A sensing chair using pressure distribution sensors

Abstract

The sensing chair project enables an ordinary office chair to become aware of its occupant's actions and needs. Surface-mounted pressure distribution sensors are placed over the seatpan and backrest of the chair for real time capturing of contact information between the chair and its occupant. Given the similarity between a pressure distribution map and a gray-scale image, pattern recognition techniques commonly used in computer and robot vision, such as principal components analysis, were successfully applied to solving the problem of sitting posture classification. The current static posture classification system operates in real time with an overall classification accuracy of 96% and 79% for familiar and unfamiliar users, respectively. The results obtained form important stepping stones toward an intelligent chair that can find applications in many areas including multimodal interfaces, intelligent environment, and safety of automobile operations.