US 12,260,077 B1
Customizing user interfaces based on neurodiverse classification
Paul Prem Rajah V, Madurai (IN); Rajkumar Mahalingam, Krishnagiri (IN); Shenilton R. S, Kanyakumari (IN); and A Francis, Chennai (IN)
Assigned to Citibank, N.A., New York, NY (US)
Filed by Citibank, N.A., New York, NY (US)
Filed on Sep. 25, 2023, as Appl. No. 18/474,115.
Int. Cl. G06F 3/04845 (2022.01); G06F 9/54 (2006.01)
CPC G06F 3/04845 (2013.01) [G06F 9/54 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A system for providing user interfaces using artificial intelligence, the system comprising:
one or more processors; and
one or more memories configured to store instructions that, when executed by the one or more processors, perform operations comprising:
receiving, at a server, user interaction data as a user interacts with a first application on a client device, wherein the user interaction data comprises one or more of key stroke dynamics data, navigation pattern data, or interaction pattern data;
inputting the user interaction data into a machine learning model to obtain, based on the user interaction data, a plurality of neurodiversity categories associated with the user, wherein the machine learning model is trained, using previously collected user interaction data to identify categories of neurodiversity within the previously collected user interaction data;
retrieving, for each neurodiversity category of the plurality of neurodiversity categories, a corresponding plurality of user interface parameters, wherein each corresponding plurality of user interface parameters comprises one or more of text display parameters, text content parameters, color parameters, or navigation parameters;
generating a first set of user interface parameters comprising user interface parameters that are identical for each neurodiversity category of the plurality of neurodiversity categories;
merging non-matching user interface parameters into a second set of user interface parameters, wherein the non-matching user interface parameters are different for one or more neurodiversity categories of the plurality of neurodiversity categories obtained from the machine learning model;
generating a set of user interface parameters based on the first set of user interface parameters and the second set of user interface parameters associated with the plurality of neurodiversity categories;
generating a customized user interface based on the set of user interface parameters for the first application on the client device; and
transmitting, to the client device, a request to change a current user interface with the customized user interface, wherein the request comprises the set of user interface parameters and a prompt requesting that the user accept or deny the request to change the current user interface.