Chair: Eve Hoggan, University of Helsinki, Finland
Touché: Enhancing Touch Interaction on Humans, Screens, Liquids, and Everyday Objects
Contribution & Benefit: Touché uses a novel Swept Frequency Capacitive Sensing technique that can easily add rich touch and gesture sensitivity to a wide variety of objects, including the human body and water.
Abstract » Touché proposes a novel Swept Frequency Capacitive Sensing technique that can not only detect a touch event, but also recognize complex configurations of the human hands and body. Such contextual information significantly enhances touch interaction in a broad range of applications, from conventional touchscreens to unique contexts and materials. For example, in our explorations we add touch and gesture sensitivity to the human body and liquids. We demonstrate the rich capabilities of Touché with five example setups from different application domains and conduct experimental studies that show gesture classification accuracies of 99% are achievable with our technology.ACM
Detecting Error-Related Negativity for Interaction Design
Contribution & Benefit: Demonstrate the capabilities of an off-the-shelf headset in detecting Error Related Negativity on a single trial basis. Show that the detection accuracies are sufficient for use in real-time interactive applications.
Abstract » This paper 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. ERN is triggered when a user either makes a mistake or the application behaves differently from their expectation. 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.ACM
Implanted User Interfaces
Contribution & Benefit: We investigate the effect of skin on traditional components for sensing input, providing output, and for communicating, synchronizing and charging wirelessly.
Abstract » We investigate implanted user interfaces that small devices provide when implanted underneath human skin. Such devices always stay with the user, making their implanted user interfaces available at all times. We discuss four core challenges of implanted user interfaces: how to sense input through the skin, how to produce output, how to communicate amongst one another and with external infrastructure, and how to remain powered. We investigate these four challenges in a technical evaluation where we surgically implant study devices into a specimen arm. We find that traditional interfaces do work through skin. We then demonstrate how to deploy a prototype device on participants, using artificial skin to simulate implantation. We close with a discussion of medical considerations of implanted user interfaces, risks and limitations, and project into the future. ACM
EEG Analysis of Implicit Human Visual Perception
Contribution & Benefit: Explores use of EEG as an implicit measure of video quality. Can be used to derive a new perception-based quality metric for use in image-based rendering and optimization of IBR techniques
Abstract » Image Based Rendering (IBR) allows interactive scene ACM
exploration from images alone. However, despite
considerable development in the area, one of the main
obstacles to better quality and more realistic visualizations
is the occurrence of visually disagreeable artifacts. In this
paper we present a methodology to map out the perception
of IBR-typical artifacts. This work presents an alternative to
traditional image and video quality evaluation methods by
using an EEG device to determine the implicit visual
processes in the human brain. Our work demonstrates the
distinct differences in the perception of different types of
visual artifacts and the implications of these differences.
Development and Evaluation of Interactive System for Synchronizing Electric Taste and Visual Content
Contribution & Benefit: Describes apparatuses to add electric taste to food or drink and the latencies for electric taste and visual stimuli to develop an interactive system synchronizing those contents.
Abstract » Electric taste is a characteristic taste produced when the tongue is electrically stimulated. We have proposed apparatuses to add electric taste to food and drink. An interactive system could be developed to synchronize video contents using the reversibility and instantaneity of electric taste. However, to do so, the presentation time must be determined based on the different latency for the perception of each sense. We measured the latencies for electric taste and visual stimuli as a basic evaluation for a content presentation system in which electric taste and visual content are synchronized.ACM