UWB-PostureGuard: A Privacy-Preserving RF Sensing System for Continuous Ergonomic Sitting Posture Monitoring

2025-08-14

AI Summary

Prolonged sedentary behavior with poor sitting posture poses significant health risks, yet existing monitoring solutions—such as camera-based systems (raising privacy concerns) or wearable devices (causing discomfort)—exhibit critical limitations. To address this, we propose a non-contact, continuous sitting posture monitoring system leveraging off-the-shelf ultra-wideband (UWB) radio sensing. Our approach innovatively integrates UWB time-domain channel response modeling, multi-scale deep feature extraction, and a temporal-aware PoseGBDT model, explicitly capturing dynamic posture evolution beyond conventional frame-wise classification. Evaluated on 10 subjects performing 19 distinct sitting postures, the system achieves 99.11% accuracy. It demonstrates strong robustness against environmental variations—including clothing thickness and furniture changes—without requiring additional hardware deployment. The solution ensures privacy preservation, user transparency, low cost, and scalability.

Technology Category

• Humans and AI: Brain-Sensing and Analysis
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Biometrics, Face, Gesture & Pose

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT

Abstract

Improper sitting posture during prolonged computer use has become a significant public health concern. Traditional posture monitoring solutions face substantial barriers, including privacy concerns with camera-based systems and user discomfort with wearable sensors. This paper presents UWB-PostureGuard, a privacy-preserving ultra-wideband (UWB) sensing system that advances mobile technologies for preventive health management through continuous, contactless monitoring of ergonomic sitting posture. Our system leverages commercial UWB devices, utilizing comprehensive feature engineering to extract multiple ergonomic sitting posture features. We develop PoseGBDT to effectively capture temporal dependencies in posture patterns, addressing limitations of traditional frame-wise classification approaches. Extensive real-world evaluation across 10 participants and 19 distinct postures demonstrates exceptional performance, achieving 99.11% accuracy while maintaining robustness against environmental variables such as clothing thickness, additional devices, and furniture configurations. Our system provides a scalable, privacy-preserving mobile health solution on existing platforms for proactive ergonomic management, improving quality of life at low costs.

Problem

• Monitors ergonomic sitting posture without privacy concerns
• Overcomes discomfort from wearable sensors with contactless UWB technology
• Achieves high accuracy in diverse real-world conditions

Innovation

• UWB sensing for contactless posture monitoring
• PoseGBDT captures temporal posture dependencies
• High accuracy across diverse real-world conditions