Modeling vibrotactile detection by logistic regression

In this study we introduce logistic regression as a method for modeling, in this case the user's detection rate, to more easily show cross-effecting factors, necessary in order to design an adaptive system. Previously such effects have been investigated by a variety of linear regression type methods but these are not well suited for developing adaptive systems. We investigate the method on a qualitative and quantitative dataset with ages spanning from seven to 79 years under indoor and outdoor experimental settings. The results show that the method is indeed a suitable candidate for quantification of, in this instance vibrotactile information, and for the future design of user-adaptive vibrotactile displays. More generally the model shows potential for designing a variety of adaptive systems.