RayKnot Use Case Suite

OVERVIEW

The RayKnot supports a broad spectrum of motion analysis needs across healthcare, sports, and robotics.

As a markerless 3D motion measurement system, it provides objective and clean kinematic data that professionals integrate into their own clinical, performance, or research workflows.

This page highlights the three core domains where RayKnot is most widely applied.

Biomechanics & Gait Analysis

RayKnot provides clinicians and researchers with precise 3D measurements of joint motion, posture, balance behaviour, and functional mobility.

It supports stroke, orthopaedic, neurological, and ageing mobility studies through repeatable and objective gait measurements.

Sports Science Research

Sports scientists use RayKnot to measure athletic movement across tasks such as running, rowing, bowling, and strength & conditioning. The motion data integrates into their performance analysis, technique refinement, asymmetry assessment, and athlete development workflows.

Human-Robot Interaction

Robotics and AI teams rely on RayKnot for structured human-motion datasets used in humanoid learning, gesture modelling, tele-operation, and physical intelligence research. Its 3D measurements help bridge human motion and robot control modelling.

Rehabilitation & Healthcare

Objective measurement of gait, posture, balance, and functional mobility to support stroke, orthopaedic, and geriatric rehabilitation workflows.

Sports Science

Quantitative 3D measurements for analysing technique, training quality, movement patterns, and athletic performance refinement.

Robotics & AI

Structured motion datasets for humanoid learning, tele-operation, imitation learning, and motion-modelling in robotics.