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Advanced Sensor Technology and Human-Computer Interaction

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 4487

Special Issue Editor

Special Issue Information

Dear Colleagues,

This Special Issue on “Advanced Sensor Technology and Human–Computer Interaction“ focuses on novel sensing and interfacing technologies that encourage new ways of interaction of humans with computers. Human–computer interaction (HCI) responds to the design, implementation, and evaluation of interactive technology.

Although HCI is still usually performed through not very sophisticated physical devices, research has gone in the direction of designing and using intelligent and adaptive sensors and actuators. Intelligent sensors for HCI incorporate at least some kind of intelligence in perception from users (e.g., speech, gesture, and gaze recognition, among others) and respond accordingly. On the other hand, adaptive HCI uses intelligence in the way it interacts with users by dealing with cognitive and affective levels of user activity (wearable sensors for affective computing, for instance). Moreover, this Special Issue also welcomes proposals based on the use of advanced intelligent sensors for HCI applications based on ambient intelligence and pervasive computing interaction, such as smart environments and/or virtual and augmented reality.

Prof. Dr. Antonio Fernández-Caballero
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent sensors for human–computer interaction (HCI)
  • sensor networks for HCI
  • body area networks for HCI
  • wearables for HCI
  • audio and visual recognition for HCI
  • pervasive computing in HCI
  • ambient intelligence in HCI
  • sensors for affective computing
  • brain–computer interfaces for HCI
  • physiological computing for HCI

Published Papers (1 paper)

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Research

18 pages, 5455 KiB  
Article
First Step toward Gestural Recognition in Harsh Environments
by Omri Alon, Sharon Rabinovich, Chana Fyodorov and Jessica R. Cauchard
Sensors 2021, 21(12), 3997; https://0-doi-org.brum.beds.ac.uk/10.3390/s21123997 - 09 Jun 2021
Cited by 2 | Viewed by 2308
Abstract
We are witnessing a rise in the use of ground and aerial robots in first response missions. These robots provide novel opportunities to support first responders and lower the risk to people’s lives. As these robots become increasingly autonomous, researchers are seeking ways [...] Read more.
We are witnessing a rise in the use of ground and aerial robots in first response missions. These robots provide novel opportunities to support first responders and lower the risk to people’s lives. As these robots become increasingly autonomous, researchers are seeking ways to enable natural communication strategies between robots and first responders, such as using gestural interaction. First response work often takes place in harsh environments, which hold unique challenges for gesture sensing and recognition, including in low-visibility environments, making the gestural interaction non-trivial. As such, an adequate choice of sensors and algorithms needs to be made to support gestural recognition in harsh environments. In this work, we compare the performances of three common types of remote sensors, namely RGB, depth, and thermal cameras, using various algorithms, in simulated harsh environments. Our results show 90 to 96% recognition accuracy (respectively with or without smoke) with the use of protective equipment. This work provides future researchers with clear data points to support them in their choice of sensors and algorithms for gestural interaction with robots in harsh environments. Full article
(This article belongs to the Special Issue Advanced Sensor Technology and Human-Computer Interaction)
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