CN116167035B - Method and system for carrying out identity recognition by collecting hand actions of intelligent watch - Google Patents
Method and system for carrying out identity recognition by collecting hand actions of intelligent watch Download PDFInfo
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Abstract
The invention provides a method and a system for carrying out identity recognition by collecting hand actions by an intelligent watch, which are applied to the field of action data recognition; capturing wearing state of a user, acquiring fitting data of wrist bones of the user based on the wearing state, acquiring action information when the user is transformed by applying a preset gyroscope sensor according to the fitting data, judging whether the action information is suitable for preset recognition conditions, outputting low-frequency current to the user based on preset directions, acquiring signal reflux of low-frequency current return, acquiring first resistance data of fat of the user and second resistance data of muscle tissues according to the signal reflux, generating weight information corresponding to the user, performing difference comparison according to the weight information and preset weight conditions, confirming that the user meets the identity recognition conditions, capturing dynamic transformation data corresponding to the action information, judging whether the dynamic transformation data accords with preset contents or not, and opening corresponding function rights to the user based on the user data of preset identities.
Description
Technical Field
The invention relates to the field of motion data identification, in particular to a method and a system for carrying out identity identification on hand motions collected by an intelligent watch.
Background
Along with the increasing number of intelligent devices used in daily life and work, the importance of the intelligent devices is also higher and higher, and the safety of the intelligent devices is also increasingly valued by people. Many devices are operated by only a person with authority, and identity identification is needed.
Conventional intelligent terminal authentication methods typically rely on heavyweight hardware and user interfaces that are not suitable for wearable devices; for example, a touch screen is generally required for a password keyboard, a user needs to memorize, the password keyboard is easy to snoop and leak, and the password keyboard has unlocking functions such as fingerprint, face recognition or voice recognition, so that safety protection of the intelligent device during unlocking is difficult to be effectively ensured in daily life.
Disclosure of Invention
The invention aims to solve the problem that safety protection is difficult to be guaranteed when an intelligent device is unlocked daily, and provides a method and a system for acquiring hand actions for identity recognition by an intelligent watch.
The invention adopts the following technical means for solving the technical problems:
the invention provides a method for identifying identity by collecting hand actions of an intelligent watch, which comprises the following steps:
capturing the wearing state of a user, acquiring fitting data of the wrist bones of the user based on the wearing state, and acquiring action information when the hand of the user is transformed by applying a preset gyroscope sensor according to the fitting data;
Judging whether the action information is suitable for preset identification conditions or not;
if yes, outputting low-frequency current to the user based on a preset direction, acquiring signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user;
performing differential comparison according to the weight information and the pre-recorded weight conditions, confirming that the user meets the identity recognition conditions, and capturing dynamic transformation data generated correspondingly to the action information;
judging whether the dynamic transformation data accords with preset content or not;
if yes, opening corresponding function authorities to the user based on user data of a preset identity.
Further, the step of outputting a low-frequency current to the user based on a preset direction, acquiring a signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user includes:
Extracting at least two or more signal reflux based on a preset interval value of the low-frequency current;
measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to obtain interval values of the bioelectrical impedance values;
comparing the interval value with a preset electrical impedance value table to generate a fat mass interval value and a muscle tissue interval value of the user;
judging whether the fat mass interval value is larger than the muscle tissue interval value;
if yes, after the identification is finished, the difference ratio of the fat mass interval value and the muscle tissue interval value is displayed in a preset display screen;
if not, generating a weight interval value corresponding to the user based on the fat mass interval value.
Further, the step of comparing the difference between the weight information and the pre-recorded weight condition to confirm that the user meets the identification condition and capturing the dynamic transformation data generated correspondingly by the action information includes:
based on the gyroscope sensor to collect the motion information, extracting corresponding dynamic data in the motion information, and applying a segmentation algorithm to identify the dynamic data to obtain at least one or more dynamic data fragments;
After the dynamic data segments are subjected to preliminary recombination, carrying out iterative reconstruction on the dynamic data segments based on an image reconstruction algorithm until the similarity of the dynamic data segments reaches a preset iterative reconstruction result, and generating dynamic recombination segments corresponding to the iterative reconstruction result;
and carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
Further, the step of opening the corresponding function authority to the current user based on the user data of the preset identity includes:
acquiring wrist fit degree and weight data of the user, and identifying current identity data of the user according to the wrist fit degree and the weight data;
judging whether the current identity data has preset functional rights or not;
if yes, providing the specific authority corresponding to the preset identity for the user in current use.
Further, the step of determining whether the dynamic transformation data accords with preset content includes:
detecting at least one or more stress data corresponding to the dynamic transformation data based on a preset pressure sensor, wherein the stress data comprises a stress direction and stress times;
Judging whether the stress data is matched with preset identification content or not;
if yes, the user is endowed with conventional function authorities, wherein the conventional function authorities comprise monitoring heart rate, step number and sleep.
Further, capturing the wearing state of the user, collecting fitting data of the wrist bones of the user based on the wearing state, and before the step of collecting motion information when the hand of the user is transformed by applying a preset gyroscope sensor according to the fitting data, comprising:
identifying image data of the user wrist bones by adopting a preset scanner, and acquiring joint azimuth information of the user wrist bones based on the image data;
judging whether the joint azimuth information has deviation with preset azimuth data or not, wherein the preset azimuth data comprises the height of a joint horizontal line;
if so, acquiring fitting data of the wrist bones of the user according to the joint azimuth information, and setting the self-adaptive telescopic distance matched with the user according to the fitting data so as to capture the wearing state of the user.
Further, before the step of determining whether the action information is adapted to the preset recognition condition, the method includes:
Acquiring at least one or more fitting information of the hand of the user according to a force application direction based on the force application direction which is obtained by the gyroscope sensor when the hand of the user is transformed, wherein the fitting information is specifically fitting information which is tightly fitted on one side of the arm of the user when the user wears the intelligent watch;
judging whether the fitting information is matched with preset fitting times or not;
if yes, running a preset identity recognition function, and comparing the arrangement information of the identity recognition function with the laminating information.
The invention also provides a system for carrying out identity recognition by collecting hand actions by the intelligent watch, which comprises:
the device comprises a capturing module, a display module and a display module, wherein the capturing module is used for capturing the wearing state of a user, acquiring fitting data of the wrist bones of the user based on the wearing state, and acquiring action information when the hands of the user are transformed by applying a preset gyroscope sensor according to the fitting data;
the judging module is used for judging whether the action information is matched with a preset identification condition or not;
the execution module is used for outputting low-frequency current to the user based on a preset direction, acquiring signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user;
The comparison module is used for carrying out difference comparison according to the weight information and the pre-recorded weight condition, confirming that the user meets the identification condition and capturing dynamic transformation data generated correspondingly to the action information;
the second judging module is used for judging whether the dynamic transformation data accords with preset content or not;
and the second execution module is used for opening corresponding function authorities to the user based on user data of a preset identity if the user data of the preset identity are the same.
Further, the execution module further includes:
an extracting unit, configured to extract at least two or more signal reflows based on a preset interval value of the low-frequency current;
the acquisition unit is used for measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to acquire interval values of the bioelectrical impedance values;
the generation unit is used for comparing the interval value with a preset electrical impedance value table to generate a fat volume interval value of the user and a muscle tissue interval value;
a judging unit for judging whether the fat mass interval value is greater than the muscle tissue interval value;
The execution unit is used for displaying the difference ratio of the fat volume interval value and the muscle tissue interval value in a preset display screen after the identification is finished if the identification is finished;
and the second execution unit is used for generating a weight interval value corresponding to the user based on the fat mass interval value if not.
Further, the comparison module further includes:
the identification unit is used for acquiring the action information based on the gyroscope sensor, extracting corresponding dynamic data in the action information, and identifying the dynamic data by applying a segmentation algorithm to obtain at least one or more dynamic data fragments;
the reorganization unit is used for carrying out preliminary reorganization on the dynamic data fragments, and then carrying out iterative reconstruction on the dynamic data fragments based on an image reconstruction algorithm until the similarity of the dynamic data fragments reaches a preset iterative reconstruction result, so as to generate dynamic reorganization fragments corresponding to the iterative reconstruction result;
and the second generation unit is used for carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
The invention provides a method and a system for identifying identity by collecting hand actions of an intelligent watch, which have the following beneficial effects:
according to the invention, after the user wears the intelligent watch, the user carries out hand movements in the wearing process to identify the hand dynamic transformation data executed by the user, the process of identity identification can be completed after the comparison can be in accordance with the preset unlocking content, and different watch function authorities are provided for different users by acquiring the identity data of the user currently wearing the intelligent watch, so that the unlocking functions such as fingerprint, face recognition or voice recognition are effectively prevented from being attacked by illegal molecules when the intelligent watch is unlocked in the daily use process, and the effective safety protection can be ensured when the user uses the intelligent watch to unlock.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for acquiring hand motion for identity recognition by a smart watch according to the present invention;
fig. 2 is a block diagram illustrating an embodiment of a system for collecting hand movements for identity recognition by a smart watch according to the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present invention, as the achievement, functional features, and advantages of the present invention are further described with reference to the embodiments, with reference to the accompanying drawings.
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, 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.
Referring to fig. 1, a method for identifying an identity by collecting hand actions of a smart watch according to an embodiment of the present invention includes:
s1, capturing a wearing state of a user, acquiring fitting data of wrist bones of the user based on the wearing state, and acquiring action information of the user when the hand is transformed by using a preset gyroscope sensor according to the fitting data;
s2: judging whether the action information is suitable for preset identification conditions or not;
s3: if yes, outputting low-frequency current to the user based on a preset direction, acquiring signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user;
S4: performing differential comparison according to the weight information and the pre-recorded weight conditions, confirming that the user meets the identity recognition conditions, and capturing dynamic transformation data generated correspondingly to the action information;
s5: judging whether the dynamic transformation data accords with preset content or not;
s6: if yes, opening corresponding function authorities to the user based on user data of a preset identity.
In this embodiment, the system captures the wearing state of the user currently wearing the smart watch, collects the fitting data of the wrist bones of the user based on the wearing state, collects the corresponding generated motion information when the hand of the user performs motion conversion according to the fitting data, and then judges whether the motion information is matched with preset identification conditions or not so as to execute corresponding different steps; for example, when the system recognizes that the user wears the smart watch and the smart watch is attached to the hand of the user, the system acquires the action information of the user as one time of lifting the hand, and the preset recognition condition is that the hand is lifted twice, at this time, the system can determine that the action information of the user cannot adapt to the preset recognition condition, cannot enable the identity recognition function set by the smart watch, and cannot use other functions of the smart watch; for example, when the system recognizes that the user wears the smart watch and the smart watch is attached to the hand of the user, the system acquires the action information of the user as the lower arm twice, and the preset recognition condition is that the lower arm is one time, that is, the system determines that the action information of the user can adapt to the preset recognition condition, the smart watch enables the identity recognition function, the system outputs a low-frequency current to the hand of the user based on the preset output direction, acquires the signal reflux of the body return of the user according to the BIA bioelectrical impedance measurement method, acquires the first resistance data of the fat in the body of the user and the second resistance data of the muscle tissue according to the signal reflux, simultaneously uploads the first resistance data and the second resistance data to a database preset in the system, analyzes the first resistance data and the second resistance data through the database, and correspondingly generates the weight information of the user (because the weight information is generated by combining the fat resistance percentage and the muscle tissue percentage, when the fat resistance percentage is higher, the weight percentage is lighter when the body weight percentage is higher, and the weight percentage is 50% and the weight percentage is 1kg when the weight percentage is higher and the weight percentage is 1kg and the weight percentage is correspondingly 1kg and the weight percentage is 1kg and the standard and the weight percentage is increased; the system compares the difference between the weight information of the user and the weight condition recorded in advance to confirm whether the current user meets the identity recognition condition, captures the action information of the next step after the user finishes testing the weight to acquire dynamic transformation data corresponding to the action information, and judges whether the dynamic transformation data accords with preset post recognition content to execute corresponding different steps; for example, after the weight of the user is tested, the system captures that the dynamic transformation data carried out by the user swings anticlockwise for two circles, and the preset post-identification content swings clockwise for two circles, at this time, the system can judge that the dynamic transformation data carried out by the current user does not accord with the preset post-identification content, and at this time, the system can only provide the user with the authority to view the weight; for example, after the weight of the user is tested, the system captures that the dynamic conversion data carried out by the user swings three circles clockwise, and the preset rear-end identification content swings two circles clockwise, at this time, the system judges that the dynamic conversion data carried out by the current user can accord with the preset rear-end identification content, at this time, the system can identify whether the identity data of the user matches with the identity information recorded in advance by the system according to the specific fitting degree of the wrist and the intelligent watch and the weight information of the user when the current user wears the intelligent watch, so as to provide corresponding open function authority for the current user; for example, the system knows that the identity of the current user belongs to the setting personnel of the smart watch by identifying the wrist fit degree and the weight information of the current user, namely, the system can provide all applicable function authorities for the current user at the moment, such as restoring factory settings of the smart watch; for example, the system knows that the identity of the current user belongs to the conventional user of the smart watch by identifying the wrist fit and weight information of the current user, that is, the system can provide the current user with the function authority of the conventional application, such as heart rate data of the test user, and the like.
In this embodiment, the step S3 of outputting a low-frequency current to the user based on a preset direction, acquiring a signal reflux of the low-frequency current return, collecting first resistance data of fat of the user and second resistance data of muscle tissue according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user includes:
s31: extracting at least two or more signal reflux based on a preset interval value of the low-frequency current;
s32: measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to obtain interval values of the bioelectrical impedance values;
s33: comparing the interval value with a preset electrical impedance value table to generate a fat mass interval value and a muscle tissue interval value of the user;
s34: judging whether the fat mass interval value is larger than the muscle tissue interval value;
s35: if yes, after the identification is finished, the difference ratio of the fat mass interval value and the muscle tissue interval value is displayed in a preset display screen;
S36: if not, generating a weight interval value corresponding to the user based on the fat mass interval value.
In this embodiment, the system extracts at least two or more signal reflux belonging to the body reflux of the user based on a preset current interval value of low-frequency current of 30kHz-300kHz, at least including a minimum value of 30kHz and 300kHz, and can measure at least two or more bioelectrical impedance values of the user according to the signal reflux, sequentially arrange the bioelectrical impedance values from less to most to obtain interval values of bioelectrical impedance values, compare the interval values with a preset impedance value table to generate a fat volume interval value and a muscle tissue interval value of the user (the smart watch sends low-frequency current through an electrode plate to form a closed loop with a human body, and the impedance value can be obtained by the principle that the muscle is easy to conduct and the fat is not conductive, when the fat volume interval value is higher, the impedance value is correspondingly higher, and when the fat volume interval value is lower, the corresponding value is also lower), and judges whether the fat volume interval value is greater than the muscle tissue interval value or not to execute corresponding different steps; for example, when the fat amount interval value is greater than the muscle tissue interval value, the system simultaneously presents the fat amount interval value and the muscle tissue interval value in the display screen of the smart watch after the identity of the user is identified, so that the current user can refer to the self health condition; for example, when the fat mass interval value is not greater than the muscle tissue interval value, the system correspondingly generates a weight interval value of the current user into the display screen of the smart watch based on the fat mass interval values.
In this embodiment, the step S4 of comparing the difference between the weight information and the pre-recorded weight condition to confirm that the user satisfies the identification condition and capturing the dynamic transformation data generated corresponding to the motion information includes:
s41: based on the gyroscope sensor to collect the motion information, extracting corresponding dynamic data in the motion information, and applying a segmentation algorithm to identify the dynamic data to obtain at least one or more dynamic data fragments;
s42: after the dynamic data segments are subjected to preliminary recombination, carrying out iterative reconstruction on the dynamic data segments based on an image reconstruction algorithm until the similarity of the dynamic data segments reaches a preset iterative reconstruction result, and generating dynamic recombination segments corresponding to the iterative reconstruction result;
s43: and carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
In this embodiment, after the gyroscope sensor provided in the smart watch collects motion information of a user, corresponding dynamic data (for example, the gyroscope sensor may present dynamic data with an upward force when the hand is lifted, for example, the gyroscope sensor may present dynamic data with a downward force when the hand is lifted) in the motion information are extracted, a preset segmentation algorithm is applied to identify the dynamic data, so as to reduce the problem of non-uniformity of motion images in the identification process, that is, at least one or more dynamic data segments existing in the motion information of the user may be identified, the dynamic data segments may be obtained, after conventional image recombination is performed on the dynamic data segments, complete dynamic data of the user may be generated, in order to reconstruct the dynamic data closest to the motion information of the user, based on a preset image reconstruction algorithm, a similarity percentage result compared with the motion information of the user may be generated in the iterative reconstruction process, after iterative reconstruction is repeated, when the similarity of the dynamic data segments reaches 80% or more, the preset iterative reconstruction result may be reached, that is, the system may determine that the reconstruction result may correspond to the dynamic data of the user, and then the system may calculate the dynamic data as the dynamic data corresponding to the motion track of the user.
It should be noted that, the above-mentioned segmentation algorithm does not depend on the static state in the course of action, but detects the segmentation point by means of the drastic change of direction in the course of motion, so there is no need to limit the motion; whereas trajectory calculation belongs to the prior art and is therefore not explained here.
In this embodiment, the step S6 of opening the corresponding function right to the current user based on the user data of the preset identity includes:
s61: acquiring wrist fit degree and weight data of the user, and identifying current identity data of the user according to the wrist fit degree and the weight data;
s62: judging whether the current identity data has preset functional rights or not;
s63: if yes, providing the specific authority corresponding to the preset identity for the user in current use.
In this embodiment, after acquiring the wrist fitness of the current user and acquiring the thickness information of the wrist of the user, the system searches a preset database for corresponding thickness information and weight data according to the thickness information and weight data of the user, if the database has the corresponding thickness information and weight data, that is, the system correspondingly has the recorded identity information belonging to the user, and meanwhile, the system judges whether the identity information of the current user has the preset function authority so as to execute corresponding different steps; for example, the system acquires that the current identity data belongs to a setting person of the smart watch, that is, the system can provide all applicable function rights for the current user at the moment, such as restoring factory settings of the smart watch; for example, the system knows that the identity of the current user belongs to the conventional user of the smart watch by identifying the wrist fit and weight information of the current user, that is, the system can provide the current user with the function authority of the conventional application, such as heart rate data of the test user, and the like.
In this embodiment, the step S5 of determining whether the dynamic transformation data accords with the preset content includes:
s51: detecting at least one or more stress data corresponding to the dynamic transformation data based on a preset pressure sensor, wherein the stress data comprises a stress direction and stress times;
s52: judging whether the stress data is matched with preset identification content or not;
s53: if yes, the user is endowed with conventional function authorities, wherein the conventional function authorities comprise monitoring heart rate, step number and sleep.
In this embodiment, the system executes at least one or more stress data (including stress direction and stress times) corresponding to dynamic transformation data generated by action information when detecting that the user wears the smart watch based on a preset pressure sensor, and determines whether the stress data matches preset post-identification content, so as to execute corresponding different steps; for example, the system detects that the dynamic transformation data of the user is stressed leftwards twice through the pressure sensor, and the preset rear-mounted identification content is stressed downwards once after being stressed upwards once, at this time, the system can judge that the stress data of the user cannot match with the preset identification content, other application rights of the intelligent watch cannot be provided for the user, and only the weight data of the user can be displayed; for example, the system detects that the dynamic transformation data of the user is stressed right once and then stressed left twice through the pressure sensor, and the preset post-identification content is stressed right once and then stressed left twice, at this time, the system can judge that the stressed data of the user can be matched with the preset identification content, and the system can endow the user with the conventional functional authority in the intelligent watch, including monitoring the heart rate of the user, the step number of the user movement, the sleeping time of the user and the like.
In this embodiment, capturing a wearing state of a user, collecting fitting data of a wrist bone of the user based on the wearing state, and before step S1 of collecting motion information when the hand of the user is transformed by applying a preset gyroscope sensor according to the fitting data, the method includes:
s101: identifying image data of the user wrist bones by adopting a preset scanner, and acquiring joint azimuth information of the user wrist bones based on the image data;
s102: judging whether the joint azimuth information has deviation with preset azimuth data or not, wherein the preset azimuth data comprises the height of a joint horizontal line;
s103: if so, acquiring fitting data of the wrist bones of the user according to the joint azimuth information, and setting the self-adaptive telescopic distance matched with the user according to the fitting data so as to capture the wearing state of the user.
In this embodiment, the system performs infrared scanning on the wrist of the user by using a preset scanner, identifies and obtains image data of the wrist bones of the user, obtains the current joint azimuth information of the hand of the user according to the image data, and then judges whether the joint azimuth information has deviation (including the height of the joint horizontal line) from preset azimuth data or not so as to execute corresponding different steps; for example, the system acquires that the joint azimuth information of the current user is dislocated, the overall joint is higher, namely the system can judge that the joint azimuth information is deviated from preset azimuth data, the system can acquire laminating data of the wrist bones of the user according to the joint azimuth information, and the self-adaptive telescopic distance matched with the user is set according to the laminating data (for example, the joint dislocation of the user is overlarge, and the intelligent watch can extend a watch chain) so as to capture the wearing state of the user; for example, the system acquires the joint azimuth information of the current user, no dislocation occurs, the whole joint is normal, namely, the system can judge that the joint azimuth information is not deviated from preset azimuth data at the moment, and the system does not need to adjust the self-adaptive telescopic distance of the intelligent watch at the moment.
In this embodiment, before step S2 of determining whether the action information is adapted to a preset recognition condition, the method includes:
s201: acquiring at least one or more fitting information of the hand of the user according to a force application direction based on the force application direction which is obtained by the gyroscope sensor when the hand of the user is transformed, wherein the fitting information is specifically fitting information which is tightly fitted on one side of the arm of the user when the user wears the intelligent watch;
s202: judging whether the fitting information is matched with preset fitting times or not;
s203: if yes, running a preset identity recognition function, and comparing the arrangement information of the identity recognition function with the laminating information.
In this embodiment, the system acquires, based on a gyroscope sensor provided in advance, a force application direction used when the user's hand performs motion conversion, and acquires at least one or more fitting information of the user's hand with the smart watch when the user's hand performs motion conversion according to the force application directions, and determines whether the fitting information matches a preset fitting number; for example, the system collects the fitting information of the user: the watch chain is respectively attached to the watch chain of the intelligent watch once up, down, left and right; the preset attaching times are four times, the system can judge that the attaching information can be matched with the preset attaching times, the system can operate a preset identity recognition function, and the arrangement information of the identity recognition function is compared with the attaching information; if the fitting condition set in the identity recognition function arrangement information of the intelligent watch is that the intelligent watch is continuously fitted three times in the right direction, when the hand of the user performs motion transformation, the force application direction can be continuously attached to the right direction for three times, and the front identification part of the intelligent watch can be completed.
Referring to fig. 2, a system for identifying a hand by capturing motion of a smart watch according to an embodiment of the present invention includes:
the capturing module 10 is configured to capture a wearing state of a user, collect fitting data of a wrist bone of the user based on the wearing state, and collect motion information of the user when the hand is transformed by applying a preset gyroscope sensor according to the fitting data;
a judging module 20, configured to judge whether the action information is adapted to a preset recognition condition;
the execution module 30 is configured to output a low-frequency current to the user based on a preset direction if the user is in the preset direction, acquire a signal reflux of the low-frequency current reflux, acquire first resistance data of the user fat and second resistance data of muscle tissues according to the signal reflux, and upload the first resistance data and the second resistance data to a preset database to generate weight information corresponding to the user;
a comparison module 40, configured to compare the weight information with the pre-recorded weight condition differently, confirm that the user meets the identification condition, and capture dynamic transformation data generated corresponding to the motion information;
a second judging module 50, configured to judge whether the dynamic transformation data accords with a preset content;
And the second execution module 60 is configured to, if yes, open a corresponding function right to the user based on user data of a preset identity.
In this embodiment, the capturing module 10 captures the wearing state of the user currently wearing the smart watch, collects the fitting data of the wrist bones of the user based on the wearing state, and collects the corresponding generated motion information when the hand of the user performs motion conversion according to the fitting data, and then the judging module 20 judges whether the motion information is suitable for the preset identification conditions to execute the corresponding different steps; for example, when the system recognizes that the user wears the smart watch and the smart watch is attached to the hand of the user, the system acquires the action information of the user as one time of lifting the hand, and the preset recognition condition is that the hand is lifted twice, at this time, the system can determine that the action information of the user cannot adapt to the preset recognition condition, cannot enable the identity recognition function set by the smart watch, and cannot use other functions of the smart watch; for example, when the system recognizes that the user wears the smart watch and the smart watch is attached to the hand of the user, the system acquires the action information of the user as the lower arm twice, and the preset recognition condition is that the lower arm is one time, that is, the execution module 30 determines that the action information of the user can adapt to the preset recognition condition, the smart watch enables the identity recognition function, the system outputs a low-frequency current to the hand of the user based on the preset output direction, acquires the signal reflux of the body return of the user according to the BIA bioelectrical impedance measurement method, acquires the first resistance data of the fat in the body of the user and the second resistance data of the muscle tissue according to the signal reflux, and simultaneously uploads the first resistance data and the second resistance data to a database preset in the system, and correspondingly generates the weight information of the user according to the percentage result obtained by analyzing the first resistance data and the second resistance data through the database (because the weight information is generated by combining the fat resistance percentage and the muscle tissue percentage, when the fat percentage is high, the weight is lighter when the fat percentage is high, and the weight percentage of the opposite muscle tissue percentage is more than 50%, and the weight percentage is correspondingly 1% when the weight is 1kg and the weight is 1% when the two is 1kg of the standard, and the weight is 1% and the weight is 1kg and the weight is increased when the two percentage is 1kg and the standard); the comparison module 40 performs differential comparison according to the weight information of the user and the weight condition recorded in advance to determine whether the current user meets the identification condition, and captures the action information of the next step after the user finishes testing the weight to obtain dynamic transformation data corresponding to the action information, and the second judgment module 50 judges whether the dynamic transformation data accords with preset post identification content to execute corresponding different steps; for example, after the weight of the user is tested, the system captures that the dynamic transformation data carried out by the user swings anticlockwise for two circles, and the preset post-identification content swings clockwise for two circles, at this time, the system can judge that the dynamic transformation data carried out by the current user does not accord with the preset post-identification content, and at this time, the system can only provide the user with the authority to view the weight; for example, after the weight of the user is tested, the system captures that the dynamic conversion data carried out by the user swings three circles clockwise, and the preset rear-end identification content swings two circles clockwise, at this time, the system judges that the dynamic conversion data carried out by the current user can accord with the preset rear-end identification content, at this time, the system can identify whether the identity data of the user matches with the identity information recorded in advance by the system according to the specific fitting degree of the wrist and the intelligent watch and the weight information of the user when the current user wears the intelligent watch, so as to provide corresponding open function authority for the current user; for example, the system recognizes that the identity of the current user belongs to the setting personnel of the smart watch by identifying the wrist fit and the weight information of the current user, that is, the second execution module 60 provides all applicable function rights for the current user at this time, for example, restoring factory settings of the smart watch; for example, the system knows that the identity of the current user belongs to the conventional user of the smart watch by identifying the wrist fit and weight information of the current user, that is, the system can provide the current user with the function authority of the conventional application, such as heart rate data of the test user, and the like.
In this embodiment, the execution module further includes:
an extracting unit, configured to extract at least two or more signal reflows based on a preset interval value of the low-frequency current;
the acquisition unit is used for measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to acquire interval values of the bioelectrical impedance values;
the generation unit is used for comparing the interval value with a preset electrical impedance value table to generate a fat volume interval value of the user and a muscle tissue interval value;
a judging unit for judging whether the fat mass interval value is greater than the muscle tissue interval value;
the execution unit is used for displaying the difference ratio of the fat volume interval value and the muscle tissue interval value in a preset display screen after the identification is finished if the identification is finished;
and the second execution unit is used for generating a weight interval value corresponding to the user based on the fat mass interval value if not.
In this embodiment, the system extracts at least two or more signal reflux belonging to the body reflux of the user based on a preset current interval value of low-frequency current of 30kHz-300kHz, at least including a minimum value of 30kHz and 300kHz, and can measure at least two or more bioelectrical impedance values of the user according to the signal reflux, sequentially arrange the bioelectrical impedance values from less to most to obtain interval values of bioelectrical impedance values, compare the interval values with a preset impedance value table to generate a fat volume interval value and a muscle tissue interval value of the user (the smart watch sends low-frequency current through an electrode plate to form a closed loop with a human body, and the impedance value can be obtained by the principle that the muscle is easy to conduct and the fat is not conductive, when the fat volume interval value is higher, the impedance value is correspondingly higher, and when the fat volume interval value is lower, the corresponding value is also lower), and judges whether the fat volume interval value is greater than the muscle tissue interval value or not to execute corresponding different steps; for example, when the fat amount interval value is greater than the muscle tissue interval value, the system simultaneously presents the fat amount interval value and the muscle tissue interval value in the display screen of the smart watch after the identity of the user is identified, so that the current user can refer to the self health condition; for example, when the fat mass interval value is not greater than the muscle tissue interval value, the system correspondingly generates a weight interval value of the current user into the display screen of the smart watch based on the fat mass interval values.
In this embodiment, the comparison module further includes:
the identification unit is used for acquiring the action information based on the gyroscope sensor, extracting corresponding dynamic data in the action information, and identifying the dynamic data by applying a segmentation algorithm to obtain at least one or more dynamic data fragments;
the reorganization unit is used for carrying out preliminary reorganization on the dynamic data fragments, and then carrying out iterative reconstruction on the dynamic data fragments based on an image reconstruction algorithm until the similarity of the dynamic data fragments reaches a preset iterative reconstruction result, so as to generate dynamic reorganization fragments corresponding to the iterative reconstruction result;
and the second generation unit is used for carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
In this embodiment, after the gyroscope sensor provided in the smart watch collects motion information of a user, corresponding dynamic data (for example, the gyroscope sensor may present dynamic data with an upward force when the hand is lifted, for example, the gyroscope sensor may present dynamic data with a downward force when the hand is lifted) in the motion information are extracted, a preset segmentation algorithm is applied to identify the dynamic data, so as to reduce the problem of non-uniformity of motion images in the identification process, that is, at least one or more dynamic data segments existing in the motion information of the user may be identified, the dynamic data segments may be obtained, after conventional image recombination is performed on the dynamic data segments, complete dynamic data of the user may be generated, in order to reconstruct the dynamic data closest to the motion information of the user, based on a preset image reconstruction algorithm, a similarity percentage result compared with the motion information of the user may be generated in the iterative reconstruction process, after iterative reconstruction is repeated, when the similarity of the dynamic data segments reaches 80% or more, the preset iterative reconstruction result may be reached, that is, the system may determine that the reconstruction result may correspond to the dynamic data of the user, and then the system may calculate the dynamic data as the dynamic data corresponding to the motion track of the user.
It should be noted that, the above-mentioned segmentation algorithm does not depend on the static state in the course of action, but detects the segmentation point by means of the drastic change of direction in the course of motion, so there is no need to limit the motion; whereas trajectory calculation belongs to the prior art and is therefore not explained here.
In this embodiment, the second execution module further includes:
the second acquisition unit is used for acquiring wrist fitting degree and weight data of the user and identifying current identity data of the user according to the wrist fitting degree and the weight data;
the second judging unit is used for judging whether the current identity data has preset functional permission or not;
and the third execution unit is used for providing the specific authority corresponding to the preset identity for the user in current use if the user is in the current use.
In this embodiment, after acquiring the wrist fitness of the current user and acquiring the thickness information of the wrist of the user, the system searches a preset database for corresponding thickness information and weight data according to the thickness information and weight data of the user, if the database has the corresponding thickness information and weight data, that is, the system correspondingly has the recorded identity information belonging to the user, and meanwhile, the system judges whether the identity information of the current user has the preset function authority so as to execute corresponding different steps; for example, the system acquires that the current identity data belongs to a setting person of the smart watch, that is, the system can provide all applicable function rights for the current user at the moment, such as restoring factory settings of the smart watch; for example, the system knows that the identity of the current user belongs to the conventional user of the smart watch by identifying the wrist fit and weight information of the current user, that is, the system can provide the current user with the function authority of the conventional application, such as heart rate data of the test user, and the like.
In this embodiment, the second judging module further includes:
the detection unit is used for detecting at least one or more times of stress data corresponding to the dynamic transformation data based on a preset pressure sensor, wherein the stress data comprises a stress direction and stress times;
the third judging unit is used for judging whether the stress data is matched with preset identification content or not;
and the fourth execution unit is used for giving the user conventional function permission if yes, wherein the conventional function permission comprises monitoring of heart rate, step number and sleep.
In this embodiment, the system executes at least one or more stress data (including stress direction and stress times) corresponding to dynamic transformation data generated by action information when detecting that the user wears the smart watch based on a preset pressure sensor, and determines whether the stress data matches preset post-identification content, so as to execute corresponding different steps; for example, the system detects that the dynamic transformation data of the user is stressed leftwards twice through the pressure sensor, and the preset rear-mounted identification content is stressed downwards once after being stressed upwards once, at this time, the system can judge that the stress data of the user cannot match with the preset identification content, other application rights of the intelligent watch cannot be provided for the user, and only the weight data of the user can be displayed; for example, the system detects that the dynamic transformation data of the user is stressed right once and then stressed left twice through the pressure sensor, and the preset post-identification content is stressed right once and then stressed left twice, at this time, the system can judge that the stressed data of the user can be matched with the preset identification content, and the system can endow the user with the conventional functional authority in the intelligent watch, including monitoring the heart rate of the user, the step number of the user movement, the sleeping time of the user and the like.
In this embodiment, further comprising:
the identification module is used for identifying the image data of the user wrist bones by adopting a preset scanner, and acquiring the joint azimuth information of the user wrist bones based on the image data;
the third judging module is used for judging whether the joint azimuth information has deviation with preset azimuth data or not, wherein the preset azimuth data comprises the height of a joint horizontal line;
and the third execution module is used for acquiring the fitting data of the wrist bones of the user according to the joint azimuth information if the joint azimuth information is received, and setting the adaptive telescopic distance matched with the user according to the fitting data so as to capture the wearing state of the user.
In this embodiment, the system performs infrared scanning on the wrist of the user by using a preset scanner, identifies and obtains image data of the wrist bones of the user, obtains the current joint azimuth information of the hand of the user according to the image data, and then judges whether the joint azimuth information has deviation (including the height of the joint horizontal line) from preset azimuth data or not so as to execute corresponding different steps; for example, the system acquires that the joint azimuth information of the current user is dislocated, the overall joint is higher, namely the system can judge that the joint azimuth information is deviated from preset azimuth data, the system can acquire laminating data of the wrist bones of the user according to the joint azimuth information, and the self-adaptive telescopic distance matched with the user is set according to the laminating data (for example, the joint dislocation of the user is overlarge, and the intelligent watch can extend a watch chain) so as to capture the wearing state of the user; for example, the system acquires the joint azimuth information of the current user, no dislocation occurs, the whole joint is normal, namely, the system can judge that the joint azimuth information is not deviated from preset azimuth data at the moment, and the system does not need to adjust the self-adaptive telescopic distance of the intelligent watch at the moment.
In this embodiment, further comprising:
the acquisition module is used for acquiring a force application direction which is used for changing the hand of the user based on the gyroscope sensor, and acquiring at least one or more fitting information of the hand of the user according to the force application direction, wherein the fitting information is specifically fitting information which is tightly attached to one side of an arm of the user when the user wears the intelligent watch;
a fourth judging module, configured to judge whether the bonding information matches a preset bonding number;
and the fourth execution module is used for running a preset identity recognition function if the identification information is the identification information, and comparing the arrangement information of the identity recognition function with the fitting information.
In this embodiment, the system acquires, based on a gyroscope sensor provided in advance, a force application direction used when the user's hand performs motion conversion, and acquires at least one or more fitting information of the user's hand with the smart watch when the user's hand performs motion conversion according to the force application directions, and determines whether the fitting information matches a preset fitting number; for example, the system collects the fitting information of the user: the watch chain is respectively attached to the watch chain of the intelligent watch once up, down, left and right; the preset attaching times are four times, the system can judge that the attaching information can be matched with the preset attaching times, the system can operate a preset identity recognition function, and the arrangement information of the identity recognition function is compared with the attaching information; if the fitting condition set in the identity recognition function arrangement information of the intelligent watch is that the intelligent watch is continuously fitted three times in the right direction, when the hand of the user performs motion transformation, the force application direction can be continuously attached to the right direction for three times, and the front identification part of the intelligent watch can be completed.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The method for identifying the identity by collecting the hand actions of the intelligent watch is characterized by comprising the following steps of:
capturing the wearing state of a user, acquiring fitting data of the wrist bones of the user based on the wearing state, and acquiring action information when the hand of the user is transformed by applying a preset gyroscope sensor according to the fitting data;
judging whether the action information is suitable for preset identification conditions or not;
if yes, outputting low-frequency current to the user based on a preset direction, acquiring signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user;
performing differential comparison according to the weight information and the pre-recorded weight conditions, confirming that the user meets the identity recognition conditions, and capturing dynamic transformation data generated correspondingly to the action information;
Judging whether the dynamic transformation data accords with preset content or not;
if yes, opening corresponding function authorities to the user based on user data of a preset identity.
2. The method for identifying the identity of the hand action collected by the smart watch according to claim 1, wherein the step of outputting a low-frequency current to the user based on a preset direction, obtaining a signal reflux of the low-frequency current return, collecting first resistance data of the user fat and second resistance data of muscle tissue according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user comprises the steps of:
extracting at least two or more signal reflux based on a preset interval value of the low-frequency current;
measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to obtain interval values of the bioelectrical impedance values;
comparing the interval value with a preset electrical impedance value table to generate a fat mass interval value and a muscle tissue interval value of the user;
Judging whether the fat mass interval value is larger than the muscle tissue interval value;
if yes, after the identification is finished, the difference ratio of the fat mass interval value and the muscle tissue interval value is displayed in a preset display screen;
if not, generating a weight interval value corresponding to the user based on the fat mass interval value.
3. The method for identifying the identity of the hand acquired by the smart watch according to claim 1, wherein the step of comparing the weight information with the pre-recorded weight condition to confirm that the user satisfies the identity identification condition and capturing the dynamic transformation data generated by the corresponding action information comprises the steps of:
based on the gyroscope sensor to collect the motion information, extracting corresponding dynamic data in the motion information, and applying a segmentation algorithm to identify the dynamic data to obtain at least one or more dynamic data fragments;
after the dynamic data segments are subjected to preliminary recombination, carrying out iterative reconstruction on the dynamic data segments based on an image reconstruction algorithm until the similarity of the dynamic data segments reaches a preset iterative reconstruction result, and generating dynamic recombination segments corresponding to the iterative reconstruction result;
And carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
4. The method for performing identity recognition by collecting hand actions by using a smart watch according to claim 1, wherein the step of opening corresponding function rights to the current user based on user data of a preset identity comprises:
acquiring wrist fit degree and weight data of the user, and identifying current identity data of the user according to the wrist fit degree and the weight data;
judging whether the current identity data has preset functional rights or not;
if yes, providing the specific authority corresponding to the preset identity for the user in current use.
5. The method for identifying an identity by capturing hand movements of a smart watch according to claim 1, wherein the step of determining whether the dynamically transformed data conforms to a preset content comprises:
detecting at least one or more stress data corresponding to the dynamic transformation data based on a preset pressure sensor, wherein the stress data comprises a stress direction and stress times;
Judging whether the stress data is matched with preset identification content or not;
if yes, the user is endowed with conventional function authorities, wherein the conventional function authorities comprise monitoring heart rate, step number and sleep.
6. The method for acquiring hand motions for identity recognition according to claim 1, wherein the step of capturing the wearing state of the user, acquiring the fitting data of the wrist bones of the user based on the wearing state, and acquiring the motion information of the hand of the user when the hand is transformed by using a preset gyroscope sensor according to the fitting data comprises the steps of:
identifying image data of the user wrist bones by adopting a preset scanner, and acquiring joint azimuth information of the user wrist bones based on the image data;
judging whether the joint azimuth information has deviation with preset azimuth data or not, wherein the preset azimuth data comprises the height of a joint horizontal line;
if so, acquiring fitting data of the wrist bones of the user according to the joint azimuth information, and setting the self-adaptive telescopic distance matched with the user according to the fitting data so as to capture the wearing state of the user.
7. The method for identifying an identity by collecting hand motions of a smart watch according to claim 1, wherein before the step of determining whether the motion information is adapted to a preset identification condition, the method comprises:
acquiring at least one or more fitting information of the hand of the user according to a force application direction based on the force application direction which is obtained by the gyroscope sensor when the hand of the user is transformed, wherein the fitting information is specifically fitting information which is tightly fitted on one side of the arm of the user when the user wears the intelligent watch;
judging whether the fitting information is matched with preset fitting times or not;
if yes, running a preset identity recognition function, and comparing the arrangement information of the identity recognition function with the laminating information.
8. System for intelligent wrist-watch gathers hand action and carries out identification, its characterized in that includes:
the device comprises a capturing module, a display module and a display module, wherein the capturing module is used for capturing the wearing state of a user, acquiring fitting data of the wrist bones of the user based on the wearing state, and acquiring action information when the hands of the user are transformed by applying a preset gyroscope sensor according to the fitting data;
the judging module is used for judging whether the action information is matched with a preset identification condition or not;
The execution module is used for outputting low-frequency current to the user based on a preset direction, acquiring signal reflux of the low-frequency current return, acquiring first resistance data of the fat of the user and second resistance data of muscle tissues according to the signal reflux, uploading the first resistance data and the second resistance data to a preset database, and generating weight information corresponding to the user;
the comparison module is used for carrying out difference comparison according to the weight information and the pre-recorded weight condition, confirming that the user meets the identification condition and capturing dynamic transformation data generated correspondingly to the action information;
the second judging module is used for judging whether the dynamic transformation data accords with preset content or not;
and the second execution module is used for opening corresponding function authorities to the user based on user data of a preset identity if the user data of the preset identity are the same.
9. The system for capturing hand motion for identification of a smart watch of claim 8, wherein the execution module further comprises:
an extracting unit, configured to extract at least two or more signal reflows based on a preset interval value of the low-frequency current;
The acquisition unit is used for measuring at least two or more bioelectrical impedance values of the user according to the signal reflux, and arranging the at least two or more bioelectrical impedance values to acquire interval values of the bioelectrical impedance values;
the generation unit is used for comparing the interval value with a preset electrical impedance value table to generate a fat volume interval value of the user and a muscle tissue interval value;
a judging unit for judging whether the fat mass interval value is greater than the muscle tissue interval value;
the execution unit is used for displaying the difference ratio of the fat volume interval value and the muscle tissue interval value in a preset display screen after the identification is finished if the identification is finished;
and the second execution unit is used for generating a weight interval value corresponding to the user based on the fat mass interval value if not.
10. The system for performing identity recognition by collecting hand motions of a smart watch according to claim 8, wherein the comparison module further comprises:
the identification unit is used for acquiring the action information based on the gyroscope sensor, extracting corresponding dynamic data in the action information, and identifying the dynamic data by applying a segmentation algorithm to obtain at least one or more dynamic data fragments;
The reorganization unit is used for carrying out preliminary reorganization on the dynamic data fragments, and then carrying out iterative reconstruction on the dynamic data fragments based on an image reconstruction algorithm until the similarity of the dynamic data fragments reaches a preset iterative reconstruction result, so as to generate dynamic reorganization fragments corresponding to the iterative reconstruction result;
and the second generation unit is used for carrying out track calculation on the dynamic reorganization fragments, generating a three-dimensional motion track corresponding to the dynamic reorganization fragments, and taking the three-dimensional motion track as dynamic transformation data of the user.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2852284Y (en) * | 2005-09-30 | 2006-12-27 | 东南亚物资有限公司 | A sports assistance system |
| CN105022471A (en) * | 2014-04-23 | 2015-11-04 | 王建勤 | Device and method for gesture recognition based on pressure sensor array |
| WO2016189358A1 (en) * | 2015-05-28 | 2016-12-01 | Continental Automotive Gmbh | Smart watch based micro-movement detection for vehicles |
| CN109117612A (en) * | 2018-07-03 | 2019-01-01 | 普联技术有限公司 | Personal identification method, device and the storage medium of smartwatch |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140085050A1 (en) * | 2012-09-25 | 2014-03-27 | Aliphcom | Validation of biometric identification used to authenticate identity of a user of wearable sensors |
| US11395628B2 (en) * | 2017-02-16 | 2022-07-26 | Samsung Electronics Co., Ltd. | Method of providing service based on biometric information and wearable electronic device |
-
2023
- 2023-04-14 CN CN202310397047.5A patent/CN116167035B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2852284Y (en) * | 2005-09-30 | 2006-12-27 | 东南亚物资有限公司 | A sports assistance system |
| CN105022471A (en) * | 2014-04-23 | 2015-11-04 | 王建勤 | Device and method for gesture recognition based on pressure sensor array |
| WO2016189358A1 (en) * | 2015-05-28 | 2016-12-01 | Continental Automotive Gmbh | Smart watch based micro-movement detection for vehicles |
| CN109117612A (en) * | 2018-07-03 | 2019-01-01 | 普联技术有限公司 | Personal identification method, device and the storage medium of smartwatch |
Non-Patent Citations (1)
| Title |
|---|
| 基于智能手表运动传感器的新型攻击及其防范;宋晨光;刘建伟;伍前红;关振宇;;通信学报(S1);全文 * |
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