ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training
Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou, Paul Lukowicz, Sungho Suh

TL;DR
ChairPose is a novel pressure-based seated pose estimation system that accurately predicts full-body sitting postures without relying on chair geometry, addressing privacy and occlusion issues of existing methods.
Contribution
It introduces the first wearable, chair-agnostic pressure sensing system with a physics-driven data augmentation pipeline for robust, generalizable seated pose estimation.
Findings
Achieves 89.4 mm mean joint error on unseen users and chairs.
Operates independently of chair geometry and occlusion.
Demonstrates robustness across diverse users and seating conditions.
Abstract
Prolonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive systems. Existing posture sensing methods such as vision-based or wearable approaches face limitations including occlusion, privacy concerns, user discomfort, and restricted deployment flexibility. We introduce ChairPose, the first full body, wearable free seated pose estimation system that relies solely on pressure sensing and operates independently of chair geometry. ChairPose employs a two stage generative model trained on pressure maps captured from a thin, chair agnostic sensing mattress. Unlike prior approaches, our method explicitly incorporates chair morphology into the inference process, enabling accurate, occlusion free, and privacy preserving pose estimation. To support generalization across diverse users…
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Taxonomy
TopicsErgonomics and Musculoskeletal Disorders · Interactive and Immersive Displays · Pressure Ulcer Prevention and Management
