LiftIQ: Gym App with AI Coach

Role UX Researcher + Designer
Year 2025
Type Educational Technology
Timeline Mar – May 2025
Team Luke Hartzell
Key Skills Motion Tracking UX, Video Instruction Design, Usability Testing, Interactive Prototyping
Prototype View Figma Prototype

Highlights

Gym-goers often lack proper guidance on form and technique, increasing injury risk.
Conducted iterative user testing to refine AI coach and multimedia instruction.
Designed an intuitive mobile interface combining AI motion tracking, instructional videos, and written resources.

Background & Pain Points

Proper Form & Hypertrophy Training

Improper form and ineffective training techniques are common among beginner to intermediate gym-goers (ages 16-30), especially those lacking access to personal trainers. Common issues include:

  • Increased injury risk due to incorrect exercise execution.
  • Confusion from conflicting online fitness information.
  • Difficulty in tracking exercise progression and form improvements.
Gym App home screen showing AI Coach, Progress Tracking, Videos, and Articles sections

Competitive Analysis

We surveyed top fitness apps (Nike Training Club, Peloton, Fitbod) and found none offer integrated AI-driven form correction. This opened an opportunity for real-time motion-tracking feedback.

UX Research

Responsibilities + Data Collection & Analysis

Initial wireframes and user flow diagrams for the Gym App

As UX lead for the LiftIQ Gym App with AI Coach, my responsibilities included:

  • Initial conceptual design grounded in fitness science.
  • Conducting detailed user tests and contextual inquiries.
  • Analyzing user feedback for iterative improvements.

Primary methods of data collection:

  • Think-aloud protocol during user interactions with prototypes.
  • Qualitative interviews focusing on fitness habits, challenges, and app interaction.
  • Competitive review of leading fitness apps
  • Expert interviews with 2 certified trainers

Analysis methods included:

  • Thematic analysis to identify patterns and common usability issues.
  • Direct feedback integration for user-centered design improvements.

Design Solutions & Iterative Prototyping

Initial Prototype

Key Features:

  • AI Coach providing real-time camera analysis and audio feedback.
  • Video walkthroughs with descriptive captions and form cues.
  • Progress tracking and detailed instructional articles.

User feedback praised the AI Coach, clear UI design, and instructional videos. However, feedback highlighted navigation difficulties due to small and inconsistent back buttons.

Videos section showing exercise categories and training videos
AI Coach feature showing real-time form analysis with highlighted muscle engagement

Mid-Fidelity Prototype Improvements

  • Enlarged and standardized back/navigation buttons for improved usability.
  • Added detailed instructional breakdowns (setup, execution, correction) based on user safety concerns.
  • Incorporated customizable playback speed for instructional videos.

Feedback indicated high user satisfaction with improved interactivity and navigational consistency.

High-Fidelity Prototype (Final Design)

Final iteration enhancements:

  • Advanced AI feedback system with highlighted visual cues.
  • Expanded instructional resources emphasizing proper form and hypertrophy techniques.
  • Enhanced progress logging for measurable improvement tracking.
  • User-friendly interface with consistent design across all screens.
Workout log showing performance metrics and form analysis

Justification & Learning Science Integration

The LiftIQ Gym App leverages several key educational principles and theories:

  • Mayer's Multimedia Principles: Incorporates dual-channel theory by providing both visual (video tutorials, highlighted muscles) and audio coaching to reduce cognitive overload.
  • Embodied Cognition & Motor Learning: Encourages active physical engagement during lessons, enhancing memory and skill acquisition.
  • Immediate Feedback: Uses real-time AI analysis for instant form corrections, significantly reducing risk and improving learning outcomes.
  • Chunking Principle: Breaks down complex exercises into manageable phases (setup, execution, correction) to facilitate easier learning.
  • Signaling Principle: Employs visual cues to guide users' attention to critical areas, improving the effectiveness of instructional feedback.
LiftIQ Logo

Reflection & Next Steps

Breaking exercises into setup, execution, and correction phases proved critical for user learning. Iterative testing highlighted the need for consistent navigation—hence the enlarged back buttons. Next, I plan to:

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