CORETEX

COGNITIVE TRAINING BACKED BY SCIENCE

CORETEX is an AI-native cognitive training platform designed to make preventive brain health proactive, engaging, and accessible. By transforming clinically-validated cognitive assessments into daily exercises, CORETEX creates a bridge between scientific validity and user engagement. The platform uses a proprietary reinforcement learning to personalize cognitive training across four key domains - Memory, Verbal, Movement, and Spatial awareness - while maintaining clear boundaries between wellness support and medical assessment.

Project Type
UX Research, UX Design, Digital Health

Company
Kolachalama Laboratory, Boston University

Year/Duration
May - Septemeber 2024, 16 weeks

Role
UX Researcher, UX Designer

Tools
Figma

Skills
Research, Testing, Rapid Prototyping, Interaction Design

PROBLEM SPACE

Digital Health

Today's cognitive health landscape presents significant barriers for adults 45+, with prohibitive costs, long wait times, and limited access to preventive care. Traditional solutions either feel overly clinical or too game-like, while existing digital tools fail to maintain engagement or scientific validity, leaving users without effective options for maintaining cognitive wellness.

RESEARCH QUESTION

How Might We

How might we create an accessible and engaging cognitive training platform that effectively combines clinical validity with personalized user experience for adults 45+, addressing the growing need for preventive cognitive health tools?

SOLUTION

AI-Native Cognitive Training

To address these challenges and democratize cognitive health support, we developed CORETEX, an AI-native cognitive training platform that transforms clinical assessments into engaging daily exercises.

DISCOVER

Problem Space, User Research, Market Research, Landscape Audit

DISCOVER

Problem Space

Identifying the gap in the current state of the cognitive healthcare market.

DISCOVER

User Research

Identifying the target audience as 45+ working professionals and their key motivators and concerns regarding cognitive healthcare. 

DISCOVER

Market Research

Undestanding the cognitive healthcare market through the perspective of changing demographics, longevity interventions, and digital interventions. 

DISCOVER

Landscape Audit

Analysing popular word games, pattern-based puzzles, and established brain-training apps based on features and triggers that help them maintain their stickiness and market favor.

DEFINE

Opportunity Space, User Needs, Point of Entry, Problem Framing, Customer Journey Map

DEFINE

Opportunity Space

Establishing the angle with which to approach the problem of closing the gap between patients and accessible cognitive health care measures. 

DEFINE

Jobs To Be Done

Identifying the functional, emotional, and social needs the target audience holds with regards to cognitive health monitoring.

DEVELOP

Problem Statement

Framing the how might we statement that guides the subsequent research and design process.

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DEVELOP

Ideation, Solution Overview, Success Metrics, Task Flows, Design Principles

DEVELOP

Feature Prioritization

Brainstorming and validating the primary features required for the MVP based on discussed metrics such as NPS, usability surveys, task completion rate, and more. 

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DEVELOP

Design Principles

To ensure users felt in control of their experience while helping them understand the involvement of the reinforcement learning (RL) model, these key principles - developed from insights from the research process - were implemented to design for transparency around the RL model.

DELIVER

Prototype, Test, Iterate

DELIVER

MVP Solutions

The following solutions were designed and implemented with a focus on both developers and the established design principles, while ensuring the appropriate integration of research insights. Working collaboratively with developers allowed for rapid iteration, testing, and refinement.