The purpose of this research is to assess the sensitivity of humans to perceive asynchrony among media signals coming from a computer application. Particularly we examine haptic-to-video and haptic-to-audio skew. For this purpose we have designed an experimental setup, where users are exposed to a basic multimedia presentation resembling a ping-pong game. For every collision between a ball and a racket, the user is able to perceive auditory, visual, and haptic cues about the collision event. We artificially introduce negative and positive delay to the auditory and visual cues with respect to the haptic stream. We subjectively evaluate the perception of inter-stream asynchrony perceived by the users using two types of haptic devices. The statistical results of our evaluation show perception rates of around 100 ms regardless of modality and type of device.

A wide range of haptic devices exist that possess the potential to offer users a rich experience in a virtual reality environment. This however depends on the haptic device to be used. Surely, removing the burden of users having to 'adjust to' operating haptic devices is welcomed. In this paper, we propose the creation of the Haptic Applications Meta Language - hereon HAML - which is an XML-based language created to describe Haptic-enabled frameworks to a high degree of detail. The envisioned goal of HAML is to allow for the creation of plug-and-play environments in which a wide array of supported haptic devices can be used in a multitude of virtual environments, with the compatibility issues being handled by automated engines instead of programmatically by the user. Therefore, we introduce the HAML framework and discuss its tentative structure, proof-of-concept implementation, and avenues for future work.

Authentication for the purposes of security has taken giant strides since the introduction of Biometrics to help identify people by their behavioral and physiological features. From organizations and corporations to educational institutes, electronic resources, and even crime scenes, Biometrics offers a wide application scope to detect fraud attempts. This paper proposes a research path to achieve the task of authenticating users that are working in a haptic-based environment. The field of Biometrics can be divided into two main classes of human features. Birth-given characteristics like fingerprints and facial features cannot be developed or altered by humans. Behavioral characteristics such as hand signature and voice fall into the second class [1]. The work presented in this paper pursues the latter class and specifically studies how a person reacts to using daily devices or tools. The fact that we can exploit people's habits in handling devices to detect identity was the hypothesis that motivated this work.