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This paper examines the application of the HBSI model to a range of dynamic signature verification capture digitizers. Behavioral biometrics (which considers the process by which a human performs a function) are inherently more complicated to analyze as they may contain a temporal modification as part of a valid capture interaction. In this study, a framework for the development of an HBSI model is outlined, based on two different signature digitizers. Both devices enabled the capture of both temporal data (dynamic) as well as an image of the completed (static) signature. Using this data, we propose a signature modality revision to the HBSI model with interaction errors classified into five categories. This study deals solely with genuine users, examining both correct and incorrect signature presentations.