ROLE OF ARTIFICIAL INTELLIGENCE-BASED WEARABLE SENSORS FOR POSTURE MONITORING AND CORRECTION AMONG UNIVERSITY STUDENTS WITH PROLONGED LAPTOP USAGE: A NARRATIVE REVIEW

Abstract

Background: College students frequently use laptops for prolonged periods of time, which results in cervicothoracic flexion and forward head posture (FHP) causing neck discomfort. Traditional posture measurement is performed using intermittent evaluations which rely on the observer’s input, while the combination of wearable inertial sensors and machine learning provides the opportunity for continuous posture classification and real-time bio- feedback.

Aim: To provide a critical summary of the available literature on wearables with artificial intelligence (AI) used for posture correction and monitoring, specifically on university students using laptops.

Literature approach: The peer-reviewed literature, which mainly covers the period from 2019 to 2026, was discovered through targeted searches and citations, and it was narratively evaluated against recognized standards such as SANRA, COSMIN, TRIPOD+AI, and CONSORT-AI.

Major findings: Wearable systems have demonstrated satisfactory performance in controlled settings, classifying seated and head-neck postures with high accuracy, and vibrating, auditory, and visual feedback can instantly improve the alignment of the body. However, randomized studies are limited and mostly consist of small and short-term trials focusing on workers rather than students, and no trial on AI-based wearable technology in student populations was found. Moreover, aspects such as free-living validity, retention of technology over time, adherence to wearables, privacy, and external validity are still poorly studied.

Conclusion: AI-based wearables, although, appear to have certain prospects as an adjunct in physiotherapy education, the existing evidence does not support the recommendation of their use in clinical practice.