Gaming and social interactions in the rehabilitation of brain injuries: a pilot study

Physical rehabilitation of brain injuries and strokes is a time consuming and costly process. Over the past decade several studies have emerged looking at the use of highly sophisticated technologies, such as robotics and virtual reality to tap into the needs of clinicians and patients. While such technologies can be a valuable tool to facilitate intensive movement practice in a motivating and engaging environment, success of therapy also depends on self-administered therapy beyond hospital stay. With the emergence of low-cost gaming consoles such as the Nintendo Wii, new opportunities arise for home-therapy paradigms centred on social interactions and values, which could reduce the sense of isolation and other depression related complications. In this paper we examine the potential, user acceptance and usability of an unmodified Nintendo Wii gaming console as a low-cost treatment alternative to complement current rehabilitation programmes.

The SAFEE on-board threat detection system

Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.