CN106388830B - Balance detection method based on Wii Balance board - Google Patents
Balance detection method based on Wii Balance board Download PDFInfo
- Publication number
- CN106388830B CN106388830B CN201610840259.6A CN201610840259A CN106388830B CN 106388830 B CN106388830 B CN 106388830B CN 201610840259 A CN201610840259 A CN 201610840259A CN 106388830 B CN106388830 B CN 106388830B
- Authority
- CN
- China
- Prior art keywords
- balance
- cop
- index
- wii
- points
- 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.)
- Expired - Fee Related
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 13
- 238000012360 testing method Methods 0.000 claims abstract description 16
- 201000003152 motion sickness Diseases 0.000 claims description 28
- 238000005259 measurement Methods 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 3
- 230000009012 visual motion Effects 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 abstract description 17
- 238000012545 processing Methods 0.000 abstract description 5
- 238000010219 correlation analysis Methods 0.000 abstract description 4
- 238000012216 screening Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000036544 posture Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- DHSSDEDRBUKTQY-UHFFFAOYSA-N 6-prop-2-enyl-4,5,7,8-tetrahydrothiazolo[4,5-d]azepin-2-amine Chemical compound C1CN(CC=C)CCC2=C1N=C(N)S2 DHSSDEDRBUKTQY-UHFFFAOYSA-N 0.000 description 1
- 206010063746 Accidental death Diseases 0.000 description 1
- 238000012935 Averaging Methods 0.000 description 1
- 206010013654 Drug abuse Diseases 0.000 description 1
- 206010028813 Nausea Diseases 0.000 description 1
- 208000008589 Obesity Diseases 0.000 description 1
- 208000018737 Parkinson disease Diseases 0.000 description 1
- 206010047513 Vision blurred Diseases 0.000 description 1
- 230000003925 brain function Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 208000002173 dizziness Diseases 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 210000003141 lower extremity Anatomy 0.000 description 1
- 230000008693 nausea Effects 0.000 description 1
- 210000000653 nervous system Anatomy 0.000 description 1
- 235000020824 obesity Nutrition 0.000 description 1
- 230000007170 pathology Effects 0.000 description 1
- 230000001766 physiological effect Effects 0.000 description 1
- 230000035935 pregnancy Effects 0.000 description 1
- 230000011514 reflex Effects 0.000 description 1
- 230000000284 resting effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 208000011117 substance-related disease Diseases 0.000 description 1
- 229950008418 talipexole Drugs 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000001720 vestibular Effects 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1116—Determining posture transitions
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/10—Athletes
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medical Informatics (AREA)
- Engineering & Computer Science (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Veterinary Medicine (AREA)
- Physiology (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Biophysics (AREA)
- Heart & Thoracic Surgery (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a kind of balance detection methods based on Wii Balance board, qualified subject is selected by stringent screening conditions to test, and acquires the balancing information of subject front and back different gestures using WBB and is recorded by matlab program.Same amount of record data are selected to carry out centralization processing, to treated, data calculate corresponding balance index, the experiment front and back variation of different indexs is obtained after the completion of calculating, correlation analysis is carried out in conjunction with the cinetosis change of rank amount of subject, to obtain the calculating that the weight of different balance indexs participates in total balance index, finally obtaining total balance index can the scientific and reasonable change conditions for characterizing balance.
Description
Technical Field
The invention belongs to the technical field of balance detection, and particularly relates to a balance detection method based on a Wii Balanceboard.
Background
Visual Induced Motion Sickness (VIMS) is a physiological discomfort phenomenon that some people cause dizziness, blurred vision, nausea and the like when watching 3D video. When technologies such as 3D and Virtual Reality (VR) are rapidly developed, such a phenomenon has become a great obstacle to user experience, and therefore, it is urgent to solve the problem. Motion sickness is a physiological phenomenon of the human body which is related to and complicated by physiological reactions, and no study has been made to give detailed analysis on the physiological phenomenon. One of the remarkable phenomena of motion sickness is deterioration of the balance of the human body, and the human balance ability is a complicated brain function. It plays an important role in people's daily life and is also an important competitive game in some sports, and generally excellent athletes all have better balance ability. Balance ability is also extremely important for patients with balance problems (stroke, parkinson's disease, etc.), and impaired balance ability can lead to falls, a major cause of accidental death in the elderly. Therefore, it is important to study and measure the balance of the human body, whether in VIMS or otherwise.
In the prior art, the Balance Board Wii Balance Board (WBB) is a very good Balance measuring tool. WBB not only has very high reliability and accurate sensitivity, but also is cheap, simple and practical. In the testing process, a Matlab program is used for collecting a center of pressure (CoP) and sensor information on a balance plate, then the collected information is subjected to centralization processing, and ideal time period data is selected for accurate analysis. Most researches generally adopt two indexes of average CoP path rate and average absolute swing distance as parameters for balancing, and the invention provides three other indexes on the basis of the two indexes: the area of the CoP main domain (domin _ area), the standard deviation of the CoP and the standard deviation of the CoP rate are selected, and five subjects are selected for experiments in total, and the results show that the two indexes before the three indexes are corrected have higher characterization capability, can well describe the obvious balance change of the current subjects after the experiments, and can more specifically explain the motion sickness condition of the subjects by combining with the subjective questionnaires of the three indexes.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a Balance detection method based on a Wii Balance board, which judges the Balance change of a tester through five Balance indexes and has the characteristics of simplicity, practicability, accurate judgment and the like.
In order to achieve the above object, the present invention provides a Balance detection method based on a Wii Balance board, comprising the steps of:
(1) obtaining balance information through balance board measurement
Measuring the body Balance of a tester under different states by using a Wii Balance board, recording a center of pressure (CoP) and a time stamp of a human body through a matlab program, and writing the CoP and the CoP into a recording file;
(2) calculating the balance index
Selecting all CoP points in 1min under a certain state from the record file, and then calculating the balance index under the state;
(2.1) Main Domain _ area
Solving the coordinate mean value of all the CoP points on the x axis and the y axis to obtain a virtual central point, and then solving the distance value between each CoP point and the virtual central point;
sorting all the distance values from small to large and storing the distance values in an array sorted _ data [ ], and solving the area of a circle by taking the sorted kth distance value as a radius to obtain a main domain area domain _ area;
sorted_data[]＝sort(data[])
domain_area＝π×(sorted_data[λ×num])2
wherein sorted () is a sorting function, λ is a parameter factor;
(2.2) CoP Standard deviation stdCoP
Calculating the standard deviation std of all CoP points in the x-axis and y-axis componentsCoP_x、stdCoP_yThen, the CoP standard deviation std of all CoP points is calculatedCoP；
Wherein n represents the number of CoP points, xi,yiRespectively represent coordinate values of the ith CoP point,coordinate values representing a virtual center point;
(2.3) CoP Rate Standard deviation
Velocity vel of adjacent CoP pointsi；
Where dis () is a function of the distance between two points, timeiIs the ith timestamp, veliIs the ith rate value;
calculating a CoP rate standard deviation vel _ std:
wherein,is the average of the rates of all neighboring CoP points;
(2.4) average CoP Path Rate vel _ mean
(2.5) average absolute CoP rocking distance sway _ dis _ mean
Wherein,representing a virtual center point;
(3) the overall balance index balance _ index
Wherein r isjIndex being the correlation coefficient of each index with visual motion sicknessjIs a corresponding balance index;
(4) and (4) calculating the overall balance index of the tester in other states according to the methods in the step (2) and the step (3), and judging the body balance of the tester according to the overall balance index in each state.
The invention aims to realize the following steps:
the Balance detection method based on the Wii Balance board selects qualified subjects through strict screening conditions for testing, and acquires Balance information of different postures before and after the test of the subjects by using WBB and records the Balance information through matlab program. Selecting the same amount of recorded data to perform centralized processing, calculating corresponding balance indexes for the processed data, obtaining the fluctuation amount of different indexes before and after the experiment after the calculation is completed, and performing correlation analysis by combining the fluctuation amount of the motion sickness grade of the subject, so that the weights of the different balance indexes are obtained to participate in the calculation of the total balance index, and finally the obtained total balance index can scientifically and reasonably represent the fluctuation condition of the balance.
Meanwhile, the Balance detection method based on the Wii Balance board further has the following beneficial effects:
(1) the balance index provided by the invention can measure the balance from different aspects, makes up the single dilemma of the traditional balance index, effectively combines each index through correlation analysis, and provides the change condition of the balance of the overall index more scientifically and reasonably.
(2) The balance plate is greatly promoted to be used for scientific research and people life, and the balance measurement becomes simple and quick for the construction of the balance index system. The balance board is easy to use and entertaining, and is popular with people; the balance detection tool can be pushed out simply and easily, is convenient for patients with poor balance to carry out effective rehabilitation treatment, can also be used for training and detection of physical exercise personnel, is greatly beneficial to the physical health of people, and improves the life quality of people.
Drawings
FIG. 1 is a diagram of a test apparatus for a Balance board Wii Balance board;
FIG. 2 is a schematic diagram of a virtual reality based dynamic driving simulator;
FIG. 3 is a schematic diagram of an evaluative experimental procedure leading to VIMS;
FIG. 4 is an experimental process and data processing flow diagram;
FIG. 5 is a trace plot of CoP points at different positions before and after the experiment.
Detailed Description
The following description of the embodiments of the present invention is provided in order to better understand the present invention for those skilled in the art with reference to the accompanying drawings. It is to be expressly noted that in the following description, a detailed description of known functions and designs will be omitted when it may obscure the subject matter of the present invention.
Examples
FIG. 1 is a diagram of a test apparatus for a Balance board Wii Balance board.
In this embodiment, as shown in fig. 1, Wii Balance Board (WBB) has excellent performance and stable reliability in measuring Balance, and the WBB is connected to a computer via bluetooth, has a sampling frequency of 30HZ, and has four pressure sensors under a rigid Balance Board, and is located at four corners.
During the test, the coordinate position of the CoP can be calculated by 4 pressure sensors. As shown in the figure1, assuming that the forces of the 4 pressure sensors are respectively expressed as fTL,fTR,fBLAnd fBL(unit: kg); the size of the balance plate is W × H (cm), and in this example, H is 22.8cm, and W is 43.3 cm. Thus, the coordinates of CoP (x, y) can be calculated by:
in general, a smaller CoP swing in a given time implies better balancing capability. For better repeatability we used the same equipment for all tests.
In this example, five young health testers were selected for the balance test. The selection criteria should follow the following principles: healthy persons without any psychiatric, psychological, pregnancy, psychiatric history, major lower limb pathology, long term medication or drug abuse history, or any disease affecting stance balance such as obesity. Finally the tester is ready to stand still for a suitable period of time (typically 30-40 seconds) while resting on the upper balance board to ensure that his centre of gravity remains at a relatively stable level.
Next, in this embodiment, the balance measurement takes six different postures: open-eye standing with both legs (OB) and closed-eye standing with both legs (CB), open-eye standing with left leg (OL) and open-eye standing with right leg (OR), closed-eye standing with left leg (CL) and closed-eye standing with right leg (CR). The tester was asked to place both hands vertically on both sides of the body during the six test poses. When participants were performing a two-leg test, requiring slippers and placing both feet on the foot area above the balance board, their hands were placed on both sides of the body with the legs supported to be straight during the test. The foot lifted when standing on one leg was about 10cm from the balance board and there was no contact between the lifted foot and the finished leg during the test.
The Balance detection method based on the Wii Balance board is explained in detail below, and comprises the following steps:
(1) obtaining balance information through balance board measurement
Measuring the body Balance of a tester under 6 states by using a Wii Balance board, recording a center of pressure (CoP) and a time stamp of a human body under each state through a matlab program, and writing the CoP and the time stamp into a recording file;
(2) calculating the balance index
Selecting all CoP points within 1min under a first state (both legs are open and the eyes are standing), in the embodiment, the sampling frequency of WBB is 30HZ, therefore 1800 CoP points are selected, and then calculating the balance index under the state;
(2.1) Main Domain _ area
The main domain area is an index for balancing the CoP moving situation and is provided for eliminating the deviation error of the outlier, and the main domain area is specifically calculated as follows:
solving the coordinate mean value of all the CoP points on the x axis and the y axis to obtain a virtual central point, and then solving the distance value between each CoP point and the virtual central point;
sorting all the distance values from small to large and storing the distance values in an array data [ ], and solving the area of a circle by taking the sorted kth distance value as a radius to obtain a main domain area domain _ area;
sorted_data[]＝sort(data[])
domain_area＝π×(sorted_data[λ×num])2
wherein sort () is a sorting function, λ is a parameter factor, and takes a value of 0.8-1.0, where λ is 0.9 and num is a total data amount of distance values in this embodiment; k is λ × num;
in this embodiment, the kth distance value generally selects a value between 80% and 100% of all distance values, and in this embodiment, selects a value at 90%;
(2.2) CoP Standard deviationstdCoP
The CoP standard deviation is an index for representing the discrete condition of CoP, and the index also reflects the balance capability to a certain extent. The calculation method comprises the following steps: calculating the standard deviation std of all CoP points in the x-axis and y-axis componentsCoP_x、stdCoP_yThen, the CoP standard deviation std of all CoP points is calculatedCoP；
Where n is 1800 denotes the number of CoP points, and xi,yiRespectively represent coordinate values of the ith CoP point,coordinate values representing a virtual center point;
(2.3) CoP Rate Standard deviation
The CoP rate standard deviation is an index for measuring the speed of the CoP rate change, and the faster the rate change, the weaker the balance capability is. The calculation method comprises the following steps: velocity vel of adjacent CoP pointsi；
Where dis () is a function of the distance between two points, timeiIs the ith timestamp, veliIs the ith rate value; calculating a CoP rate standard deviation vel _ std:
wherein,is the average of the rates of all neighboring CoP points;
(2.4) average CoP Path Rate vel _ mean
The sum of the distances of all the CoP points adjacent to each other in sequence is calculated and then divided by the time
(2.5) average absolute CoP rocking distance sway _ dis _ mean
For all CoP points and mean valuesSumming the distances of the points (virtual center points) and then averaging;
wherein,representing a virtual center point;
(3) the overall balance index balance _ index
Wherein r isjFor each fingerIndex, the correlation coefficient of a target with visual motion sicknessjIs a corresponding balance index; wherein r isjSatisfies the following conditions:
wherein, XkIs the balance index variation statistic of sample k, YkFor the motion sickness level variation statistic of sample k,is the average of the respective statistics; m is the total amount of samples of the subject under different measurement states;
in this embodiment, 5 subjects are selected, and each subject selects 2 states, so that m is 10;
(4) and (4) calculating the overall balance index of the tester in other states according to the methods in the step (2) and the step (3), and judging the body balance of the tester according to the overall balance index in each state.
Experimental verification
As shown in fig. 2, a virtual reality based dynamic driving simulator was created, consisting of a moving cab and a 180 ° VR scene based projection screen, which stimulates the visual and vestibular nervous systems to produce VIMS. A three-stage protocol was designed for VIMS evaluation as shown in figure 3.
The first part is the initial part, the subject stands on the balance board in a quiet state, the eye-open state is recorded for 1min, the eye-closed state is recorded for 1min, and the balance condition of the subject in a normal state is recorded.
The second part is the generation of VIMS, which drives a long curved stretch that easily causes motion sickness in the subject. The level of motion sickness of the subject gradually increases during driving.
The third part is that the driving is stopped when the subject feels uncomfortable, the balance measurement is carried out on the subject after the stopping, the subject still keeps a quiet standing state on the balance board, and the eye-open standing state and the eye-closed standing state are recorded for one minute respectively.
Throughout the procedure, the subject's motion sickness rating was also recorded by subjective questionnaires, with the motion sickness rating being divided into five: normal (level 0), weak (level 1), normal (level 2), strong (level 3), intolerable (level 4). The overall experimental process and data processing flow chart is shown in fig. 4.
Five subjects are measured in the experiment, and a CoP trajectory graph is simulated through collected CoP data, so that the change situation of the human body pressure center can be more clearly seen. Fig. 5 is a graph showing CoP before and after the first test, fig. 5-a is a graph showing a measurement trace of open eyes before driving, fig. 5-b is a graph showing a measurement trace of closed eyes before driving, fig. 5-c is a graph showing a measurement trace of open eyes after driving, and fig. 5-d is a graph showing a measurement trace of closed eyes after driving. Similar to other subjects, it is obvious that the range of the CoP trace after the experiment is obviously increased compared with that before the experiment by observing the CoP trace map. We can therefore be sure that the experiment does have a physiological effect on the subject, thereby reducing its balance.
To specify the magnitude of the change in balance ability, we can calculate our balance index and combine it with the subject's subjective questionnaire to describe the problem, and table 1 shows the balance data change for the five indices. From table 1, it can be seen that the motion sickness degrees of the subjects before and after the experiment are obviously different, and with the increase of the motion sickness grade, the general tendency of each balance index is increased, and the increase degree is different from one person to another; of course, all index variations are not consistent, since like Domain _ area, average rocking distance, and CoP standard deviation are considered from the CoP range level, and CoP path rate and CoP rate standard deviation are considered from the CoP speed level. The change of the balance of the human body is also shown from the two aspects, and the change emphasis of each person is different. In general, the center of pressure of a part of a person can be kept in a relatively stable range during motion sickness, but the CoP rate of the part of the person fluctuates greatly. Subject 001 is when the level of motion sickness changes greatly, but several indexes at the range level only change slightly, but the CoP rate standard deviation changes greatly; while more subjects typically range in both CoP range and CoP rate variation. In addition, we note that the level of motion sickness for the closed eye condition is lower than for the open eye condition because the experiment was to test the subject for open eye condition first and then for closed eye condition, and thus the subject's motion sickness was alleviated when the closed eye condition was measured.
Table 1 shows the variation of five major balance indexes of the subjects
TABLE 1
In order to more clearly and intuitively explain the change of the index of each subject before and after the experiment, the change of the index of each subject before and after the experiment is compared, and the result is shown in table 2. As is clear from the data in the table, the index data becomes large as a whole when the motion sickness occurs. The level of motion sickness is obtained in the form of questionnaires and each person's motion sickness is differently endured, so we see that the amount of change in the index and the level of motion sickness are not so consistent. As shown by the OA-OB state of No. 001 and the CA-CB state of No. 002, the results of the motion sickness are quite different although the indexes of the two are similar. Therefore, the direct corresponding relation between the objective index data and the subjective feeling cannot be accurately considered in the experiment, and the experiment only proves that the objective index data can really measure the change condition of the balance by the subjective grade. In order to clarify that the five indices indicate the importance of the results, correlation analysis was made for the five indices and the motion sickness results. The results show that Domain _ area is in significant positive correlation with the motion sickness level (r ═ 0.813)**Significance level 0.01), CoP standard deviation was peaceful with motion sickness ratingPositive correlation (r ═ 0.562), CoP rate standard deviation with motion sickness level correlation coefficient r ═ 0.483, CoP path rate with motion sickness level correlation coefficient r ═ 0.402, average rocking distance with motion sickness level correlation coefficient r ═ 0.365 (generally when correlation coefficient r is between 0.33 and 0.7, we consider a flat positive correlation). Therefore, the importance degree of the balance index according to the relevance is ordered as follows: main domain area (domain _ area), CoP standard deviation, CoP rate standard deviation, CoP path rate, average rocking distance. In addition, a total balance weighting index balance _ index can be calculated according to the correlation magnitude of each index, and the balance variation condition is observed through the total balance weighting index balance _ index, so that the balance of the tester is further judged.
Table 2 is the data before and after the five balance index experiments for the subjects;
TABLE 2
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.
Claims (4)
1. A Balance detection method based on a Wii Balance board is characterized by comprising the following steps:
(1) obtaining balance information through balance board measurement
Measuring the body Balance of a tester under different states by using a Wii Balance board, recording a pressure center point (CoP) and a time stamp of a human body through a matlab program, and writing the CoP and the time stamp into a recording file;
(2) calculating the balance index
Selecting all CoP points in 1min under a certain state from the record file, and then calculating the balance index under the state;
(2.1) Main Domain _ area
Solving the coordinate mean value of all the CoP points on the x axis and the y axis to obtain a virtual central point, and then solving the distance value between each CoP point and the virtual central point;
sorting all the distance values from small to large and storing the distance values in an array sorted _ data [ ], and solving the area of a circle by taking the sorted kth distance value as a radius to obtain a main domain area domain _ area;
sorted_data[]＝sort(data[])
domain_area＝π×(sorted_data[λ×num])2
where num is the total amount of data of the distance value, sorted () is a sorting function, and λ is a parameter factor;
(2.2) CoP Standard deviation stdCoP
Calculating the standard deviation std of all CoP points in the x-axis and y-axis componentsCoP_x、stdCoP_yThen, the CoP standard deviation std of all CoP points is calculatedCoP；
Wherein n represents the number of CoP points, xi,yiRespectively represent coordinate values of the ith CoP point,coordinate values representing a virtual center point;
(2.3) CoP Rate Standard deviation
Velocity vel of adjacent CoP pointsi；
Where dis () is a function of the distance between two points, timeiIs the ith timestamp, veliIs the ith rate value;
calculating a CoP rate standard deviation vel _ std:
wherein,is the average of the rates of all neighboring CoP points;
(2.4) average CoP Path Rate vel _ mean
(2.5) average absolute CoP rocking distance sway _ dis _ mean
Wherein,representing a virtual center point;
(3) the overall balance index balance _ index
Wherein r isjIndex being the correlation coefficient of each index with visual motion sicknessjIs a corresponding balance index;
(4) and (4) calculating the overall balance index of the tester in other states according to the methods in the step (2) and the step (3), and judging the body balance of the tester according to the overall balance index in each state.
2. The method for detecting Balance based on Wii Balance board according to claim 1, wherein r isjSatisfies the following conditions:
wherein, XkIs the balance index variation statistic of sample k, YkFor the motion sickness level variation statistic of sample k,is the average of the respective statistics; m is the total amount of samples in different measurement states of the subject.
3. The method as claimed in claim 1, wherein the Wii Balance board is connected to a computer via bluetooth, and the sampling frequency is 30 HZ.
4. The Balance detecting method based on the Wii Balance board as claimed in claim 1, wherein four pressure sensors are provided at four corners of the Wii Balance board, and during the test, the coordinate position of CoP is calculated by using the values of 4 pressure sensors; the specific calculation is as follows:
let the stress of the 4 pressure sensors be fTL,fTR,fBLAnd fBLThe unit: kg; the length and width of the Wii Balance board are H multiplied by W (cm), and the coordinates of CoP (x, y) are as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610840259.6A CN106388830B (en) | 2016-09-22 | 2016-09-22 | Balance detection method based on Wii Balance board |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610840259.6A CN106388830B (en) | 2016-09-22 | 2016-09-22 | Balance detection method based on Wii Balance board |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106388830A CN106388830A (en) | 2017-02-15 |
| CN106388830B true CN106388830B (en) | 2019-05-28 |
Family
ID=57997318
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610840259.6A Expired - Fee Related CN106388830B (en) | 2016-09-22 | 2016-09-22 | Balance detection method based on Wii Balance board |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106388830B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108309236B (en) * | 2018-01-15 | 2021-08-27 | 新绎健康科技有限公司 | Human body balance evaluation method and system |
| CN109528201A (en) * | 2018-10-30 | 2019-03-29 | 天津科技大学 | A kind of balanced capacity detection method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201248696Y (en) * | 2008-06-24 | 2009-06-03 | 王培勇 | Body balance detecting instrument |
| US10660558B2 (en) * | 2013-03-29 | 2020-05-26 | San Diego State University Research Foundation | Apparatus and method for detecting clinically relevant changes in balance |
| JP2014204759A (en) * | 2013-04-10 | 2014-10-30 | 国立大学法人広島大学 | Standing posture balance evaluating/training system |
| CN104346518A (en) * | 2014-04-29 | 2015-02-11 | 奥美之路(北京)技术顾问有限公司 | Chinese population static balance capability assessment model |
-
2016
- 2016-09-22 CN CN201610840259.6A patent/CN106388830B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN106388830A (en) | 2017-02-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109637625B (en) | Self-learning fitness plan generation system | |
| US7513622B2 (en) | System and method of enhancing a retino-geniculo-cortical pathway for a particular physical activity | |
| US9078598B2 (en) | Cognitive function evaluation and rehabilitation methods and systems | |
| US10706730B2 (en) | Perceptual-cognitive-motor learning system and method | |
| US20180228430A1 (en) | System, method and apparatus for rehabilitation with tracking | |
| Ujevic et al. | Differences between health-related physical fitness profiles of Croatian children in urban and rural areas | |
| CN113693552A (en) | Visual fatigue monitoring method and device, electronic equipment and readable storage medium | |
| Roberts et al. | The Bath University rugby shuttle test (BURST): a pilot study | |
| WO2022193425A1 (en) | Exercise data display method and system | |
| CN110232963A (en) | A kind of upper extremity exercise functional assessment system and method based on stereo display technique | |
| CN104083174A (en) | Exercise ability evaluation model | |
| Spathis et al. | Reliability and validity of a talent identification test battery for seated and standing Paralympic throws | |
| CN106388830B (en) | Balance detection method based on Wii Balance board | |
| Cikajlo et al. | Movement analysis of pick-and-place virtual reality exergaming in patients with Parkinson’s disease | |
| CN110353692B (en) | System and method for evaluating physical ability, fatigue and recovery ability based on biological signals | |
| Lai et al. | Fun and accurate static balance training to enhance fall prevention ability of aged adults: a preliminary study | |
| Sterkowicz et al. | IMPORTANCE OF COORDINATION MOTOR ABILITIES IN EXPERT-LEVEL ON-SIGHT SPORT CLIMBING. | |
| CN208339523U (en) | A kind of evaluation system for sexy system training of being emotionally stable | |
| Kwak et al. | The effect of balance training using touch controller-based fully immersive virtual reality devices on balance and walking ability in patients with stroke: A pilot randomized controlled trial | |
| Obata et al. | Development of an Exercise Application to Support Physical Function Improvement and Training for Remote Workers | |
| TWI767447B (en) | Cognition evaluation system and method | |
| CN215128665U (en) | Balance testing device | |
| Spasić et al. | Differences in Balance with Eyes Closed, Eyes Opened and Virtual Reality Environment: A pilot-study | |
| CN107224697B (en) | Evaluation system and evaluation method for coordinative sensory system training | |
| US20220221486A1 (en) | Stillness Measurement Apparatus, System, and Method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190528 Termination date: 20190922 |