PostureGuard: Stop the "Tech Neck" with MediaPipe, Electron, and Real-Time Vision 🚀 A developer built PostureGuard, a real-time posture monitoring tool using MediaPipe, OpenCV, and Electron. The tool runs on a standard CPU and detects forward head posture via pose estimation, sending alerts through a WebSocket bridge to a Vue.js frontend. Are you reading this right now while hunched over like a shrimp? 🥐 If your neck feels like it’s supporting a bowling ball at a 45-degree angle, you aren't alone. "Tech Neck" is the silent productivity killer for developers. In this tutorial, we are building PostureGuard , a lightweight, real-time posture monitoring tool. We’ll leverage Computer Vision , MediaPipe , and Electron to create a desktop companion that yells at you politely when you slouch. By using Real-time Pose Estimation , we can detect cervical spine misalignment without needing a beefy GPU. Most AI vision projects require massive compute power. However, by using MediaPipe's lightweight blazepose model and OpenCV , we can run inference on a standard CPU. This makes it perfect for a background utility app. We’ll be using a WebSocket bridge to connect our Python-based vision engine with a sleek Electron + Vue.js frontend. For those looking into more advanced production-ready AI patterns or enterprise-grade computer vision architectures, I highly recommend checking out the deep dives over at WellAlly Tech Blog https://www.wellally.tech/blog . The system logic is split into three parts: the Vision Engine sensing , the Signal Bridge transport , and the Desktop UI interaction . php graph TD A Webcam Feed -- |Frames| B MediaPipe Pose Detection B -- |Keypoints| C Angle Calculation Logic C -- |Trigger Alert| D Python WebSocket Server D -- |JSON Data| E Electron Main Process E -- |IPC Message| F Vue.js Frontend UI F -- |Visual Warning| G User Corrects Posture style B fill: f9f,stroke: 333,stroke-width:2px style F fill: 42b983,stroke: 333,stroke-width:2px Before we dive in, ensure you have the following installed: We need to track three specific points: the Ear , the Shoulder , and the Nose . By calculating the angle between these coordinates, we can determine if the head is protruding forward the dreaded "Forward Head Posture" . python import cv2 import mediapipe as mp import math mp pose = mp.solutions.pose pose = mp pose.Pose static image mode=False, min detection confidence=0.5 def calculate tilt angle ear, shoulder : Calculate the angle relative to the vertical axis angle = math.degrees math.atan2 ear.y - shoulder.y, ear.x - shoulder.x return abs angle + 90 Normalizing so 0 is upright cap = cv2.VideoCapture 0 while cap.isOpened : success, image = cap.read results = pose.process cv2.cvtColor image, cv2.COLOR BGR2RGB if results.pose landmarks: landmarks = results.pose landmarks.landmark Landmark 7: Left Ear, Landmark 11: Left Shoulder ear = landmarks 7 shoulder = landmarks 11 tilt = calculate tilt angle ear, shoulder if tilt 25: print "🚨 Slouching Detected Angle:", tilt Here we would send data via WebSockets cv2.imshow 'PostureGuard Feed', image if cv2.waitKey 5 & 0xFF == 27: break cap.release To talk to our Electron app, we’ll use a simple WebSocket server. This allows the Python script to run as a background "Sidecar" process. python import asyncio import websockets import json async def handler websocket : while True: Pseudo-logic: Send alert if slouching is detected data = {"status": "bad posture", "angle": 32.5} await websocket.send json.dumps data await asyncio.sleep 1 start server = websockets.serve handler, "localhost", 8765 asyncio.get event loop .run until complete start server asyncio.get event loop .run forever In our Vue component, we listen for these messages and trigger a system notification or an on-screen overlay. // PostureMonitor.vue