The focus of this study was the investigation of target handshapes in American Sign Language fingerspelling in order to determine whether there was a difference between static canonical structures and structures produced in the context of a movement sequence. This was achieved by measuring the joint angles of a signing hand with an 18-sensor CyberGlove® by Virtual Technologies, Inc.

A discriminant analysis was used to identify targets that occurred at points of minimum angular joint velocity. A multivariate analysis of variance with planned compansons was then applied to these dynamic data along with the static data to test the hypothesis.

The results showed that there was a significant difference between handshapes produced statically and those produced dynamically, which suggested that a simple, cipher model of static handshapes produced within the context of a movement sequence is not sufficient to account for the production and perception of fingerspelling. These findings may be applied to future research in sign language recognition, so that consideration of the variability of target handshapes, as influenced by the spatiotemporal environment, might be incorporated into future models.