IMPROVEMENTS IN A FIBEROPTIC SKIN-SURFACE SENSOR

Outputs from a fibre-optic skin-surface sensor have been mathematicall y or statistically investigated for better extraction of information a bout the skin-surface conditions. Methods employed in this study inclu de simple or multiple regression analysis, functional fitting (for ext racting characteristic parameters) and principal-component analysis. T he regression analysis using the sensor outputs and the skin water con tent has made it clear that a large applied force of the sensor is pre ferable and that a measurement time period of 6-7 s is required to obt ain the maximum correlation. For reduction of the measurement time per iod, the use of multiple correlation has been found to be advantageous . Principal-component analysis using the sensor outputs has revealed t hat the first principal component has a much larger contribution ratio and corresponds to the degree of skin hydration. However, it is not c lear what the second component means.