People today spend longer seated resulting from changes in demand on the workforce. As a result there is a need for a greater understanding of factors affecting pressure sore formation and comfort in general. In order to monitor the body-cushion interface temperature, we have developed a portable five-channel temperature measuring system which can be powered by a laptop. An Empirical Mode Decomposition (EMD) was used to remove noise of thermal data between body and seat contact surface. The performance of this data driven filter was compared with three other filters (medium filter, adaptive filter and wavelet filter) with the help of the goodness of fitness statistics as judgment criteria. Results showed the EMD-based filter worked better than traditional de-noising algorithms with the lowest RMSE (root-mean-square-error) and the highest R2 values
