Brain Computer Interface
Detecting Error-Related Negativity for Interaction Design
Error-Related Negativity is a brain pattern triggered when a user either makes a mistake or the application behaves differently from their expectation. Our first work examines the ability to detect a characteristic brain potential called the Error-Related Negativity (ERN) using off-the-shelf headsets and explores its applicability to HCI. We first show that ERN can be seen on signals captured by EEG headsets like Emotiv™ when doing a typical multiple choice reaction time (RT) task – Flanker task. We then present a single-trial online ERN algorithm that works by pre-computing the coefficient matrix of a logistic regression classifier using some data from a multiple choice reaction time task and uses it to classify incoming signals of that task on a single trial of data. We apply it to an interactive selection task that involved users selecting an object under time pressure. Furthermore the study was conducted in a typical office environment with ambient noise. Our results show that online single trial ERN detection is possible using off-the-shelf headsets during tasks that are typical of interactive applications. We then design a Superflick experiment with an integrated module mimicking an ERN detector to evaluate the accuracy of detecting ERN in the context of assisting users in interactive tasks. Based on these results we discuss and present several HCI scenarios for use of ERN.
In the next step, we investigates ERN in collaborative settings where observing another user (the executer) perform a task is typical and then explores its applicability to HCI. We first show that ERN can be detected on signals captured by commodity EEG headsets like an Emotiv headset when observing another person perform a typical multiple-choice reaction time task. We then investigate the anticipation effects by detecting ERN in the time interval when an executer is reaching towards an answer. We show that we can detect this signal with both a clinical EEG device and with an Emotiv headset. Our results show that online single trial detection is possible using both headsets during tasks that are typical of collaborative interactive applications. However there is a trade-off between the detection speed and the quality/prices of the headsets. Based on the results, we discuss and present several HCI scenarios for use of ERN in observing tasks and collaborative settings.
Chi Thanh Vi, Izdihar Jamil, David Coyle, Sriram Subramanian, “Error Related Negativity in Observering Interacive Tasks”, In proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI 2014), ACM. Toronto, Canada. 2014.
Chi Thanh Vi, Sriram Subramanian, “Detecting Error-related Negativity For Interaction Design”, In proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI 2012), ACM. Austin, Texas, USA. 2012. ♦ Best Paper Award ♦
Chi Thanh Vi, Sriram Subramanian, “Online Single Trial Ern Detection As An Interaction Aid In HCI Applications”, In CHI 2011 Workshop on Brain and Body Interfaces: Designing for Meaningful Interaction. Vancouver, Canada. 2011.