CN108664147A - A kind of bradykinesia and tremble quantitative testing device and detection method - Google Patents
A kind of bradykinesia and tremble quantitative testing device and detection method Download PDFInfo
- Publication number
- CN108664147A CN108664147A CN201710203576.1A CN201710203576A CN108664147A CN 108664147 A CN108664147 A CN 108664147A CN 201710203576 A CN201710203576 A CN 201710203576A CN 108664147 A CN108664147 A CN 108664147A
- Authority
- CN
- China
- Prior art keywords
- bradykinesia
- data
- trembles
- subject
- testing device
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 206010044565 Tremor Diseases 0.000 title claims abstract description 71
- 208000006083 Hypokinesia Diseases 0.000 title claims abstract description 58
- 206010006100 Bradykinesia Diseases 0.000 title claims abstract description 54
- 238000012360 testing method Methods 0.000 title claims abstract description 39
- 238000001514 detection method Methods 0.000 title abstract description 15
- 230000033001 locomotion Effects 0.000 claims abstract description 24
- 208000024891 symptom Diseases 0.000 claims abstract description 13
- 230000001133 acceleration Effects 0.000 claims abstract description 12
- 238000000034 method Methods 0.000 claims description 21
- 238000004458 analytical method Methods 0.000 claims description 17
- 238000007405 data analysis Methods 0.000 claims description 17
- 201000010099 disease Diseases 0.000 claims description 11
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 11
- 210000003857 wrist joint Anatomy 0.000 claims description 10
- 241000209094 Oryza Species 0.000 claims description 9
- 235000007164 Oryza sativa Nutrition 0.000 claims description 9
- 235000009566 rice Nutrition 0.000 claims description 9
- 238000005259 measurement Methods 0.000 claims description 6
- 238000003556 assay Methods 0.000 claims description 5
- WTDRDQBEARUVNC-UHFFFAOYSA-N L-Dopa Natural products OC(=O)C(N)CC1=CC=C(O)C(O)=C1 WTDRDQBEARUVNC-UHFFFAOYSA-N 0.000 claims description 3
- 125000004122 cyclic group Chemical group 0.000 claims description 3
- 229960004502 levodopa Drugs 0.000 claims description 3
- 230000036651 mood Effects 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 claims description 3
- 210000001364 upper extremity Anatomy 0.000 claims description 3
- 210000000707 wrist Anatomy 0.000 claims description 3
- WTDRDQBEARUVNC-LURJTMIESA-N L-DOPA Chemical compound OC(=O)[C@@H](N)CC1=CC=C(O)C(O)=C1 WTDRDQBEARUVNC-LURJTMIESA-N 0.000 claims description 2
- 239000011159 matrix material Substances 0.000 claims description 2
- 210000004247 hand Anatomy 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 12
- 229940079593 drug Drugs 0.000 abstract description 8
- 239000003814 drug Substances 0.000 abstract description 8
- 238000013135 deep learning Methods 0.000 abstract description 4
- 238000002474 experimental method Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 102000015554 Dopamine receptor Human genes 0.000 description 1
- 108050004812 Dopamine receptor Proteins 0.000 description 1
- 208000037048 Prodromal Symptoms Diseases 0.000 description 1
- 208000007271 Substance Withdrawal Syndrome Diseases 0.000 description 1
- 229940035676 analgesics Drugs 0.000 description 1
- 239000000730 antalgic agent Substances 0.000 description 1
- 239000000090 biomarker Substances 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- MHUWZNTUIIFHAS-CLFAGFIQSA-N dioleoyl phosphatidic acid Chemical compound CCCCCCCC\C=C/CCCCCCCC(=O)OCC(COP(O)(O)=O)OC(=O)CCCCCCC\C=C/CCCCCCCC MHUWZNTUIIFHAS-CLFAGFIQSA-N 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000013011 mating Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 238000009774 resonance method Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
- G06F3/033—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
- G06F3/0354—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor with detection of 2D relative movements between the device, or an operating part thereof, and a plane or surface, e.g. 2D mice, trackballs, pens or pucks
- G06F3/03545—Pens or stylus
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a kind of bradykinesias and tremble quantitative testing device and detection method, are related to medical instruments field.Bradykinesia of the present invention is arranged in pairs or groups together by software combination hardware electronics using realizing with tremble aided detection method and device.This platform scheme passes through deep learning, big data mode captures and analyzes the fine data that subject is inputted by electronic handwriting pen, obtain the hand-written run duration of subject, middle position movement velocity, acceleration maximum value, it trembles frequency, the amplitude to tremble, position (the x of pen when hand-written, y), the movement locus in plane 1cm write from electronic writing input equipment, the data such as the dynamics indexs such as speed and acceleration, with from trembling, bradykinesia, the typical motions such as tetanic it is slow with tremble core symptom angle provide bradykinesia and tremble (especially early stage) quantifiable objective indicator auxiliary detection and medication effect tracking solution.
Description
Technical field
The present invention relates to the quantitative detection that medical instruments field more particularly to a kind of synkinesia are slow and tremble, softwares
It is combined with hardware, it is whole to quantify aided detection method and device scheme.
Background technology
Bradykinesia and the diagnosis trembled and the tracking of subject's medication effect rely primarily on doctor, and clinical experience accumulates for many years
Subjective judgement, specialist culture rely primarily on face-to-face professor and case continuous accumulation.Since shortage is objective, can quantify
Diagnostic method, bradykinesia and the early diagnosis trembled are difficult, and manifest symptom even occur, the doctor to lack experience
The disease for being easy to possess with other similar symptom is obscured, and mistaken diagnosis is caused.
Current most helpful auxiliary examination method is DAT：Dopamine receptor is set to develop by analgesics screening platform, it is rear logical
It crosses magnetic nuclear resonance method and detects result；Disadvantage：Expensive, most apparent defect is intrusive and radioactivity, is unfavorable for wide
General popularization.UPDRS scales：The test of Britain's authority's think-tank, the score for evaluating subject by answering a series of design problem,
As a result more accurate, it can be as effective reference of doctor, at low cost, disadvantage：Testing time is long, needs the medical staff of profession
Accurately record and give a mark, to early stage bradykinesia with tremble insensitive, be not easy to large-scale promotion and duplication.
Research domestic at present concentrates on the diagnosis of prodromal stage, be mostly the directions blood, hydrocrania biomarker,
Medical image direction, gene direction, research direction stay in academic research mostly, need to carry out invasive test to subject,
Or test process and verify it is cumbersome, reproducibility and convertibility are very poor.
Therefore, those skilled in the art is dedicated to developing a kind of bradykinesia and tremble auxiliary detection device and method,
Prompted with writing data quantitative by subject bradykinesia and tremble (especially early stage bradykinesia and tremble) possibility,
Degree and quantitative analysis track medication effect.
Invention content
In view of the drawbacks described above of the prior art, the technical problem to be solved by the present invention is to how using analysis writing number
According to mode quantitatively detect the bradykinesia of subject and tremble possibility, degree or medication effect.
To achieve the above object, the present invention provides a kind of bradykinesias and the quantitative testing device that trembles, including write defeated
Enter module, data acquisition module, data analysis module, wherein the writing input module connects the data acquisition module, institute
It states data acquisition module and connects the data analysis module, the data acquisition module acquires quilt by writing input module in real time
The writing data of examination person；The data provided by the data acquisition module, the data analysis module are configured as quantitatively dividing
Analysis bradykinesia and the tendentiousness or severity trembled.
Further, the writing input module includes electronic writing input equipment, and track data reading rate is more than etc.
In 200 points/second.
Further, the writing data acquisition of the data collecting module collected includes the run duration write, middle position fortune
Dynamic speed, acceleration maximum value, frequency of trembling and amplitude, the position of pen and pen are being felt from the writing input module when writing
Movement locus that should be in.
Further, ranging from 0~1 centimetre of the distance of reaction.
Further, the data acquisition module further includes writing to copy and determine wrist joint rotary picture line template unit, institute
It includes Archimedian screw template to state personal letter and copy modular unit, rice character matrix plate and determines wrist key rotary picture line template.
Further, the data acquisition module further includes state of an illness information module, and the clinical data includes name, property
Not, race, age, contact method, occupation, weight, height, schooling, family history, comorbidity, the PD courses of disease, nearly 1 year/mono-
Number of falls and levodopa equivalent dose in month.
Further, the data analysis module is configured as calculating any time subject writing data coordinates and standard
The Euclidean distance of coordinate, and the correspondence of time and Euclidean distance is changed into frequency by Short Time Fourier Transform
Domain obtains cyclic graph by frequency-domain analysis, finally obtains tremble frequency and the amplitude that trembles.
Further, the data analysis module is configured as comparing trembling for subject and healthy population and frequency and trembles
Amplitude difference, and obtain test result.
Further, the data analysis module is configured as assessing from the extracting data linear dimensions of handwriting trace and transport
Dynamic slow degree.
Further, the linear dimensions includes completing task time, movement velocity and acceleration of motion maximum value；Its
In, the movement velocity value median.
Further, the data analysis module is configured as going out subject and normal person's numerical value by measuring variance analysis
The otherness showed in the characteristic quantity of the linear dimensions, and obtain test result.
The present invention also provides a kind of bradykinesias and the quantitative detecting method that trembles, and include the following steps：
Step 1, subject are write by writing input module, and data acquisition module acquires the writing number of subject in real time
According to；
Step 2, subject select imitation, the imitation in setting-out modular unit, setting-out template to copy；
Step 3, each copied for subject, setting-out template copy, setting-out when, data acquisition module records person's handwriting
Track, average speed, maximum speed, minimum speed, time, peak accelerator person's handwriting dynamics numerical value；
Step 4, assay upper limb written handwriting during exercise between, average speed, peak accelerator in subject and
Difference between normal person's numerical value, including the differences such as the different courses of disease, writing state of the severity of motor symptoms, objective to sentence
Disconnected subject is with the presence or absence of apparent tendency and its severity of the residing course of disease and motor symptoms.
Further, the sequence of the imitation is followed successively by spiral of Archimedes pattern, rice word pattern and determines wrist joint rotation
Turn.
Further, the imitation step of the spiral of Archimedes pattern is clockwise imitation spiral of being therefrom in a good mood.
Further, the imitation step of the rice word pattern is from center to 8 directions, and 45 ° of each direction interval is stretched out
Straight line, since straight top back and forth it is each three times, and continue down successively clockwise.
Further, described the step of determining wrist joint rotation is using wrist joint as the center of circle, hold a pen with it is maximum can and range
Camber line is drawn back and forth 5 times, carried out in white space.
Further, in the step 4, the data of the assay further include that subject data itself are persistently right
Than.
Further, the difference is in two comparison among groups, and using duplicate measurements variance analysis, enumeration data compares using χ2
It examines, using 95% as confidence interval, P ＜ 0.05 then think that difference is significant.
Bradykinesia of the present invention with tremble aided detection method and device is set by software combination hardware electronic
It is standby to arrange in pairs or groups together using realizing.This platform scheme captures by deep learning, big data mode and analyzes subject
The fine data inputted by electronic handwriting pen obtain the hand-written run duration of subject, middle position movement velocity, acceleration most
Be worth greatly, frequency of trembling, the amplitude to tremble, it is hand-written when pen position (x, y) and pen write from electronic writing input equipment
The data such as the dynamics indexs such as the movement locus in plane 1cm, speed and acceleration, with from tremble, bradykinesia, the allusion quotations such as tetanic
Type bradykinesia and core symptom angle is trembled to provide bradykinesia and tremble (especially early stage bradykinesia and tremble)
The auxiliary detection of quantifiable objective indicator and the solution of medication effect tracking.
This detection method measurement process is simple, convenient, and survey can be completed without a large amount of wearable devices and test accessory
Examination, and this test is not simple one-to-one for a certain or a few content progress in the standards such as UPDRS scales
Quantified to assist the test of scale etc., this test method can inspection of the complete independently for bradykinesia and situation of trembling on the spot
Survey and provide test result and report, and be from the hand-written angle of dynamic come from tremble, bradykinesia, multiple typical cases such as tetanic
The dimension of bradykinesia and core symptom of trembling judged, objective judgement high with accuracy rate, rapid, can providing quantization
The advantage of standard.Test process is safe from harm to subject and side effect, of low cost, simple and convenient, convenient for extensive
It promotes and applies.
The software aspects of bradykinesia of the present invention and quantitative detection of trembling：The hand-written movement that data are carried out
The data such as time, middle position movement velocity, acceleration maximum value, frequency of trembling, the amplitude to tremble, with from tremble, it is bradykinesia, strong
The slow algorithm analyzed with core symptom angle of trembling of typical motions such as straight, and include deep learning algorithm and big data
Algorithm, the above core algorithm of the software can not only ensure through the accurate analytical judgment quilt to subject's writing pencil data
Examination person's hand exercise feature whether meet bradykinesia and the nucleus movement symptom trembled prompt subject suffer from bradykinesia with
It trembles the possibility and medication effect of (especially early stage bradykinesia and tremble), and with the continuous accumulation of case, this is soft
Part constantly automatically can also optimize the analysis model of itself by the algorithm of big data and deep learning, so that
The accuracy of analysis and evaluation result continues to optimize promotion.Software is the hand-written number of the subject obtained to the hardware in scheme
According to the main means analyzed.
The hardware aspect of bradykinesia of the present invention and quantitative detection of trembling：Hardware aspect, electronic handwritten input are set
It is standby --- the hardware device comprising the plane that electronic handwriting pen and writing pencil are write, and the reading rate of electronic pen data reaches
200 points/second or more can be combined with the software in this programme to be used.Hardware product is to obtain subject's hand-written data
Main collecting device, apparatus-form differs, as long as can accomplish that data above collects that subject can be asked to carry out is hand-written
Any associated electrical handwriting input device of input can be used.
Compared to the prior art, bradykinesia of the present invention and quantitative testing device accuracy rate of trembling are high, it is possible to provide
Rapidly, quantifiable objective examination criteria is referred to for doctor；The quantitatively evaluating that subject's medication effect can be directed to is tracked；Quilt
Examination person's convenient test, quick, safety, without invasive, without side-effects；Measurement is operated without health care professional；To early stage
Bradykinesia and sensitivity of trembling carry out emphasis prompt to its possibility；Of low cost, easy-to-use, objective, data acquisition is easy, just
It is widely popularized on a large scale, it might even be possible to be generalized to community, benefit numerous person in middle and old age subject, be detected at any time, be conducive to disease
Sick early discovery, early treatment, early control；Intelligent medical treatment detection platform scheme Innovation, measurement result increase with case load, can be continuous
It improves and improves.
The technique effect of the design of the present invention, concrete structure and generation is described further below with reference to attached drawing, with
It is fully understood from the purpose of the present invention, feature and effect.
Description of the drawings
Fig. 1 is the Archimedian screw experiment pattern of the preferred embodiment of the present invention；
Fig. 2 is the rice word experiment pattern of the preferred embodiment of the present invention；
Fig. 3 is the structure drawing of device of the preferred embodiment of the present invention.
Specific implementation mode
As shown in figure 3, bradykinesia of the present invention and the quantitative testing device that trembles include handwriting input module, data
Acquisition module, data analysis module, wherein the handwriting input module connects the data acquisition module, the data acquisition
Module connects the data analysis module, and the data acquisition module acquires the writing of subject by handwriting input module in real time
Data；The data provided by the data acquisition module, the data analysis module are configured as quantitative analysis bradykinesia
With the apparent tendency or severity or medication effect trembled.
Subject uses process：Subject carries out a series of setting in advance first in hardware plane by electronic handwriting pen
The test content counted, software after obtaining the writing pencil data write during the test of this subject, software
Backstage can carry out operational analysis, after subject completes test, subject be prompted to suffer from bradykinesia and the possibility trembled.
Technological means：The platform technology scheme that software and hardware is combined
1. data collection
Before hand-written parameter collection, the clinical data of subject is collected in detail：Name, sex, race, age, contact
Mode, occupation, weight, height, schooling, family history, comorbidity, the PD courses of disease, number of falls and left-handed in nearly 1 year/January
DOPA equivalent dose.
2. instrument and detection process
This, which is detected, mating uses electronic handwritten hardware input equipment to record the writing data of subject in real time.Pen when hand-written
Position (x, y), the movement locus in plane 1cm write from electronic writing input equipment, the power such as speed and acceleration
Learning index can be by connected computer record.
Subject is sitting in bright and clear, quiet room on adjustable for height seat, loosens simultaneously upright position, makes shirtfront
Apart from keyboard 10cm, right body median line is aligned electronic handwritten hardware input equipment center line.It is introduced from testing staff to subject
Electronic handwritten input equipment application method and operating process.Subject first writes name or some simple words are familiar with handwriting equipment,
Font size with oneself the most comfortable and speed (or according to assigned frequency) of writing are tested in OFF phases (15 hours ＞ after drug withdrawal).
For track real-time display when writing on handwriting equipment or on the paper of handwriting equipment covering, subject can see oneself
Handwriting trace, therefore fed back with natural vision under normal writing state.Each subject is according to same sequence in electronic hand
3 tasks of completion are write on input equipment, are in advance graphically displayed at imitation on handwriting equipment or hand with the software of designed, designed
On the paper of write device covering, the writing plane test of pen contact handwriting equipment starts, and pen leaves plane 10s and is considered as termination, in
Way is not required to stop without cause specific, is continued by doctor's button after completing each task.
Task 1：Archimedes curve copies (clockwise of being therefrom in a good mood copies spiral), as shown in Figure 1；
Task 2：Rice word figure copy (from center to 8 directions back and forth it is each three times) from center to 8 directions, each direction
45 ° of interval stretching straight lines advise subject is each back and forth since straight top and to continue down successively clockwise three times, such as Fig. 2 institutes
Show；
Task 3：Determine wrist joint rotation (surveying the movement velocity under normal range of joint motion)：Using wrist joint as the center of circle, in plate
On advise subject to hold a pen with it is maximum can and range draw camber line back and forth 5 times (being carried out in white space)
3. data processing and statistical analysis
When executing each task for subject, electronic handwritten input equipment records the track of person's handwriting, average speed,
The person's handwritings dynamics numerical value such as maximum speed, minimum speed, time, peak accelerator, uses software analysis data.Two comparison among groups are adopted
With duplicate measurements variance analysis, enumeration data compares using χ2It examines, using 95% as confidence interval, P ＜ 0.05 then think poor
It is different significant.With assay upper limb handwriting during exercise between, average speed, peak accelerator in subject and just
Difference (including the differences such as the different courses of disease, the hand-written state of the severity of motor symptoms) between ordinary person's numerical value, it is objective to sentence
Severity of the disconnected subject with the presence or absence of apparent bradykinesia and tremble tendency and its residing course of disease and motor symptoms.
The assessment of 3.1 bradykinesias
We assess the degree of bradykinesia from three linear dimensions of extracting data of handwriting tracks.Parameter one：It completes
Task time；Parameter two：Experimenter's movement velocity；Parameter three：Experimenter's acceleration of motion maximum value.Wherein, parameter two will be kept away
Exempt from data of subject during acceleration or deceleration, it is believed that subject is within most times in proper motion speed
Degree, therefore can be using the median inside sets of speeds as the value of parameter two.Subject is can be seen that by measuring variance analysis
The otherness that normal person's numerical value is shown in three characteristic quantities more than person.
3.2 frequencies trembled and amplitude
Archimedian screw experiment, the experiment of rice word determine wrist to test all to be to copy experiment.We calculate and are tested at any time
The Euclidean distance (Euclidean Metric) of person's coordinate and standard coordinate, and the time is corresponding with Euclidean distance
Relationship changes into frequency domain by Short Time Fourier Transform (Short-Time Fourier transform), is obtained by frequency-domain analysis
Cyclic graph, to obtain trembling frequency (HZ) and the amplitude that trembles (mm).By frequency-domain analysis it can be found that subject is in each test
In show tremble frequency and tremor amplitude has difference.
By the data of in summary several aspects, comprehensive analysis below table numerical value summarizes and whether prompts subject
It is had differences between normal person.
* p value：Such as continuous variable, with Kruskal Wallis rank sum tests；As counting variable has theoretical value<10, it uses
Fisher accurately calculates probabilistic method and obtains a result.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that the ordinary skill of this field is without wound
The property made labour, which according to the present invention can conceive, makes many modifications and variations.Therefore, all technician in the art
Pass through the available technology of logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Scheme, all should be in the protection domain being defined in the patent claims.
Claims (18)
1. a kind of bradykinesia and the quantitative testing device that trembles, which is characterized in that including writing input module, data acquisition module
Block, data analysis module, wherein the writing input module connects the data acquisition module, and the data acquisition module connects
The data analysis module is connect, the data acquisition module acquires the writing data of subject by writing input module in real time；
The data provided by the data acquisition module, the data analysis module are configured as quantitative analysis bradykinesia and tremble
Tendentiousness or severity.
2. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the writing input module
Including electronic writing input equipment, track data reading rate is more than or equal to 200 points/second.
3. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the data acquisition module
The writing data acquisition of acquisition includes the run duration write, middle position movement velocity, acceleration maximum value, frequency of trembling and shakes
Width, the movement locus of the position of pen and pen from the writing input module in distance of reaction when writing.
4. bradykinesia as claimed in claim 3 and the quantitative testing device that trembles, which is characterized in that the distance of reaction range
It is 0~1 centimetre.
5. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the data acquisition module
Further include writing to copy and determine wrist joint rotary picture line template unit, it includes Archimedian screw that the personal letter, which copies modular unit,
Template, rice character matrix plate and determines wrist key rotary picture line template.
6. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the data acquisition module
Further include state of an illness information module, for the state of an illness information module for acquiring clinical data, the clinical data includes name, property
Not, race, age, contact method, occupation, weight, height, schooling, family history, comorbidity, the PD courses of disease, nearly 1 year/mono-
Number of falls and levodopa equivalent dose in month.
7. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the data analysis module
It is configured as calculating the Euclidean distance of coordinate and standard coordinate that any time subject writes data, and time and Europe
The correspondence that distance is obtained in several changes into frequency domain by Short Time Fourier Transform, and cyclic graph is obtained by frequency-domain analysis, finally
To frequency and the amplitude that trembles of trembling.
8. bradykinesia as claimed in claim 7 and the quantitative testing device that trembles, which is characterized in that the data analysis module
It is configured as comparing tremble frequency and the amplitude difference that trembles of subject and healthy population, and obtains test result.
9. bradykinesia as described in claim 1 and the quantitative testing device that trembles, which is characterized in that the data analysis module
It is configured as assessing the degree of bradykinesia from the extracting data linear dimensions of handwriting trace.
10. bradykinesia as claimed in claim 9 and the quantitative testing device that trembles, which is characterized in that the linear dimensions packet
It includes and completes task time, movement velocity and acceleration of motion maximum value；Wherein, the movement velocity value median.
11. bradykinesia as claimed in claim 10 and the quantitative testing device that trembles, which is characterized in that the data analysis mould
Block is configured as going out what subject showed with normal person's numerical value in the characteristic quantity of the linear dimensions by measuring variance analysis
Otherness, and obtain test result.
12. a kind of bradykinesia and the quantitative detecting method that trembles, which is characterized in that include the following steps：
Step 1, subject are write by writing input module, and data acquisition module acquires the writing data of subject in real time；
Step 2, subject select imitation, the imitation in setting-out modular unit, setting-out template to copy；
Step 3, each copied for subject, setting-out template copy, setting-out when, data acquisition module records the rail of person's handwriting
Mark, average speed, maximum speed, minimum speed, time, peak accelerator person's handwriting dynamics numerical value；
Step 4, assay upper limb written handwriting during exercise between, average speed, peak accelerator in subject and normal
Difference between number value, including the differences such as the different courses of disease, writing state of the severity of motor symptoms, carry out objective judgement quilt
Examination person is with the presence or absence of apparent tendency and its severity of the residing course of disease and motor symptoms.
13. bradykinesia as claimed in claim 12 and the quantitative detecting method that trembles, which is characterized in that the sequence of the imitation
It is followed successively by spiral of Archimedes pattern, rice word pattern and determines wrist joint rotation.
14. bradykinesia as claimed in claim 13 and the quantitative detecting method that trembles, which is characterized in that Archimedes's spiral shell
The imitation step of spin line pattern is clockwise imitation spiral of being therefrom in a good mood.
15. bradykinesia as claimed in claim 13 and the quantitative detecting method that trembles, which is characterized in that the rice word pattern
It is 45 ° of each direction interval stretching straight line from center to 8 directions to copy step, since straight top back and forth it is each three times, and it is suitable
Hour hands continue down successively.
16. bradykinesia as claimed in claim 13 and the quantitative detecting method that trembles, which is characterized in that described to determine wrist joint rotation
The step of turning be using wrist joint as the center of circle, hold a pen with it is maximum can and range draw camber line back and forth 5 times, carried out in white space.
17. bradykinesia as claimed in claim 12 and the quantitative detecting method that trembles, which is characterized in that in the step 4,
The data of the assay further include that subject data itself persistently compare.
18. bradykinesia as claimed in claim 12 and the quantitative detecting method that trembles, which is characterized in that the difference is at two groups
Between compare, using duplicate measurements variance analysis, enumeration data compares using χ2It examines, using 95% as confidence interval, P ＜ 0.05
Then think that difference is significant.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710203576.1A CN108664147A (en) | 2017-03-30 | 2017-03-30 | A kind of bradykinesia and tremble quantitative testing device and detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710203576.1A CN108664147A (en) | 2017-03-30 | 2017-03-30 | A kind of bradykinesia and tremble quantitative testing device and detection method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108664147A true CN108664147A (en) | 2018-10-16 |
Family
ID=63786470
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710203576.1A Pending CN108664147A (en) | 2017-03-30 | 2017-03-30 | A kind of bradykinesia and tremble quantitative testing device and detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108664147A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109717832A (en) * | 2018-11-26 | 2019-05-07 | 中国科学院软件研究所 | A kind of hand movement function analytical equipment based on handwriting input |
| CN110544410A (en) * | 2019-07-15 | 2019-12-06 | 山东第一医科大学(山东省医学科学院) | handwriting capability quantitative evaluation system and method |
| CN111528842A (en) * | 2020-05-26 | 2020-08-14 | 复嶂环洲生物科技(上海)有限公司 | Quantitative assessment method for Parkinson disease symptoms based on physiological and behavioral indexes |
| CN113017618A (en) * | 2021-03-18 | 2021-06-25 | 西安交通大学医学院第一附属医院 | Rapid diagnosis instrument for upper limb myotonic dyskinesia |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101612044A (en) * | 2009-08-04 | 2009-12-30 | 中国科学院合肥物质科学研究院 | Wearable human arm tremor detection device and signal processing method thereof |
| CN103315744A (en) * | 2013-07-01 | 2013-09-25 | 中国科学院合肥物质科学研究院 | Hand tremor detection method |
| CN104127187A (en) * | 2014-08-05 | 2014-11-05 | 戴厚德 | Wearable system and method for cardinal symptom quantitative detection of Parkinson patients |
-
2017
- 2017-03-30 CN CN201710203576.1A patent/CN108664147A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101612044A (en) * | 2009-08-04 | 2009-12-30 | 中国科学院合肥物质科学研究院 | Wearable human arm tremor detection device and signal processing method thereof |
| CN103315744A (en) * | 2013-07-01 | 2013-09-25 | 中国科学院合肥物质科学研究院 | Hand tremor detection method |
| CN104127187A (en) * | 2014-08-05 | 2014-11-05 | 戴厚德 | Wearable system and method for cardinal symptom quantitative detection of Parkinson patients |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109717832A (en) * | 2018-11-26 | 2019-05-07 | 中国科学院软件研究所 | A kind of hand movement function analytical equipment based on handwriting input |
| CN110544410A (en) * | 2019-07-15 | 2019-12-06 | 山东第一医科大学(山东省医学科学院) | handwriting capability quantitative evaluation system and method |
| CN110544410B (en) * | 2019-07-15 | 2021-06-22 | 山东第一医科大学(山东省医学科学院) | Handwriting capability quantitative evaluation system and method |
| CN111528842A (en) * | 2020-05-26 | 2020-08-14 | 复嶂环洲生物科技(上海)有限公司 | Quantitative assessment method for Parkinson disease symptoms based on physiological and behavioral indexes |
| CN113017618A (en) * | 2021-03-18 | 2021-06-25 | 西安交通大学医学院第一附属医院 | Rapid diagnosis instrument for upper limb myotonic dyskinesia |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Drotár et al. | Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease | |
| Impedovo et al. | A handwriting-based protocol for assessing neurodegenerative dementia | |
| US9610029B2 (en) | System and method to facilitate analysis of brain injuries and disorders | |
| CN108664147A (en) | A kind of bradykinesia and tremble quantitative testing device and detection method | |
| US20170296101A1 (en) | System and method to facilitate analysis of brain injuries and disorders | |
| CN114224296B (en) | Parkinson's motion symptom quantitative evaluation system based on wearable sensing device | |
| JP4524054B2 (en) | Support system for pathological diagnosis, medication prescription and functional recovery training for brain and nervous system diseases | |
| CN112704500B (en) | Mental state screening system, mental state screening method and storage medium | |
| Basjaruddin et al. | Measurement device for stress level and vital sign based on sensor fusion | |
| Skaramagkas et al. | Multi-modal deep learning diagnosis of parkinson’s disease—A systematic review | |
| CN108962379B (en) | Mobile phone auxiliary detection system for cranial nerve system diseases | |
| Surangsrirat et al. | Tremor assessment using spiral analysis in time-frequency domain | |
| CN107045393A (en) | Line test multi-channel data collecting method and system based on digital pen | |
| CN112687378A (en) | Parkinson's disease dyskinesia symptom monitoring platform and application thereof | |
| JP5911962B2 (en) | Systems and methods for facilitating analysis of brain injury and damage | |
| CN109717831B (en) | Non-interference type nervous system disease auxiliary detection system based on touch gestures | |
| Chen et al. | Gait analysis based Parkinson’s disease auxiliary diagnosis system | |
| Smits et al. | Reproducibility of standardized fine motor control tasks and age effects in healthy adults | |
| Fairhurst et al. | Developing a generic approach to online automated analysis of writing and drawing tests in clinical patient profiling | |
| Eun et al. | Development of personalized urination recognition technology using smart bands | |
| Lara-Garduno et al. | 3D-Trail-Making Test: A Touch-Tablet Cognitive Test to Support Intelligent Behavioral Recognition. | |
| Tolonen et al. | Distinguishing Parkinson's disease from other syndromes causing tremor using automatic analysis of writing and drawing tasks | |
| Anthony et al. | Gesture dynamics: Features sensitive to task difficulty and correlated with physiological sensors | |
| US10786182B2 (en) | System and method for passive remote monitoring of patients' fine motor behavior | |
| Allebawi et al. | A new online Arabic handwriting dataset for analyzing Parkinson’s disease |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20181016 |