A crosstalk-free interdigital electrode piezoresistive sensor matrix-based human-machine interaction system for automatic sitting posture recognition

Abstract

Sedentarism with poor posture has been a significant concern for students and office workers. In this work, for inappropriate sitting posture monitoring, we developed a human machine interaction (HMI) system based on a piezoresistive sensor matrix, which achieves crosstalk-free pressure distribution detection by the inserting diodes method (IDM) with a structure simplified by the interdigital electrode (IDE) configuration. To measure the pressure distribution, a sensor matrix of 9×14 piezoresistive sensing pixels is fabricated by the standard flexible printed circuit (FPC) technique. The single sensing pixel shows a high sensitivity in the pressure below 20 kPa, covering the range of the human-seat contact pressure, and demonstrates the highest sensitivity of 9.865% kPa−1. The combination of the IDE and the IDM eliminates the crosstalk error completely, enabling the sensor matrix to accurately measure the human-chair contact pressure distribution. To develop an HMI system for sitting posture detection, pressure distribution data from subjects of different body shapes, including sitting upright, leaning forward, slumped sitting, crossing right legs, and crossing left legs, is collected using the proposed sensor matrix and used for training and evaluation of the convolution neural network (CNN) model. Accurate posture classification is achieved both in within-group and cross-group tests, showing the highest accuracy of 99.14% and an excellent generalization performance. With an excellent performance of crosstalk-free pressure distribution detection, the device in this study exhibits great application potential in daily sitting posture monitoring.