CN115984855B - Intelligent pen writing behavior feature analysis method and device - Google Patents
Intelligent pen writing behavior feature analysis method and device Download PDFInfo
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Abstract
The invention relates to the field of data processing, in particular to a method and a device for analyzing writing behavior characteristics of an intelligent pen, wherein the method comprises the following steps: collecting pressure data and writing notes; judging time interval conditions according to the pressure acquisition time interval, and slicing the pressure data to form a plurality of pressure slice data; performing writing behavior feature analysis on a plurality of pieces of pressure slice data according to pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values, and counting the number of marks to confirm the importance level of writing note data corresponding to the marked pressure values so as to form writing behavior features of writing notes; and marking the corresponding written notes in a corresponding form according to the importance levels corresponding to the pressure values in the writing behavior characteristics. According to the method, the importance degree of the note is obtained through analysis of the pressure value, so that automatic note marking is realized, and the processing effect and the processing efficiency of the writing behavior feature analysis of the intelligent pen are improved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a method and a device for analyzing writing behavior characteristics of an intelligent pen.
Background
The intelligent pen is mainly used for collecting information of writing marks on ordinary paper through dot matrix, electromagnetism and other technologies. The dot matrix pen and the electromagnetic pen respectively realize handwriting data acquisition through password identification, electromagnetic induction and other technologies.
Chinese patent application publication No.: the CN110515474a patent discloses a smart stylus comprising: a writing part for generating writing notes under the manipulation of writing behavior; the note acquisition device is used for acquiring the written notes and obtaining corresponding electronic notes; and the communication chip is used for uploading the electronic notes to a server so that the server can store the electronic notes.
In the prior art, the written notes generated by the user under the control of the writing behaviors are collected and stored, but the written notes of the writing behaviors of the user are stored, so that the processing efficiency in the characteristic analysis of the writing behaviors is low.
Disclosure of Invention
Therefore, the invention provides the method and the device for analyzing the writing behavior characteristics of the intelligent pen, which can solve the problem of low processing efficiency of the writing behavior characteristics analysis of the intelligent pen.
In order to achieve the above object, the present invention provides a method for analyzing writing behavior characteristics of an intelligent pen, the method comprising:
collecting pressure data of a pressure sensing device in the intelligent pen, and collecting writing notes of the intelligent pen;
judging whether the two pressure acquisition time intervals meet the time interval conditions according to the pressure acquisition time intervals, marking the previous pressure acquisition time in the two pressure acquisition time intervals meeting the first preset time interval conditions, and slicing the pressure data corresponding to the marked pressure acquisition time to form a plurality of pressure slice data;
performing writing behavior feature analysis on a plurality of pieces of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to comparison results, counting the number of marks to confirm the important grades of writing note data corresponding to the marked pressure values, and forming the writing behavior features corresponding to writing notes by the pressure values and the important grades;
corresponding form marking is carried out on the corresponding written notes according to the importance levels corresponding to the pressure values in the writing behavior characteristics;
and counting feedback data of the user for marking the written notes within a preset period time, and correcting a preset pressure value according to the number of error marks in the feedback data.
Further, when slicing the pressure data, judging whether two pressure acquisition time intervals in the pressure data meet the time interval conditions according to the pressure acquisition time intervals, wherein,
if the two pressure acquisition time intervals are judged to be in accordance with the first preset time interval condition, slicing the pressure data is determined, and the previous pressure acquisition time is marked;
if the two pressure acquisition time intervals are judged to be in accordance with the second preset time interval condition, the pressure data are not sliced;
the first preset time interval condition is that two pressure acquisition time intervals are larger than or equal to a preset pressure acquisition time interval, and the second preset time interval condition is that two pressure acquisition time intervals are smaller than the preset pressure acquisition time interval.
Further, when slicing the pressure data to form the pressure slice data, slicing a corresponding pressure value sequence in the pressure data according to the marked pressure acquisition time to form a plurality of pressure value sequence segments, and associating each pressure value sequence segment with the corresponding pressure acquisition time to form a pressure slice, wherein the pressure slice data comprises a plurality of pressure slices.
Further, when writing behavior characteristic analysis is performed on a plurality of pressure slice data, comparing a pressure value sequence section in the pressure slice with a preset pressure value, wherein,
if any pressure value in the pressure value sequence section accords with a first preset pressure value condition, performing text marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a second preset pressure value condition, carrying out digital marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a third preset pressure value condition, not marking the pressure value which accords with the first preset pressure value condition;
the first preset pressure value condition is that the pressure value is larger than a second preset pressure value, the second preset pressure value condition is that the pressure value is larger than or equal to the first preset pressure value and smaller than or equal to the second preset pressure value, the third preset pressure value condition is that the pressure value is smaller than the third preset pressure value, and the first preset pressure value is smaller than the second preset pressure value.
Further, when the pressure value meeting the preset pressure value condition is marked, counting the number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section, when any pressure value in the pressure value sequence section meets the first preset pressure value condition, counting the number of characters marks in the pressure value sequence section, when any pressure value in the pressure value sequence section meets the second preset pressure value condition, counting the number of the characters marks in the pressure value sequence section, judging the number of characters marks and the level of the number marks according to the preset number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section,
if the number of the character marks accords with a first preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is one level;
if the number of the character marks accords with a second preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is a second level;
if the number of the digital marks accords with a first preset digital mark condition, judging that the level of the number of the digital marks, namely the important level of the written note data corresponding to the pressure value sequence section, is three-level;
if the number of the digital marks accords with a second preset digital mark condition, judging that the level of the number of the digital marks is four, namely the important level of the written note data corresponding to the pressure value sequence section;
the first preset text marking condition is that the number of text marks is larger than or equal to the preset number of marks, the second preset text marking condition is that the number of text marks is smaller than the preset number of marks, the first preset digital marking condition is that the number of digital marks is larger than or equal to the preset number of marks, and the second preset digital marking condition is that the number of digital marks is smaller than the preset number of marks.
Further, corresponding form marking is carried out on the written notes corresponding to the written behavior characteristics, the written notes corresponding to the pressure value sequence sections are matched according to the pressure value sequence sections and the importance levels in the written behavior characteristics, the corresponding written notes are matched according to the pressure acquisition time corresponding to the pressure value sequence sections, the matched written notes are marked according to the importance levels corresponding to the pressure value sequence sections, and different importance levels correspond to different marking forms.
Further, if the two pressure acquisition time intervals are larger than the twice preset pressure acquisition time interval, judging that the intelligent pen is finished writing, forming an ending instruction, and ending acquiring the pressure data and the writing note data according to the ending instruction.
Further, the invention provides a writing behavior feature analysis method of an intelligent pen, which further comprises the following steps:
and forming an abnormal instruction when judging that any pressure value in the pressure value sequence section does not accord with the preset pressure value condition.
Further, the first preset pressure value and the second preset pressure value are corrected according to the number of error marks in the feedback data, two correction modes for correcting the first preset pressure value and the second preset pressure value are determined according to the number of error marks in the preset period time,
the first correction mode is that the error mark quantity selects a first preset correction coefficient to reduce the preset pressure value and the second preset pressure value under a first preset error mark condition;
the second correction mode is that the number of error marks does not correct the first preset pressure value and the second preset pressure value under a second preset error mark condition;
the first preset error marking condition is that the number of the error marks is larger than the number of the preset error marks, and the second preset error marking condition is that the number of the error marks is smaller than or equal to the number of the preset error marks.
The invention also provides an intelligent pen writing behavior characteristic analysis device, which comprises:
the acquisition module is used for acquiring pressure data of the pressure sensing device in the intelligent pen and acquiring writing notes of the intelligent pen;
the segmentation module is connected with the acquisition module and is used for judging whether the two pressure acquisition time intervals meet the time interval conditions according to the pressure acquisition time intervals, marking the previous pressure acquisition time in the two pressure acquisition time intervals meeting the first preset time interval conditions, and slicing the pressure data corresponding to the marked pressure acquisition time to form a plurality of pressure slice data;
the analysis module is connected with the segmentation module and is used for carrying out writing behavior feature analysis on a plurality of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to comparison results, counting the number of marks to confirm the importance level of writing note data corresponding to the marked pressure values, and forming the writing behavior features corresponding to writing notes by the pressure values and the importance level;
the marking module is connected with the analysis module and used for marking corresponding written notes in a corresponding mode according to the importance level corresponding to the pressure value in the writing behavior characteristic;
the correction module is connected with the marking module and used for counting feedback data of the user for marking the written notes in a preset period time and correcting a preset pressure value according to the number of error marks in the feedback data.
Compared with the prior art, the method has the advantages that the time interval conditions are judged according to the pressure acquisition time interval, the pressure data are sliced to form a plurality of pressure slice data, the slicing of the pressure data is realized, the continuous pressure data are sliced into one section, the accurate analysis is carried out on the pressure slice data, the writing behavior feature analysis is carried out on the plurality of pressure slice data according to the pressure value in the pressure slice data, the pressure value in the pressure slice data is compared with the preset pressure value, the pressure value is marked according to the comparison result, the number of marks is counted to confirm the important grade of writing note data corresponding to the marked pressure value, the pressure value and the important grade form the writing behavior feature of the corresponding writing note, the important grade of the corresponding note is determined according to the pressure value, the greater the pressure value is more important, the corresponding writing note is marked in a corresponding form according to the important grade of the pressure value in the writing behavior feature, the automatic marking of the note is realized, the automatic marking of the note is carried out through the analysis on the pressure value to obtain the important grade of the note, the automatic marking of the note is carried out, the preset pressure value is corrected according to the feedback data, the intelligent behavior feature analysis is improved, and the intelligent writing behavior feature analysis and the writing behavior feature analysis is more accurate.
In particular, by judging the time interval condition according to the pressure acquisition time interval and slicing whether the pressure data is determined, the pressure data is sliced, and continuous pressure data is sliced into a section for accurate analysis.
In particular, slicing the pressure data to form a plurality of pressure slice data, so as to realize slicing the pressure data, and slicing the continuous pressure data into a section for accurate analysis.
And finally, marking the corresponding written note in a corresponding form according to the importance level corresponding to the pressure value in the writing behavior characteristics, realizing automatic marking of the note, obtaining the importance level of the note through analysis of the pressure value, realizing automatic marking of the note, and improving the processing effect and efficiency of the writing behavior characteristic analysis of the intelligent pen.
In particular, the number of marks is counted to confirm the importance level of the written note data corresponding to the marked pressure value, the pressure value and the importance level are formed into the written behavior feature corresponding to the written note, the importance level of the corresponding note is determined according to the pressure value, the larger the pressure value is, the more important the representation is, and finally the corresponding written note is marked in a corresponding mode according to the importance level corresponding to the pressure value in the written behavior feature, so that the automatic marking of the note is realized, the importance level of the note is obtained through the analysis of the pressure value, the automatic marking of the note is realized, and the processing effect and the efficiency of the intelligent pen written behavior feature analysis are improved.
In particular, two correction modes for correcting the first preset pressure value and the second preset pressure value are determined according to the number of error marks in the preset period time, and the first preset pressure value and the second preset pressure value are continuously corrected through feedback data, so that the writing behavior feature analysis of the intelligent pen is more accurate, and the processing effect and the processing efficiency of the writing behavior feature analysis of the intelligent pen are improved.
Drawings
FIG. 1 is a schematic flow chart of a method for analyzing writing behavior characteristics of an intelligent pen according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for analyzing writing behavior characteristics of an intelligent pen according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an intelligent pen writing behavior feature analysis device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an analysis module in the intelligent pen writing behavior feature analysis device according to the embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, the method for analyzing writing behavior characteristics of an intelligent pen according to the embodiment of the invention includes:
step S110, collecting pressure data of a pressure sensing device in the intelligent pen, and collecting writing notes of the intelligent pen;
step S120, judging whether the two pressure acquisition time intervals meet the time interval conditions according to the pressure acquisition time intervals, marking the previous pressure acquisition time in the two pressure acquisition time intervals meeting the first preset time interval conditions, and slicing the pressure data corresponding to the marked pressure acquisition time to form a plurality of pressure slice data;
step S130, performing writing behavior feature analysis on a plurality of pieces of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to the comparison result, counting the number of marks to confirm the importance level of writing note data corresponding to the marked pressure values, and forming the pressure values and the importance level into writing behavior features corresponding to writing notes;
step S140, corresponding form marks are carried out on corresponding written notes according to the importance levels corresponding to the pressure values in the writing behavior characteristics;
and step S150, counting feedback data of the user for marking the written notes within a preset period time, and correcting a preset pressure value according to the number of error marks in the feedback data.
Specifically, the writing note data is writing note data which is acquired by an imaging device on the intelligent pen and identified according to the object, and can be characters, graphics or the like.
Specifically, the embodiment of the invention realizes the segmentation of pressure data by judging time interval conditions according to pressure acquisition time intervals and slicing the pressure data to form a plurality of pressure slice data, so that continuous pressure data is segmented into one section, the section is accurately analyzed, the writing behavior feature analysis is carried out on the plurality of pressure slice data according to the pressure value in the pressure slice data, the pressure value in the pressure slice data is compared with a preset pressure value, the pressure value is marked according to a comparison result, the number of marks is counted to confirm the importance level of writing note data corresponding to the marked pressure value, the pressure value and the importance level form the writing behavior feature of the corresponding writing note, the importance level of the corresponding note is determined according to the pressure value, the greater the pressure value is more important, the corresponding writing note is marked in a corresponding form according to the importance level corresponding to the pressure value in the writing behavior feature, the automatic marking of the note is realized, the importance level of the note is obtained through the analysis of the pressure value, the automatic marking of the note is realized, the first preset pressure value and the second preset pressure value are continuously corrected through feedback data, the intelligent pen behavior feature analysis is more accurate, and the writing behavior feature analysis effect is improved.
Specifically, when slicing the pressure data, judging whether two pressure acquisition time intervals in the pressure data meet the time interval conditions according to the pressure acquisition time intervals, wherein,
if the two pressure acquisition time intervals are judged to be in accordance with the first preset time interval condition, slicing the pressure data is determined, and the previous pressure acquisition time is marked;
if the two pressure acquisition time intervals are judged to be in accordance with the second preset time interval condition, the pressure data are not sliced;
the first preset time interval condition is that two pressure acquisition time intervals are larger than or equal to a preset pressure acquisition time interval, and the second preset time interval condition is that two pressure acquisition time intervals are smaller than the preset pressure acquisition time interval.
Specifically, the two pressure acquisition time intervals are time intervals between consecutive two pressure values.
Specifically, according to the embodiment of the invention, the time interval condition is judged according to the pressure acquisition time interval, and whether the pressure data are sliced is determined, so that the slicing of the pressure data is realized, and the continuous pressure data are sliced into a section for accurate analysis.
Specifically, when slicing the pressure data to form the pressure slice data, slicing a corresponding pressure value sequence in the pressure data according to the marked pressure acquisition time to form a plurality of pressure value sequence segments, and associating each pressure value sequence segment with the corresponding pressure acquisition time to form a pressure slice, wherein the pressure slice data comprises a plurality of pressure slices.
Specifically, the pressure data includes a pressure acquisition time and a pressure value corresponding to the acquisition time, and a plurality of pressure values form a pressure value sequence.
Specifically, the embodiment of the invention cuts the pressure data into a plurality of pressure slice data by slicing the pressure data, so that the continuous pressure data is cut into one section for accurate analysis.
Specifically, when writing behavior characteristic analysis is performed on a plurality of pressure slice data, comparing a pressure value sequence section in the pressure slice with a preset pressure value, wherein,
if any pressure value in the pressure value sequence section accords with a first preset pressure value condition, performing text marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a second preset pressure value condition, carrying out digital marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a third preset pressure value condition, not marking the pressure value which accords with the first preset pressure value condition;
the first preset pressure value condition is that the pressure value is larger than a second preset pressure value, the second preset pressure value condition is that the pressure value is larger than or equal to the first preset pressure value and smaller than or equal to the second preset pressure value, the third preset pressure value condition is that the pressure value is smaller than the third preset pressure value, and the first preset pressure value is smaller than the second preset pressure value.
Specifically, the text mark and the digital mark are only marks, can be set by themselves, and ensure that the marks conforming to the first preset pressure value condition and the second preset pressure value condition are different.
Specifically, according to the embodiment of the invention, the writing behavior feature analysis is carried out on a plurality of pieces of pressure slice data according to the pressure values in the pressure slice data, the pressure values in the pressure slice data are compared with the preset pressure values, different forms of marks are carried out on the pressure values according to the comparison result, the importance degree of corresponding notes is further determined, the larger the pressure values are, the more important the representation is, and finally the corresponding writing notes are correspondingly marked according to the importance level corresponding to the pressure values in the writing behavior feature, so that the automatic note marking is realized, the importance degree of the notes is obtained through the analysis of the pressure values, the automatic note marking is realized, and the processing effect and the processing efficiency of the writing behavior feature analysis of the intelligent pen are improved.
Specifically, when the pressure value meeting the preset pressure value condition is marked, counting the number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section, when any pressure value in the pressure value sequence section meets the first preset pressure value condition, counting the number of characters marks in the pressure value sequence section, when any pressure value in the pressure value sequence section meets the second preset pressure value condition, counting the number of the characters marks in the pressure value sequence section, judging the number of characters marks and the level of the number marks according to the preset number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section,
if the number of the character marks accords with a first preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is one level;
if the number of the character marks accords with a second preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is a second level;
if the number of the digital marks accords with a first preset digital mark condition, judging that the level of the number of the digital marks, namely the important level of the written note data corresponding to the pressure value sequence section, is three-level;
if the number of the digital marks accords with a second preset digital mark condition, judging that the level of the number of the digital marks is four, namely the important level of the written note data corresponding to the pressure value sequence section;
the first preset text marking condition is that the number of text marks is larger than or equal to the preset number of marks, the second preset text marking condition is that the number of text marks is smaller than the preset number of marks, the first preset digital marking condition is that the number of digital marks is larger than or equal to the preset number of marks, and the second preset digital marking condition is that the number of digital marks is smaller than the preset number of marks.
Specifically, the embodiment of the invention confirms the importance level of the written note data corresponding to the marked pressure value by counting the number of marks, forms the pressure value and the importance level into the written behavior feature of the corresponding written note, determines the importance level of the corresponding note according to the pressure value, and further marks the corresponding written note in a corresponding form according to the importance level corresponding to the pressure value in the written behavior feature, so as to realize automatic marking of the note, obtain the importance level of the note through analysis of the pressure value, realize automatic marking of the note and improve the processing effect and efficiency of the intelligent pen written behavior feature analysis.
Specifically, corresponding form marking is performed according to the written notes corresponding to the written behavior characteristics, the written notes corresponding to the pressure value sequence sections are matched according to the pressure value sequence sections and the importance levels in the written behavior characteristics, the corresponding written notes are matched according to the pressure acquisition time corresponding to the pressure value sequence sections, the matched written notes are marked according to the importance levels corresponding to the pressure value sequence sections, and different importance levels correspond to different marking forms.
Specifically, if the two pressure acquisition time intervals are larger than the twice preset pressure acquisition time interval, judging that the intelligent pen is finished writing, forming an ending instruction, and ending acquiring the pressure data and the writing note data according to the ending instruction.
Referring to fig. 2, the method for analyzing writing behavior characteristics of an intelligent pen according to the embodiment of the present invention further includes:
step S160, forming an abnormal command when it is determined that any pressure value in the pressure value sequence segment does not meet the preset pressure value condition.
Specifically, the abnormal instruction is used for prompting the intelligent pen to fail.
Specifically, the first preset pressure value and the second preset pressure value are corrected according to the number of error marks in the feedback data, two correction modes for correcting the first preset pressure value and the second preset pressure value are determined according to the number of error marks in the preset period time,
the first correction mode is that the error mark quantity selects a first preset correction coefficient to reduce the preset pressure value and the second preset pressure value under a first preset error mark condition;
the second correction mode is that the number of error marks does not correct the first preset pressure value and the second preset pressure value under a second preset error mark condition;
the first preset error marking condition is that the number of the error marks is larger than the number of the preset error marks, and the second preset error marking condition is that the number of the error marks is smaller than or equal to the number of the preset error marks.
Specifically, according to the embodiment of the invention, two correction modes for correcting the first preset pressure value and the second preset pressure value are determined according to the number of error marks in the preset period time, and the first preset pressure value and the second preset pressure value are continuously corrected through feedback data, so that the writing behavior feature analysis of the intelligent pen is more accurate, and the processing effect and the processing efficiency of the writing behavior feature analysis of the intelligent pen are improved.
Referring to fig. 3, an intelligent pen writing behavior feature analysis device provided in an embodiment of the present invention includes:
the acquisition module 210 is used for acquiring pressure data of the pressure sensing device in the intelligent pen and acquiring writing notes of the intelligent pen;
the slicing module 220 is connected with the acquisition module, and is used for judging time interval conditions according to the pressure acquisition time interval and slicing the pressure data to form a plurality of pressure slice data;
the analysis module 230 is connected with the segmentation module, and is used for performing writing behavior feature analysis on a plurality of pieces of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to the comparison result, counting the number of marks to confirm the importance level of the writing note data corresponding to the marked pressure values, and forming the writing behavior features corresponding to the writing notes by the pressure values and the importance level;
the marking module 240 is connected with the analysis module and is used for marking the corresponding written note in a corresponding form according to the importance level corresponding to the pressure value in the writing behavior characteristic;
and the correction module 250 is connected with the marking module and is used for counting feedback data of the user for marking the written notes in a preset period time and correcting a preset pressure value according to the number of error marks in the feedback data.
Specifically, the embodiment of the invention judges time interval conditions according to the pressure acquisition time interval through the segmentation module, segments the pressure data to form a plurality of pressure slice data, segments the continuous pressure data into one section, accurately analyzes the pressure slice data, the analysis module carries out writing behavior feature analysis on the plurality of pressure slice data according to the pressure value in the pressure slice data, compares the pressure value in the pressure slice data with a preset pressure value, marks the pressure value according to a comparison result, counts the number of marks to confirm the importance level of writing note data corresponding to the marked pressure value, forms the writing behavior feature of the corresponding writing note by the pressure value and the importance level, determines the importance level of the corresponding note according to the pressure value, and finally marks the corresponding writing note in a corresponding form according to the importance level corresponding to the pressure value in the writing behavior feature, so as to realize automatic marking of the note, and automatically marks the note through analyzing the pressure value to obtain the importance level of the note, thereby improving the processing effect and efficiency of intelligent writing behavior feature analysis.
Referring to fig. 4, the analysis module includes a comparing unit 251 for comparing a pressure value in the pressure slice data with a preset pressure value, a marking unit 252 for marking the pressure value according to the comparison result, a counting unit 253 for counting the number of marks, a confirming unit 254 for confirming an importance level of the written note data corresponding to the marked pressure value, and a forming unit 255 for forming the pressure value and the importance level into a writing behavior feature corresponding to the written note.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A method for analyzing writing behavior characteristics of an intelligent pen, comprising:
collecting pressure data of a pressure sensing device in the intelligent pen, and collecting writing notes of the intelligent pen;
judging whether the two pressure acquisition time intervals meet the time interval conditions according to the pressure acquisition time intervals, marking the previous pressure acquisition time in the two pressure acquisition time intervals meeting the first preset time interval conditions, and slicing the pressure data corresponding to the marked pressure acquisition time to form a plurality of pressure slice data;
performing writing behavior feature analysis on a plurality of pieces of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to comparison results, counting the number of marks to confirm the important grades of writing note data corresponding to the marked pressure values, and forming the writing behavior features corresponding to writing notes by the pressure values and the important grades;
corresponding form marking is carried out on the corresponding written notes according to the importance levels corresponding to the pressure values in the writing behavior characteristics;
counting feedback data of a user for marking writing notes within a preset period time, and correcting a preset pressure value according to the number of error marks in the feedback data;
when slicing the pressure data, judging whether two pressure acquisition time intervals in the pressure data accord with time interval conditions according to the pressure acquisition time intervals, wherein,
if the two pressure acquisition time intervals are judged to be in accordance with the first preset time interval condition, slicing the pressure data is determined, and the previous pressure acquisition time is marked;
if the two pressure acquisition time intervals are judged to be in accordance with the second preset time interval condition, the pressure data are not sliced;
the first preset time interval condition is that two pressure acquisition time intervals are larger than or equal to a preset pressure acquisition time interval, and the second preset time interval condition is that the two pressure acquisition time intervals are smaller than the preset pressure acquisition time interval;
when the pressure value meeting the preset pressure value condition is marked, counting the number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section, when any pressure value in the pressure value sequence section meets the first preset pressure value condition, counting the number of characters marks in the pressure value sequence section, when any pressure value in the pressure value sequence section meets the second preset pressure value condition, counting the number of the characters marks in the pressure value sequence section, judging the number of the characters marks and the level of the number marks according to the preset number of marks to confirm the importance level of the written note data corresponding to the pressure value sequence section,
if the number of the character marks accords with a first preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is one level;
if the number of the character marks accords with a second preset character mark condition, judging that the level of the number of the character marks, namely the important level of the written note data corresponding to the pressure value sequence section, is a second level;
if the number of the digital marks accords with a first preset digital mark condition, judging that the level of the number of the digital marks, namely the important level of the written note data corresponding to the pressure value sequence section, is three-level;
if the number of the digital marks accords with a second preset digital mark condition, judging that the level of the number of the digital marks is four, namely the important level of the written note data corresponding to the pressure value sequence section;
the first preset text marking condition is that the number of text marks is larger than or equal to the preset number of marks, the second preset text marking condition is that the number of text marks is smaller than the preset number of marks, the first preset digital marking condition is that the number of digital marks is larger than or equal to the preset number of marks, and the second preset digital marking condition is that the number of digital marks is smaller than the preset number of marks;
correcting the first preset pressure value and the second preset pressure value according to the number of error marks in the feedback data, determining two correction modes for correcting the first preset pressure value and the second preset pressure value according to the number of error marks in the preset period time, wherein,
the first correction mode is that the error mark quantity selects a first preset correction coefficient to reduce the preset pressure value and the second preset pressure value under a first preset error mark condition;
the second correction mode is that the number of error marks does not correct the first preset pressure value and the second preset pressure value under a second preset error mark condition;
the first preset error marking condition is that the number of error marks is larger than the number of preset error marks, and the second preset error marking condition is that the number of error marks is smaller than or equal to the number of preset error marks;
when slicing the pressure data to form the pressure slice data, slicing a corresponding pressure value sequence in the pressure data according to the marked pressure acquisition time to form a plurality of pressure value sequence segments, and associating each pressure value sequence segment with the corresponding pressure acquisition time to form a pressure slice, wherein the pressure slice data comprises a plurality of pressure slices;
when writing behavior characteristic analysis is carried out on a plurality of pressure slice data, comparing a pressure value sequence section in the pressure slice with a preset pressure value, wherein,
if any pressure value in the pressure value sequence section accords with a first preset pressure value condition, performing text marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a second preset pressure value condition, carrying out digital marking on the pressure value which accords with the first preset pressure value condition;
if any pressure value in the pressure value sequence section accords with a third preset pressure value condition, not marking the pressure value which accords with the first preset pressure value condition;
the first preset pressure value condition is that the pressure value is larger than a second preset pressure value, the second preset pressure value condition is that the pressure value is larger than or equal to the first preset pressure value and smaller than or equal to the second preset pressure value, the third preset pressure value condition is that the pressure value is smaller than the third preset pressure value, and the first preset pressure value is smaller than the second preset pressure value;
marking corresponding forms of the written notes according to the corresponding written notes of the writing behavior characteristics, matching the written notes corresponding to the pressure value sequence sections according to the pressure value sequence sections and the importance levels in the writing behavior characteristics, matching the corresponding written notes according to the pressure acquisition time corresponding to the pressure value sequence sections, marking the matched written notes according to the importance levels corresponding to the pressure value sequence sections, and enabling different importance levels to correspond to different marking forms;
if the two pressure acquisition time intervals are larger than the twice preset pressure acquisition time interval, judging that the intelligent pen is finished writing, forming an ending instruction, and ending acquiring the pressure data and the writing note data according to the ending instruction.
2. The smart pen writing behavior feature analysis method of claim 1, further comprising:
and forming an abnormal instruction when judging that any pressure value in the pressure value sequence section does not accord with the preset pressure value condition.
3. A smart pen writing behavior feature analysis apparatus applying the smart pen writing behavior feature analysis method of claim 1 or 2, comprising:
the acquisition module is used for acquiring pressure data of the pressure sensing device in the intelligent pen and acquiring writing notes of the intelligent pen;
the segmentation module is connected with the acquisition module and is used for judging whether the two pressure acquisition time intervals meet the time interval conditions according to the pressure acquisition time intervals, marking the previous pressure acquisition time in the two pressure acquisition time intervals meeting the first preset time interval conditions, and slicing the pressure data corresponding to the marked pressure acquisition time to form a plurality of pressure slice data;
the analysis module is connected with the segmentation module and is used for carrying out writing behavior feature analysis on a plurality of pressure slice data according to the pressure values in the pressure slice data, comparing the pressure values in the pressure slice data with preset pressure values, marking the pressure values according to comparison results, counting the number of marks to confirm the importance level of writing note data corresponding to the marked pressure values, and forming the writing behavior features corresponding to writing notes by the pressure values and the importance level;
the marking module is connected with the analysis module and used for marking corresponding written notes in a corresponding mode according to the importance level corresponding to the pressure value in the writing behavior characteristic;
the correction module is connected with the marking module and used for counting feedback data of the user for marking the written notes in a preset period time and correcting a preset pressure value according to the number of error marks in the feedback data.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101518786B1 (en) * | 2013-11-29 | 2015-05-15 | 주식회사 하이딥 | Feedback method of touch pressure level and device including touch screen performing the same |
| CN105739859A (en) * | 2016-01-25 | 2016-07-06 | 广东欧珀移动通信有限公司 | Reading marking method and terminal device |
| CN106952516A (en) * | 2017-05-16 | 2017-07-14 | 武汉科技大学 | A kind of student classroom writes the intelligent analysis system of period |
| CN108573245A (en) * | 2018-04-28 | 2018-09-25 | 北京奇禄管理咨询有限公司 | A kind of track restoring method based on dot matrix image |
| CN108859508A (en) * | 2018-06-01 | 2018-11-23 | 广东小天才科技有限公司 | A kind of smart pen |
| CN109189262A (en) * | 2018-08-14 | 2019-01-11 | 中新国际电子有限公司 | A kind of touch-control feedback method and device and a kind of electronic equipment |
| CN109308474A (en) * | 2018-09-26 | 2019-02-05 | 广东小天才科技有限公司 | Glasses photographic method, smart pen, glasses and storage medium based on smart pen |
| CN110515474A (en) * | 2019-08-23 | 2019-11-29 | 深圳市元征科技股份有限公司 | A kind of intelligent handwriting pen, notes storage method and server |
| CN210851771U (en) * | 2019-07-29 | 2020-06-26 | 广东小天才科技有限公司 | Intelligent pen |
| CN111931600A (en) * | 2020-07-21 | 2020-11-13 | 深圳市鹰硕教育服务股份有限公司 | Intelligent pen image processing method and device and electronic equipment |
| CN112487883A (en) * | 2020-11-16 | 2021-03-12 | 深圳市鹰硕教育服务有限公司 | Intelligent pen writing behavior characteristic analysis method and device and electronic equipment |
| CN112541377A (en) * | 2019-09-20 | 2021-03-23 | 北京万维智能技术有限公司 | Handwriting restoration method |
-
2023
- 2023-02-24 CN CN202310160426.2A patent/CN115984855B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101518786B1 (en) * | 2013-11-29 | 2015-05-15 | 주식회사 하이딥 | Feedback method of touch pressure level and device including touch screen performing the same |
| CN105739859A (en) * | 2016-01-25 | 2016-07-06 | 广东欧珀移动通信有限公司 | Reading marking method and terminal device |
| CN106952516A (en) * | 2017-05-16 | 2017-07-14 | 武汉科技大学 | A kind of student classroom writes the intelligent analysis system of period |
| CN108573245A (en) * | 2018-04-28 | 2018-09-25 | 北京奇禄管理咨询有限公司 | A kind of track restoring method based on dot matrix image |
| CN108859508A (en) * | 2018-06-01 | 2018-11-23 | 广东小天才科技有限公司 | A kind of smart pen |
| CN109189262A (en) * | 2018-08-14 | 2019-01-11 | 中新国际电子有限公司 | A kind of touch-control feedback method and device and a kind of electronic equipment |
| CN109308474A (en) * | 2018-09-26 | 2019-02-05 | 广东小天才科技有限公司 | Glasses photographic method, smart pen, glasses and storage medium based on smart pen |
| CN210851771U (en) * | 2019-07-29 | 2020-06-26 | 广东小天才科技有限公司 | Intelligent pen |
| CN110515474A (en) * | 2019-08-23 | 2019-11-29 | 深圳市元征科技股份有限公司 | A kind of intelligent handwriting pen, notes storage method and server |
| CN112541377A (en) * | 2019-09-20 | 2021-03-23 | 北京万维智能技术有限公司 | Handwriting restoration method |
| CN111931600A (en) * | 2020-07-21 | 2020-11-13 | 深圳市鹰硕教育服务股份有限公司 | Intelligent pen image processing method and device and electronic equipment |
| CN112487883A (en) * | 2020-11-16 | 2021-03-12 | 深圳市鹰硕教育服务有限公司 | Intelligent pen writing behavior characteristic analysis method and device and electronic equipment |
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|---|---|
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