when the watch is started, recording basic data information of the target user, such as a guardian mobile phone account number of the target user, identity information and body information of the target user, and the like, and correlating the watch information, the target user information and guardian information, the identity acquisition unit is used for identifying wrist veins of the target user through an ultrasonic sensor to obtain wrist vein images, and the information monitoring unit is used for monitoring the data information shared by the user in real time by using the watch.
The data monitoring system further comprises: the cloud management module;
the input end of the cloud management module is connected with the output end of the information monitoring module, the output end of the cloud management module is connected with the input end of the health analysis module, and the output end of the health analysis module is connected with the input end of the cloud management module;
the cloud management module is used for safely storing acquired watch user information and analysis results, and comprises a data storage unit, a cloud temporary storage unit and a data cleaning unit, wherein the data storage unit is used for safely storing acquired data information and analyzed shared information type data, the cloud temporary storage unit is used for temporarily storing information which does not contain insensitive words but has large influence on users, and the data cleaning unit is used for deleting wrist vein images of users acquired in a historical manner, only the last wrist vein image is reserved, the cloud storage space is saved, and the data storage resources are saved;
the data monitoring system further comprises: a user display module;
the input end of the user display module is connected with the output end of the health analysis module;
the user display unit is used for displaying shared information of a user according to an analysis result and comprises a first display unit and a second display unit, wherein the first display unit is used for locking a watch when the watch end judges that the user is not bound, shielding negative information containing sensitive words for the user when the watch end judges that the user is bound, displaying shared information with small influence, and the second display unit is used for displaying shared information which does not contain sensitive words for a guardian and has large influence on the user, and the guardian selects whether to display the user at the watch end. Whether the user using the watch is the target user can be effectively determined, the watch is prevented from being held by other people, the situation that the watch operation interface is opened in face of the target user is avoided, the health data of other people are prevented from being monitored, the situation that the analysis of the health data of the target user is influenced is avoided, only the target user can use the watch, the data safety and property safety of the target user are guaranteed, the situation that the information influencing the health of the user avoids sensitive words to display the user is avoided, the negative influence of shared information on the user is reduced, the user is prevented from being stimulated by the negative information, the physical health of the user is guaranteed, the psychological health of the user is also guaranteed, and the use experience of the user is improved.
Example 1:
if a certain characteristic point is found, the characteristic point change vector is obtained when the wrist vein image is acquired for the 2 nd timeThe included angle is->When the wrist vein image is acquired for the 3 rd time, the characteristic point change vector is obtained as +.>The included angle is->The characteristic point change vector is when the wrist vein image is acquired for the 4 th timeRadius r=1.5, then the correlation distance of wrist vein image acquired 3 rd time +.>
Correlation angleThe correlation distance of the wrist vein image acquired 4 th time The error is large, indicating that the user using the watch is inconsistent with the facial recognition binding user at the moment, and locking the system.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A health data monitoring method based on cloud computing is characterized by comprising the following steps of: comprises the following steps:
s1, acquiring watch information, inputting face information of a target user when the watch is started for use, and binding the watch with the target user;
s2, when the watch is in a wearing and using state, acquiring wrist vein information of a user in real time, comparing and analyzing wrist vein image information of the user in two adjacent times, and determining user identity information of the user using the watch;
s3, analyzing the information content which is transmitted and shared by a user through a watch according to the user identity condition analyzed in the step S2, shielding negative information, monitoring and analyzing the human health condition when the user views the information, analyzing the information causing heart rate variation, and screening related information for temporary shielding;
S4, shielding the information according to the analysis result in the step S3, and reminding and notifying related users;
in step S1, when the watch is started, the face information of a target user is recorded through a camera on the watch, and meanwhile, the data information of the target user is recorded;
in step S2, the following steps are included:
s201, monitoring the state of the watch, and analyzing the acquired data by utilizing cloud computing when the watch is in a wearing and using state;
the wrist vein of the target user is identified through the ultrasonic sensor, when the target user starts to use the watch, the image information of the wrist vein is obtained in real time through ultrasonic waves, the characteristic points of the wrist vein of the user are obtained, the preset time interval is t, and the watch is formedVector set a= { a 1 ，a 2 ，...，a m Wherein m is the number of vector sets formed by acquiring images of the vein of the wrist, a m A vector set formed for the wrist vein image acquired for the mth time;
s202, calculating the similarity k between vector sets through the following formula:
wherein a is i-1 A vector set formed for the i-1 st acquired wrist vein image,represented as vector set a i-1 The%>Elements, a i Vector set formed for wrist vein image expressed as ith acquisition, +.>Represented as vector set a i The%>Element(s)>Represented as vector set a i-1 Middle->The module of the individual element->Represented as vector set a i Middle->Modulo, delta, of the individual elements, expressed as a set of vectors a i The number of elements in (a);
setting a threshold k for similarity Threshold value When k is greater than or equal to k Threshold value When the watch is in the normal use mode, the normal use mode of the watch is started; when k is<k Threshold value When the watch is locked, the watch is locked;
s203, acquiring the shape of a user 'S hand using a watch through an ultrasonic sensor, placing the shape into a coordinate system, obtaining real-time coordinate of metacarpophalangeal joint position points connected with the palm of the middle finger as phi (x, y), obtaining coordinate of radius and ulna connecting position points at the wrist as omega (x', y '), and inputting standard coordinate of metacarpophalangeal joint position points connected with the palm of the middle finger as phi' (x) in advance Label (C) ，y Label (C) ) Then the included angle theta is rotated Rotation The method comprises the following steps:
the monitored wrist-to-finger part of the wrist vein diagram takes a point omega (x ', y') as a circle center, and the angle is theta Rotation Performing rotation treatment;
corresponding matching is carried out on adjacent wrist vein images through a characteristic point matching algorithm to obtain a change vector of the same characteristic, and a set is formedWherein (1)>Expressed as a vector formed between the wrist vein image acquired at the mth time and the same characteristic point position of the wrist vein image acquired at the (m-1) th time, and the included angle set is theta= { theta 1 ，θ 2 ，…，θ m-1 And }, where θ m-1 Denoted as->And->The included angle between the two images is the characteristic point change vector of +.>An included angle of theta i-3 In the case of the wrist vein image acquired at the i-1 th time, the feature point variation vector is obtained as +.>An included angle of theta i-2 In the case of the wrist vein image acquired the ith time, the feature point change vector is +.>The associated distance L' of the wrist vein image acquired at the i-1 th time is calculated by the following formula:
wherein L' is represented as the associated distance of the wrist vein image acquired for the i-2 th time, θ ** The association angle is expressed as the association angle at the characteristic point of the wrist vein image acquired in the i-1 th time, according to the wrist vein images acquired in the first time, the second time and the third time, the association distance and the association angle of the wrist vein image acquired in the third time can be obtained, and the association distance of the wrist vein image is obtained through iterative operation in sequence;
then the angle is correlatedThe association included angle is the included angle between the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the first time and the connecting line of the same characteristic point in the wrist vein image acquired for the i-1 th time and the wrist vein image acquired for the i-2 th time;
s204, calculating the association distance L in the ith acquired wrist vein image through the following formula:
The position of the characteristic point of the first wrist vein image is acquired as (x) 1 ，y 1 ) Taking the point as the center of a circle, the radius r sets the error range as follows: (x-x) 1 ) 2 +(y-y 1 ) 2 ＝r 2 When the limiting distance L is less than or equal to r, the characteristic points of the wrist vein meet the requirements, and a normal use mode of the watch is started; when limiting the distance L>r, if the wrist vein image is abnormal, locking the watch;
s205, repeating the steps S203-S204 on all characteristic points acquired on the wrist vein image, judging the identity of the user, locking the system when the user using the watch is inconsistent with the facial recognition binding user, and deleting the acquired data;
in step S3, the following steps are included:
s301, according to the analysis result in the step S2, when the current user of the watch is judged to be a target user, word enabling algorithm is utilized to map the word information which is monitored to be transmitted and shared by the target user through the watch into a numerical vector space, the monitored word information and the information in a pre-input sensitive word database are identified and screened, negative information containing sensitive words is screened, and information which does not contain the sensitive words is displayed for the user;
s302, when the target user views the shared information, the human health data of the target user is monitored through the watch, and the heart rate value of the user monitored when the jth user views the shared information is marked as P j The blood pressure value is recorded as Q j The blood oxygen value is recorded as R j ；
Mood-fluctuation index W for target user by the following formula j And (3) performing calculation:
obtaining a standard emotion fluctuation index according to the historical human health monitoring dataWherein (1)>Expressed as average heart rate value of the target user, +.>Expressed as mean blood pressure value of the target user, +.>Expressed as the average blood oxygen value of the target user; when W is j >W Label (C) When the method is used, the checked shared information is marked, and keyword information in the shared information is extracted at the same time to form a vector set E j ；
S303, when the target user views the shared information, repeating the steps S301-S302 to obtain a set E= { E 1 ，E 2 ，…，E n N is represented as the number of marked shared information, E n A set of vectors formed for keywords in the shared information represented as the nth tag;
the shared correlation index α is calculated by the following formula:
wherein E is c A set of vectors, E, represented as a keyword in the c-th tagged shared information d The vector set formed by the keywords in the shared information denoted as the d-th mark, μ as the hyper-parameter, |E c ∩E d The I is represented as a vector set E c Sum vector set E d The number of all elements in the intersection of (a)Quantity, |E c ∪E d The I is represented as a vector set E c Sum vector set E d The number of all elements in the union, |E c -E d The I is represented as a vector set E c Removing and vector set E d The number of elements remaining after all elements that are the same, |E d -E c The I is represented as a vector set E d Medium removal and vector set E c The number of the remaining elements after the same all elements in the list is set as alpha by the sharing association index threshold value Threshold value When alpha is greater than or equal to alpha Threshold value When the two sharing information is marked as the same type, when alpha<α Threshold value When the shared information is different in type, the shared information is marked twice;
computing and analyzing shared association indexes among all vector sets in the set E to obtain a set F= { (F) 1 ，f 1 )，(F 2 ，f 2 )，…，(F v ，f v ) V is expressed as the number of types of marks, F v Denoted as type v, (F) v ，f v ) The number of shared information denoted as v-th type has f v A plurality of;
s304, calculating the influence degree beta through the following formula:
wherein f u Indicated as the amount of shared information marked as the u-th type, z as a variable, a threshold value is set as beta Threshold value When beta is greater than or equal to beta Threshold value Temporarily storing the shared information in the cloud; when beta is<β Threshold value When the target user is displayed;
s305, repeating the steps S301-S304 for monitoring the shared data information in real time, and analyzing and judging the influence degree of the shared data information;
in step S4, according to the analysis result in step S3, screening the sharing information monitored in real time, temporarily storing the sharing information with a large influence degree in the cloud, reminding and notifying the guardian of the target user, and selecting whether to display the target user after checking.
2. A cloud computing-based health data monitoring system that performs a cloud computing-based health data monitoring method as set forth in claim 1, characterized by:
the data monitoring system includes: a health analysis module;
the health analysis module is used for judging the user identity of the watch, analyzing the shared information on the watch, and comprises an identity identification unit and an information screening unit, wherein the identity identification unit is used for identifying the user identity of the watch through cloud computing in the use state of the watch, comparing the user identities of the watch used for two times adjacently, and the information screening unit is used for analyzing the real-time shared information when judging that the user used is the watch binding user, analyzing the type of the shared information and screening out the information with small influence on the user.
3. The cloud computing based health data monitoring system of claim 2, wherein: the data monitoring system further comprises: an information monitoring module;
the output end of the information monitoring module is connected with the input end of the health analysis module;
the information monitoring module is used for monitoring the identity and the shared information of a user in real time and comprises a data binding unit, an identity acquisition unit and a shared monitoring unit, wherein the data binding unit is used for recording facial information of a target user through a camera on the watch when the watch is started, recording basic data information of the target user, the identity acquisition unit is used for identifying wrist veins of the target user through an ultrasonic sensor to obtain wrist vein images, and the shared monitoring unit is used for monitoring the data information of the user which is shared in real time by using the watch.
4. A cloud computing based health data monitoring system as in claim 3, wherein: the data monitoring system further comprises: the cloud management module;
the input end of the cloud management module is connected with the output end of the information monitoring module, the output end of the cloud management module is connected with the input end of the health analysis module, and the output end of the health analysis module is connected with the input end of the cloud management module;
the cloud management module is used for safely storing acquired watch user information and analysis results, and comprises a data storage unit, a cloud temporary storage unit and a data cleaning unit, wherein the data storage unit is used for safely storing acquired data information and analyzed shared information type data, the cloud temporary storage unit is used for temporarily storing information which does not contain insensitive words but has large influence on users, and the data cleaning unit is used for deleting historically acquired wrist vein images of the users.
5. The cloud computing based health data monitoring system of claim 4, wherein: the data monitoring system further comprises: a user display module;
the input end of the user display module is connected with the output end of the health analysis module;
The user display module is used for displaying shared information of a user according to an analysis result, and comprises a first display unit and a second display unit, wherein the first display unit is used for locking a watch when the watch end judges that the user is not bound, shielding negative information containing sensitive words for the user when the watch end judges that the user is bound, displaying shared information with small influence, and the second display unit is used for displaying shared information which does not contain sensitive words for a guardian and has large influence on the user, and the guardian selects whether to display the watch end user or not.
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