Evidence map›Paper›PMID 28420114›Full record

ArticleSensors (Basel, Switzerland)2017

Fuzzy System-Based Target Selection for a NIR Camera-Based Gaze Tracker.

Rizwan Ali Naqvi, Muhammad Arsalan, Kang Ryoung Park

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rizwan Ali NaqviDivision of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. rizwanali@dongguk.edu.
Muhammad ArsalanDivision of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. arsal@dongguk.edu.
Kang Ryoung ParkDivision of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. parkgr@dongguk.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gaze-based interaction (GBI) techniques have been a popular subject of research in the last few decades. Among other applications, GBI can be used by persons with disabilities to perform everyday tasks, as a game interface, and can play a pivotal role in the human computer interface (HCI) field. While gaze tracking systems have shown high accuracy in GBI, detecting a user's gaze for target selection is a challenging problem that needs to be considered while using a gaze detection system. Past research has used the blinking of the eyes for this purpose as well as dwell time-based methods, but these techniques are either inconvenient for the user or requires a long time for target selection. Therefore, in this paper, we propose a method for fuzzy system-based target selection for near-infrared (NIR) camera-based gaze trackers. The results of experiments performed in addition to tests of the usability and on-screen keyboard use of the proposed method show that it is better than previous methods.

Indexed as

fuzzy systemgazing at a target to select itGBINIR camera-based gaze tracker

Identifiers

PMID28420114
PMCPMC5424739

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.