Lenek's LeXIS: Lung Disease Diagnosis in Rural India

Introduction

As a UX/UI designer at Lenek, I spearheaded the design and development of the software interface for LeXIS, an ultraportable X-ray imaging system. Our goal was to address the critical issue of late-stage diagnosis of lung diseases like tuberculosis, pneumonia, pneumothorax, and pleural effusion in rural India. The project aimed to facilitate early detection and intervention through a user-friendly, AI-integrated system easily deployable in remote areas.

• Project Name: Lenek's LeXIS UI/UX Design
• Role: UX/UI Designer
• Duration: January 2023 – November 2023
• Team Size: 5
• Tools Used: Figma, Adobe XD, Python (for AI integration testing)

Problem Statement

Millions in rural India lack access to timely lung disease diagnosis, leading to delayed treatment and poorer outcomes. Existing healthcare infrastructure is often inadequate, and patients frequently present with advanced disease stages. This necessitates a solution that is portable, affordable, easy-to-use, and provides accurate diagnostics at the point of care.

Objectives and Goals

Our primary objectives were to design a user interface that: 1. Was intuitive and easy to use for operators with varying levels of technical expertise. 2. Successfully integrated AI-driven diagnostic capabilities for faster and more accurate results. 3. Streamlined the workflow for X-ray examinations and data management. 4. Provided clear and easily understandable results, minimizing misinterpretations. 5. Was adaptable to various settings and user needs.

Research and Insights

We conducted user interviews with potential operators (healthcare workers, community health volunteers) and radiologists to understand their needs and challenges. Surveys and focus groups provided additional insight into user preferences and pain points. This informed the creation of user personas representing various skill levels and experience.

Ideation and Concept Development

Initial ideation involved brainstorming sessions and sketching potential interface designs. We explored various approaches to information architecture, navigation, and AI integration. Early prototypes were created and iteratively refined based on user feedback from usability tests. We prioritized a clean and uncluttered interface to ensure ease of use, even under challenging field conditions.

Design Process

Wireframes were developed to outline the information hierarchy and user flow. We used Figma to create interactive prototypes, testing various design solutions with target users. The final visual design incorporated a clear and legible typeface, a color palette that improved readability, and intuitive icons. User testing ensured the interface was accessible and efficient for all users.

Challenges and Solutions

A primary challenge was balancing simplicity with functionality. We needed to create an interface that was easy to use for non-technical operators yet powerful enough to integrate advanced AI features. We addressed this by using clear visual cues, concise instructions, and well-organized information layouts. Integrating AI seamlessly into the workflow was also challenging. This involved careful consideration of data flow, feedback mechanisms, and result presentation.

Final Outcome

The final design is a clean, intuitive, and efficient interface that streamlines the entire X-ray process. Key features include dedicated buttons for different body parts, a preview mode for quick image review, and a clear presentation of AI-generated diagnostic results. The system’s modular design caters to diverse user skills and allows for easy updates and maintenance.

Learnings and Reflections

This project highlighted the importance of user-centered design, particularly when dealing with complex technologies in resource-constrained environments. Thorough user research and iterative testing proved crucial in developing a successful and impactful solution. I learned the value of close collaboration with engineers and AI specialists to seamlessly integrate advanced features into a user-friendly interface. In future projects, I would dedicate more time to user training materials and incorporate more comprehensive feedback mechanisms.

Conclusion

Lenek, with its intuitive software interface, holds the potential to revolutionize lung disease diagnosis in rural India. By empowering healthcare workers with advanced diagnostic tools and simplifying complex procedures, the system strives to improve healthcare access, reduce diagnostic delays, and ultimately save lives. Future plans include expanding AI capabilities, refining the interface based on user feedback, and ensuring wider adoption across various regions.