scholarly journals M[eye]cro

2021 ◽  
Vol 5 (EICS) ◽  
pp. 1-22
Author(s):  
Jérémy Wambecke ◽  
Alix Goguey ◽  
Laurence Nigay ◽  
Lauren Dargent ◽  
Daniel Hauret ◽  
...  
Keyword(s):  
State Of The Art ◽  
Eye Gaze ◽  
The State ◽  
Controlled Experiment ◽  
Selection Task ◽  
Interaction Technique ◽  
Time Performance ◽  
Free Interaction

We present M[eye]cro an interaction technique to select on-screen objects and navigate menus through the synergistic use of eye-gaze and thumb-to-finger microgestures. Thumb-to-finger microgestures are gestures performed with the thumb of a hand onto the fingers of the same hand. The active body of research on microgestures highlights expected properties including speed, availability and eye-free interaction. Such properties make microgestures a good candidate for multitasking. However, while praised, the state-of-the-art hypothesis stating that microgestures could be beneficial for multitasking has never been quantitatively verified. We study and compare M[eye]cro to a baseline, i.e., a technique based on physical controllers, in a cockpit-based context. This context allows us to design a controlled experiment involving multitasking with low- and high-priority tasks in parallel. Our results show that performances of the two techniques are similar when participants only perform the selection task. However, M[eye]cro tends to yield better time performance when participants additionally need to treat high-priority tasks in parallel. Results also show that M[eye]cro induces less fatigue and is mostly preferred.

scholarly journals Exploring Large Virtual Environments by Thoughts Using a Brain–Computer Interface Based on Motor Imagery and High-Level Commands

2010 ◽  
Vol 19 (1) ◽  
pp. 54-70 ◽  
Author(s):  
Fabien Lotte ◽  
Aurélien van Langhenhove ◽  
Fabrice Lamarche ◽  
Thomas Ernest ◽  
Yann Renard ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Motor Imagery ◽  
State Of The Art ◽  
Complex Interaction ◽  
The State ◽  
Virtual Museum ◽  
Interaction Technique ◽  
Low Level ◽  
Points Of Interest ◽  
High Level

Brain–computer interfaces (BCI) are interaction devices that enable users to send commands to a computer by using brain activity only. In this paper, we propose a new interaction technique to enable users to perform complex interaction tasks and to navigate within large virtual environments (VE) by using only a BCI based on imagined movements (motor imagery). This technique enables the user to send high-level mental commands, leaving the application in charge of most of the complex and tedious details of the interaction task. More precisely, it is based on points of interest and enables subjects to send only a few commands to the application in order to navigate from one point of interest to the other. Interestingly enough, the points of interest for a given VE can be generated automatically thanks to the processing of this VE geometry. As the navigation between two points of interest is also automatic, the proposed technique can be used to navigate efficiently by thoughts within any VE. The input of this interaction technique is a newly-designed self-paced BCI which enables the user to send three different commands based on motor imagery. This BCI is based on a fuzzy inference system with reject options. In order to evaluate the efficiency of the proposed interaction technique, we compared it with the state of the art method during a task of virtual museum exploration. The state of the art method uses low-level commands, which means that each mental state of the user is associated with a simple command such as turning left or moving forward in the VE. In contrast, our method based on high-level commands enables the user to simply select its destination, leaving the application performing the necessary movements to reach this destination. Our results showed that with our interaction technique, users can navigate within a virtual museum almost twice as fast as with low-level commands, and with nearly half the commands, meaning with less stress and more comfort for the user. This suggests that our technique enables efficient use of the limited capacity of current motor imagery-based BCI in order to perform complex interaction tasks in VE, opening the way to promising new applications.

scholarly journals Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding

2020 ◽  
Vol 34 (05) ◽  
pp. 9032-9039
Author(s):  
Zhixing Tian ◽  
Yuanzhe Zhang ◽  
Xinwei Feng ◽  
Wenbin Jiang ◽  
Yajuan Lyu ◽  
...  
Keyword(s):  
State Of The Art ◽  
The State ◽  
Selection Task ◽  
Multiple Perspectives ◽  
Selection Models ◽  
Proposed Model ◽  
Adversarial Examples ◽  
Overall Performance ◽  
Traditional Representation

This paper focuses on the answer sentence selection task. Unlike previous work, which only models the relation between the question and each candidate sentence, we propose Multi-Perspective Graph Encoder (MPGE) to take the relations among the candidate sentences into account and capture the relations from multiple perspectives. By utilizing MPGE as a module, we construct two answer sentence selection models which are based on traditional representation and pre-trained representation, respectively. We conduct extensive experiments on two datasets, WikiQA and SQuAD. The results show that the proposed MPGE is effective for both types of representation. Moreover, the overall performance of our proposed model surpasses the state-of-the-art on both datasets. Additionally, we further validate the robustness of our method by the adversarial examples of AddSent and AddOneSent.

BezelCursor

2016 ◽  
Vol 8 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Wing Ho Andy Li ◽  
Hongbo Fu ◽  
Kening Zhu
Keyword(s):  
User Study ◽  
State Of The Art ◽  
The State ◽  
Mode Switching ◽  
Target Acquisition ◽  
Interaction Technique ◽  
Interaction Styles ◽  
Touch Screens ◽  
Pointing Gesture ◽  
Art Techniques

The authors present BezelCursor, a novel one-handed thumb interaction technique for target acquisition on mobile touch screens of various sizes. Their technique combines bezel-initiated interaction and pointing gesture to solve the problem of limited screen accessibility afforded by the thumb. With a fixed, comfortable grip of a mobile touch device, a user may employ the tool to easily and quickly access a target located anywhere on the screen, using a single fluid action. Unlike the existing technologies, the authors' technique requires no explicit mode switching to invoke and can be smoothly used together with commonly adopted interaction styles such as direct touch and dragging. Their user study shows that BezelCursor requires less grip adjustment, and is more accurate or faster than the state-of-the-art techniques when using a fixed secure grip.

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

Hypothesis-Evidence Coordination: The State of the Art

2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  
State Of The Art ◽  
The State

The State of the Art

1968 ◽  
Vol 13 (9) ◽  
pp. 479-480
Author(s):  
LEWIS PETRINOVICH
Keyword(s):  
State Of The Art ◽  
The State

Needs Assessment: The State of the Art

1984 ◽  
Vol 29 (5) ◽  
pp. 426-428
Author(s):  
Anthony R. D'Augelli
Keyword(s):  
Needs Assessment ◽  
State Of The Art ◽  
The State

Biofeedback: The State of the Art

1991 ◽  
Vol 36 (2) ◽  
pp. 140-140
Author(s):  
John A. Corson
Keyword(s):  
State Of The Art ◽  
The State

Adult development meets social sciences—Reviewing the state of the art.

2016 ◽  
Vol 21 (2) ◽  
pp. 136-153 ◽  
Author(s):  
Elke Fein ◽  
Thomas Jordan
Keyword(s):  
Social Sciences ◽  
Adult Development ◽  
State Of The Art ◽  
The State

Adaptive mental testing: The state of the art.

1979 ◽  
Author(s):  
James R. McBride
Keyword(s):  
State Of The Art ◽  
The State ◽  
Mental Testing
Sign in / Sign up

Export Citation Format

Share Document