In the era of telehealth, the gap between a patient's living room and the physiotherapy clinic is closing fast. Thanks to breakthroughs in Computer Vision and Edge AI, we no longer need expensive motion-capture suits to track movement. Using MediaPipe, Pose Estimation, and WebAssembly, we can turn a standard webcam into a sophisticated clinical tool that provides real-time biomechanical feedback. This tutorial will show you how to build a lightweight skeleton tracking system capable of analyzing exercises like squats or lunges. We will leverage TensorFlow.js and the high-performance MediaPipe runtime to calculate joint angles directly in the browser. If you're looking for more advanced production-ready patterns and deep dives into AI-driven healthcare, be sure to check out the technical resources at WellAlly Tech Blog, which served as the inspiration for this architecture. To achieve "real-time" performance (30+ FPS) on a browser, we need a pipeline that minimizes latency. By using WebAssembly (WASM), MediaPipe processes video frames at near-native speeds. graph TD A[Webcam Stream] --> B[React Camera Component] B --> C[MediaPipe Pose Engine] C --> D{Keypoint Detection} D --> E[Angle Calculation Logic] E --> F[Visual Overlay / Canvas] E --> G[Speech Synthesis Feedback] G --> H[User: 'Straighten your back!'] Before we dive into the code, ensure you have a React environment ready. We will be using: MediaPipe Pose: For high-fidelity body tracking. React: For the UI layer. WebAssembly: To run the ML models efficiently in-browser. First, we need to set up the MediaPipe Pose listener. This engine detects 33 3D landmarks on the human body. import { Pose } from "@mediapipe/pose"; import * as cam from "@mediapipe/camera_utils"; const pose = new Pose({ locateFile: (file) => { return `https://cdn.jsdelivr.net/npm/@mediapipe/pose/${file}`; }, }); pose.setOptions({ modelComplexity: 1, smoothLandmarks: true, minDetectionConfidence: 0.5, minTrackingConfidence: 0.5, }); For physical therapy, knowing "where" a joint is isn't enough; we need to know the angle. For a squat, we calculate the angle between the Hip, Knee, and Ankle. /** * Calculates the angle between three points (A, B, C) * B is the vertex (e.g., the Knee) */ function calculateAngle(a, b, c) { const radians = Math.atan2(c.y - b.y, c.x - b.x) - Math.atan2(a.y - b.y, a.x - b.x); let angle = Math.abs((radians * 180.0) / Math.PI); if (angle > 180.0) angle = 360 - angle; return angle; } // Usage in the MediaPipe results callback: const kneeAngle = calculateAngle(results.poseLandmarks[24], // Hip results.poseLandmarks[26], // Knee results.poseLandmarks[28]);// Ankle Now, let's turn those numbers into actionable advice. If the user's knee angle suggests they are squatting too shallowly or their form is collapsing, the system will trigger a voice command. const provideFeedback = (angle) => { const synth = window.speechSynthesis; if (angle > 160) { // Standing up return "Lower your hips more."; } else if (angle < 90) { // Too deep for some patients const utter = new SpeechSynthesisUtterance("Great depth, keep your back straight!"); synth.speak(utter); } }; While this implementation is great for a weekend project, production-grade Remote Physiotherapy platforms require much more: data persistence, HIPAA compliance, and advanced filtering to handle "noisy" environments. For developers looking to take this to the next level—such as implementing multi-person tracking or integrating with backend HL7 FHIR standards—I highly recommend exploring the deep-dive articles at wellally.tech/blog. They offer incredible insights into the intersection of Edge AI and modern healthcare infrastructure. By combining MediaPipe's skeleton tracking with simple trigonometric functions, we've built a system that can literally "see" and "correct" human movement. This is the power of modern Vision AI—bringing specialized expertise to anyone with a browser and a webcam. What's next? Add a "Rep Counter" using a simple state machine. Integrate a Chart.js dashboard to track knee mobility over time. Share your progress in the comments below! 👇