CN112684920A - Self-adaptive adjusting method of mouse DPI and application thereof - Google Patents
Self-adaptive adjusting method of mouse DPI and application thereof Download PDFInfo
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Abstract
The invention provides a self-adaptive adjusting method of mouse DPI and application thereof. The mouse DPI value can be initially selected according to the user category, the selection efficiency is high, the calculation amount can be obviously reduced, and the initially selected mouse DPI value which is matched with the user category can be obtained for different user categories. The mouse DPI value is adjusted for the first time after the initial selection, and the adjustment of the mouse DPI value is completed through more than one time of subsequent adjustment, so that the mouse DPI value can be further more adaptive to the corresponding user category, and compared with the method for selecting the DPI value by adopting algorithms such as optimal iteration and the like in the prior art, the calculation amount can be obviously reduced, the workload of a host is reduced, the host is prevented from being halted or occupied with a large amount of calculation resources, and the adjustment time is short.
Description
Technical Field
The invention relates to the field of mice, in particular to a self-adaptive adjusting method of a mouse DPI and application thereof.
Background
The optical mouse is a commonly used electronic device, wherein the optical mouse mainly comprises four parts of core components, namely a light emitting component, a lens component, a photoelectric sensor and a control chip. When the mouse moves, the photoelectric sensor records continuous patterns, then the front and back comparison analysis processing of each picture is carried out to judge the moving direction and displacement of the mouse, so as to obtain the moving numerical values of the mouse in the x and y directions, and the numerical values are transmitted to the host after being processed. Wherein, DPI (dot per inch) is an important characteristic parameter of the mouse, DPI of the mouse is the positioning precision of the mouse, and the unit is DPI or cpi, which means the maximum information number that can be accurately positioned every inch of movement of the mouse. DPI is the number of points per inch, i.e., the number of points a pointer moves on the screen per inch of mouse movement.
The mouse in the prior art does not provide a DPI adjusting function, so that when a user actually uses the mouse, the DPI of the mouse needed by different scenes is not consistent, for example, when the user plays a game, the mouse needs to have a very high DPI, and when the user performs a drawing operation, the DPI needs to be lower. The DPI adjustment is to achieve the effect of adjusting the sensitivity of the mouse by adjusting the sampling frequency of the sensor so as to adapt the mouse to different working requirements. In the conventional technology, a user can only adjust the DPI of the mouse through a device manager on a host, so that the burden of the user is increased, the DPI is still fixed after adjustment, the flexibility is poor, the user can only adjust the DPI according to self feeling or subjective prediction, and the adjustment effect cannot achieve the expected purpose.
Aiming at the technical problem, the prior art provides an automatic mouse DPI adjusting method and a speed self-adaptive mouse capable of identifying different task types. The task environment used by the user is judged, the DPI value is automatically selected, namely the adaptive mouse speed is automatically selected, so that the requirements of the user on different tasks are met, the operation precision of a specific task can be improved, the operation time is shortened, the physical distance for the user to move the mouse is reduced, and fatigue is relieved.
However, the prior art has obvious defects, for example, different requirements of different types of users on the mouse DPI are not considered, and in practical situations, the number of task type users is usually multiple, uncertain and difficult to predict, so that the automatic adjustment method is applicable to few users, and is mostly an automatic adjustment method for the mouse DPI of a specific user in some specific professional fields.
In addition, in the prior art, for each task type, the gradient is adjusted by taking a specific value as the DPI, a user is required to test the operation efficiency under different gradients respectively according to the specification, and the workload is large and time-consuming for the user. In the prior art, the optimal mouse DPI value is solved through algorithms such as traversal or iteration, the calculated amount is large under the conditions of more parameters, larger data volume and the like, so that the calculation resources of a host are greatly occupied, the normal work of the host is influenced, and the host is halted or a long time is needed to obtain the solving result if serious conditions exist.
Further, in the prior art, the task type ID is determined by the ferz's law log2(D/W +1), and then the optimal DPI is tested for each task type ID to maximize the mouse operation efficiency. In practice, however, the optimal DPI required for the same task type ID is different in different application scenarios through operational efficiency, thus further making this prior art applicable only to specific scenarios.
In addition, in some prior art, the host needs to collect a large amount of data and complete the solution of the optimal mouse DPI value, and then generates an instruction to adjust the DPI value of the mouse. In a period of time before the adjustment is completed, the actual DPI value of the mouse is the DPI value before the adjustment, except that the adjustment process occupies computing resources, if the DPI value before the adjustment is not matched with the requirement, the mouse is still not matched with the actual requirement in the time during the adjustment process, and the use of a user is influenced.
In addition, in the prior art, only the user authentication method based on the behavior habit of the user mouse is used, so that the required data volume is extremely large, the method is not suitable for user classification aiming at DPI selection, and the user classification methods in other fields are not suitable for user classification aiming at DPI selection.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a self-adaptive adjusting method of a mouse DPI and application thereof, which are applicable to various user categories, have small calculated amount and high adjusting speed, and the specific technical scheme is as follows:
a self-adaptive adjusting method of a mouse DPI is characterized in that flexible pressure and temperature sensors are respectively arranged at a plurality of positions on the top of the mouse, and the self-adaptive adjusting method comprises the following steps:
s1: identifying a user category, comprising:
s11: the method comprises the steps of taking the start of mouse movement as the start time of a click task, taking the click of the mouse as the end time of the click task, and collecting pressure information of the flexible pressure and temperature sensor at the end time to extract click force characteristics of a user; selecting a moment after the collection starting moment and before the collection finishing moment to collect the temperature information and the pressure information of the flexible pressure and temperature sensor so as to extract the temperature characteristics of the fingers of the user and the holding force characteristics of the fingers on the mouse;
s12: performing S11 for multiple times to obtain a preset amount of training data, wherein the training data comprise click strength characteristics, temperature characteristics and holding strength characteristics of fingers to the mouse of each click task;
s13: inputting the obtained training data into a preset training model for classification training to obtain a classification model;
s14: aiming at the current user, acquiring click strength characteristics, temperature characteristics and mouse holding strength characteristics of fingers on a mouse of a plurality of times of click tasks, and inputting the click strength characteristics, temperature characteristics and mouse holding strength characteristics into the concave classification model to obtain the category of the current user;
s2: selecting a mouse DPI value adaptive to a current user as an initial DPI value;
s3: adjusting a DPI value of the mouse:
s31: the method comprises the steps that a mouse starts to move to be clicked to serve as a click task, real-time coordinates of the mouse are collected according to a preset sampling frequency f1, a host receives sampling time and real-time coordinates of each time, the sampling time and the real-time coordinates are stored in a storage medium through a point location information table P, the point location information table P of subsequent multiple click tasks is collected continuously, and a plurality of obtained point location information tables P are stored;
s32: respectively reconstructing a track of each click task according to the point location information tables;
s33: grouping and screening the reconstructed trajectories according to the similarity to obtain a sample group;
s34: in the sample group, sequencing each corresponding track according to the start time of each click task, calculating the average speed of a mouse in each track, and then performing linear fitting on the average speed of each track;
s35: and correcting the DPI value of the mouse according to the slope of the straight line obtained by fitting.
In a specific embodiment, a first flexible pressure and temperature sensor is arranged on the left front side of the top of the mouse, a second flexible pressure and temperature sensor is arranged on the right front side of the top of the mouse, a third flexible pressure and temperature sensor is arranged on the left side wall, and a fourth flexible pressure and temperature sensor is arranged on the right side wall;
the specific implementation method of the S11 comprises the following steps: taking the start of mouse movement as the start time of a click task, taking the click of the mouse as the end time of the click task, and collecting the pressure information of the third flexible pressure and temperature sensor and the fourth flexible pressure and temperature sensor at the end time to extract the index finger click force characteristic and the middle finger click force characteristic of the user; selecting a moment after the collection starting moment and before the collection finishing moment to collect the temperature information and the pressure information of the first flexible pressure and temperature sensor to the fourth flexible pressure and temperature sensor so as to extract the temperature characteristics of the thumb, the index finger, the middle finger and the ring finger of the user and extract the holding force characteristics of the thumb, the index finger, the middle finger and the ring finger of the user on the mouse;
the specific implementation method of the S12 comprises the following steps: executing the S11 for multiple times to obtain a preset number of training data, wherein the training data comprise index finger click force, middle finger click force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force of each click task; the training data comprises index finger clicking force, middle finger clicking force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force of each clicking task.
In a specific embodiment, the specific implementation method of S2 includes:
s21: establishing a selection table P of initial DPI values of the mouse, wherein the selection table P comprises setting the initial DPI values of the mouse as I initial, and the selection method comprises the steps of selecting according to a formula I initial-I0 + K N, wherein I0 is a starting value, K is a constant, and N is a gradient variable; preferably, I0 is 200, K is 50, N e (1, 2, 3 … … 40);
s22: the DPI value adapted to the user category is selected from the selection table P and set as the initial DPI value of the mouse.
In a specific embodiment, where P is ═ AO [ T0, X0, Y0], Ai [ Ti, Xi, Yi ], … …, An [ Tn, Xn, Yn ] }, where AO is the initial mouse position for the click task, Ai represents the sampling time information at the ith time, Ti represents the time, Xi represents the abscissa of the mouse relative to the origin of coordinates, Yi represents the ordinate of the mouse relative to the origin of coordinates, and 0< i < n, where n represents the number of samples.
In a specific embodiment, the step of respectively reconstructing a track of each click task according to each point location information table includes:
s321: establishing a coordinate system;
s322: reconstructing each point in a point location information table P ═ AO [ T0, X0, Y0], Ai [ Ti, Xi, Yi ], … …, An [ Tn, Xn, Yn ] } in a coordinate system;
s323: connecting the points in sequence according to a time sequence and through a smooth curve to realize the reconstruction of a one-time click task;
s324: repeating the step S321 to the step S323 to realize the reconstruction of the next click task, and circulating the steps until the reconstruction of all the click tasks is completed;
the step of grouping the reconstructed trajectories according to the similarity comprises the following steps:
s341: calculating an included angle between a previous point position and a subsequent point position when the point position is taken as a center in the same track, setting the included angle as a deviation angle of the point position, and further calculating the deviation angle of each point position between a starting point and an end point in the same track;
s342: and step S341, calculating deviation angles of each point location in each track, and if all deviation angles in a certain track are smaller than a preset threshold, listing the track into a sample group until all tracks are screened.
In a specific embodiment, in step S47, the step of correcting the DPI value of the mouse according to the slope of the fitted straight line includes:
if the slope of the straight line obtained by fitting is less than 0, reducing the DPI value of the mouse by a preset decrement;
if the slope of the straight line obtained by fitting is greater than or equal to 0 and smaller than a preset slope threshold value of the straight line, maintaining the current DPI value of the mouse;
and if the slope of the straight line obtained by fitting is larger than the threshold value of the slope of the preset straight line, increasing the DPI value of the mouse by a preset increment.
In a specific embodiment, the predetermined slope threshold is 0.1.
In a specific embodiment, S4: and according to the method of S3, the DPI value of the mouse is adjusted more than once, and the adjustment of the DPI value of the mouse is completed.
A computer system combined by a mouse and a host is used for realizing the self-adaptive adjusting method of the mouse DPI in any technical scheme, and comprises the host and the mouse, wherein flexible pressure and temperature sensors are respectively arranged at a plurality of positions on the top of the mouse, the mouse is also provided with a detection module, a first communication module and an execution module, and the host is provided with a storage medium, a second communication module and a processing module;
the detection module is configured to acquire a real-time coordinate of the mouse according to a preset sampling frequency f1, the first communication module is configured to send acquisition information of the detection module to the host through the second communication module, the host is configured to generate a control instruction for controlling the DPI of the mouse according to the adaptive adjustment method for the DPI of the mouse according to any one of the foregoing technical solutions, and the execution module is configured to adjust the DPI of the mouse according to the control instruction of the host.
A computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the adaptive adjustment method for a mouse DPI according to any of the preceding claims.
The invention has at least the following beneficial effects:
according to the self-adaptive adjusting method of the mouse DPI, a preset amount of training data is obtained through the clicking strength characteristic and the temperature characteristic of each click task and the holding strength characteristic of fingers to the mouse, the obtained training data is input into a preset training model for classification training, so that a classification model is obtained, and the category of the current user is identified. The mouse operation habit of the user can be regarded as through clicking the dynamics characteristic, the dynamics characteristic that grips of finger to mouse, and the user is categorised based on the mouse operation habit of user of being convenient for, still passes through the metabolic information when the temperature characteristic is regarded as the user operation mouse simultaneously, combines the user classification who goes on behavioral habit and metabolic information from this, preference and fatigue degree when can truly reflect the user operation mouse more for subsequent selection and the adjustment of mouse DPI can be more corresponding.
Further, a DPI value adapted to the user category is selected from the selection table P and set as an initial DPI value of the mouse. Therefore, the mouse DPI value can be initially selected according to the user category, on one hand, the selection efficiency is high, the calculation amount can be obviously reduced, and on the other hand, the initially selected mouse DPI value which is matched with the mouse DPI value can be obtained for different user categories.
Further, in the specific adjusting method of the invention, real-time coordinates of the mouse are collected, the host respectively reconstructs a track of each click task according to the point location information table, and groups and screens the reconstructed tracks according to the similarity to obtain a sample group. Therefore, a track which is useful for adjusting the DPI of the mouse can be obtained through screening, noise is eliminated, accuracy of an adjusting result can be improved, and calculated amount can be reduced. Further, deviation angles of point positions in each track are calculated, and if all deviation angles in a certain track are smaller than a preset threshold value, the track is listed into a sample group until all tracks are screened. Therefore, the linear track and the approximate linear track which mainly act on the adjustment of the DPI value of the mouse and the user operation relation can be screened out, and noises such as curve tracks and the like are eliminated, so that the DPI adjustment is more suitable for the real use environment and the actual requirements of users.
Further, in the specific adjusting method of the present invention, in the sample group, each corresponding track is sorted according to the start time of each click task, the average speed of the mouse in each track is calculated, then the average speed of each track is linearly fitted, and the DPI value of the mouse is corrected according to the linear slope obtained by the fitting. Therefore, the DPI value of the mouse can be adjusted according to the speed change rule when the user operates the mouse, and compared with the prior art, the adjustment result is more fit with the actual situation.
Further, after the initial selection, the DPI value of the mouse is adjusted for the first time, and the DPI value of the mouse is adjusted for more than one time in a subsequent way. On one hand, compared with the initial selection, the mouse DPI value can be further more adapted to the corresponding user category by adjusting the mouse DPI value more than twice. On the other hand, compared with the prior art that the DPI value is selected by adopting the algorithms such as the optimal iteration and the like, the technical scheme of the invention can obviously reduce the calculation amount, thereby reducing the workload of the host computer, avoiding the host computer from crashing or occupying a large amount of calculation resources, and avoiding the slow adjustment caused by the infinite iteration in the prior art because the time length of each adjustment period is short and controllable.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a general flow chart of an adaptive adjusting method of a mouse DPI in an embodiment;
FIG. 2 is a flow diagram of identifying user categories in an embodiment;
FIG. 3 is a flowchart illustrating the first adjustment of the DPI value of the mouse according to the embodiment;
FIG. 4 is a flowchart illustrating reconstructing a track of each click task according to each point location information table in the embodiment;
fig. 5 is a flowchart illustrating grouping and screening of reconstructed trajectories according to similarity to obtain a sample group in the embodiment.
Detailed Description
The present invention will be further described with reference to the following embodiments. The drawings are only for purposes of illustration and are not to be construed as limiting the patent.
Examples
As shown in fig. 1 to fig. 5, the present embodiment provides an adaptive adjustment method for a DPI of a mouse, where flexible pressure and temperature sensors are respectively disposed at multiple positions on the top of the mouse.
Specifically, a first flexible pressure and temperature sensor is arranged on the left front side of the top of the mouse, a second flexible pressure and temperature sensor is arranged on the right front side of the top of the mouse, a third flexible pressure and temperature sensor is arranged on the left side wall of the mouse, and a fourth flexible pressure and temperature sensor is arranged on the right side wall of the mouse.
The self-adaptive adjusting method comprises the following steps:
s1: identifying a user category, comprising:
s11: the method comprises the steps of taking the start of mouse movement as the start time of a click task, taking the click of the mouse as the end time of the click task, and collecting pressure information of a flexible pressure and temperature sensor at the end time to extract click force characteristics of a user; and selecting a moment after the collection starting moment and before the collection ending moment to collect the temperature information and the pressure information of the flexible pressure and temperature sensor so as to extract the temperature characteristics of the fingers of the user and the holding force characteristics of the fingers on the mouse.
Specifically, the mouse starts to move as the starting time of a click task, the mouse click is used as the ending time of the click task, and the pressure information of a third flexible pressure temperature sensor and a fourth flexible pressure temperature sensor at the ending time is collected to extract the index finger click force characteristic and the middle finger click force characteristic of the user; and selecting a moment after the collection starting moment and before the collection finishing moment to collect the temperature information and the pressure information of the first flexible pressure and temperature sensor to the fourth flexible pressure and temperature sensor so as to extract the temperature characteristics of the thumb, the index finger, the middle finger and the ring finger of the user and extract the holding force characteristics of the thumb, the index finger, the middle finger and the ring finger of the user on the mouse.
S12: s11 is performed multiple times to obtain a preset amount of training data, which includes click strength characteristics, temperature characteristics, and finger-to-mouse grip strength characteristics of each click task. Among them, the number of execution times of S11 is preferably 100 or more.
Specifically, S11 is executed multiple times to obtain a preset number of training data, where the training data includes index finger click strength, middle finger click strength, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding strength, index finger holding strength, middle finger holding strength, and ring finger holding strength of each click task; the training data comprises index finger click force, middle finger click force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force of each click task.
S13: and inputting the obtained training data into a preset training model for classification training to obtain a classification model.
In particular, a training model can be constructed for classification using a split-type decision tree. Wherein, in the split decision tree, index finger click force, middle finger click force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force are attributes of characteristics. For one attribute, searching the splitting attribute of the root node, forming decision tree branches by samples with the same value of the splitting attribute in the training data, executing the steps in a recursive mode for each decision tree branch, and continuing splitting other attributes until the depth (the number of the levels of the nodes) of the decision tree reaches a preset threshold value or all the data attributes are used up.
In addition, other types of decision tree construction modes can be adopted in the embodiment, and other classification models, such as a random forest method, can also be adopted. For the specific method for training various classification models, reference may be made to the prior art, and details are not repeated in this embodiment.
S14: and aiming at the current user, acquiring the click strength characteristic and the temperature characteristic of the click task for a plurality of times (for example, 10-20 times) and the holding strength characteristic of the finger on the mouse, and inputting the characteristics into a classification model to obtain the category of the current user.
S2: and selecting the mouse DPI value adapted to the current user as the initial DPI value. The specific method comprises the following steps:
s21: the method comprises the steps of selecting according to a formula I initial (I0 + K N), wherein I0 is a starting value, K is a constant, and N is a gradient variable. Preferably, I0 is 200, K is 50, N ∈ (1, 2, 3 … … 40).
S22: the DPI value adapted to the user category is selected from the selection table P and set as the initial DPI value of the mouse.
In an exemplary embodiment, the step of selecting the DPI value adapted to the user category from the selection table P and setting as the initial DPI value of the mouse includes: and if any numerical value of the click strength characteristic, the temperature characteristic or the holding strength characteristic of the finger to the mouse of the user category is larger, selecting and setting the I initial with the DPI value of the mouse larger than a preset threshold value from the selection table P. And if any numerical value of the click strength characteristic, the temperature characteristic or the holding strength characteristic of the finger to the mouse of the user category is smaller, selecting and setting the I initial with the DPI value of the mouse smaller than the preset threshold value from the selection table P. Therefore, the initial DPI value of the mouse is set to be relatively large for a user who consumes large energy when operating the mouse, so that the user can move the mouse at a relatively high speed, the overall energy consumption of the user is reduced, and fatigue is delayed. The initial DPI value of the mouse is set to be relatively large for a user with low energy consumption when the mouse is operated, so that the user can accurately operate when editing or drawing a document, and the operation precision is improved.
The preset threshold is preferably 500. It should be noted that the preset threshold of 500 is only one preferred example, and those skilled in the art may set the preset threshold higher than 500, for example, 550, 600, 650, 700, etc., or set the preset threshold smaller than 500, for example, 450, 400, 350, etc., according to the specific application scenario and the user characteristics when implementing the adaptive adjustment method for the mouse DPI of the present embodiment.
Therefore, according to the adaptive adjustment method of the mouse DPI in the embodiment, a preset amount of training data is obtained through the clicking strength characteristic, the temperature characteristic and the mouse holding strength characteristic of fingers of each click task, the obtained training data is input into a preset training model for classification training, so that a classification model is obtained, and the category of the current user is identified. The mouse operation habit of the user can be regarded as through clicking the dynamics characteristic, the dynamics characteristic that grips of finger to mouse, and the user is categorised based on the mouse operation habit of user of being convenient for, still passes through the metabolic information when the temperature characteristic is regarded as the user operation mouse simultaneously, combines the user classification who goes on behavioral habit and metabolic information from this, preference and fatigue degree when can truly reflect the user operation mouse more for subsequent selection and the adjustment of mouse DPI can be more corresponding. Further, a DPI value adapted to the user category is selected from the selection table P and set as an initial DPI value of the mouse. Therefore, the mouse DPI value can be initially selected according to the user category, on one hand, the selection efficiency is high, the calculation amount can be obviously reduced, and on the other hand, the initially selected mouse DPI value which is matched with the mouse DPI value can be obtained for different user categories.
S3: adjusting a DPI value of the mouse:
s31: the method comprises the steps of taking a mouse as a click task when the mouse starts to move to click, collecting real-time coordinates of the mouse according to a preset sampling frequency f1, receiving sampling time and real-time coordinates each time by a host, initially storing the sampling time and the real-time coordinates in a storage medium through a point location information table P, continuously collecting the point location information table P of subsequent multiple click tasks, and storing a plurality of obtained point location information tables P.
Specifically, the mouse starts to move to click as a click task, real-time coordinates of the mouse are collected according to a preset sampling frequency f within a preset sampling period T, the host receives the sampling time and the real-time coordinates each time, and the real-time coordinates are stored in a storage medium through a point location information table P. Where, P is ═ AO [ T0, X0, Y0], Ai [ Ti, Xi, Yi ], … …, An [ Tn, Xn, Yn ] }, where AO is the initial mouse position of the click task, Ai represents the sampling time information at the ith time, Ti represents the time, Xi represents the abscissa of the mouse relative to the origin of coordinates, Yi represents the ordinate of the mouse relative to the origin of coordinates, 0< i < n, and n represents the number of sampling times. For example, AO [ T0, X0, Y0] represents An initial time T0, An abscissa X0 of the mouse relative to the origin of coordinates, An ordinate Y0 of the mouse relative to the origin of coordinates, and Ai [ Ti, Xi, Yi ] represents An i-th sampling time Ti, An abscissa Xi of the mouse relative to the origin of coordinates, An ordinate Yi of the mouse relative to the origin of coordinates, An [ Tn, Xn, Yn ] represents a sampling time Tn of a last sampling within a sampling period T, An abscissa Xn of the mouse relative to the origin of coordinates, and An ordinate Yn of the mouse relative to the origin of coordinates. Illustratively, the sampling frequency f may be 20HZ, i.e. 20 times per second.
And continuing to collect the point location information table P of the subsequent multi-click task according to the method, for example, continuing to collect the point location information table P of the subsequent 200-click task. Then, the plurality of point location information tables P are obtained.
S32: and respectively reconstructing the track of each click task according to the point location information tables.
The step of respectively reconstructing the track of each click task according to each point location information table comprises the following steps:
s321: and establishing a coordinate system.
S322: each point in the point location information table P is reconstructed in the coordinate system, where "AO" { AO [ T0, X0, Y0], Ai [ Ti, Xi, Yi ], … …, An [ Tn, Xn, Yn ] }.
S323: and connecting the points in sequence according to a time sequence and through a smooth curve to realize the reconstruction of the one-time click task.
S324: and repeating the step S441 to the step S443 to reconstruct the next click task, and circulating the steps until the reconstruction of all the click tasks is completed.
By the method, the track of each click task is respectively reconstructed according to each point location information table, so that the DPI value of the mouse can be adjusted by processing and analyzing the rule of the mouse track image.
S33: and grouping and screening the reconstructed tracks according to the similarity to obtain a sample group. The step of grouping the reconstructed tracks according to the similarity comprises the following steps:
s331: in the same track, for any point location, calculating an included angle between a previous point location and a next point location with the point location as a center, setting the included angle as a deviation angle of the point location, and further calculating the deviation angle of each point location between a starting point and an end point in the same track.
S332: and calculating deviation angles of point positions in each track according to the method in the step S451, and if all deviation angles in a certain track are smaller than a preset threshold value, listing the track into a sample group until the screening of all tracks is completed.
Preferably, the preset threshold value of the deviation angle ranges from 5 degrees to 15 degrees, and further preferably ranges from 10 degrees. Therefore, the straight line and the track similar to the straight line are listed in the sample group, and other tracks are eliminated. Practical tests show that when a user operates a mouse, the operation tracks mainly aiming at movement are straight tracks and approximate straight tracks, the DPI value of the mouse has a large influence on the straight tracks and the approximate straight tracks, and the DPI value of the mouse has a small significance on the operation of the user on other tracks, such as curve tracks with large deviation angles. The linear track and the approximate linear track which are mainly used for adjusting the DPI value of the mouse and the user operation relation are screened out, and noises such as curve tracks are eliminated, so that the DPI adjustment is more suitable for real use environments and actual requirements of users, the accuracy of adjustment results is improved, and the occupation of computing resources is reduced.
S34: in the sample group, sequencing each corresponding track according to the start time of each click task, calculating the average speed of the mouse in each track, and then performing linear fitting on the average speed of each track.
S35: and correcting the DPI value of the mouse according to the slope of the straight line obtained by fitting.
Specifically, in step S35, the step of correcting the DPI value of the mouse according to the slope of the fitted straight line includes:
if the slope of the straight line obtained by fitting is less than 0, reducing the DPI value of the mouse by a preset decrement;
if the slope of the straight line obtained by fitting is greater than or equal to 0 and smaller than a preset slope threshold value of the straight line, maintaining the current DPI value of the mouse;
and if the slope of the straight line obtained by fitting is larger than the threshold value of the slope of the preset straight line, increasing the DPI value of the mouse by a preset increment.
Illustratively, the preset straight-line slope threshold is 0.1. It should be noted that, for different users and different scenes, the preset slope threshold of the straight line may be changed.
Therefore, the DPI value of the mouse can be adjusted according to the speed change rule when the user operates the mouse, and compared with the prior art, the adjustment result is more fit with the actual situation. Specifically, when a user normally operates a mouse, along with the improvement of proficiency of the real-time program D0, for the movement of the mouse with a linear track and an approximate linear track, if the speed of the mouse is kept unchanged or slightly increased, the normal rule can be determined, it is indicated that the initial DPI value of the mouse selected according to the user category meets the user requirement and the operation habit, the slope of the straight line obtained by fitting is greater than or equal to 0 and smaller than a preset slope threshold value, and the mouse can maintain the current DPI value, that is, the DPI value of the mouse does not need to be adjusted. If the slope of the straight line obtained by fitting is less than 0, it indicates that although the proficiency level of the real-time program D0 is improved, the speed of moving the mouse by the user is reduced, and it can be determined that the user emphasizes the requirement on the operation precision in the real-time program D0, and the DPI value of the mouse can be reduced by a preset decrement, so that the DPI value of the mouse is more adaptive to the requirement of the user. If the slope of the straight line obtained by fitting is greater than the preset slope threshold value, it indicates that the proficiency level of the real-time program D0 is improved, but the mouse moving speed of the user is gradually increased, and it can be determined that the user emphasizes the requirement on the mouse moving speed in the real-time program D0, the DPI value of the mouse is increased by a preset increment, so that the DPI value of the mouse is more adaptive to the requirement of the user.
S4: and according to the method of the step S3, the DPI value of the mouse is adjusted for more than one time, and the adjustment of the DPI value of the mouse is completed. By carrying out more than one subsequent adjustment on the DPI value of the mouse, the adjustment result of the DPI value of the mouse can be corrected for the second time, and the adjustment accuracy is improved.
In this embodiment, the adjustment of the DPI value of the mouse is completed by performing the first adjustment and the more than one subsequent adjustment on the DPI value of the mouse after the initial selection. On one hand, compared with the initial selection, the mouse DPI value can be further more adapted to the corresponding user category by adjusting the mouse DPI value more than twice. On the other hand, compared with the prior art that the DPI value is selected by adopting the algorithms such as the optimal iteration and the like, the technical scheme of the invention can obviously reduce the calculation amount, thereby reducing the workload of the host and avoiding the host from crashing or occupying a large amount of calculation resources.
The embodiment also provides a computer system combining a mouse and a host, which is used for realizing the self-adaptive adjusting method of the mouse DPI of any scheme.
The detection module is used for acquiring real-time coordinates of the mouse according to a preset sampling frequency f, the first communication module is used for sending acquisition information of the detection module to the host through the second communication module, the host is used for generating a control instruction for controlling the DPI of the mouse according to the self-adaptive adjustment method of the DPI of the mouse in any scheme, and the execution module is used for adjusting the DPI of the mouse according to the control instruction of the host.
A computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the adaptive adjustment method for mouse DPI according to any of the previous aspects.
As one skilled in the art will appreciate, the drawings are merely schematic representations of one preferred implementation scenario and the blocks or flows in the drawings are not necessarily required to practice the present invention.
Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above-mentioned invention numbers are merely for description and do not represent the merits of the implementation scenarios.
The above disclosure is only a few specific implementation scenarios of the present invention, however, the present invention is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present invention.
Claims (10)
1. A self-adaptive adjusting method of a mouse DPI is characterized in that a plurality of positions on the top of the mouse are respectively provided with a flexible pressure temperature sensor, and the self-adaptive adjusting method comprises the following steps:
s1: identifying a user category, comprising:
s11: the method comprises the steps of taking the start of mouse movement as the start time of a click task, taking the click of the mouse as the end time of the click task, and collecting pressure information of the flexible pressure and temperature sensor at the end time to extract click force characteristics of a user; selecting a moment after the collection starting moment and before the collection finishing moment to collect the temperature information and the pressure information of the flexible pressure and temperature sensor so as to extract the temperature characteristics of the fingers of the user and the holding force characteristics of the fingers on the mouse;
s12: performing S11 for multiple times to obtain a preset amount of training data, wherein the training data comprise click strength characteristics, temperature characteristics and holding strength characteristics of fingers to the mouse of each click task;
s13: inputting the obtained training data into a preset training model for classification training to obtain a classification model;
s14: aiming at the current user, acquiring click strength characteristics, temperature characteristics and mouse holding strength characteristics of fingers on a mouse of a plurality of times of click tasks, and inputting the click strength characteristics, temperature characteristics and mouse holding strength characteristics into the concave classification model to obtain the category of the current user;
s2: selecting a mouse DPI value adaptive to a current user as an initial DPI value;
s3: adjusting a DPI value of the mouse:
s31: the method comprises the steps of taking the mouse as a click task when the mouse starts to move and click, collecting real-time coordinates of the mouse according to a preset sampling frequency f1, receiving the sampling time and the real-time coordinates by a host, and passing through a point location information table P in a storage mediumFirst stageStoring, and continuously collecting point location information table P of subsequent multi-click tasksFirst stageStoring the obtained multiple point location information tables PFirst stage；
S32: respectively reconstructing a track of each click task according to the point location information tables;
s33: grouping and screening the reconstructed trajectories according to the similarity to obtain a sample group;
s34: in the sample group, sequencing each corresponding track according to the start time of each click task, calculating the average speed of a mouse in each track, and then performing linear fitting on the average speed of each track;
s35: and correcting the DPI value of the mouse according to the slope of the straight line obtained by fitting.
2. The adaptive adjusting method of the mouse DPI according to claim 1, wherein a first flexible pressure and temperature sensor is arranged on the left front side of the top of the mouse, a second flexible pressure and temperature sensor is arranged on the right front side of the top of the mouse, a third flexible pressure and temperature sensor is arranged on the left side wall, and a fourth flexible pressure and temperature sensor is arranged on the right side wall;
the specific implementation method of the S11 comprises the following steps: taking the start of mouse movement as the start time of a click task, taking the click of the mouse as the end time of the click task, and collecting the pressure information of the third flexible pressure and temperature sensor and the fourth flexible pressure and temperature sensor at the end time to extract the index finger click force characteristic and the middle finger click force characteristic of the user; selecting a moment after the collection starting moment and before the collection finishing moment to collect the temperature information and the pressure information of the first flexible pressure and temperature sensor to the fourth flexible pressure and temperature sensor so as to extract the temperature characteristics of the thumb, the index finger, the middle finger and the ring finger of the user and extract the holding force characteristics of the thumb, the index finger, the middle finger and the ring finger of the user on the mouse;
the specific implementation method of the S12 comprises the following steps: executing the S11 for multiple times to obtain a preset number of training data, wherein the training data comprise index finger click force, middle finger click force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force of each click task; the training data comprises index finger clicking force, middle finger clicking force, thumb temperature, index finger temperature, middle finger temperature, ring finger temperature, thumb holding force, index finger holding force, middle finger holding force and ring finger holding force of each clicking task.
3. The adaptive adjustment method for mouse DPI according to claim 1, wherein the specific implementation method of S2 comprises:
s21: establishing a selection table P of initial DPI values of the mouse, including setting the initial DPI values of the mouse to IFirst stageThe selection method comprises the following steps of formula IFirst stage＝I0+ K × N, wherein I0Is a starting value, K is a constant, and N is a gradient variable; preferably, I0Is 200, K is 50, N is equal to (1, 2, 3 … … 40);
s22: the DPI value adapted to the user category is selected from the selection table P and set as the initial DPI value of the mouse.
4. The adaptive adjusting method of mouse DPI according to claim 1, wherein P isFirst stage＝{AO[T0，X0，Y0]，Ai[Ti，Xi，Yi]，……，An[Tn，Xn，Yn]AO is the initial position of the mouse of the click task, Ai represents the sampling time information at the ith time, Ti represents the time, Xi represents the abscissa of the mouse relative to the origin of coordinates, Yi represents the ordinate of the mouse relative to the origin of coordinates, and 0<i<n, n represents the number of samples.
5. The adaptive adjusting method of mouse DPI according to claim 1, wherein the step of reconstructing the trace of each click task according to each point location information table comprises:
s321: establishing a coordinate system;
s322: reconstructing a point location information table P in a coordinate systemFirst stage＝{AO[T0，X0，Y0]，Ai[Ti，Xi，Yi]，……，An[Tn，Xn，Yn]Points in (j) };
s323: connecting the points in sequence according to a time sequence and through a smooth curve to realize the reconstruction of a one-time click task;
s324: repeating the step S321 to the step S323 to realize the reconstruction of the next click task, and circulating the steps until the reconstruction of all the click tasks is completed;
the step of grouping the reconstructed trajectories according to the similarity comprises the following steps:
s341: calculating an included angle between a previous point position and a subsequent point position when the point position is taken as a center in the same track, setting the included angle as a deviation angle of the point position, and further calculating the deviation angle of each point position between a starting point and an end point in the same track;
s342: and step S341, calculating deviation angles of each point location in each track, and if all deviation angles in a certain track are smaller than a preset threshold, listing the track into a sample group until all tracks are screened.
6. The adaptive adjusting method of mouse DPI according to claim 1, wherein the step of modifying the DPI value of the mouse according to the fitted slope of the straight line in step S47 comprises:
if the slope of the straight line obtained by fitting is less than 0, reducing the DPI value of the mouse by a preset decrement;
if the slope of the straight line obtained by fitting is greater than or equal to 0 and smaller than a preset slope threshold value of the straight line, maintaining the current DPI value of the mouse;
and if the slope of the straight line obtained by fitting is larger than the threshold value of the slope of the preset straight line, increasing the DPI value of the mouse by a preset increment.
7. The adaptive adjusting method of mouse DPI according to claim 1, wherein the preset slope threshold is 0.1.
8. The adaptive adjustment method for mouse DPI according to claim 1, wherein S4: and according to the method of S3, the DPI value of the mouse is adjusted more than once, and the adjustment of the DPI value of the mouse is completed.
9. A computer system combining a mouse and a host, which is used for realizing the self-adaptive adjusting method of the mouse DPI according to any one of claims 1 to 8, and is characterized by comprising the host and the mouse, wherein flexible pressure and temperature sensors are respectively arranged at a plurality of positions on the top of the mouse, the mouse is further provided with a detection module, a first communication module and an execution module, and the host is provided with a storage medium, a second communication module and a processing module;
the detection module is used for acquiring real-time coordinates of the mouse according to a preset sampling frequency f1, the first communication module is used for sending acquisition information of the detection module to the host through the second communication module, the host is used for generating a control instruction for controlling the DPI of the mouse according to the adaptive adjustment method of the DPI of the mouse as claimed in any one of claims 1 to 8, and the execution module is used for adjusting the DPI of the mouse according to the control instruction of the host.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for adaptive adjustment of a mouse DPI according to any of the claims 1-8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117271271A (en) * | 2023-11-21 | 2023-12-22 | 深圳市利新联电子有限公司 | Hand fatigue identification method, system and storage medium based on mouse usage monitoring |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101105730A (en) * | 2007-08-20 | 2008-01-16 | 骆仲铙 | Mouse DPI preset value setting method and mouse |
| CN101714035A (en) * | 2009-11-07 | 2010-05-26 | 硕维科技有限公司 | Mouse DPI automatic regulation method and DPI automatic regulation mouse |
| CN103530546A (en) * | 2013-10-25 | 2014-01-22 | 东北大学 | Identity authentication method based on mouse behaviors of user |
| CN104252294A (en) * | 2013-06-26 | 2014-12-31 | 原相科技股份有限公司 | Computer system including mouse device with adjustable dpi based on screen size and operating method thereof |
| US20150097779A1 (en) * | 2013-10-08 | 2015-04-09 | Pixart Imaging Inc. | Method of adjusting sampling precision of a navigation device, related navigation device and related terminal device |
| CN105260041A (en) * | 2015-09-30 | 2016-01-20 | 中国航天员科研训练中心 | automatic mouse DPI adjusting method and speed-adaptive mouse |
| US9927883B1 (en) * | 2015-01-12 | 2018-03-27 | Google Llc | Mouse resolution estimation |
| CN107960124A (en) * | 2016-05-16 | 2018-04-24 | 深圳维盛半导体科技有限公司 | A kind of mouse and method of DPI automatic adjustments |
| CN109871676A (en) * | 2019-03-14 | 2019-06-11 | 重庆邮电大学 | Three identity identifying methods and system based on mouse behavior |
| CN110135487A (en) * | 2019-05-09 | 2019-08-16 | 国网山东省电力公司滨州供电公司 | A kind of computer user mouse Behavior modeling method |
| CN110347436A (en) * | 2019-07-13 | 2019-10-18 | 韶关市启之信息技术有限公司 | A kind of personalized method and system for adjusting mouse movement speed |
-
2020
- 2020-12-31 CN CN202011635280.5A patent/CN112684920B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101105730A (en) * | 2007-08-20 | 2008-01-16 | 骆仲铙 | Mouse DPI preset value setting method and mouse |
| CN101714035A (en) * | 2009-11-07 | 2010-05-26 | 硕维科技有限公司 | Mouse DPI automatic regulation method and DPI automatic regulation mouse |
| CN104252294A (en) * | 2013-06-26 | 2014-12-31 | 原相科技股份有限公司 | Computer system including mouse device with adjustable dpi based on screen size and operating method thereof |
| US20150002397A1 (en) * | 2013-06-26 | 2015-01-01 | Pixart Imaging Inc. | Computer system including mouse device with adjustable dpi based on screen size and operating method thereof |
| US20150097779A1 (en) * | 2013-10-08 | 2015-04-09 | Pixart Imaging Inc. | Method of adjusting sampling precision of a navigation device, related navigation device and related terminal device |
| CN103530546A (en) * | 2013-10-25 | 2014-01-22 | 东北大学 | Identity authentication method based on mouse behaviors of user |
| US9927883B1 (en) * | 2015-01-12 | 2018-03-27 | Google Llc | Mouse resolution estimation |
| CN105260041A (en) * | 2015-09-30 | 2016-01-20 | 中国航天员科研训练中心 | automatic mouse DPI adjusting method and speed-adaptive mouse |
| CN107960124A (en) * | 2016-05-16 | 2018-04-24 | 深圳维盛半导体科技有限公司 | A kind of mouse and method of DPI automatic adjustments |
| CN109871676A (en) * | 2019-03-14 | 2019-06-11 | 重庆邮电大学 | Three identity identifying methods and system based on mouse behavior |
| CN110135487A (en) * | 2019-05-09 | 2019-08-16 | 国网山东省电力公司滨州供电公司 | A kind of computer user mouse Behavior modeling method |
| CN110347436A (en) * | 2019-07-13 | 2019-10-18 | 韶关市启之信息技术有限公司 | A kind of personalized method and system for adjusting mouse movement speed |
Non-Patent Citations (4)
| Title |
|---|
| NAN ZHENG: ""An Efficient User Verification System Using Angle-Based Mouse Movement Biometrics"", 《ACM TRANSACTIONS ON INFORMATION AND SYSTEM SECURITY》 * |
| NAN ZHENG: ""An efficient user verification system via mouse movements"", 《COMPUTER AND COMMUNICATIONS SECURITY》 * |
| 王淼: ""行为截获技术对鼠标动力学身份认证的影响"", 《微电子学与计算机》 * |
| 陈宇: ""基于鼠标动力学的用户身份认证技术研究与实现"", 《中国优秀硕士学位论文全文数据库（电子期刊）信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117271271A (en) * | 2023-11-21 | 2023-12-22 | 深圳市利新联电子有限公司 | Hand fatigue identification method, system and storage medium based on mouse usage monitoring |
| CN117271271B (en) * | 2023-11-21 | 2024-03-22 | 深圳市利新联电子有限公司 | Hand fatigue identification method, system and storage medium based on mouse usage monitoring |
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