System and method for incorporating dyslexia detection in handwriting pattern recognition systems

• US 6,304,667 B1
• Filed: 06/21/2000
• Issued: 10/16/2001
• Est. Priority Date: 06/21/2000
• Status: Expired due to Fees

• Current Assignee: Patented Protected Properties, LLC
• Original Assignee: Carmen T. Reitano
• Inventors: Reitano, Carmen T.
• Primary Examiner(s): Chang, Jon
• Application Number:
  US09/598,577
• Time in Patent Office: 482 Days
• Field of Search: 382/128, 382/186, 382/187, 382/188, 382/189, 382/209, 382/215, 382/217, 382/218, 382/309, 382/310
• US Class Current: 382/128
• CPC Class Codes: G06F 18/28 Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries
• CPC Class Codes: G06V 30/1423 the instrument generating sequences of position coordinates corresponding to handwriting preprocessing or recognising digital ink G06V30/32

Abstract

A method for incorporating dyslexia detection into existing handwriting pattern recognition software includes a database of distorted characters along with the database of legitimate characters with which the handwriting samples are compared. The distorted characters are those recognized as typical of those produced by dyslexic persons. The system used may be a personal computer, a personal digital assistant, or an Internet system. Whatever system is used, a means of freehand drawing must be included, such as a stylus with pressure sensitive drawing area, a drawing tablet, or pen-pad-type device. A character is first presented to the student for reproduction. The student then draws a character on the pad, attempting to reproduce the character. The system software detects a correspondence between the character input and the legitimate characters, when occurring. When the drawn character does not correspond to a legitimate character, but does correspond to one of the distorted character sets, the result is stored, and later reported.

Claims

1. A method for detecting dyslexia in a handwriting pattern recognition system, which includes a database of legitimate characters comprising:

(a) including in the database a set of distorted characters;

(b) presenting a character to be input by a student;

(c) inputting characters by the student;

(d) detecting a correspondence between each input character and one of the distorted characters;

(e) determining a pattern of inputting of characters which correspond to distorted characters; and

(f) reporting said pattern.

2. The method of claim 1, wherein the set of distorted characters further comprises mirror images of the legitimate characters.

3. The method of claim 2, wherein each distorted character is associated with a legitimate character, and wherein said reporting further comprises statistical reporting of distorted characters input.

4. The method of claim 3, wherein the set of distorted characters further comprises a subset of global distorted characters and one or more subsets of local distorted characters.

5. The method of claim 4, wherein the subsets of local distorted characters are collected by statistical sampling methods from individual users, and wherein a subset of local distorted characters is associated with each individual user.

6. The method of claim 5, further comprising associating each distorted character with a true character, and reporting the true character together with the distorted character detected.

7. A method for detecting dyslexia in a handwriting pattern recognition system, which includes a database of legitimate characters and words comprising:

(a) including in the database a set of distorted characters;

(b) presenting a word to be input by a student;

(c) inputting words containing characters by a student;

(d) detecting a correspondence between each input character and one of the distorted characters;

(e) determining a pattern of inputting of distorted characters; and

(f) detecting a pattern of selection of distorted characters in the words input; and

(g) reporting said patterns.

8. The method of claim 7, wherein the set of distorted characters further comprises mirror images of the legitimate characters.

9. The method of claim 8, wherein each distorted character is associated with a legitimate character, and wherein said reporting further comprises statistical reporting of distorted characters input.

10. The method of claim 9, wherein the pattern recognition system further comprises contextually identifying the words input from the database of legitimate words, the method further comprising substituting the legitimate character corresponding to each distorted character detected prior to said contextual identification.

11. The method of claim 10, further comprising determining a pattern of characters which correspond to inputting of distorted characters in certain words;

and reporting said pattern.

12. A system for detecting dyslexia in a handwriting pattern recognition system, which includes a database of legitimate characters comprising:

(a) a database of distorted characters;

(b) means for presenting a character to be input by a student;

(c) means for inputting characters by the student;

(d) means for detecting a correspondence between each input character and one of the distorted characters;

(e) means for determining a pattern of inputting of characters which respond to distorted characters; and

(f) means for reporting said pattern.

13. The system of claim 12, wherein the database of distorted characters further comprises mirror images of the legitimate characters.

14. The system of claim 13, wherein each distorted character is associated with a legitimate character, and wherein said reporting further comprises statistical reporting of distorted characters input.

15. The system of claim 14, wherein the set of distorted characters further comprises a subset of global distorted characters and one or more subsets of local distorted characters.

16. The system of claim 15, wherein the subsets of local distorted characters are collected by statistical sampling methods from individual users, and wherein a subset of local distorted characters is associated with each individual user.

17. The system of claim 16, further comprising means for associating each distorted character with a true character, and means for reporting the true character together with the distorted character detected.

18. A system for detecting dyslexia in a handwriting pattern recognition system, which includes a database of legitimate characters and words comprising:

(a) a database of distorted characters;

(b) means for presenting a word to be input by a student;

(c) means for inputting words containing characters by a student;

(d) means for detecting a correspondence between each input character and one of the distorted characters;

(e) means for determining a pattern of inputting of characters which correspond to distorted characters; and

(f) means for detecting a pattern of selection of distorted characters in the words input; and

(g) means for reporting said patterns.

19. The system of claim 18, wherein the set of distorted characters further comprises mirror images of the legitimate characters.

20. The system of claim 19, wherein each distorted character in the database is associated with a legitimate character, and wherein said means for reporting further comprises statistical means for reporting of distorted characters input.

21. The system of claim 20, wherein the pattern recognition system further comprises means for contextually identifying the words input from the database of legitimate words, the system further comprising means for substituting the legitimate character corresponding to each distorted character detected prior to said contextual identification.

22. The system of claim 21, further comprising means for determining a pattern of inputting of characters which respond to words distorted characters in certain words;

and reporting said pattern.

23. The system of claim 22, wherein the database of distorted characters, the means for presenting a word to be input by a student, the means for inputting words containing characters by a student, the means for detecting a correspondence between each input character and one of the distorted characters, the means for determining a pattern of inputting of distorted characters, the means for detecting a pattern of selection of distorted characters in the words input, and the means for reporting said pattern are contained within a device chosen from the list consisting of:

computers;

personal digital assistants;

computer games; and

a device communicating over a data communications network with an INTERNET server.