FHP-RTFS - Posture Correction System

Real-time feedback system for Forward Head Posture using markerless skeletal tracking - ISEF 2020 Finalist

Project Overview

FHP-RTFS (Forward Head Posture - Real-Time Feedback System) is a computer vision-based solution for detecting and correcting poor posture when using digital devices. This project became a 2020 Regeneron ISEF finalist.

The Problem

Forward Head Posture (FHP) is a growing health concern in the digital age, where prolonged use of computers and mobile devices leads to:

  • Neck and shoulder pain
  • Reduced lung capacity
  • Headaches and fatigue
  • Long-term spinal issues

Traditional measurement methods require physical medical devices and cannot provide real-time feedback during device usage.

Our Solution

We developed a contactless feedback system that:

  1. Uses 3D webcam data for markerless skeletal tracking
  2. Measures FHP angle in real-time without any physical attachments
  3. Provides audio feedback when posture deteriorates
  4. Tracks improvement over time

Technical Implementation

Computer Vision Pipeline

  • Implemented markerless skeletal tracking using depth cameras
  • Developed novel measurement criterion for FHP angle
  • Real-time processing of 3D point cloud data
  • Audio feedback system for immediate user notification

Key Technologies

  • 3D depth sensing cameras
  • Computer vision algorithms for pose estimation
  • Real-time data processing
  • Audio feedback generation

Results

Our system demonstrated remarkable effectiveness:

  • 81% improvement in participants’ Forward Head Posture
  • Non-invasive measurement without medical equipment
  • Real-time feedback enables immediate behavior correction
  • Scalable solution applicable to various environments

Recognition

  • 2020 Regeneron ISEF Finalist - One of the world’s largest international pre-college science competitions
  • 2019 Korea Science and Engineering Fair (KSEF) Gold Award - First place, leading to ISEF qualification
  • 2020 SASA Campus Awards (Research) - Recognized for outstanding research contribution

Impact

This project demonstrates how accessible technology can address real health concerns:

  • Makes posture correction technology available without expensive medical equipment
  • Provides immediate feedback rather than periodic check-ups
  • Scalable to home, office, and educational environments
  • Proved the effectiveness of preventive health technology
Combining computer vision and health technology to solve everyday problems.

Project Duration: Feb 2019 - Feb 2020
Role: Software Lead
Organization: Sejong Academy of Science and Arts (SASA)
Awards: ISEF 2020 Finalist, KSEF 2019 Gold Award

References