CN103315744A - Hand tremor detection method - Google Patents
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Abstract
The invention discloses a hand tremor detection method. The hand tremor detection method is characterized in that hand tremor detection includes finger tremor detection, wrist tremor detection and arm tremor detection; the hand tremor detection is completed through a hand tremor detection system, and the hand tremor detection system comprises a hand tremor detection module which is composed of a handwriting input module, a handwritten data acquisition module, a handwritten data storage module and a handwritten data processing module. The hand tremor detection method includes the steps: firstly, executing hand tremor detection drawing activities through the handwriting input module, secondly, acquiring handwritten data generated from the hand tremor detection drawing activities executed by a detected person through the handwritten data acquisition module, and finally, performing hand tremor detection index calculation through the handwritten data processing module. The hand tremor detection method can achieve more comprehensive and meticulous quantitative hand tremor detection and is simple and feasible.
Description
Technical field
The present invention relates to the hand detection method of trembling, be used for the detection by quantitative of finger, wrist and arm tremor, with auxiliary clinical diagnosis, curative effect evaluation and the state of illness monitoring that trembles.
Background technology
Tremble is a kind of because involuntary rhythmicity that the alternately property contraction of antagonism muscle group causes, property wobbling action alternately are common in the diseases such as parkinson disease, senile tremor, essential tremor.Human upper limb is the multiple position of trembling, and trembles to make patient's fine movement obstacle occur, the daily routines such as impact is write, diet; cause the patient can't take care of oneself when serious; therefore, the accurate and sharp state of an illness of trembling is judged, to early diagnosis and the curative effect evaluation important in inhibiting that trembles.
At present, the clinical evaluation mode of trembling mostly is on the basis of questionnaire survey and tremor amplitude is marked according to estimating scale by specialist, and is closely related with doctor's clinical experience, inevitably brought subjective and fuzzy factor.The defective of tradition clinical evaluation mode so that objective, quantitative, effectively tremble the proposition of detection method become in the urgent need to.
The existing detection method of trembling is mainly finished based on special detection device, as adopt acceleration transducer to obtain the information of trembling in measured's motor process, perhaps dynamo-electric (the electromyography of collection surface, EMG) signal is used for trembling analysis, realized the trembling quantitative measurement of signal of these detection methods, but still there is limitation: need design different equipment or module based on the checkout gear of the equipment such as acceleration transducer to the detection of finger, wrist and arm tremor, the patient need wear checkout gear and carry out daily routines, uses obstacle large; For the instrumentation that the patient physiological signals of trembling detects, usually comparatively expensive, the patients ' psychological burden is larger in the testing process.
In order to tackle the problems referred to above, it is movable that some detection methods of trembling adopt with the closely-related drawing of daily life, gathers measured's draw data, calculate the hand metric of trembling, realizing that hand trembles on the basis of quantitative measurement, have simple and easy to do and characteristics noninvasive, for example:
(1) document " two statistical indicator detection by quantitative hand tremors of Freehandhand-drawing straight line, helical " (Zhou Zuwei, Wang Jian, Deng. two statistical indicator detection by quantitative hand tremors of Freehandhand-drawing straight line, helical. Chinese Clinical neuroscience .2002,10 (2): 175-177) adopt and to allow the patient that trembles describe the method for helix and straight line, make the curve number value of describing to obtain by image recognition, then statistical analysis obtains mean deviation and weighted average mean square deviation as the quantitative target of hand tremor.This detection method of trembling provides a kind of quantitative measurement mode of trembling, but owing to just the drawing result of static state is analyzed, the information of trembling that provides is limited.
(2) document " Spiral Analysis:A New Technique for Measuring Tremor With a Digitizing Tablet " (Seth L.Pullman.Spiral Analysis:A New Technique for Measuring Tremor With a Digitizing Tablet. Movement Disorders.1998,13 (3): 85-89) adopt digital handwriting plate to gather patient's Freehandhand-drawing helix, proposed the extracting method of patient's helix geometric properties and the computational methods of clinical order of severity evaluation index DOS (Degree of Severity) under the polar coordinate system, be used for the clinical state of an illness evaluation of parkinson disease and the effectiveness of the method has been carried out clinical verification.This detection method of trembling based on digital handwriting plate has realized the analysis to drawing font information and kinematics information, tremble and insufficient but only the kinesiology characteristics of trembling are analyzed for comprehensive sign, in the literary composition features such as pressure peak frequency have been carried out Primary Study, also only limit to the aspect of global characteristics, do not possess careful property.
Provide the tremble approach of quantitative measurement of hand based on the detection method of trembling of drawing activity, but owing to just the drawing result of static state is analyzed, or the kinesiology characteristics that show in the drawing course are analyzed, the information of trembling that provides is not comprehensive, the analysis of the Z-TEK point that trembles only is confined to the aspect of global characteristics, and the index that provides is the tolerance of chattering that the comprehensive function of hand each several part is produced, is unfavorable for pointing, the independent detection of wrist and arm tremor.
Simultaneously, owing to lacking the effective ways that fully healing is trembled, therapeutic treatment can only play certain mitigation to trembling of patient, therefore, need clinically therapeutic effect is followed the tracks of judgement, the simple and easy to do monitoring system of trembling will provide for the clinical treatment that trembles effective evaluation measures.
Summary of the invention
The present invention is for avoiding the existing problem of above-mentioned prior art, provides a kind of hand based on drawing activity detection method of trembling, to detecting respectively finger, wrist, arm tremor, so that the testing result of trembling is more accurate, careful, comprehensive.
The present invention is that the technical solution problem adopts following technical scheme:
The tremble characteristics of detection method of hand of the present invention are: described hand trembles to detect and comprises that tremble detections, wrist of finger tremble and detect and the arm tremor detection; Described hand trembles to detect by the hand detection system of trembling and finishes, the described hand detection system of trembling comprises the hand detection module that trembles, and the described hand detection module that trembles is comprised of handwriting input module, hand-written data acquisition module, hand-written data memory module and hand-written data processing module;
The described hand detection method of trembling is to carry out as follows:
A, carry out hand by the handwriting input module and tremble that to detect drawing movable:
Described handwriting input module comprises handwriting input plane and handwriting input pen;
Described hand tremble detect the drawing activity comprise for finger tremble the finger that detects tremble detect drawing movable, be used for the tremble wrist that detects of wrist and tremble that to detect drawing movable and be used for arm tremor that arm tremor detects to detect drawing movable;
The measured holds described handwriting input pen and carries out successively finger tremble and detect that drawing is movable, wrist is trembled and detect drawing activity and arm tremor and detect movable three hands of drawing and tremble that to detect drawing movable on described handwriting input plane, every hand trembled, and to detect drawing movable, the measured adopts respectively left hand and the right hand to draw n time, and n is not less than 2; The measured carries out hand and trembles and detect drawing when movable, will tremble to this hand and detect the drawing person's handwriting that the drawing activity produces and show in described handwriting input plane; The measured whenever executes hand and trembles and detect drawing when movable, and the hand that the handwriting input module need be carried out the next item down painting that detects the drawing activity that trembles is pointed out;
Described finger trembles and detects the drawing activity and be: the measured keeps wrist and arm motionless, with the described handwriting input pen of finger gripping drawing inclined straight line in the handwriting input plane, the inclination angle of the straight line of described inclination is produced by outer motion towards palm by measured's finger gripping handwriting input pen, what left-hand finger was trembled the movable drafting of detection drawing is the straight line that is tilted to the right, what right finger was trembled the movable drafting of detection drawing is the straight line that is tilted to the left, the length of the straight line that tilts depends on the motion amplitude of finger, and the measured keeps each finger to tremble detecting the straight length of the inclination that the drawing activity draws consistent with the inclination angle;
Described wrist is trembled and detected the drawing activity and be: the measured keeps finger and arm motionless, with the described handwriting input pen of finger gripping, rotate the drive handwriting input pen by wrist and in the handwriting input plane, draw camber line, the curvature of described camber line rotarily drives from inside to outside the handwriting input pen motion by measured's wrist and produces, the left hand wrist is trembled and is detected drawing movable what draw is camber line to the upper right side bending, right hand wrist is trembled and is detected drawing movable what draw is curve to the upper left side bending, the length of camber line depends on the rotation amplitude of wrist, and the arc length that the measured need keep each wrist to tremble detecting the drawing activity to draw as far as possible is consistent with curvature;
Described arm tremor detects the drawing activity: with square pre-rendered on the handwriting input plane as borderline region, the described foursquare length of side is 5-10cm, the measured keep the finger and wrist motionless, with the described handwriting input pen of finger gripping, drive by arm motion that handwriting input pen is drawn and the circle of described square inscribe in described borderline region;
B, hand-written data acquisition module gather the measured and carry out hand and tremble and detect the movable hand-written data that produces of drawing
Described hand-written data acquisition module comprises positional information Acquisition Circuit and force information sensor; The measured adopts left hand and the right hand to carry out successively n finger by the handwriting input module to tremble and detect that drawing is movable, n wrist trembled and detected drawing activity and the activity of n arm tremor detection drawing, described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled and detect the movable hand-written data that produces of drawing, and hand of the every execution of measured trembles and detects the drawing activity and just obtain one group of hand-written data;
Described hand-written data comprises positional information time series and force information time series; Described positional information detects the movable person's handwriting positional information that produces of drawing for the measured trembles by handwriting input module execution hand, the person's handwriting positional information adopts cartesian coordinate system to represent, the information acquisition circuit of described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and trembled to detect the movable person's handwriting positional information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the positional information time series of drawing activity; The force information sensor of described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled to detect the movable force information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the force information time series of drawing activity;
The qualification inspection of c, hand-written data
Described hand-written data acquisition module Real-time Collection measured carry out each hand tremble detect the movable hand-written data that produces of drawing after, this group hand-written data is carried out the qualification inspection, if by the qualification inspection, then should organize hand-written data and deposit the hand-written data memory module in, otherwise, this time hand trembles, and to detect the movable hand-written data that produces of drawing invalid, the hand-written data acquisition module returns information to the handwriting input module, the handwriting input module is sent early warning, and the measured re-executes this hand and trembles that to detect drawing movable;
Described qualification inspection refers to judge that the measured carries out hand and whether trembles the number of the number of the included positional information of positional information time series that detects one group of hand-written data that the drawing activity obtains and the included force information of force information time series greater than predefined threshold value T, T 〉=20, if, judge that then this group hand-written data is by the qualification inspection, otherwise, judge that this group hand-written data is not by the qualification inspection;
D, carry out hand by the hand-written data processing module and tremble and detect index and calculate
The hand-written data memory module sends to the hand-written data processing module with the hand-written data of storage, and described hand-written data processing module is calculated the measured by described hand-written data and used respectively left hand and the right hand to carry out every hand hand that detects drawing activity detection index of trembling of trembling; Carry out every hand the tremble desired value that detects index and right hand of the hand that detects the drawing activity that tremble with left hand and carry out every hand hand that detects drawing activity result that the desired value that detects index trembles and detect as measured's hand that trembles that trembles;
Described hand trembles and detects index and be comprised of undulatory property index and chattering frequency index;
Described undulatory property index is comprised of positional fluctuation index and fluctuation index, described positional fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the movable person's handwriting curve that produces of drawing, and described fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the application of force in the drawing activity;
Described chattering frequency index is comprised of speed chattering frequency index and power chattering frequency index, described speed chattering frequency measure of criterions measured carries out hand and trembles and detect velocity characteristic time series chattering frequency in the drawing activity, and described power chattering frequency measure of criterions measured carries out hand and trembles and detect force information time series chattering frequency in the drawing activity;
Order
The desired value of expression positional fluctuation index, order
The desired value of expression fluctuation index, order
The desired value of expression speed chattering frequency index, order
The desired value of expression power chattering frequency index; Wherein m is that hand trembles and detects the type of drawing activity, and m=1 represents to tremble finger, and to detect drawing movable, and m=2 represents to tremble wrist, and to detect drawing movable, and it is movable that m=3 represents that arm tremor detects drawing; Wherein Signal trembles and detects the hands type of drawing activity for carrying out hand, and Signal=0 represents to tremble the left hand hand, and to detect drawing movable, and Signal=1 represents to tremble right hand hand, and to detect drawing movable; The tremble calculating of the desired value that detects index of described hand is carried out as follows:
D1, hand-written data processing module are obtained m=1 from the hand-written data memory module, and n corresponding during Signal=0 organizes hand-written data;
D2, adopt filtering algorithm to carry out Filtering Processing to the measured n that gets access to group hand-written data;
D3, calculate desired value and the chattering frequency desired value of undulatory property index as follows;
Calculate
Adopt the Time Series Matching algorithm to be combined the person's handwriting curve difference value of calculating each combination to mating in twos through the positional information time series of the n of Filtering Processing group hand-written data, obtain
Individual person's handwriting curve difference value, the meansigma methods of trying to achieve person's handwriting curve difference value is the desired value of positional fluctuation index
Described Time Series Matching algorithm refers to time series is mated the also algorithm of difference value between the sequence of calculation;
Calculate
Adopt the Time Series Matching algorithm to be combined the force information difference value of calculating each combination to mating in twos through the force information time series of the n of Filtering Processing group hand-written data, obtain
Individual force information difference value is tried to achieve
The meansigma methods of individual force information difference value is the desired value of fluctuation index
Calculate
Adopt difference algorithm to calculate corresponding velocity characteristic time series by the positional information time series of every group of hand-written data, calculate the number of the extreme point that the velocity characteristic time series of every group of hand-written data occurs average each second, obtain n velocity characteristic time series per second extreme point number, the desired value of speed chattering frequency index
Be the meansigma methods of n velocity characteristic time series per second extreme point number;
Calculate
Calculate the number of the extreme point that the force information time series of every group of hand-written data occurs average each second, obtain n force information time series per second extreme point number, power chattering frequency index
Desired value be the meansigma methods of n force information time series per second extreme point number;
Type according to the force information sensor of described hand-written data acquisition module, described force information is one dimension positive pressure information, one dimension axial compressive force information, three-dimensional hand-written force information, one dimension grip information or three-dimensional grip information, described one dimension positive pressure information refers to the pen point pressure perpendicular to the handwriting input plane, described one dimension axial compressive force information refers to along the pen point pressure of handwriting input pen axial direction, the hand-written force information of described three-dimensional refers to perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the pen point pressure that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle, described one dimension grip information refers to put on the grip of handwriting input pen, and described three-dimensional grip information refers to put on the grip edge of handwriting input pen perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the component that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle;
When the force information of hand-written data acquisition module collection is one dimension positive pressure information, calculate
With
The force information of Shi Caiyong is one dimension positive pressure information; When the force information of hand-written data acquisition module collection is one dimension axial compressive force information, calculate
With
The force information of Shi Caiyong is one dimension axial compressive force information; When the force information of hand-written data acquisition module collection is three-dimensional hand-written force information, calculate
With
The force information of Shi Caiyong is perpendicular to the pen point pressure information on the handwriting input in-plane; When the force information of hand-written data acquisition module collection is one dimension grip information, calculate
With
The force information of Shi Caiyong is one dimension grip information; When the force information of hand-written data acquisition module collection is three-dimensional grip information, calculate
With
The force information of Shi Caiyong is the information of making a concerted effort of the three-dimensional grip that calculates by Euclidean distance;
D4, Signal value among the step a is changed to 1, repeating step d2 and d3;
D5, m value among the step a is changed to 2, repeating step d2, d3 and d4;
After d6, steps d 5 are finished, m value in the steps d 1 is changed to 3, repeating step d2, d3 and d4;
D7, the VP that will be calculated by steps d 1-d6
1 0, VP
2 0, VP
3 0, VP
1 1, VP
2 1, VP
3 1, VF
1 0, VF
2 0, VF
3 0, VF
1 1, VF
2 1, VF
3 1, FV
1 0, FV
2 0, FV
3 0, FV
1 1, FV
2 1, FV
3 1, FF
1 0, FF
2 0, FF
3 0, FF
1 1, FF
2 1And FF
3 1Gather the result who trembles and detect as measured's hand.
The tremble characteristics of detection method of hand of the present invention also are: the described hand detection system of trembling also comprises measured's information management module, hand tremble monitoring modular, network communication module and the data memory module that trembles;
Described measured's information management module is used for user's registration and authenticating user identification; Use for the first time the tremble measured of detection system of hand to submit to the log-on message that comprises personal information and identity information to carry out user's registration by measured's information management module, measured's information management module transmits described log-on message and is stored to the data memory module that trembles by network communication module; The measured who has carried out user registration submits identity information to when using hand to tremble detection system, measured's information management module compares the identity information of its submission with the identity information that is stored to the data memory module that trembles, determine measured's identity, realize subscriber authentication;
The described hand monitoring modular that trembles receives hand hand that detection module the transmits detection desired value of trembling of trembling, and by the network communication module access data memory module that trembles, tremble according to this hand of measured's identity storage measured and to detect desired value and obtain measured's hand and tremble and detect the historical record of desired value, the described hand monitoring modular that trembles shows this hand of measured testing result and measured's hand monitoring record that trembles that trembles by display device;
The described hand monitoring record that trembles refers to that the described hand monitoring modular that trembles trembles and detects the time dependent curve of desired value according to measured's hand tremble measured's hand that testing result draws of the historical record that detects desired value and this hand that trembles.
Described filtering algorithm is RC filtering or gaussian filtering.
Described Time Series Matching algorithm is that dynamic time warping algorithm, dynamic time warping algorithm improve algorithm or ER
2Algorithm.
Described personal information is name, sex, age, disease type and ill duration; Described identity information is the one or any combination in password, smart card, username and password, the fingerprint.
Compared with the prior art, beneficial effect of the present invention is embodied in;
1, the hand provided by the invention comprehensive detection that detection method realizes that hand trembles of trembling: according to the physiologic characteristic of hand-written motion, design three hands tremble detect that the drawing activity is respectively applied to point, the detection of trembling of wrist and arm, overcome existing detection method based on checkout equipment and need to design distinct device and measure the shortcoming that the hand different parts trembles, also efficiently solved existing detection method based on the drawing activity simultaneously and can't realize problem that the hand different parts detected separately;
2. the hand provided by the invention detection method of trembling has realized more comprehensive, the careful detection by quantitative of trembling: the hand of employing trembles and detects objective that index calculating method realized trembling, quantitative measurement, and from the person's handwriting geometric properties, kinematics character, the angle of dynamic characteristic has reflected amplitude and the frequency characteristics of trembling, particularly force information trembles the extraction of index so that testing result is more comprehensive, adopt difference value comparison algorithm calculating location undulatory property index and fluctuation index, solved the problem that different people applies the power difference in size, to the analysis of hand-written data more careful, accurately;
3. the hand provided by the invention detection method of trembling is simple and easy to do, has noninvasive: detect measured's hand based on hand activities common in this class daily life of drawing and tremble, alleviated the measured that the testing process of trembling causes nervous and tired;
4. the hand carried of the present invention detection system of trembling has realized the tremble tracking of the state of an illness of the storage of the information of effectively trembling and measured.
Description of drawings
Fig. 1 is the tremble flow chart of detection method of hand of the present invention;
Fig. 2 is that right finger of the present invention is trembled and detected the schematic diagram of drawing activity;
Fig. 3 is that right hand wrist of the present invention is trembled and detected the schematic diagram of drawing activity;
Fig. 4 is the schematic diagram that right hand arm tremor of the present invention detects the drawing activity;
Fig. 5 is the tremble structural representation of detection module of hand of the present invention;
Fig. 6 is the tremble structural representation of detection system of hand of the present invention.
The specific embodiment
The tremble characteristics of detection method of the present embodiment hand are: hand trembles to detect and comprises that tremble detections, wrist of finger tremble and detect and the arm tremor detection; Hand trembles to detect by the hand detection system of trembling and finishes, as shown in Figure 6, the hand detection system of trembling comprises the hand detection module that trembles, as shown in Figure 5, the hand detection module that trembles is comprised of handwriting input module, hand-written data acquisition module, hand-written data memory module and hand-written data processing module;
As shown in Figure 1, the hand detection method of trembling is to carry out as follows:
A, carry out hand by the handwriting input module and tremble that to detect drawing movable:
The handwriting input module comprises handwriting input plane and handwriting input pen;
Hand tremble detect the drawing activity comprise for finger tremble the finger that detects tremble detect drawing movable, be used for the tremble wrist that detects of wrist and tremble that to detect drawing movable and be used for arm tremor that arm tremor detects to detect drawing movable;
The measured holds described handwriting input pen and carries out successively finger tremble and detect that drawing is movable, wrist is trembled and detect drawing activity and arm tremor and detect movable three hands of drawing and tremble that to detect drawing movable on the handwriting input plane, every hand trembled, and to detect drawing movable, the measured adopts respectively left hand and the right hand to draw n time, n is not less than 2, and measured's left hand drafting number of times is identical with right hand drafting number of times; The measured carries out hand and trembles and detect drawing when movable, will tremble to this hand and detect the drawing person's handwriting that the drawing activity produces and show in the handwriting input plane; The measured whenever executes hand and trembles and detect drawing when movable, and the hand that the handwriting input module need be carried out the next item down painting that detects the drawing activity that trembles is pointed out;
Finger trembles and detects the drawing activity and be: the measured keeps wrist and arm motionless, with the described handwriting input pen of finger gripping drawing inclined straight line in the handwriting input plane, the inclination angle of the straight line that tilts is produced by outer motion towards palm by measured's finger gripping handwriting input pen, what left-hand finger was trembled the movable drafting of detection drawing is the straight line that is tilted to the right, as shown in Figure 2, what right finger was trembled the movable drafting of detection drawing is the angled straight lines that is tilted to the left, the length of the straight line that tilts depends on the motion amplitude of finger, keeps each finger to tremble among the measured detecting the straight length of the inclination that the drawing activity draws consistent with the inclination angle;
Wrist is trembled and detected the drawing activity and be: the measured keeps finger and arm motionless, with the described handwriting input pen of finger gripping, rotate the drive handwriting input pen by wrist and in the handwriting input plane, draw camber line, the curvature of camber line rotarily drives from inside to outside the handwriting input pen motion by measured's wrist and produces, the left hand wrist is trembled and is detected drawing movable what draw is camber line to the upper right side bending, as shown in Figure 3, right hand wrist is trembled and is detected drawing movable what draw is curve to the upper left side bending, the length of camber line depends on the rotation amplitude of wrist, and the arc length that the measured need keep each wrist to tremble detecting the drawing activity to draw as far as possible is consistent with curvature;
Arm tremor detects the drawing activity: as shown in Figure 4, with square pre-rendered on the handwriting input plane as borderline region, the foursquare length of side is 5-10cm, the measured keep the finger and wrist motionless, with the described handwriting input pen of finger gripping, drive by arm motion that handwriting input pen is drawn and the circle of described square inscribe in described borderline region;
B, hand-written data acquisition module gather the measured and carry out hand and tremble and detect the movable hand-written data that produces of drawing
The hand-written data acquisition module comprises positional information Acquisition Circuit and force information sensor; The measured adopts left hand and the right hand to carry out successively n finger by the handwriting input module to tremble and detect that drawing is movable, n wrist trembled and detected drawing activity and the activity of n arm tremor detection drawing, the hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled and detect the movable hand-written data that produces of drawing, and hand of the every execution of measured trembles and detects the drawing activity and just obtain one group of hand-written data;
Hand-written data comprises positional information time series and force information time series; Positional information detects the movable person's handwriting positional information that produces of drawing for the measured trembles by handwriting input module execution hand, the person's handwriting positional information adopts cartesian coordinate system to represent, the positional information Acquisition Circuit of hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and trembled to detect the movable person's handwriting positional information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the positional information time series of drawing activity; The force information sensor of hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled to detect the movable force information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the force information time series of drawing activity;
The qualification inspection of c, hand-written data
Hand-written data acquisition module Real-time Collection measured carry out each hand tremble detect the movable hand-written data that produces of drawing after, this group hand-written data is carried out the qualification inspection, if by the qualification inspection, then should organize hand-written data and deposit the hand-written data memory module in, otherwise, this time hand trembles, and to detect the movable hand-written data that produces of drawing invalid, and the measured re-executes this hand and trembles that to detect drawing movable;
The qualification inspection refers to judge that the measured carries out hand and whether trembles the number of the number of the included positional information of positional information time series that detects one group of hand-written data that the drawing activity obtains and the included force information of force information time series greater than predefined threshold value T, T 〉=20, if, judge that then this group hand-written data is by the qualification inspection, otherwise, judge that this group hand-written data is not by the qualification inspection;
D, carry out hand by the hand-written data processing module and tremble and detect index and calculate
The hand-written data memory module sends to the hand-written data processing module with the hand-written data of storage, and the hand-written data processing module is calculated the measured by hand-written data and used respectively left hand and the right hand to carry out every hand hand that detects drawing activity detection index of trembling of trembling; Carry out every hand the tremble desired value that detects index and right hand of the hand that detects the drawing activity that tremble with left hand and carry out every hand hand that detects drawing activity result that the desired value that detects index trembles and detect as measured's hand that trembles that trembles;
Hand trembles and detects index and be comprised of undulatory property index and chattering frequency index;
The undulatory property index is comprised of positional fluctuation index and fluctuation index, positional fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the movable person's handwriting curve that produces of drawing, and fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the application of force in the drawing activity;
The chattering frequency index is comprised of speed chattering frequency index and power chattering frequency index, speed chattering frequency measure of criterions measured carries out hand and trembles and detect velocity characteristic time series chattering frequency in the drawing activity, and power chattering frequency measure of criterions measured carries out hand and trembles and detect force information time series chattering frequency in the drawing activity;
Order
The desired value of expression positional fluctuation index, order
The desired value of expression fluctuation index, order
The desired value of expression speed chattering frequency index, order
The desired value of expression power chattering frequency index; Wherein m is that hand trembles and detects the type of drawing activity, and m=1 represents to tremble finger, and to detect drawing movable, and m=2 represents to tremble wrist, and to detect drawing movable, and it is movable that m=3 represents that arm tremor detects drawing; Wherein Signal trembles and detects the hands type of drawing activity for carrying out hand, and Signal=0 represents to tremble the left hand hand, and to detect drawing movable, and Signal=1 represents to tremble right hand hand, and to detect drawing movable; The tremble calculating of the desired value that detects index of described hand is carried out as follows:
D1, hand-written data processing module are obtained m=1 from the hand-written data memory module, and n corresponding during Signal=0 organizes hand-written data;
D2, adopt filtering algorithm to carry out Filtering Processing to the measured n that gets access to group hand-written data;
Filtering algorithm is the algorithm of RC filtering, gaussian filtering or other realization hand-written data noise filterings;
D3, calculate desired value and the chattering frequency desired value of undulatory property index as follows;
Calculate
Adopt the Time Series Matching algorithm to be combined the person's handwriting curve difference value of calculating each combination to mating in twos through the positional information time series of the n of Filtering Processing group hand-written data, obtain
Individual person's handwriting curve difference value, the meansigma methods of trying to achieve person's handwriting curve difference value is the desired value of positional fluctuation index
The Time Series Matching algorithm refers to time series is mated the also algorithm of difference value between the sequence of calculation; The Time Series Matching algorithm is dynamic time warping algorithm DTW(Dynamic Time Warping), the dynamic time warping algorithm improves algorithm, Extended R-squared (ER
2) algorithm or other realize the algorithm that difference value is calculated between time series;
Calculate
Adopt the Time Series Matching algorithm to be combined the force information difference value of calculating each combination to mating in twos through the force information time series of the n of Filtering Processing group hand-written data, obtain
Individual force information difference value is tried to achieve
The meansigma methods of individual force information difference value is the desired value of fluctuation index
Calculate
Adopt difference algorithm to calculate corresponding velocity characteristic time series by the positional information time series of every group of hand-written data, calculate the number of the extreme point that the velocity characteristic time series of every group of hand-written data occurs average each second, obtain n velocity characteristic time series per second extreme point number, the desired value of speed chattering frequency index
Be the meansigma methods of n velocity characteristic time series per second extreme point number;
Calculate
Calculate the number of the extreme point that the force information time series of every group of hand-written data occurs average each second, obtain n force information time series per second extreme point number, power chattering frequency index
Desired value be the meansigma methods of n force information time series per second extreme point number;
Type according to the force information sensor of hand-written data acquisition module, force information is one dimension positive pressure information, one dimension axial compressive force information, three-dimensional hand-written force information, one dimension grip information or three-dimensional grip information, one dimension positive pressure information refers to the pen point pressure perpendicular to the handwriting input plane, one dimension axial compressive force information refers to along the pen point pressure of handwriting input pen axial direction, three-dimensional hand-written force information refers to perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the pen point pressure that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle, one dimension grip information refers to put on the grip of handwriting input pen, and three-dimensional grip information refers to put on the grip edge of handwriting input pen perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the component that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle;
When the force information of hand-written data acquisition module collection is one dimension positive pressure information, calculate
With
The force information of Shi Caiyong is one dimension positive pressure information; When the force information of hand-written data acquisition module collection is one dimension axial compressive force information, calculate
With
The force information of Shi Caiyong is one dimension axial compressive force information; When the force information of hand-written data acquisition module collection is three-dimensional hand-written force information, calculate
With
The force information of Shi Caiyong is perpendicular to the pen point pressure information on the handwriting input in-plane; When the force information of hand-written data acquisition module collection is one dimension grip information, calculate
With
The force information of Shi Caiyong is one dimension grip information; When the force information of hand-written data acquisition module collection is three-dimensional grip information, calculate
With
The force information of Shi Caiyong is the information of making a concerted effort of the three-dimensional grip that calculates by Euclidean distance;
D4, Signal value among the step a is changed to 1, repeating step d2 and d3;
D5, m value among the step a is changed to 2, repeating step d2, d3 and d4;
After d6, steps d 5 are finished, m value in the steps d 1 is changed to 3, repeating step d2, d3 and d4;
D7, the VP that will be calculated by steps d 1-d6
1 0, VP
2 0, VP
3 0, VP
1 1, VP
2 1, VP
3 1, VF
1 0, VF
2 0, VF
3 0, VF
1 1, VF
2 1, VF
3 1, FV
1 0, FV
2 0, FV
3 0, FV
1 1, FV
2 1, FV
3 1, FF
1 0, FF
2 0, FF
3 0, FF
1 1, FF
2 1And FF
3 1Gather the result who trembles and detect as measured's hand.
As shown in Figure 6, the hand detection system of trembling also comprises measured's information management module, hand tremble monitoring modular, network communication module and the data memory module that trembles;
Measured's information management module is used for user's registration and authenticating user identification; Use for the first time the tremble measured of detection system of hand to submit to the log-on message that comprises personal information and identity information to carry out user's registration by measured's information management module, measured's information management module transmits log-on message and is stored to the data memory module that trembles by network communication module; The measured who has carried out user registration submits identity information to when using hand to tremble detection system, measured's information management module compares the identity information of its submission with the identity information that is stored to the data memory module that trembles, determine measured's identity, realize subscriber authentication; Described personal information is name, sex, age, disease type and ill duration, also can comprise other reflections personal considerations's information; Identity information is the one or any combination in password, smart card, username and password, the fingerprint;
The hand monitoring modular that trembles receives hand hand that detection module the transmits detection desired value of trembling of trembling, and by the network communication module access data memory module that trembles, tremble according to this hand of measured's identity storage measured and to detect desired value and obtain measured's hand and tremble and detect the historical record of desired value, the hand monitoring modular that trembles shows this hand of measured testing result and measured's hand monitoring record that trembles that trembles by display device;
The hand monitoring record that trembles refers to that the hand monitoring modular that trembles trembles and detects the time dependent curve of desired value according to measured's hand tremble measured's hand that testing result draws of the historical record that detects desired value and this hand that trembles.
In the implementation, if the handwriting equipment of selecting trembles the detection module except having the tremble hand of detection system of the present embodiment hand, also have measured's information management module, hand tremble monitoring modular and network communication module, then with this handwriting equipment directly as measured's information management module, the hand of the present embodiment tremble detection module, hand tremble monitoring modular and network communication module;
If the handwriting input device of selecting only has handwriting input module and the hand-written data acquisition module of the present embodiment, then it is connected with computer, with computer as hand-written data memory module, hand-written data processing module, measured's information management module, the hand of the present embodiment tremble monitoring modular and network communication module.
Claims (5)
1. hand detection method of trembling is characterized in that: described hand trembles to detect and comprises that tremble detections, wrist of finger tremble and detect and the arm tremor detection; Described hand trembles to detect by the hand detection system of trembling and finishes, the described hand detection system of trembling comprises the hand detection module that trembles, and the described hand detection module that trembles is comprised of handwriting input module, hand-written data acquisition module, hand-written data memory module and hand-written data processing module;
The described hand detection method of trembling is to carry out as follows:
A, carry out hand by the handwriting input module and tremble that to detect drawing movable:
Described handwriting input module comprises handwriting input plane and handwriting input pen;
Described hand tremble detect the drawing activity comprise for finger tremble the finger that detects tremble detect drawing movable, be used for the tremble wrist that detects of wrist and tremble that to detect drawing movable and be used for arm tremor that arm tremor detects to detect drawing movable;
The measured holds described handwriting input pen and carries out successively finger tremble and detect that drawing is movable, wrist is trembled and detect drawing activity and arm tremor and detect movable three hands of drawing and tremble that to detect drawing movable on described handwriting input plane, every hand trembled, and to detect drawing movable, the measured adopts respectively left hand and the right hand to draw n time, and n is not less than 2; The measured carries out hand and trembles and detect drawing when movable, will tremble to this hand and detect the drawing person's handwriting that the drawing activity produces and show in described handwriting input plane; The measured whenever executes hand and trembles and detect drawing when movable, and the hand that the handwriting input module need be carried out the next item down painting that detects the drawing activity that trembles is pointed out;
Described finger trembles and detects the drawing activity and be: the measured keeps wrist and arm motionless, with the described handwriting input pen of finger gripping drawing inclined straight line in the handwriting input plane, the inclination angle of the straight line of described inclination is produced by outer motion towards palm by measured's finger gripping handwriting input pen, what left-hand finger was trembled the movable drafting of detection drawing is the straight line that is tilted to the right, what right finger was trembled the movable drafting of detection drawing is the straight line that is tilted to the left, the length of the straight line that tilts depends on the motion amplitude of finger, and the measured keeps each finger to tremble detecting the straight length of the inclination that the drawing activity draws consistent with the inclination angle;
Described wrist is trembled and detected the drawing activity and be: the measured keeps finger and arm motionless, with the described handwriting input pen of finger gripping, rotate the drive handwriting input pen by wrist and in the handwriting input plane, draw camber line, the curvature of described camber line rotarily drives from inside to outside the handwriting input pen motion by measured's wrist and produces, the left hand wrist is trembled and is detected drawing movable what draw is camber line to the upper right side bending, right hand wrist is trembled and is detected drawing movable what draw is curve to the upper left side bending, the length of camber line depends on the rotation amplitude of wrist, and the arc length that the measured need keep each wrist to tremble detecting the drawing activity to draw as far as possible is consistent with curvature;
Described arm tremor detects the drawing activity: with square pre-rendered on the handwriting input plane as borderline region, the described foursquare length of side is 5-10cm, the measured keep the finger and wrist motionless, with the described handwriting input pen of finger gripping, drive by arm motion that handwriting input pen is drawn and the circle of described square inscribe in described borderline region;
B, hand-written data acquisition module gather the measured and carry out hand and tremble and detect the movable hand-written data that produces of drawing
Described hand-written data acquisition module comprises positional information Acquisition Circuit and force information sensor; The measured adopts left hand and the right hand to carry out successively n finger by the handwriting input module to tremble and detect that drawing is movable, n wrist trembled and detected drawing activity and the activity of n arm tremor detection drawing, described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled and detect the movable hand-written data that produces of drawing, and hand of the every execution of measured trembles and detects the drawing activity and just obtain one group of hand-written data;
Described hand-written data comprises positional information time series and force information time series; Described positional information detects the movable person's handwriting positional information that produces of drawing for the measured trembles by handwriting input module execution hand, the person's handwriting positional information adopts cartesian coordinate system to represent, the information acquisition circuit of described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and trembled to detect the movable person's handwriting positional information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the positional information time series of drawing activity; The force information sensor of described hand-written data acquisition module is carried out each hand according to fixing data acquiring frequency Real-time Collection measured and is trembled to detect the movable force information that produces of drawing and become this hand to tremble by the acquisition time der group and detect the force information time series of drawing activity;
The qualification inspection of c, hand-written data
Described hand-written data acquisition module Real-time Collection measured carry out each hand tremble detect the movable hand-written data that produces of drawing after, this group hand-written data is carried out the qualification inspection, if by the qualification inspection, then should organize hand-written data and deposit the hand-written data memory module in, otherwise, this time hand trembles, and to detect the movable hand-written data that produces of drawing invalid, the hand-written data acquisition module returns information to the handwriting input module, the handwriting input module is sent early warning, and the measured re-executes this hand and trembles that to detect drawing movable;
Described qualification inspection refers to judge that the measured carries out hand and whether trembles the number of the number of the included positional information of positional information time series that detects one group of hand-written data that the drawing activity obtains and the included force information of force information time series greater than predefined threshold value T, T 〉=20, if, judge that then this group hand-written data is by the qualification inspection, otherwise, judge that this group hand-written data is not by the qualification inspection;
D, carry out hand by the hand-written data processing module and tremble and detect index and calculate
The hand-written data memory module sends to the hand-written data processing module with the hand-written data of storage, and described hand-written data processing module is calculated the measured by described hand-written data and used respectively left hand and the right hand to carry out every hand hand that detects drawing activity detection index of trembling of trembling; Carry out every hand the tremble desired value that detects index and right hand of the hand that detects the drawing activity that tremble with left hand and carry out every hand hand that detects drawing activity result that the desired value that detects index trembles and detect as measured's hand that trembles that trembles;
Described hand trembles and detects index and be comprised of undulatory property index and chattering frequency index;
Described undulatory property index is comprised of positional fluctuation index and fluctuation index, described positional fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the movable person's handwriting curve that produces of drawing, and described fluctuation measure of criterions measured carries out hand and trembles and detect the degree of fluctuation of the application of force in the drawing activity;
Described chattering frequency index is comprised of speed chattering frequency index and power chattering frequency index, described speed chattering frequency measure of criterions measured carries out hand and trembles and detect velocity characteristic time series chattering frequency in the drawing activity, and described power chattering frequency measure of criterions measured carries out hand and trembles and detect force information time series chattering frequency in the drawing activity;
Order
The desired value of expression positional fluctuation index, order
The desired value of expression fluctuation index, order
The desired value of expression speed chattering frequency index, order
The desired value of expression power chattering frequency index; Wherein m is that hand trembles and detects the type of drawing activity, and m=1 represents to tremble finger, and to detect drawing movable, and m=2 represents to tremble wrist, and to detect drawing movable, and it is movable that m=3 represents that arm tremor detects drawing; Wherein Signal trembles and detects the hands type of drawing activity for carrying out hand, and Signal=0 represents to tremble the left hand hand, and to detect drawing movable, and Signal=1 represents to tremble right hand hand, and to detect drawing movable; The tremble calculating of the desired value that detects index of described hand is carried out as follows:
D1, hand-written data processing module are obtained m=1 from the hand-written data memory module, and n corresponding during Signal=0 organizes hand-written data;
D2, adopt filtering algorithm to carry out Filtering Processing to the measured n that gets access to group hand-written data;
D3, calculate desired value and the chattering frequency desired value of undulatory property index as follows;
Calculate
Adopt the Time Series Matching algorithm to be combined the person's handwriting curve difference value of calculating each combination to mating in twos through the positional information time series of the n of Filtering Processing group hand-written data, obtain
Individual person's handwriting curve difference value, the meansigma methods of trying to achieve person's handwriting curve difference value is the desired value of positional fluctuation index
Described Time Series Matching algorithm refers to time series is mated the also algorithm of difference value between the sequence of calculation;
Calculate
Adopt the Time Series Matching algorithm to be combined the force information difference value of calculating each combination to mating in twos through the force information time series of the n of Filtering Processing group hand-written data, obtain
Individual force information difference value is tried to achieve
The meansigma methods of individual force information difference value is the desired value of fluctuation index
Calculate
Adopt difference algorithm to calculate corresponding velocity characteristic time series by the positional information time series of every group of hand-written data, calculate the number of the extreme point that the velocity characteristic time series of every group of hand-written data occurs average each second, obtain n velocity characteristic time series per second extreme point number, the desired value of speed chattering frequency index
Be the meansigma methods of n velocity characteristic time series per second extreme point number;
Calculate
Calculate the number of the extreme point that the force information time series of every group of hand-written data occurs average each second, obtain n force information time series per second extreme point number, power chattering frequency index
Desired value be the meansigma methods of n force information time series per second extreme point number;
Type according to the force information sensor of described hand-written data acquisition module, described force information is one dimension positive pressure information, one dimension axial compressive force information, three-dimensional hand-written force information, one dimension grip information or three-dimensional grip information, described one dimension positive pressure information refers to the pen point pressure perpendicular to the handwriting input plane, described one dimension axial compressive force information refers to along the pen point pressure of handwriting input pen axial direction, the hand-written force information of described three-dimensional refers to perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the pen point pressure that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle, described one dimension grip information refers to put on the grip of handwriting input pen, and described three-dimensional grip information refers to put on the grip edge of handwriting input pen perpendicular to the handwriting input plane, be parallel to person's handwriting positional information transverse coordinate axis and the component that is parallel on three orthogonal directions of person's handwriting positional information along slope coordinate axle;
When the force information of hand-written data acquisition module collection is one dimension positive pressure information, calculate
With
The force information of Shi Caiyong is one dimension positive pressure information; When the force information of hand-written data acquisition module collection is one dimension axial compressive force information, calculate
With
The force information of Shi Caiyong is one dimension axial compressive force information; When the force information of hand-written data acquisition module collection is three-dimensional hand-written force information, calculate
With
The force information of Shi Caiyong is perpendicular to the pen point pressure information on the handwriting input in-plane; When the force information of hand-written data acquisition module collection is one dimension grip information, calculate
With
The force information of Shi Caiyong is one dimension grip information; When the force information of hand-written data acquisition module collection is three-dimensional grip information, calculate
With
The force information of Shi Caiyong is the information of making a concerted effort of the three-dimensional grip that calculates by Euclidean distance;
D4, Signal value among the step a is changed to 1, repeating step d2 and d3;
D5, m value among the step a is changed to 2, repeating step d2, d3 and d4;
After d6, steps d 5 are finished, m value in the steps d 1 is changed to 3, repeating step d2, d3 and d4;
D7, the VP that will be calculated by steps d 1-d6
1 0, VP
2 0, VP
3 0, VP
1 1, VP
2 1, VP
3 1, VF
1 0, VF
2 0, VF
3 0, VF
1 1, VF
2 1, VF
3 1, FV
1 0, FV
2 0, FV
3 0, FV
1 1, FV
2 1, FV
3 1, FF
1 0, FF
2 0, FF
3 0, FF
1 1, FF
2 1And FF
3 1Gather the result who trembles and detect as measured's hand.
2. the hand according to claim 1 detection method of trembling is characterized in that: the described hand detection system of trembling also comprises measured's information management module, hand tremble monitoring modular, network communication module and the data memory module that trembles;
Described measured's information management module is used for user's registration and authenticating user identification; Use for the first time the tremble measured of detection system of hand to submit to the log-on message that comprises personal information and identity information to carry out user's registration by measured's information management module, measured's information management module transmits described log-on message and is stored to the data memory module that trembles by network communication module; The measured who has carried out user registration submits identity information to when using hand to tremble detection system, measured's information management module compares the identity information of its submission with the identity information that is stored to the data memory module that trembles, determine measured's identity, realize subscriber authentication;
The described hand monitoring modular that trembles receives hand hand that detection module the transmits detection desired value of trembling of trembling, and by the network communication module access data memory module that trembles, tremble according to this hand of measured's identity storage measured and to detect desired value and obtain measured's hand and tremble and detect the historical record of desired value, the described hand monitoring modular that trembles shows this hand of measured testing result and measured's hand monitoring record that trembles that trembles by display device;
The described hand monitoring record that trembles refers to that the described hand monitoring modular that trembles trembles and detects the time dependent curve of desired value according to measured's hand tremble measured's hand that testing result draws of the historical record that detects desired value and this hand that trembles.
3. the described hand detection method of trembling according to claim 1, it is characterized in that: described filtering algorithm is RC filtering or gaussian filtering.
4. the described hand detection method of trembling according to claim 1, it is characterized in that: described Time Series Matching algorithm is that dynamic time warping algorithm, dynamic time warping algorithm improve algorithm or ER
2Algorithm.
5. the described hand detection method of trembling according to claim 2, it is characterized in that: described personal information is name, sex, age, disease type and ill duration; Described identity information is the one or any combination in password, smart card, username and password, the fingerprint.
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| CN109050085A (en) * | 2018-09-25 | 2018-12-21 | 绵阳鼎飞益电子科技有限公司 | A kind of pen used for parkinsonism patient |
| CN110101386A (en) * | 2019-06-05 | 2019-08-09 | 温州市中心医院 | A kind of Parkinson's auxiliary detection device |
| CN110569800A (en) * | 2019-09-10 | 2019-12-13 | 武汉大学 | detection method of handwriting signal |
| CN110569800B (en) * | 2019-09-10 | 2022-04-12 | 武汉大学 | Detection method of handwriting signal |
| CN113341797A (en) * | 2021-05-27 | 2021-09-03 | 深圳中学 | Non-contact fingertip tremor recording system and method |
| CN113341797B (en) * | 2021-05-27 | 2023-01-17 | 深圳中学 | Non-contact fingertip tremor recording system and method |
| CN113609975A (en) * | 2021-08-04 | 2021-11-05 | 苏州小蓝医疗科技有限公司 | Modeling method for tremor detection, hand tremor detection device and method |
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