Sports and Fitness: AI-Powered Movement and Performance Analysis
We develop computer vision and machine learning solutions that help sports and fitness products understand movement, improve technique, and deliver more personalised training experiences.
Get in touchGiving Vision to Sports and Fitness Technology
From movement analysis and exercise recognition to real-time coaching and mobile deployment, we build AI systems for connected fitness products, training platforms, and professional performance environments.
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Movement and Pose Analysis
Computer vision systems that track body position, joint movement, posture, and exercise technique using standard or specialised cameras.
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Exercise Recognition and Counting
AI models that recognise exercises, count repetitions, measure movement patterns, and identify whether activities are performed correctly.
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Real-Time Form Feedback
Immediate visual feedback that helps users improve technique, maintain proper posture, and reduce potentially unsafe movement.
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Performance and Engagement Insights
Multimodal analysis of movement, attention, effort, engagement, and other behavioural signals during training.
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Mobile and Edge AI
Efficient AI models deployed on smartphones, connected fitness equipment, wearables, and other edge devices for responsive, privacy-conscious analysis.
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Custom AI Development
Tailored AI solutions built around specific sports and fitness applications, from initial feasibility studies to production deployment.
Use Cases For Sports and Fitness Industry
Examples of how machine learning and computer vision can help transform sports events, sport tech and help pave the way for better results and experiences.
Training platforms often lack insight into how users are actually performing and responding
Digital training, coaching, and simulation platforms can track basic metrics such as repetitions, completion rates, or session duration, but often have limited understanding of movement quality, engagement, cognitive workload, stress, or frustration. Without this context, it is difficult to adapt training effectively to the individual user or identify when performance is being affected by physical or cognitive factors.
Multimodal AI for real-time performance and behavioural analysis
Computer vision and machine learning can combine camera, microphone, and wearable data to analyse movement together with behavioural and cognitive-affective signals such as attention, engagement, workload, stress, and frustration.
Integrated into a training platform, these insights can be used to dynamically adjust content, difficulty, pacing, or feedback according to the user’s current performance and state. The technology can support digital coaching applications, fitness platforms, professional simulators, and other connected training systems while being developed as reusable AI components for integration into existing products.
- Computer Vision / Machine Learning
- Multimodal AI
- Movement and Behaviour Analysis
- Cognitive-Affective Analysis
- Detection and Classification AI
- Sensor and Wearable Data Integration
- Adaptive AI Systems
- R&D
- Custom AI Development
Incorrect movement can reduce training effectiveness and increase injury risk
Athletes and fitness users often train without continuous access to a coach who can monitor technique and provide immediate feedback. Small deviations in posture, joint position, or movement patterns can reduce exercise effectiveness and, over time, contribute to unnecessary strain or injury. Traditional video review is useful, but it is often manual, retrospective, and difficult to scale across large numbers of users.
Camera-based movement and technique analysis
Computer vision and machine learning can analyse body position, movement patterns, joint angles, and exercise execution using standard cameras or mobile devices. The system can compare observed movement against predefined technique criteria, identify deviations, and provide real-time or post-session feedback on form and execution. Integrated into fitness, coaching, or rehabilitation platforms, the technology can support repetition counting, range-of-motion analysis, movement quality assessment, and personalized corrective guidance. This enables digital products to deliver more consistent technique feedback while reducing dependence on continuous one-to-one supervision.
- Computer Vision / Machine Learning
- Body and Pose Analysis
- Movement and Activity Recognition
- Measurement and Position Estimation
- Mobile AI
- Detection and Classification AI
- R&D
- Custom AI Development
