Adjusting data input speed in a human-computer interface system controlled by eye gaze and electroencephalography data
Background
The eye-tracking-based communication systems open up opportunities for interaction in the lives of many patients with severe motor impairments. In these systems, users need to focus their gaze on a key until it is fully entered. However, these systems are not truly refined in terms of design and interaction efficiency, and they may still cause discomfort for users, such as eye strain or typing errors. Some solutions have been proposed to address this issue, but so far, no comprehensive solution has been found.
Objective
In this research, we have proposed a novel method to adjust data inputting speed in human-computer interfaces controlled by eye gaze and electroencephalography (EEG) data.
Methods
It combines EEG data to extract the user’s attention level. We then flexibly adjust the time users need to keep their gaze on a key on the system and personalize the user experience using their own data. This approach aims to enhance interaction efficiency by increasing interaction speed while maintaining accuracy. We evaluated this method on an eye-tracking-based spelling communication system for Vietnamese people, proposed by our team, involving 20 healthy individuals and 4 people with motor function impairments.
Results
The results indicated that communication speed through the system increased by 20–80% for participants, and not only did the time improve, but the communication effectiveness also increased linearly. This outcome was achieved for both healthy individuals and patients.
Conclusions
Through experimentation, we have demonstrated the feasibility and effectiveness of our approach, showing improvements in typing speed over successive trials. This result is highly meaningful as it optimizes dwell time and interaction efficiency in the ET-based system without having to compromise by increasing the error rate when directly reducing dwell time.
