CN107167133B - Tooth brushing evaluation method - Google Patents
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- CN107167133B CN107167133B CN201710371541.9A CN201710371541A CN107167133B CN 107167133 B CN107167133 B CN 107167133B CN 201710371541 A CN201710371541 A CN 201710371541A CN 107167133 B CN107167133 B CN 107167133B
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Abstract
The invention discloses a tooth brushing evaluation method and system, wherein the method comprises the following steps: s1, acquiring a triaxial acceleration signal output by a triaxial accelerometer and a triaxial angular velocity signal output by a triaxial gyroscope in the intelligent toothbrush; s2, dividing the collected sampling data into a plurality of time window data by using a fixed-length window division method; s3, calculating the mean value of the triaxial acceleration data, the variance value of the resultant angular velocity data and the variance value of the triaxial angular velocity data of each time window data; carrying out attitude calculation on the quaternion of the sampled data obtained by calculation to obtain a relative Euler angle; s4, obtaining the tooth brushing time length, the tooth brushing coverage rate and the tooth brushing posture correcting rate according to the calculation result of the step S3; s5, multiplying the brushing time, the brushing coverage rate and the brushing posture correction rate by respective weights respectively, and adding to obtain a brushing evaluation result; the invention can comprehensively analyze the tooth brushing time, the tooth brushing coverage rate and the tooth brushing posture correcting rate to obtain a quantitative tooth brushing evaluation result.
Description
Technical Field
The invention relates to the technical field of oral health. And more particularly, to a method and system for evaluating teeth brushing.
Background
Research and investigation shows that the periodontal health rate of adults aged 35-44 years in China is only 14.5%, people have far behind oral health awareness in developed countries, and 85% of dental caries and periodontal disease can be avoided by effective tooth brushing.
At present, the standardized tooth brushing method recommended by the Chinese dental medical society is a horizontal vibrating brush method (simplified to brush method), and the brush method is a tooth brushing method capable of effectively removing dental plaque in gingival sulcus; the brushing brush is lightly wiped, so that the brushing method is mastered, dental plaques on each tooth surface can be cleared, and dental plaques in the tooth neck and the gingival sulcus can be effectively removed; the specific operation key is as follows: firstly, a toothbrush handle is held by hands, a brush head is placed at the neck part of a back tooth on one side in an oral cavity, bristles form an angle of about 45 degrees with a tooth surface, the bristles point to the tooth root direction (upper teeth and lower teeth), slight pressure is applied, so that part of the bristles enter a gingival sulcus, and part of the bristles are placed on gums; secondly, brushing teeth by taking 2-3 teeth as a group, brushing the teeth at the same part for at least 3-5 times by using a short-distance horizontal vibration reciprocating action, then rotating the toothbrush towards the direction of a dental crown, and continuously brushing the labial (buccal) lingual (palatal) surfaces of the teeth; after the first part is brushed, moving the toothbrush to the position of the next group of 2-3 teeth for replacement, keeping an overlapped area with the first part, and continuing brushing the teeth of the next part; fourthly, when brushing the front lingual surface, vertically placing the brush head on the tooth surface to enable the front brush hairs to contact the gingival margin, and brushing from top to bottom. Brushing the lower anterior lingual surface from bottom to top; when brushing the occlusal surface, the brush hair points to the occlusal surface and is brushed back and forth by slightly exerting force in a front-back short distance.
The tooth brushing research carried out by scientific research institutions shows that three problems exist when people brush teeth, so that the teeth are not brushed cleanly, and the teeth and the gum are damaged; firstly, the tooth brushing time is not enough, so that dental plaque on teeth cannot be completely removed; secondly, the brushing area is not complete enough (e.g. the inner side of a person's teeth is easily overlooked), resulting in some teeth not being brushed; third, the irregular brushing motion (e.g., lateral or longitudinal brushing rather than brushing) can lead to gum and tooth damage.
Through tooth brushing research and dental plaque observation carried out by scientific research institutions, an effective tooth brushing course capable of following brushing is developed, the tooth brushing time of 3 minutes is quantified, and according to the difficulty degree of accumulation and removal of dental plaque, the time required for brushing each tooth surface and the brushing method for brushing the teeth are set. The toothbrush is sleeved with an effective tooth brushing course, and scientific and rigorous clinical verification proves that the efficiency of removing dental plaque is remarkably improved.
At present, intelligent tooth brushing products become an important application of oral health, and some products in the market feed back tooth brushing effect of a user in a scoring mode based on sensor data; however, some of these scoring rules are only related to brushing time, some rely on zone identification only, and do not list an effective brushing method as an assessment guide, which is not comprehensive or reasonable.
Therefore, there is a need for a tooth brushing evaluation method and system that quantitatively evaluates tooth brushing quality in three dimensions, i.e., tooth brushing duration, action accuracy, and coverage of tooth brushing area.
Disclosure of Invention
The invention aims to provide a tooth brushing evaluation method and system, which can quantitatively evaluate tooth brushing quality and feed back an evaluation result to a user by starting from three dimensions of tooth brushing time length, action correctness and coverage degree of a tooth brushing area.
In order to achieve the purpose, the invention adopts the following technical scheme:
a tooth brushing evaluation method comprises the following steps:
s1, collecting triaxial acceleration signals output by a triaxial accelerometer and triaxial angular velocity signals output by a triaxial gyroscope in the intelligent toothbrush as sampling data;
s2, dividing the collected sampling data into a plurality of time window data by using a fixed-length window division method;
s3, calculating the mean value of the triaxial acceleration data, the variance value of the resultant angular velocity data and the variance value of the triaxial angular velocity data of each time window data; calculating quaternion of the sampled data, and performing attitude calculation on the quaternion to obtain a relative Euler angle;
s4, obtaining the tooth brushing time length according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data; obtaining the tooth brushing coverage rate according to the mean value and the relative Euler angle of the triaxial acceleration data of each time window data; obtaining the tooth brushing posture correcting rate according to the variance value of the three-axis angular velocity data of each time window data;
and S5, respectively multiplying the tooth brushing time length, the tooth brushing coverage rate and the tooth brushing posture correcting rate by the corresponding weights, and adding to obtain a tooth brushing evaluation result.
Preferably, step S1 further includes: the sampled data is filtered using a moving average filtering algorithm.
Preferably, in step S4, the obtaining the brushing time period according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data for each time window data further includes:
the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data are compared with a set brushing action experience threshold value to judge the brushing action, and the sum of the time window lengths of the time window data judged to be the brushing action is taken as the brushing time.
Preferably, the step S4, the obtaining of the brushing coverage according to the mean and the relative euler angles of the three-axis acceleration data of each time window data further comprises:
dividing the tooth area into an occlusal area and a non-occlusal area according to the comparison of the absolute values of the acceleration mean values of the X axis and the Y axis;
dividing an occlusal surface tooth area into an upper occlusal surface area and a lower occlusal surface area according to the positive and negative of the Y-axis acceleration mean value; according to the size of the relative Euler angle, the upper occlusal surface area is further divided into a left upper occlusal surface subarea and a right upper occlusal surface subarea, and the lower occlusal surface area is further divided into a left lower occlusal surface subarea and a right lower occlusal surface subarea;
dividing a non-occlusal surface tooth area into a non-occlusal surface upper tooth area and a non-occlusal surface lower tooth area according to the positive and negative values of the Y-axis acceleration mean value and the comparison between the Y-axis acceleration mean value and a non-occlusal surface empirical threshold value; dividing a non-occlusal surface upper tooth area into a non-occlusal surface upper tooth outer area and a non-occlusal surface upper tooth inner area according to the positive and negative of the X-axis acceleration mean value, and dividing a non-occlusal surface lower tooth area into a non-occlusal surface lower tooth outer area and a non-occlusal surface lower tooth inner area;
the outer side area of the upper teeth of the non-occlusal surface is further divided into a left upper outer subarea, a middle upper outer subarea and a right upper outer subarea according to the size of the relative Euler angle; further dividing the inner area of the upper teeth on the non-occlusal surface into a left upper inner subarea, a middle upper inner subarea and a right upper inner subarea; further dividing the outer area of the lower teeth of the non-occlusal surface into a left lower outer subarea, a middle lower outer subarea and a right lower outer subarea; further dividing the inner area of the lower teeth of the non-occlusal surface into a left lower inner subarea, a middle lower inner subarea and a right lower inner subarea;
and (3) carrying out the comparison judgment on the average value and the relative Euler angle of the triaxial acceleration data of each time window data to obtain a partition corresponding to each time window data:
and counting the sum of the time window lengths of the time window data corresponding to the partitions to serve as the coverage rate of the partitions, and adding the coverage rates of the partitions to obtain the brushing coverage rate.
Preferably, obtaining the brushing posture correction rate according to the variance value of the three-axis angular velocity data of each time window data further comprises:
the time window data in which the tooth brushing motion is determined and the corresponding tooth area is the tooth brushing area is determined as follows: if the variance values of the Z-axis angular velocity data of the time window data reach the set brushing experience threshold and are respectively greater than the variance values of X, Y-axis angular velocity data, determining that the time window data are time window data of brushing action;
and counting the sum of the time window lengths of the time window data corresponding to the tooth brushing areas as the posture correction rate of the tooth brushing areas, and adding the posture correction rates of the tooth brushing areas to obtain the tooth brushing posture correction rate.
Preferably, the brushing tooth area includes: a lower left lateral zone, a lower middle lateral zone, a lower right medial zone, a lower left medial zone, an upper left lateral zone, an upper middle lateral zone, an upper right lateral zone, an upper left medial zone, and an upper right medial zone.
Preferably, in step S5, the method further includes, before the tooth brushing duration, the tooth brushing coverage rate and the tooth brushing posture correction rate are multiplied by the respective weights and then added to obtain the tooth brushing evaluation result:
and judging whether the tooth brushing time is longer than 180 seconds or not, and if so, setting the tooth brushing time to be 180 seconds.
Preferably, the method further comprises:
and S6, feeding back the brushing time, the brushing coverage rate, the brushing posture correcting rate and the brushing evaluation result through voice or images.
A tooth brushing evaluation system for executing the tooth brushing evaluation method comprises an intelligent toothbrush for executing the step S1 and an intelligent terminal which is in wireless connection with the intelligent toothbrush and executes the steps S2-S5.
Preferably, the intelligent terminal also feeds back the brushing time, the brushing coverage rate, the brushing posture correction rate and the brushing evaluation result through voice or images.
The invention has the following beneficial effects:
according to the technical scheme, comprehensive analysis can be performed on three aspects of tooth brushing time, action correctness and coverage degree of a tooth brushing area, so that the tooth brushing quality is quantitatively evaluated, and an evaluation result is fed back to a user in real time.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
FIG. 1 shows a flow chart of a brushing assessment method.
Figure 2 shows a flow chart for calculating brushing time.
Figure 3 shows a schematic axial view of a three-axis accelerometer.
Fig. 4 shows a flow chart for identifying different dental zones.
Fig. 5 shows a schematic sectional, zoned view of an adult tooth.
FIG. 6 shows a flow chart for identifying a brush.
Detailed Description
In order to more clearly illustrate the invention, the invention is further described below with reference to preferred embodiments and the accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. It is to be understood by persons skilled in the art that the following detailed description is illustrative and not restrictive, and is not to be taken as limiting the scope of the invention.
As shown in fig. 1, the tooth brushing evaluation method disclosed by the invention comprises the following steps:
a tooth brushing evaluation method comprises the following steps:
s1, collecting three-axis acceleration signals output by a three-axis accelerometer and three-axis angular velocity signals output by a three-axis gyroscope in the intelligent toothbrush (including related products of the intelligent toothbrush) as sampling data, and filtering the sampling data by using a moving average filtering algorithm;
s2, dividing the collected sampling data into a plurality of time window data by using a fixed-length window division method;
s3, calculating the mean value of the triaxial acceleration data, the variance value of the resultant angular velocity data and the variance value of the triaxial angular velocity data of each time window data; calculating quaternion of the sampled data, and performing attitude calculation on the quaternion to obtain a relative Euler angle;
s4, obtaining the tooth brushing time length according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data; obtaining the tooth brushing coverage rate according to the mean value and the relative Euler angle of the triaxial acceleration data of each time window data; obtaining the tooth brushing posture correcting rate according to the variance value of the three-axis angular velocity data of each time window data;
s5, judging whether the tooth brushing time is longer than 180 seconds, if so, setting the tooth brushing time to be 180 seconds, and then respectively multiplying the tooth brushing time, the tooth brushing coverage rate and the tooth brushing posture correcting rate by the corresponding weights and adding to obtain a tooth brushing evaluation result;
and S6, feeding back the brushing time, the brushing coverage rate, the brushing posture correcting rate and the brushing evaluation result through voice or images.
Wherein the content of the first and second substances,
in the step S4, in the step S,
obtaining the brushing time period according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data further comprises:
the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data are compared with a set brushing action experience threshold value to judge the brushing action, and the sum of the time window lengths of the time window data judged to be the brushing action is taken as the brushing time.
Obtaining the brushing coverage rate according to the mean and relative euler angles of the three-axis acceleration data of each time window data further comprises:
dividing the tooth area into an occlusal area and a non-occlusal area according to the comparison of the absolute values of the acceleration mean values of the X axis and the Y axis;
dividing an occlusal surface tooth area into an upper occlusal surface area and a lower occlusal surface area according to the positive and negative of the Y-axis acceleration mean value; according to the size of the relative Euler angle, the upper occlusal surface area is further divided into a left upper occlusal surface subarea and a right upper occlusal surface subarea, and the lower occlusal surface area is further divided into a left lower occlusal surface subarea and a right lower occlusal surface subarea;
dividing a non-occlusal surface tooth area into a non-occlusal surface upper tooth area and a non-occlusal surface lower tooth area according to the positive and negative values of the Y-axis acceleration mean value and the comparison between the Y-axis acceleration mean value and a non-occlusal surface empirical threshold value; dividing a non-occlusal surface upper tooth area into a non-occlusal surface upper tooth outer area and a non-occlusal surface upper tooth inner area according to the positive and negative of the X-axis acceleration mean value, and dividing a non-occlusal surface lower tooth area into a non-occlusal surface lower tooth outer area and a non-occlusal surface lower tooth inner area;
the outer side area of the upper teeth of the non-occlusal surface is further divided into a left upper outer subarea, a middle upper outer subarea and a right upper outer subarea according to the size of the relative Euler angle; further dividing the inner area of the upper teeth on the non-occlusal surface into a left upper inner subarea, a middle upper inner subarea and a right upper inner subarea; further dividing the outer area of the lower teeth of the non-occlusal surface into a left lower outer subarea, a middle lower outer subarea and a right lower outer subarea; further dividing the inner area of the lower teeth of the non-occlusal surface into a left lower inner subarea, a middle lower inner subarea and a right lower inner subarea;
and (3) carrying out the comparison judgment on the average value and the relative Euler angle of the triaxial acceleration data of each time window data to obtain a partition corresponding to each time window data:
and counting the sum of the time window lengths of the time window data corresponding to the partitions to serve as the coverage rate of the partitions, and adding the coverage rates of the partitions to obtain the brushing coverage rate.
Obtaining the tooth brushing posture correction rate according to the variance value of the three-axis angular velocity data of each time window data further comprises:
the time window data in which the tooth brushing motion is determined and the corresponding tooth area is the tooth brushing area is determined as follows: if the variance values of the Z-axis angular velocity data of the time window data reach the set brushing experience threshold and are respectively greater than the variance values of X, Y-axis angular velocity data, determining that the time window data are time window data of brushing action;
and counting the sum of the time window lengths of the time window data corresponding to the tooth brushing areas as the posture correction rate of the tooth brushing areas, and adding the posture correction rates of the tooth brushing areas to obtain the tooth brushing posture correction rate.
The brushing tooth area includes: a lower left lateral zone, a lower middle lateral zone, a lower right medial zone, a lower left medial zone, an upper left lateral zone, an upper middle lateral zone, an upper right lateral zone, an upper left medial zone, and an upper right medial zone.
The tooth brushing evaluation method can be divided into four steps from another aspect: calculating the tooth brushing time length and multiplying the tooth brushing time length by the weight alpha of the tooth brushing time length to obtain a total score of the tooth brushing time length, calculating the tooth brushing coverage rate and multiplying the tooth brushing coverage rate by the weight beta of the tooth brushing coverage rate to obtain a total score of the tooth brushing coverage rate, calculating the tooth brushing posture correcting rate and multiplying the tooth brushing posture correcting rate by the weight gamma of the tooth brushing posture correcting rate to obtain a total score of the tooth brushing posture correcting rate, wherein alpha + beta + gamma is 100, and finally adding the total score of the tooth brushing time length, the total score of the tooth brushing coverage rate and the total score.
Wherein the content of the first and second substances,
as shown in FIG. 2, calculating the brushing time duration and multiplying by the brushing time duration weight α to obtain the total score further comprises:
collecting three-axis acceleration signals output by a three-axis accelerometer and three-axis angular velocity signals output by a three-axis gyroscope arranged in the intelligent toothbrush as sampling data, wherein the sampling data comprises a three-axis acceleration signal a of the ith sampling pointx(i)、ay(i)、az(i) And three-axis angular velocity signal omegax(i)、ωy(i)、ωz(i) Axial information is shown in FIG. 3; then filtering the sampled data by using an n-order moving average filtering algorithm to eliminate noise influence; with n equal to 5, the signal a is outputx(i) For example, the moving average filter formula is:
dividing the acquired sampling data into a plurality of time window data by using a fixed-length window division method, wherein each time window data comprises sampling data of N sampling points (for example, a time window is 1 second, and the sampling frequency is 10Hz, so each time window data comprises the sampling data of 10 sampling points);
calculating the variance value of the resultant acceleration data and the variance value of the resultant angular velocity data of each time window data, wherein the resultant acceleration data of the time window data is
The resultant angular velocity data for the time window data is:the variance value of the combined acceleration data of the time window data is
Mean value of resultant acceleration data of time window dataThe variance value of the resultant angular velocity data of the time window data is
Wherein the mean value of the resultant angular velocity data of the time window data
And comparing the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data with a set tooth brushing action experience threshold value to judge the tooth brushing action, eliminating the static and random actions, and taking the sum of the time window lengths of the time window data which is judged to be the tooth brushing action as the tooth brushing time length.
After the tooth brushing time length is obtained, judging whether the tooth brushing time length is more than 180 seconds (3 minutes), if so, setting the tooth brushing time length to be 180 seconds, and if the tooth brushing time length is more than 180 seconds, scoring the tooth brushing time length as the tooth brushing time length weight alpha; if the brushing time is less than 180 seconds, for example, A seconds (A <180), the total brushing time is (A/180). times.alpha.
As shown in fig. 4, calculating the brushing coverage and multiplying by the brushing coverage weight β to obtain the total brushing coverage score further comprises:
collecting three-axis acceleration signals output by a three-axis accelerometer and three-axis angular velocity signals output by a three-axis gyroscope arranged in the intelligent toothbrush as sampling data, wherein the sampling data comprises a three-axis acceleration signal a of the ith sampling pointx(i)、ay(i)、az(i) And three-axis angular velocity signal omegax(i)、ωy(i)、ωz(i) Axial information is shown in FIG. 3; then filtering the sampled data by using an n-order moving average filtering algorithm to eliminate noise influence; with n equal to 5, the signal a is outputx(i) For example, the moving average filter formula is:
dividing the acquired sampling data into a plurality of time window data by using a fixed-length window division method, wherein each time window data comprises sampling data of N sampling points (for example, a time window is 1 second, and the sampling frequency is 10Hz, so each time window data comprises the sampling data of 10 sampling points);
calculating the mean value of the three-axis acceleration data of each time window data, wherein the mean value of the X-axis acceleration is
Mean value of acceleration of Y axis of
Mean value of Z-axis acceleration
Calculating quaternion of the sampling data, and carrying out attitude calculation on the quaternion to obtain a relative Euler angle;
dividing the tooth area into an occlusal surface area and an area non-occlusal surface area according to the comparison of the absolute values of the acceleration mean values of the X axis and the Y axis;
dividing an occlusal surface tooth area into an upper occlusal surface area and a lower occlusal surface area according to the positive and negative of the Y-axis acceleration mean value; according to the size of the relative Euler angle, the upper occlusal surface area is further divided into a left upper occlusal surface subarea and a right upper occlusal surface subarea, and the lower occlusal surface area is further divided into a left lower occlusal surface subarea and a right lower occlusal surface subarea;
dividing non-occlusal surface tooth areas (total 12 subareas) into non-occlusal surface upper tooth areas and non-occlusal surface lower tooth areas according to the positive and negative values of the Y-axis acceleration mean value and the comparison between the Y-axis acceleration mean value and the non-occlusal surface empirical threshold value; dividing a non-occlusal surface upper tooth area into a non-occlusal surface upper tooth outer area and a non-occlusal surface upper tooth inner area according to the positive and negative of the X-axis acceleration mean value, and dividing a non-occlusal surface lower tooth area into a non-occlusal surface lower tooth outer area and a non-occlusal surface lower tooth inner area;
the outer side area of the upper teeth of the non-occlusal surface is further divided into a left upper outer subarea, a middle upper outer subarea and a right upper outer subarea according to the size of the relative Euler angle; further dividing the inner area of the upper teeth on the non-occlusal surface into a left upper inner subarea, a middle upper inner subarea and a right upper inner subarea; further dividing the outer area of the lower teeth of the non-occlusal surface into a left lower outer subarea, a middle lower outer subarea and a right lower outer subarea; further dividing the inner area of the lower teeth of the non-occlusal surface into a left lower inner subarea, a middle lower inner subarea and a right lower inner subarea;
and (3) carrying out the comparison judgment on the average value and the relative Euler angle of the triaxial acceleration data of each time window data to obtain a partition corresponding to each time window data:
and counting the sum of the time window lengths of the time window data corresponding to the partitions to serve as the coverage rate of the partitions, and adding the coverage rates of the partitions to obtain the brushing coverage rate.
As shown in fig. 5 and table one, the identified region is 16 segments, each segment having its corresponding brushing time, and the coverage ratio of each segment is (1/16) × 100% ═ 6.25%. If a partition corresponds to a time ti`Second, the coverage rate of the subarea per second of the brush is (6.25/t)i`) X is 100%; according to the above rule, the total coverage rate after the tooth brushing is finished can be calculatedThe overall brushing coverage score is B x β.
Table one: adult tooth position sectional and sectional explanation
As shown in fig. 6, calculating the tooth brushing posture correcting rate and multiplying the tooth brushing posture correcting rate by the tooth brushing posture correcting rate weight γ to obtain the total score of the tooth brushing posture correcting rate further includes:
collecting three-axis acceleration signals output by a three-axis accelerometer and three-axis angular velocity signals output by a three-axis gyroscope arranged in the intelligent toothbrush as sampling data, wherein the sampling data comprises a three-axis acceleration signal a of the ith sampling pointx(i)、ay(i)、az(i) And three-axis angular velocity signal omegax(i)、ωy(i)、ωz(i) Axial information is shown in FIG. 3; then filtering the sampled data by using an n-order moving average filtering algorithm to eliminate noise influence; with n equal to 5, the signal a is outputx(i) For example, the moving average filter formula is:
dividing the acquired sampling data into a plurality of time window data by using a fixed-length window division method, wherein each time window data comprises sampling data of N sampling points (for example, a time window is 1 second, and the sampling frequency is 10Hz, so each time window data comprises the sampling data of 10 sampling points);
calculating the variance value of the combined acceleration data, the variance value of the combined angular velocity data and the variance value of the triaxial angular velocity data of each time window data, wherein the combined acceleration data of the time window data is
The resultant angular velocity data for the time window data is:
the variance value of the combined acceleration data of the time window data is
Mean value of resultant acceleration data of time window data
The variance value of the resultant angular velocity data of the time window data is
Wherein the mean value of the resultant angular velocity data of the time window data
The variance value of the X-axis angular velocity data is
Wherein
The variance value of the Y-axis angular velocity data isWherein
The variance value of the Z-axis angular velocity data is
Wherein
Comparing the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data with a set tooth brushing action experience threshold value to judge tooth brushing actions and eliminate static and random actions;
the time window data in which the tooth brushing motion is determined and the corresponding tooth area is the tooth brushing area is determined as follows: the Z-axis angular velocity data of the brushing action has obvious change, so that if the variance value of the Z-axis angular velocity data of the time window data reaches the set brushing experience threshold value and is respectively greater than the variance value of the X-axis angular velocity data and the variance value of the Y-axis angular velocity data, the time window data is judged to be the time window data of the brushing action;
and counting the sum of the time window lengths of the time window data corresponding to the tooth brushing areas as the posture correction rate of the tooth brushing areas, and adding the posture correction rates of the tooth brushing areas to obtain the tooth brushing posture correction rate.
As shown in table two, the brushing teeth area should be brushed for 10, and the ratio of the brushing posture correction rate per each partition is (1/10) × 100% ═ 10%; if the corresponding brushing time is tjSecond, the positive attitude ratio of the area per second of brushing is (10/t)j) 100% of the total weight; according to the above rule, the total posture correcting rate after the tooth brushing is finished can be calculated
The total score of the posture correcting rate of tooth brushing is C multiplied by gamma.
Table two description of coverage and posture correction ratio of tooth brushing
| Partitioning | Partition duration(s) | Percentage of coverage per second (%) | Brush with brush head | Ratio of posture correction per second (%) |
| Left lower |
12 | 0.52 | Is that | 0.83 |
| Middle lower |
9 | 0.69 | Is that | 1.11 |
| Lower right |
12 | 0.52 | Is that | 0.83 |
| Lower right |
18 | 0.35 | Is that | 0.56 |
| Middle lower |
9 | 0.69 | Whether or not | —— |
| Left lower |
18 | 0.35 | Is that | 0.56 |
| Upper left |
12 | 0.52 | Is that | 0.83 |
| Middle upper |
9 | 0.69 | Is that | 1.11 |
| Upper right |
12 | 0.52 | Is that | 0.83 |
| Upper right |
18 | 0.35 | Is that | 0.56 |
| Middle and upper |
9 | 0.69 | Whether or not | —— |
| Upper left |
18 | 0.35 | Is that | 0.56 |
| Upper left occlusal surface zone | 6 | 1.04 | Whether or not | —— |
| Left lower occlusal surface partition | 6 | 1.04 | Whether or not | —— |
| Right lower occlusal surface zone | 6 | 1.04 | Whether or not | —— |
| Upper right occlusal surface zone | 6 | 1.04 | Whether or not | —— |
The final brushing score is (A/180). alpha. + Bxbeta. + Cxgamma.
The specific value of each threshold in the invention depends on different types of sensors (sensors comprise a three-axis accelerometer and a three-axis gyroscope) of different manufacturers, and the value range and the precision of each type of sensor are different, so that a threshold which is generally applicable to all sensors cannot be given. The threshold may be determined as follows: after the sensors and corresponding associated hardware are selected, they are statistically derived by a dental professional in an experiment for a number of times.
The invention also discloses a tooth brushing evaluation system for executing the tooth brushing evaluation method, which comprises the intelligent toothbrush for executing the step S1 and an intelligent terminal which is in wireless connection with the intelligent toothbrush and executes the steps S2-S6, wherein the wireless connection can be Bluetooth or WIFI direct connection and the like, and the intelligent terminal can be an intelligent mobile phone or a tablet computer and the like.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.
Claims (8)
1. A method for evaluating tooth brushing, comprising the steps of:
s1, collecting triaxial acceleration signals output by a triaxial accelerometer and triaxial angular velocity signals output by a triaxial gyroscope in the intelligent toothbrush as sampling data;
s2, dividing the collected sampling data into a plurality of time window data by using a fixed-length window division method;
s3, calculating the mean value of the triaxial acceleration data, the variance value of the resultant angular velocity data and the variance value of the triaxial angular velocity data of each time window data; calculating quaternion of the sampled data, and performing attitude calculation on the quaternion to obtain a relative Euler angle;
s4, obtaining the tooth brushing time length according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data; obtaining the tooth brushing coverage rate according to the mean value and the relative Euler angle of the triaxial acceleration data of each time window data; obtaining the tooth brushing posture correcting rate according to the variance value of the three-axis angular velocity data of each time window data;
and S5, respectively multiplying the tooth brushing time length, the tooth brushing coverage rate and the tooth brushing posture correcting rate by the corresponding weights, and adding to obtain a tooth brushing evaluation result.
2. The tooth brushing evaluation method according to claim 1, wherein step S1 further comprises: the sampled data is filtered using a moving average filtering algorithm.
3. The method of claim 1, wherein the step S4 of obtaining a brushing time period according to the variance value of the combined acceleration data and the variance value of the combined angular velocity data for each time window data further comprises:
the variance value of the combined acceleration data and the variance value of the combined angular velocity data of each time window data are compared with a set brushing action experience threshold value to judge the brushing action, and the sum of the time window lengths of the time window data judged to be the brushing action is taken as the brushing time.
4. The toothbrushing evaluation method according to claim 3, wherein the step S4 of obtaining toothbrushing coverage based on the mean and relative Euler angles of the three-axis acceleration data of each time window data further comprises:
dividing the tooth area into an occlusal area and a non-occlusal area according to the comparison of the absolute values of the acceleration mean values of the X axis and the Y axis;
dividing an occlusal surface tooth area into an upper occlusal surface area and a lower occlusal surface area according to the positive and negative of the Y-axis acceleration mean value; according to the size of the relative Euler angle, the upper occlusal surface area is further divided into a left upper occlusal surface subarea and a right upper occlusal surface subarea, and the lower occlusal surface area is further divided into a left lower occlusal surface subarea and a right lower occlusal surface subarea;
dividing a non-occlusal surface tooth area into a non-occlusal surface upper tooth area and a non-occlusal surface lower tooth area according to the positive and negative values of the Y-axis acceleration mean value and the comparison between the Y-axis acceleration mean value and a non-occlusal surface empirical threshold value; dividing a non-occlusal surface upper tooth area into a non-occlusal surface upper tooth outer area and a non-occlusal surface upper tooth inner area according to the positive and negative of the X-axis acceleration mean value, and dividing a non-occlusal surface lower tooth area into a non-occlusal surface lower tooth outer area and a non-occlusal surface lower tooth inner area;
the outer side area of the upper teeth of the non-occlusal surface is further divided into a left upper outer subarea, a middle upper outer subarea and a right upper outer subarea according to the size of the relative Euler angle; further dividing the inner area of the upper teeth on the non-occlusal surface into a left upper inner subarea, a middle upper inner subarea and a right upper inner subarea; further dividing the outer area of the lower teeth of the non-occlusal surface into a left lower outer subarea, a middle lower outer subarea and a right lower outer subarea; further dividing the inner area of the lower teeth of the non-occlusal surface into a left lower inner subarea, a middle lower inner subarea and a right lower inner subarea;
and (3) carrying out the comparison judgment on the average value and the relative Euler angle of the triaxial acceleration data of each time window data to obtain a partition corresponding to each time window data:
and counting the sum of the time window lengths of the time window data corresponding to the partitions to serve as the coverage rate of the partitions, and adding the coverage rates of the partitions to obtain the brushing coverage rate.
5. The method for evaluating tooth brushing according to claim 4, wherein the step S4 of obtaining the tooth brushing posture correction rate according to the variance value of the three-axis angular velocity data of each time window data further comprises:
the time window data in which the tooth brushing motion is determined and the corresponding tooth area is the tooth brushing area is determined as follows: if the variance values of the Z-axis angular velocity data of the time window data reach the set brushing experience threshold and are respectively greater than the variance values of X, Y-axis angular velocity data, determining that the time window data are time window data of brushing action;
and counting the sum of the time window lengths of the time window data corresponding to the tooth brushing areas as the posture correction rate of the tooth brushing areas, and adding the posture correction rates of the tooth brushing areas to obtain the tooth brushing posture correction rate.
6. The tooth brushing assessment method according to claim 5, wherein the brushing tooth area comprises: a lower left lateral zone, a lower middle lateral zone, a lower right medial zone, a lower left medial zone, an upper left lateral zone, an upper middle lateral zone, an upper right lateral zone, an upper left medial zone, and an upper right medial zone.
7. The method of claim 1, wherein the step S5, before the step of adding the brushing time duration, the brushing coverage rate and the brushing posture correction rate multiplied by the respective weights to obtain the brushing evaluation result, further comprises:
and judging whether the tooth brushing time is longer than 180 seconds or not, and if so, setting the tooth brushing time to be 180 seconds.
8. The tooth brushing assessment method according to claim 1 further comprising:
and S6, feeding back the brushing time, the brushing coverage rate, the brushing posture correcting rate and the brushing evaluation result through voice or images.
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| CN108805390B (en) * | 2018-04-12 | 2021-07-30 | 浙江大学城市学院 | Intelligent tooth brushing process evaluation method |
| CN108904085B (en) * | 2018-04-13 | 2020-09-08 | 深圳市力博得科技有限公司 | Tooth brushing evaluation method, device and equipment based on intelligent toothbrush and storage medium |
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| CN110608753A (en) * | 2019-08-30 | 2019-12-24 | 深圳市云顶信息技术有限公司 | Oral cavity area identification method, oral cavity area identification device, computer equipment and storage medium |
| CN110619289B (en) * | 2019-08-30 | 2022-06-07 | 深圳市云顶信息技术有限公司 | Oral cavity area identification method, oral cavity area identification device, computer equipment and storage medium |
| CN111096540A (en) * | 2020-01-16 | 2020-05-05 | 深圳缇铭科技有限公司 | Method for guiding user to brush teeth, system for guiding user to brush teeth and storage device |
| CN112213134B (en) * | 2020-09-27 | 2022-09-27 | 北京斯年智驾科技有限公司 | Electric toothbrush oral cavity cleaning quality detection system and detection method based on acoustics |
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