Intelligent Health Recommendation System for Computer Users

TL;DR

This paper presents an intelligent health recommendation system that analyzes computer users' behaviors through visual cues like head pose, blink rate, and yawn frequency to promote healthier postures and habits.

Contribution

It introduces a novel system combining non-rigid face tracking and behavior analysis to provide personalized health recommendations for computer users.

Findings

Effective detection of head pose, blink rate, and yawn frequency.

Integration of visual cues into a health recommendation system.

Potential to reduce health issues related to prolonged computer use.

Abstract

The time people spend in front of computers has been increasing steadily due to the role computers play in modern society. Individuals who sit in front of computers for an extended period of time, specifically with improper postures may incur various health issues. In this work, individuals' behaviors in front of computers are studied using web cameras. By means of non-rigid face tracking system, data are analyzed to determine the 3D head pose, blink rate and yawn frequency of computer users. When combining these visual cues, a system of intelligent personal assistants for computer users is proposed.