Computing technologies for diagnosis and therapy of language-related disorders

Abstract

The present disclosure relates to computing technologies for diagnosis and therapy of language-related disorders. Such technologies enable computer-generated diagnosis and computer-generated therapy delivered over a network to at least one computing device. The diagnosis and therapy are customized for each patient through a comprehensive analysis of the patient's production and reception errors, as obtained from the patient over the network, together with a set of correct responses at each phase of evaluation and therapy.

1 . A method of diagnosis, the method comprising:
 establishing, via a server, over a network, a secure session with a browser running on an operating system of a client, wherein the client comprises an input device and an output device, wherein the operating system manages the input device and the output device;   during the secure session:
 serving, via the server, over the network, a graphical user interface to the browser such that the output device outputs the graphical user interface, wherein the graphical user interface is programmed to receive a first input via the input device and a second input via the input device; 
 in response to receiving, via the server, over the network, the first input from the client, storing, via the server, the first input in a first data structure, analyzing, via the server, the first data structure, including the first input, against a second data structure comprising a set of task content generation data and a set of predicted task response data, obtaining, via the server, a first set of criteria based on the analyzing, selecting, via the server, a first type content in a third data structure based on the first set of criteria, creating, via the server, a first task content dynamically from the set of task content generation data based on the first type content and the first input, and serving, via the server, over the network, the first task content to the graphical user interface; and 
 in response to receiving, via the server, over the network, the second input from the client based on the first task content, storing, via the server, the second input in the first data structure, analyzing, via the server, the first data structure, including the first input and the second input, against the second data structure, obtaining, via the server, a second set of criteria based on the analyzing, and determining, via the server, at least one of whether to create, via the server, a second task content dynamically from the set of task content generation data based on the first type content, the first input, and the second input, whether to select, via the server, a second type content in the third data structure based on the second set of criteria, or whether to serve, via the server, over the network, a diagnosis message to the graphical user interface, wherein the diagnosis message is associated with the first data structure. 
   
     
     
         2 . The method of  claim 1 , wherein the first data structure, the second data structure, and the third data structure are stored in a database, wherein the first data structure and the third data structure are smaller in size than the second data structure. 
     
     
         3 . The method of  claim 1 , wherein at least one of the first data structure, the second data structure, or the third data structure is stored in a database, wherein the database is stored in a memory, wherein the memory is non-volatile, wherein the memory comprises a random access memory. 
     
     
         4 . The method of  claim 1 , wherein the third data structure is a table. 
     
     
         5 . The method of  claim 1 , wherein the second data comprises a first table and a second table, wherein the first table comprises the set of task content generation data and the second table comprises the set of predicted task response data, wherein the first task content is created dynamically from the first table. 
     
     
         6 . The method of  claim 1 , wherein the first input comprises an incorrect task response content. 
     
     
         7 . The method of  claim 1 , wherein the second input comprises an incorrect task response content, wherein the second task content is created based on the second input. 
     
     
         8 . The method of  claim 1 , wherein at least one of the first task content or the second task content comprises an interactive content. 
     
     
         9 . The method of  claim 1 , wherein the diagnosis message comprises a language-related condition diagnosis content. 
     
     
         10 . A method of therapy, the method comprising:
 establishing, via a server, over a network, a secure session with a browser running on an operating system of a client, wherein the client comprises an input device and an output device, wherein the operating system manages the input device and the output device;   during the secure session:
 serving, via the server, over the network, a graphical user interface to the browser such that the output device outputs the graphical user interface, wherein the graphical user interface is programmed to receive a first input via the input device and a second input via the input device; 
 in response to receiving, via the server, over the network, the first input from the client, storing, via the server, the first input in a first data structure, analyzing, via the server, the first data structure, including the first input, against a second data structure comprising a set of task content generation data and a set of predicted task response data, obtaining, via the server, a first set of criteria based on the analyzing, selecting, via the server, a first type content in a third data structure based on the first set of criteria, creating, via the server, a first task content dynamically from the set of task content generation data based on the first type content and the first input, and serving, via the server, over the network, the first task content to the graphical user interface; and 
 in response to receiving, via the server, over the network, the second input from the client based on the first task content, storing, via the server, the second input in the first data structure, analyzing, via the server, the first data structure, including the first input and the second input, against the second data structure, obtaining, via the server, a second set of criteria based on the analyzing, and determining, via the server, at least one of whether to create, via the server, a second task content dynamically from the set of task content generation data based on the first type content, the first input, and the second input, whether to select, via the server, a second type content in the third data structure based on the second set of criteria, or whether to serve, via the server, over the network, a therapy message to the graphical user interface, wherein the therapy message is associated with the first data structure. 
   
     
     
         11 . The method of  claim 10 , wherein the first data structure, the second data structure, and the third data structure are stored in a database, wherein the first data structure and the third data structure are smaller in size than the second data structure. 
     
     
         12 . The method of  claim 10 , wherein at least one of the first data structure, the second data structure, or the third data structure is stored in a database, wherein the database is stored in a memory, wherein the memory is non-volatile, wherein the memory comprises a random access memory. 
     
     
         13 . The method of  claim 10 , wherein the third data structure is a table. 
     
     
         14 . The method of  claim 10 , wherein the second data comprises a first table and a second table, wherein the first table comprises the set of task content generation data and the second table comprises the set of predicted task response data, wherein the first task content is created dynamically from the first table. 
     
     
         15 . The method of  claim 10 , wherein the first input comprises an incorrect task response content. 
     
     
         16 . The method of  claim 10 , wherein the second input comprises an incorrect task response content, wherein the second task content is created based on the second input. 
     
     
         17 . The method of  claim 10 , wherein at least one of the first task content or the second task content comprises an interactive content. 
     
     
         18 . The method of  claim 10 , wherein the therapy message comprises a language-related condition therapy content. 
     
     
         19 . A method of therapy, the method comprising:
 serving, via a server, over a network, an audio content to a browser running on an operating system of a client, wherein the client comprises a speaker and a camera, wherein the operating system manages the speaker and the camera;   receiving, via the server, over the network, an input from the client, wherein the input comprises an image content captured via the camera at least one of during or after the speaker outputs the audio content;   extracting, via the server, a pattern from the image content;   comparing, via the server, the pattern against a set of parameters in a data structure, wherein the data structure comprises a set of task content generation data and a set of predicted task response data;   identifying, via the server, a match based on the comparing;   creating, via the server, a feedback message based on the match; and   serving, via the server, over the network, the feedback message to the client.   
     
     
         20 . The method of  claim 19 , wherein the client is a first client, wherein the audio content is created at a second client communicating with the server over the network as the first client communicates with the server over the network.