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A battery-free, wireless graphene pressure sensor for machine learning-assisted posture classification and VR/AR visualization in smart healthcare environments

2026/01/01 by Myungwoo Choi, Younghan Kim, Hyeonseok Han +21 · 1 voice
Engineering · Health Professions · #Advanced Sensor and Energy Harvesting Materials #Non-Invasive Vital Sign Monitoring #Pressure Ulcer Prevention and Management

paper · doi:10.1039/d5mh02270c

openalex publication_date 2026/01/01 · openalex created_date 2026/02/24 · openalex updated_date 2026/08/04

Abstract

, gauge factor = 8.6) and excellent stability (over 1000 operational cycles). The platform enables real-time, reversible detection of pressure and temperature at the skin-device interfaces without external power source. By leveraging deep-learning algorithms, particularly deep neural networks (DNNs), the acquired signals are classified into distinct sitting postures, thereby enabling intelligent and continuous monitoring of patient status. Furthermore, integrated augmented- and virtual-reality (AR/VR) interfaces visualize pressure distributions in real time, enabling immersive and remote healthcare oversight. Collectively, this work introduces a graphene-based smart sensing platform that seamlessly integrates wireless operation, AI-driven analytics, and AR/VR visualization for advanced patient monitoring as a sort of personalized and interactive smart healthcare.

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