Woohee Byun
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Down Dog


Yoga app with lacked injury-specific customization, leading to accessibility issues for users with limited mobility. I designed an Injury Filter System that enables posture-level exclusions, ensuring safer, personalized sessions.






TEAM
Solo Project
ROLE
UX/UI Design
DURATION

16 weeks RECOGNITION

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PROBLEM
While in-person yoga instructors often suggest alternative postures for practitioners with physical limitations, most at-home yoga apps lack personalized modification options.
OUTCOME
I redesigned the app with an automated pose filtering system that allows users to customize their yoga flows based on physical constraints.



FINAL DESIGN

Assessment Onboarding


Start with a guided assessment to shape your flow. Just share your goals, current condition, and any limitations—your practice adjusts from there.

Injury-aware Filter


Add an injury filter to leave out discomfort-inducing poses—bringing clarity and ease to every session.


In-depth Pose Library


Follow up the pose library with a supplemental screen—offering clear context, visual cues, and easy-to-understand guidance for every posture you explore.







MARKET RESEARCH

16.9% of U.S. adults practiced yoga in the past year

Yoga has gained significant popularity in recent years, with nearly 1 in 6 U.S. adults reporting practicing it. With an increasing emphasis on mental well-being and physical fitness, people from all walks of life recognize the benefits of yoga.





EMPATHY INTERVIEW


Lack of in-app guidance led to unsafe adaptations

I conducted semi-structured interview with 7 yogis with diverse experience and injuries. Due to lack of modification unlike in-person studios, I discovered that users often modify poses intuitively or skip based on their past experience which can often lead to unsafe or inefficient practice.






Competitive Evaluation

What’s missing across different platforms?

I compared Down Dog, Pocket Yoga, and Yoga Studio against core user needs identified in our research. The goal of competitive evaluation was to understand how users with injuries build customized practice, and discover friction points in the process.

This analysis revealed shared gaps across all three platforms—the absence of injury-based modification.






PROBLEM IDENTIFICATION


Digital yoga experiences fail to support users’ real-life conditions

From in-depth interview, competitive evaluation, and gap analysis, I was able to find common findings across yoga practitioners–centered around lack of personalization, unclear pose guidance, and inaccessible interfaces.








IDEATION

Improvement opportunities uncovered

 Based on key challenges identified from the research phase, I ideated opportunities for each to better improve the user experience of the Down Dog app.






CONCEPT EXPLORATION

Divergent concepts were explored with Crazy Eights

To address the challenge, I brainstormed 4 distinct concepts: an AI motion tracking feature, modification-specific visual and audio cues, modified poses based on low flexibility or common injuries, and an injury-based filter.

While all 4 concepts have capability to satisfy users’ needs, I focused on an injury-based filter after understanding the technical limitations and challenges based on users’ mental model.






CONCEPT REFINEMENT

From sketch to systematic solution

 After evaluation feasibility and user needs, I refined the concept around an injury filter system that allows users to input sensitive areas. This input dynamically filters out unsafe poses or suggests modifications. I also visualized the improved backend logic, ensuring the experience is both adaptable and scalable - balancing personalization with simplicity.





USABILITY TESTING

Rapid prototyping revealed usability challenges

To validate the effectiveness of the redesigned experience, I conducted a series of usability tests, including A/B testing and multivariate testing.




    ❌ Light information was not preferred by users as it doesn’t add much value of pose library.✅ Medium-length text was preferred by most of participants as it was in-depth enough to assist visual demonstration.❌ Too detailed information was not needed for users with visual demonstration.



    ❌ Participants expected to see any kind of visual demonstration to understand better.❌ Participants wanted to know how to get to the posture with better context and motion.✅ Proceeded the design with short video clip providing better context and understanding.



    ❌ Participants barely used a search bar as they were expected to already know about the name of the pose.✅ Added filters that are easily categorized for beginners and intermediates without knowing the exact term.




    SOLUTION

    Yoga flow made just for you and your body

    Injury-based filter is implemented to solve the main challenge of users with various physical conditions. In-depth pose library and assessment onboarding was added along to support the challenge.

    This solution not only aligns with existing back-end system but also dedicates and emphasizes the importance of taking care of users’ body before they realize.












    VALIDATION

    Did the new experience actually feel safer and personal to users?

    To validate the effectiveness of the redesigned experience by measuring cognitive load, I conducted eye tracking heatmap, NASA-TLX, and preference testing with follow-up interview.









    OUTCOME & IMPACT

    Where It Landed


    I successfully presented the project to key leadership and spectators during the Thesis Show. Some of the feedbacks I got from mentors and faculty include:






    REFLECTIONS

    What did I learn from this project?

    Validate assumptions early and often.
     User testing isn’t just a final step—it’s an ongoing process that grounded our decisions in reality. By validating ideas early, I uncovered usability issues we hadn’t anticipated and ensured that our designs aligned with actual user needs, not just internal opinions.

    Work in layers, not lines.
    Working on the Down Dog project taught me that research, design, and testing rarely happen in neat phases. Often, I had to juggle refining wireframes, revisiting research insights, and gathering feedback simultaneously—progress wasn’t linear, but layered.

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      ©Woohee 2025