A Functional PCA Model for the Study of Time Series of Pressure Maps

Principal component analysis and functional regression are combined in a model to analyze a time series of pressure maps. The model is tested measuring the pressures over a chair seat while a subject performs a combination of simple movements. A sampling rate of 3 Hz is adequate for applying the model in sitting postures. The model is able to detect patterns of movement over time, although more variables are necessary if the movements produce similar pressure distributions.