Human Computer Interface using Eye Gazing with error fixation in Smooth and Saccadic Eye Movement

Human Computer Interface (HCI) requires proper coordination and definition of features that serve as input to the system. The parameters of a saccadic and smooth eye movement tracking are observed and a comparison is drawn for HCI. This methodology is further incorporated with Pupil, OpenCV and Microsoft Visual Studio for image processing to identify the position of the pupil and observe the pupil movement direction in real-time. Once the direction is identified, it is possible to determine the accurate cruise position which moves towards the target. To quantify the differences between the step-change tracking of saccadic eye movement and incremental tracking of smooth eye movement, the test was conducted on two users. With the help of incremental tracking of smooth eye movement, an accuracy of 90% is achieved. It is found that the incremental tracking requires an average time of 7.21s while the time for step change tracking is just 2.82s. Based on the observations, it is determined that, when compared to the saccadic eye movement tracking, the smooth eye movement tracking is over four times more accurate. Therefore, the smooth eye tracking was found to be more accurate, precise, reliable, and predictable to use with the mouse cursor than the saccadic eye movement tracking.

Improvement of association between confidence and accuracy after integration of discrete evidence over time

When making decisions in real-life, we may receive discrete pieces of evidence during a time period. Although subjects are able to integrate information from separate cues to improve their accuracy, confidence formation is controversial. Due to a strong positive relation between accuracy and confidence, we predicted that confidence followed the same characteristics as accuracy and would improve following the integration of information collected from separate cues. We applied a Random-dot-motion discrimination task in which participants had to indicate the predominant direction of dot motions by saccadic eye movement after receiving one or two brief stimuli (i.e., pulse(s)). The interval of two pulses (up to 1s) was selected randomly. Color-coded targets facilitated indicating confidence simultaneously. Using behavioral data, computational models, pupillometry and EEG methodology we show that in double-pulse trials: (i) participants improve their confidence resolution rather than reporting higher confidence comparing with single-pulse trials, (ii) the observed confidence follow neural and pupillometry markers of confidence, unlike in weak and brief single-pulse trials. Overall, our study showed improvement of associations between confidence and accuracy in decision results from the integration of stimulus separated by different temporal gaps.

Previous motor actions outweigh sensory information in sensorimotor learning

Humans can use their previous experience in form of statistical priors to improve decisions. It is however unclear how such priors are learned and represented. Importantly, it has remained elusive whether prior learning is independent of the sensorimotor system involved in the learning process or not, as both modality-specific and modality-general learning have been reported in the past. Here, we used a saccadic eye movement task to probe the learning and representation of a spatial prior across a few trials. In this task, learning occurs in an unsupervised manner and through encountering trial-by-trial visual hints drawn from a distribution centered on the target location. Using a model-comparison approach, we found that participants’ prior knowledge is largely represented in the form of their previous motor actions, with minimal influence from the previously seen visual hints. By using two different motor contexts for response (looking either at the estimated target location, or exactly opposite to it), we could further compare whether prior experience obtained in one motor context can be transferred to the other. Although learning curves were highly similar, and participants seemed to use the same strategy for both response types, they could not transfer their knowledge between contexts, as performance and confidence ratings dropped to naïve levels after a switch of the required response. Together, our results suggest that humans preferably use the internal representations of their previous motor actions, rather than past incoming sensory information, to form statistical sensorimotor priors on the timescale of a few trials.