Transforming movement analysis with AI and wearable technology

Portable. Powerful. Privacy-Protecting. Engineered for clinical insight, scalable performance, and next-gen biomechanics research.

Our Services

We have created an AI-powered movement analysis system that transforms raw IMU data into precise biomechanics insights. No cameras. No force plates. No dedicated lab space. No privacy concerns. Our unique service delivers a portable, powerful, and privacy-protected movement analysis solution.

Integration

Our system is designed to work seamlessly with any IMU sensors. Provided the raw IMU data is saved in C3D format—the industry standard for motion capture—our interface can read, process, and analyse it.

Measurement

Integrated with seven IMU sensors, our system delivers powerful biomechanical insights, from joint angles and ground reaction forces to internal musculoskeletal forces across the ankle, knee, and hip joints. No bulky lab equipment. No complex setup. No images that reveal user identity. Our solution makes measurement easy, accessible, and scalable — anytime, anywhere.

Analysis

From understanding the forces underlying gait and functional movement, including individual muscle forces and joint contact forces, to optimising orthopaedic surgery, rehabilitation treatments, and assistive device design, we empower clinicians, healthcare professionals, engineers, and coaches to unlock the full potential of movement science for better outcomes.

Trusted by Researchers

Our system’s continuous evolution is powered by our world-leading research. This expertise ensures our solutions remain cutting-edge, robust, and perfectly tailored to meet the demands of modern biomechanics research and clinical practice.

Research & Development

Discover more about our work by reviewing our latest research papers.

TFNet: A Temporal-frequency Domain Model for Gait Biomechanical Signal Prediction

Measuring Lower-Limb Kinematics in Walking: Wearable Sensors Achieve Comparable Reliability to Motion Capture Systems and Smartphone Cameras

Gait Intention Prediction Using a Lower-limb Musculoskeletal Model and Long Short-term Memory Neural Networks

wearable sensors
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Our Team

Led by Dr. Ziyun Ding from the University of Birmingham, our team combines expertise in biomechanics, machine learning, and wearable technology. We’re researchers, engineers, and innovators driven by a mission to make advanced movement analysis accessible beyond the lab.

Ziyun Ding

Entrepreneurial Lead

Jonathan Roberts

Technical Transfer Officer

Qingyao Bian

Principal Scientific Advisor

Partner with Us to Shape the Future of Movement Analysis

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