eCushion: A Textile Pressure Sensor Array Design and Calibration for Sitting Posture Analysis

TLDR

Sitting posture analysis is widely used in biomedical, education, and health‑care settings, and researchers seek economical, comfortable monitoring methods, with techniques such as sensor calibration, data representation, and dynamic time‑warping improving recognition rates. The study introduces Smart Cushion, a textile‑based system that accurately and non‑invasively analyzes human sitting posture. The system employs an electrical textile sensor characterized by offset, scaling, crosstalk, and rotation, and the authors design and implement the Smart Cushion platform. Experimental results demonstrate that Smart Cushion achieves a recognition rate exceeding 85.9%.

Abstract

Sitting posture analysis is widely applied in many daily applications in biomedical, education, and health care domains. It is interesting to monitor sitting postures in an economic and comfortable manner. Accordingly, we present a textile-based sensing system, called Smart Cushion, which analyzes the sitting posture of human being accurately and non-invasively. First, we introduce the electrical textile sensor and its electrical characteristics, such as offset, scaling, crosstalk, and rotation. Second, we present the design and implementation of the Smart Cushion system. Several effective techniques have been proposed to improve the recognition rate of sitting postures, including sensor calibration, data representation, and dynamic time warping-based classification. Last, our experimental results show that the recognition rate of our Smart Cushion system is in excess of 85.9%.