August 9, 2025

Multi-Sensor Based Body Upright Balance and Neck Posture Detection System.

Key Points

MAIN FINDING: The multi-sensor posture detection system achieved an accuracy of 97% in identifying poor body posture.
KEY EVIDENCE: Validation was conducted using 32 experimental datasets, demonstrating the system's reliability.
APPROACH: The system combines pressure sensors and a camera with a neural network and MobileNet model.
SIGNIFICANCE: Improved posture monitoring can lead to better musculoskeletal health and workplace ergonomics.

Abstract

Poor sitting posture is a major contributor to musculoskeletal health problems, such as neck pain, lower back pain, and spinal deformities, caused by prolonged slouching or hunching during activities like computer and smartphone use. To address these issues, this study developed an intelligent posture detection system utilizing a multi-sensor setup combining pressure sensors and a camera, integrated with a fully connected neural network and a pre-trained MobileNet model. The system was validated using 32 experimental datasets, achieving an overall accuracy of 97%. This research highlights the potential of AI-driven posture monitoring systems to improve workplace ergonomics and promote better health.

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Cite This Study

Zhang et al. (Thu,) studied this question.

synapsesocial.com/papers/689dfe97d61984b91e13bef7 https://doi.org/https://doi.org/10.3233/shti251133

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