D2.1 Requirements and Specification - CORBYS

D2.1 Requirements and Specification
innovative and informative new knowledge about the state and condition of the monitored subject. The
technology gaps can therefore be separated into a hardware part and a software part.
With respect to hardware the challenge is to build the most relevant sensors in a system that is
� Simple and safe to use
� Effectively combines and integrates multiple sensors in integrated devices
� A shared sensor interface that makes possible accurate time stamping and simultaneous analysis of
data
� Choose and handle a mix of wired and wireless sensors
In software the challenge is to develop relevant sensor fusion algorithms for the CORBYS gait rehabilitation
platform, and to verify and validate these.
Not all sensors and algorithms described in the sections above can be included; hence a prioritisation will be
required.
11 State­of­the­Art in Situation assessment (UR)
This section describes the current state-of-the-art on the approaches, methods and tools for automatic situation
assessment to enhance a decision made by the system making the process in a mixed-initiative intimate manmachine
interactivity context.
11.1 Introduction
Widespread commercial availability of technology has shifted human-computer interaction paradigm from a
conventional keyboard-mouse combination to more flexible modes of interactivity. Such systems comprise of
a number of modalities by which they may acquire user input to perform a function explicitly or implicitly
requested by the user. The collection of input from various modalities enables the development of intelligent
systems that are context-aware and aid in the shift from traditional systems to a more natural approach for
interaction and usability (Hurtig and Jokinen, 2006).
Context-aware interactive systems aim to adapt to the needs and behavioural patterns of users and offer a way
forward for enhancing the efficacy and quality of experience (QoE) in human-computer interaction. The
various modalities that contribute to such systems each provide a specific uni-modal response that is
integratively presented as a multi-modal interface capable of interpretation of multi-modal user input and
appropriately responding through dynamically adapted multi-modal interactive flow management.
Multimodal systems provide increased accuracy and precision (and in turn improved reliability) in terms of
context-awareness and situation assessment by incorporating information from a number of input modalities.
This approach offers a kind of fault-tolerant way of managing modalities. In the case that one of the
modalities fails or contains noisy data, information from other modalities can be used to minimise ambiguity
regarding situation assessment arising from a failed or noisy modality. The improvement in more reliable
context- sensing and thus more appropriately responsive behaviour by the interactive system is said to be a
likely outcome of multimodal fusion (Corradini et al. 2005).
Various application areas exist for such multimodal systems that can make use of feasible hardware devices to
acquire input not only at a neuro-motor but also at a physiological level for instance: in a patient monitoring
system, monitoring heart rate, perspiration, blood pressure etc. Further examples of multimodal systems
112