Main Investigator: Dr Ing. Nathaniel Barbara, Centre for Biomedical Cybernetics
Main Investigator: Prof. Ing. Tracey Camilleri, Centre for Biomedical Cybernetics, Department of Systems and Control Engineering
Main Investigator: Prof. Ing. Kenneth Camilleri, Centre for Biomedical Cybernetics, Department of Systems and Control Engineering
Systems Engineer: Ing. Matthew Mifsud, Department of Systems and Control Engineering
Research Support Officer: Ms Rodianne Sciberras
Externally funded: Ministry for Education, Sport, Youth, Research and Innovation (€35,585)
Summary:
The SmartGaze project builds upon the success of the first version of this project funded through the Xjenza Malta Smart Cities Programme, through which significant progress was made in developing a state-of-the-art system that enables users to control devices, such as air conditioners, TVs, and motorised blinds, using their head-gaze and eye movements alone. Notably, this system does not rely on any computer interfaces that typically require users to select icons to initiate specific commands. Instead, devices are controlled by having users rotate their heads towards the desired device, allowing it to be identified by the system through location and head orientation tracking. Once a device is selected, the user performs subtle up, down, left, or right eye movements, or blinks, that are detected by signal processing algorithms and used to execute device-specific commands. These movements are captured using electrooculography (EOG) signals, which are low-magnitude biopotentials generated by the eyes that are recorded via electrodes attached to the face. Specifically, they are recorded using the JINS MEME EOG glasses which incorporates electrodes inconspicuously within the bridge and nose pads of a pair of glasses. Complementing this system, the team has been developing a custom-designed, wireless, wearable, discrete and unobtrusive EOG acquisition device in the form of a lightweight eye mask, with integrated sensors to record EOG signals and head orientation.
The new SmartGaze project aims to further enhance this technology by improving the system's accuracy and reliability. This project seeks to leverage advancements in artificial intelligence, signal processing and machine learning to refine the algorithms used for the detection of the user’s eye movements, ensuring greater reliability and a more seamless experience. Additionally, with the support of this funding, another iteration of the wearable eye masks’ form-factor will be undertaken, focusing on making it more discrete and aesthetically pleasing while ensuring stable electrode contact. This refinement will not only improve the performance, but it will also enhance user comfort and user acceptance. Furthermore, necessary upgrades to an existing prototype system will be purchased as needed to deploy the SmartGaze prototype in a specialized residence for individuals with severe mobility impairments, such as Dar Bjorn. This installation will empower residents to control their environment independently and will help collect valuable feedback from end users.
