Specification of multiparty audio and video interaction based on the Reference Model of Open Distributed Processing

The Reference Model of Open Distributed Processing (RM-ODP) is an emerging ISO/ITU-T standard. It provides a framework of abstractions based on viewpoints, and it defines five viewpoint languages to model open distributed systems. This paper uses the viewpoint languages to specify multiparty audio/video exchange in distributed systems. To the designers of distributed systems, it shows how the concepts and rules of RM-ODP can be applied.\ud \ud The ODP ¿binding object¿ is an important concept to model continuous data flows in distributed systems. We take this concept as a basis for multiparty audio and video flow exchanges, and we provide five ODP viewpoint specifications, each emphasising a particular concern. To ensure overall correctness, special attention is paid to the mapping between the ODP viewpoint specifications

Interpreting streaming biosignals:in search of best approaches to augmenting mobile health monitoring with machine learning for adaptive clinical decision support

We investigate Body Area Networks for ambulant patient monitoring. As well as sensing physiological parameters, BAN applications may provide feedback to patients. Automating formulation of feedback requires realtime analysis and interpretation of streaming biosignals and other context and knowledge sources. We illustrate with two prototype applications: the first is designed to detect epileptic seizures and support appropriate intervention. The second is a decision support application aiding weight management; the goal is to promote health and prevent chronic illnesses associated with overweight/obesity. We begin to explore extending these and other m-health applications with generic AI-based decision support and machine learning. Monitoring success of different behavioural change strategies could provide a basis for machine learning, enabling adaptive clinical decision support by personalising and adapting strategies to individuals and their changing needs. Data mining applied to BAN data aggregated from large numbers of patients opens up possibilities for discovery of new clinical knowledge