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VisionFitness

VisionFitness is a pair of smart glasses that projects a full-size hologram personal trainer, tracks posture, and recommends workouts, helping busy users exercise conveniently anywhere.

  • Smart Glasses with Integrated Camera

  • Projection of Augmented Reality AI- Powered Fitness Trainer

  • Real-Time Fitness Data via Built-in Heart Rate and Motion Sensors

  • Future Plans: Integrated Posture Correction Technology

What it does

VisionFitness is a pair of AI smart glasses that projects a hologram personal trainer. It provides real-time workout guidance using the user’s fitness data and available equipment, allowing busy users to exercise anytime without the need of planning.


Your inspiration

I realised that many people, especially busy working adults, struggle to find time or motivation to exercise regularly. I was intrigued by AR technology and with the latest advancements in AI, I want to combine both to create a personalised virtual personal trainer. VisionFitness is designed with built-in cameras to capture the surrounding environment and automatically recommend suitable workouts based on available fitness equipment or open space, removing the need for users to plan their sessions. It tracks posture and fitness progress in real-time, offering personalised guidance tailored to the user’s fitness level and environment.


How it works

VisionFitness is a pair of AI-powered smart glasses that combines Augmented Reality (AR) and Artificial Intelligence to create a virtual personal trainer. The built-in cameras scan the surroundings to detect available space and fitness equipment. Using this information, the glasses project a life-size hologram trainer directly in front of the user through AR lenses. In the future there will be 360 degree cameras use to track the user’s body movements, allowing the AI to monitor posture and provide real-time corrections. Fitness data like calories burned and heart rate are displayed inside the lenses and users can control the system using voice commands for a fully hands-free workout. The AI trainer is trained using exercise data from professional trainers and motion capture technology. By learning from correct and incorrect examples, it recognises mistakes and provides accurate guidance. Over time, it improves by learning from real user workouts.


Design process

The design process began with identifying the problem of busy adults struggling to find time and motivation to exercise. I explored existing AR and AI technologies to conceptualise a wearable solution. Inspired by advanced mixed-reality devices, I envisioned a lightweight spectacle that could project holographic guidance directly in front of the user. I started by rendering prototypes and refining the glasses to make them lightweight and sporty for daily wear. I added micro-cameras for environment detection and real-time body tracking. I have refined the prototype to display a full-size holographic trainer and take in voice commands. The latest version integrates personalised workout recommendations, and real-time fitness data display, making workouts fully interactive, hands-free, and adaptable to different spaces.


How it is different

There are many fitness applications and tools around, but VisionFitness is different as it combines AI and Augmented Reality in a lightweight spectacle. Unlike typical apps, it projects a full-size hologram trainer in front of the user for real-time, personalised guidance. The built-in cameras detect surroundings and available equipment to recommend suitable workouts, removing the need for planning. Users can also give voice commands to the AI trainer, enabling a fully hands-free, interactive experience. This makes exercising more convenient, engaging, and accessible anywhere without relying on mobile screens or bulky devices.


Future plans

My future plan is to incorporate body posture correction and enhance battery life for longer usage. I also aim to expand VisionFitness beyond fitness guidance by integrating features such as recommending healthy recipes based on ingredients detected in the user’s surroundings.


Awards


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