
In this course, we explore how ordinary cameras and modern computer vision techniques can support objective movement assessment during telehealth consultations.
Topics include:
Observation versus measurement
Markerless motion capture
Range of motion
Body sway
Clinical workflows
Real-world implementation
Limitations and practical considerations
This course is intended for physiotherapists, exercise physiologists, sports scientists, rehabilitation professionals, researchers, and students. Practical demonstrations use PoseIQ Live.
In this section, we explore the principles behind markerless motion capture and camera-based movement analysis.
Using ordinary cameras, computer vision systems can estimate body landmarks, create geometric relationships between them, and calculate clinically useful movement measures.
In this lesson, we cover:
Markerless pose estimation
Body landmarks
Joint geometry
Movement over time
Tracking quality
Measurement limitations
Clinical interpretation
The objective is not to replace clinical expertise, but to support it with objective information.
Practical demonstrations use PoseIQ Live.
In this section, we look at the simple workflow behind remote movement measurement with PoseIQ Live. A clinician sends one link, the patient opens it on their phone, steps into view, performs a movement, and the clinician receives movement information in real time. This approach can work alongside Zoom, Google Meet, or a standard phone call, keeping the technology simple for both clinicians and patients.
How can we move from simply observing movement to measuring it objectively?
In this section, we explore how camera-based movement measurement works, from identifying body landmarks and calculating joint angles to tracking motion over time and estimating range of motion.
We also look at the most important principle: objective data supports professional judgement, rather than replacing it.
Movement is more than joint angles. In this section, we explore how camera-based tracking can be used to visualize whole-body sway and movement trajectories.
We look at how sway patterns change across different tasks, what those patterns may tell us about stability and movement strategy, and the important difference between a practical camera-based body-centre estimate and laboratory-grade centre-of-mass measurement.
Learn how movement data moves from observation and measurement to useful clinical context and reporting.
Learn the simple setup principles that improve camera-based movement tracking, from lighting and framing to visibility and video quality.
Learn some practical applications of teleheath and remote rehabilitation and what comes next following this course.
A quick demonstration of PoseIQ Live, showing how clinicians, therapists and coaches can assess movement remotely using a standard camera. It enables real-time movement tracking and objective measurements through a simple browser-based workflow, with no specialised equipment required.
Objective Telehealth: From Observation to Measurement
Telehealth makes it possible to see patients and clients anywhere, but observing movement through a camera is not the same as objectively measuring it.
This short, practical course introduces the fundamentals of camera-based movement measurement for telehealth, rehabilitation, exercise and human movement applications.
You’ll start by exploring the difference between observing movement and measuring it. From there, you’ll learn in simple terms how a normal camera can detect body landmarks and use them to estimate useful movement measures.
We’ll then work through practical examples including joint angles, range of motion, body sway and functional movement. You’ll also see how a simple remote movement session can work between a clinician and patient using everyday devices.
The course covers the practical factors that affect camera-based measurement, including camera position, framing, lighting, body visibility and connection quality. You’ll learn what to check when tracking or measurements don’t look right.
Finally, we’ll bring everything together into a simple workflow: observe, measure, capture, add context and report.
The emphasis throughout the course is not on replacing professional judgement. Objective measurement provides an additional layer of information that can support observation, communication, follow-up and clinical reasoning.
This course is designed to be accessible even if you have no previous experience with computer vision or camera-based movement analysis.