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Updated: Sep 3, 2025

A Vibrotactile Feedback Device for Seated Balance Assessment and Training
Published on: January 20, 2019
Intelligent Posture Training: Machine-Learning-Powered Human Sitting Posture Recognition Based on a Pressure-Sensing
Katia Bourahmoune1, Karlos Ishac2, Toshiyuki Amagasa3
1Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba 305-8577, Japan.
Abstract:
We present a solution for intelligent posture training based on accurate, real-time sitting posture monitoring using the LifeChair IoT cushion and supervised machine learning from pressure sensing and user body data. We demonstrate our system's performance in sitting posture and seated stretch recognition tasks with over 98.82% accuracy in recognizing 15 different sitting postures and 97.94% in recognizing six seated stretches. We also show that user BMI divergence significantly affects posture recognition accuracy using machine learning. We validate our method's performance in five different real-world workplace environments and discuss training strategies for the machine learning models. Finally, we propose the first smart posture data-driven stretch recommendation system in alignment with physiotherapy standards.
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