Conversational AI for Personalized Well-being Data Collection

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Solution Overview

Problem

Individuals often neglect their well-being due to competing priorities, and conventional methods lack personalization, leading to inefficient or incorrect well-being promotion efforts.

Innovation Solution

A computer-implemented method for guided user data collection and recommendation generation using conversational artificial intelligence to obtain and analyze well-being data, identifying triggering events, and providing personalized user action recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional well-being promotion methods are used, then well-being guidance can be provided to users, but the guidance is not personalized and may be inefficient or incorrect

Engineering Contradiction:

Improvepersonalization of well-being guidanceVSAvoidefficiency of well-being promotion

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs preliminary data collection during routine user interactions with the application, gathering well-being related information before it is needed for generating personalized guidance. This allows the system to have individualized data ready when creating well-being recommendations, resolving the contradiction between personalization and efficiency.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If individualized data collection is implemented, then accurate well-being recommendations can be generated, but users may forget or fail to provide necessary updates

Engineering Contradiction:

Improveaccuracy of well-being dataVSAvoidtime for data collection

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system merges well-being data collection with the user's existing interaction patterns with the application. By integrating data collection into routine usage rather than requiring separate dedicated input sessions, the system achieves accurate individualized data gathering without adding significant time burden to the user.

Inventive Principle:

Principle #5Merging (Combining)

3Loss of information

If multiple information prompts are presented to users, then comprehensive well-being data can be collected, but the process becomes complex and time-consuming

Engineering Contradiction:

Improvecompleteness of well-being dataVSAvoidcomplexity of data collection process

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system segments well-being data collection into multiple small, contextually relevant portions that are gathered incrementally during different user interactions. This breaks down the complex task of comprehensive data collection into manageable segments that users provide naturally over time, reducing perceived complexity while maintaining data completeness.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20220189623A1Systems and methods of guided information intake

Publication Date: 2022.06.16 STATE FARM MUTAL AUTOMOBILE INSURANCE COMPANY

AI summary

Systems and methods relating to collecting guided user data generating recommendations are disclosed, with particular reference to collecting user data related to the well-being of a user. Such systems and methods include obtaining well-being data associated with a user and determining that a triggering event has occurred based at least upon the well-being data collected. A user log may be generated by iteratively presenting a plurality of information prompts to the user. In generating the user log, the systems and methods may apply a conversational artificial intelligence model, receive user responses to prompts, and add data entries to the user log. A user action recommendation based upon the data entries may be generated and presented to the user.