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AI in Communication Technologies for Cognitive Impairments

Individuals with cognitive impairments often encounter digital communication barriers, limiting their social and digital inclusion. Current assistive technologies fall short in addressing diverse cognitive and linguistic needs effectively.

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Question that started this project:

"How can the application of AI in communication technologies be effectively designed to address the digital and language divide experienced by individuals with Cognitive Impairments?"

Span:

18 Weeks.

Team

Solo Thesis Project

Methods

Observational Study, Literature Review, Wizard of Oz Testing, Iterative Prototyping and Testing.

Tools:

Figma, ProtoPie, Blender, Open AI, Illustrator,
Obsidian, Microsoft Teams.

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  • Language Barriers: The predominance of English in assistive technologies marginalizes non-English speakers, especially in linguistically diverse regions like India.

  • Limited Customization: Existing AAC (Augmentative and Alternative Communication) tools lack adaptability to individual user needs and preferences.

  • Complex Navigation: Poorly designed interfaces and convoluted workflows hinder usability for individuals with cognitive challenges.

  • Lack of Engagement: Ineffective use of visuals and tactile feedback reduces user satisfaction and accessibility.

User Pain Points

  • Social isolation and dependency on caregivers.

  • Missed opportunities for inclusion in the digital ecosystem.

  • Inefficient self-expression, affecting education, employment, and daily life activities.

Impact of Problem

Research Methods

Observational Study:

  • Conducted remote user observations in Bengaluru and New Delhi to understand interaction patterns with existing AAC tools.

  • Interviewed and observed psychologists and occupational therapists while they interacted with users to gather insights.

  • Captured feedback on language preferences and usability challenges.

Wizard of Oz Testing:

Simulated AI-driven features, including predictive text and multilingual support, to evaluate user responses.

Prototyping and Testing:

Designed prototypes using Figma and Protopie for iterative feedback and testing.

Framwork

Solution Framework

Multilingual AI Integration:

Support for multiple Indian languages with real-time translation.

Adaptive AI Features: 

Predictive text, contextual understanding, and customization for users and caregivers.

Empathetic Design

Simplified interfaces, enhanced visuals, and tactile feedback for an intuitive user experience.

Collaborative Development: 

Engaged caregivers, therapists, and users throughout the design process to ensure inclusivity.

Visual Evolution

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Visual Evolution

Before

Challenges Identified:

  • English-only interfaces limiting accessibility.

  • Ineffective navigation and customization.

  • Lack of engaging and adaptive visuals.

After

Redesigned Features:

  • Multilingual support with real-time translation.

  • Enhanced visuals using principles of color psychology and adaptive font styles.

  • Simplified navigation pathways and customizable user profiles.

  • Haptic feedback for tactile interaction.

Design Iterations

  • Iteration 1: Addressed foundational issues like navigation complexity and animation overload.

  • Iteration 2: Using the Wizard of Oz technique, AI integration was simulated for multilingual modules and customization processes.

  • Iteration 3: Focused on supporting long conversations and ensuring the typing view space remained visible for improved usability.

Testing Outcomes

  • Testing: It was observed that users experienced increased ease of communication and engagement with simulated AI features, as they were unable to directly report due to their disabilities.

  • Prototype Iterations: Significant improvement in task completion rates.

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Why This Works

  • Strategic Alignment: The solution aligns with the growing demand for inclusive digital tools that cater to linguistic and cognitive diversity, particularly in regions like India.

  • Validated by Testing: Real-world testing through observational studies and Wizard of Oz simulations ensured the solution’s practicality and user relevance.

  • Empathy in Design: By focusing on user-specific customization and regional needs, the design fosters a holistic and inclusive communication environment for individuals with cognitive impairments.

Measurable Results

User Impact

  • Improved accessibility for non-English speakers through multilingual support.

  • Enhanced autonomy with reduced dependency on caregivers.

  • Higher satisfaction scores during prototype testing.

Real-World Outcomes

  • Highlighted the potential of AI-driven tools to bridge linguistic and cognitive divides.

  • Provided a scalable framework for future assistive technology development.

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