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IEEE Transactions on Human-Machine Systems Template

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About the IEEE Transactions on Human-Machine Systems format

IEEE Transactions on Human-Machine Systems is a peer-reviewed journal published by IEEE, covering Human-Automation Interaction and Safety, EEG and Brain-Computer Interfaces, Gaze Tracking and Assistive Technology. Over its lifetime it has published 1,669 papers, which have received 36,005 citations.

PublisherIEEE
Reference styleNumbered (IEEE)
Numbered — [1], [2] in the text
[1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Human-Machine Systems, vol. 12, no. 3, pp. 45–58, 2023.

Formats any DOI in IEEE Transactions on Human-Machine Systems style. No sign-up.

Abbreviation (ISO-4)THMS
Publishes research inHuman-Automation Interaction and Safety EEG and Brain-Computer Interfaces Gaze Tracking and Assistive Technology Cognitive Computing and Networks Tactile and Sensory Interactions
ISSN2168-2291
Citation impact (2-yr)2.42
h-index90
i10-index718
Top institutions publishing hereDelft University of Technology
Journal websiteieeexplore.ieee.org
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Papers published in IEEE Transactions on Human-Machine Systems per year

136
2014
131
2015
132
2016
141
2017
87
2018
96
2019
93
2020
135
2021
156
2022
106
2023
114
2024
143
2025

Citation impact of IEEE Transactions on Human-Machine Systems by publication year

5.4K
2014
5.1K
2015
3.8K
2016
4.2K
2017
2.6K
2018
2.5K
2019
2K
2020
2.8K
2021
2.6K
2022
1.1K
2023
606
2024
219
2025

Citations each year’s papers have accumulated so far — the most recent years are still building up.

Most-cited papers in IEEE Transactions on Human-Machine Systems

The GRASP Taxonomy of Human Grasp Types

Thomas Feix, Javier Romero, Heinz‐Bodo Schmiedmayer et al. · 4 Sep 2015

In this paper, we analyze and compare existing human grasp taxonomies and synthesize them into a single new taxonomy (dubbed “The GRASP Taxonomy” after the GRASP project funded by the European Commission). We consider only static and stable grasps performed by one hand. The goal is to extract the largest set of different grasps that…

1,002 citations Cite SaveGo to paper →
Human–Agent Teaming for Multirobot Control: A Review of Human Factors Issues

Jessie Y. C. Chen, Michael J. Barnes · 24 Jan 2014

The human factors literature on intelligent systems was reviewed in relation to the following: efficient human supervision of multiple robots, appropriate human trust in the automated systems, maintenance of human operator's situation awareness, individual differences in human-agent (H-A) interaction, and retention of human decision authority. A number of approaches-from flexible automation to autonomous agents-were reviewed,…

Evaluating Fluency in Human–Robot Collaboration

Guy Hoffman · 1 Apr 2019

Collaborative fluency is the coordinated meshing of joint activities between members of a well-synchronized team. In recent years, researchers in human-robot collaboration have been developing robots to work alongside humans aiming not only at task efficiency, but also at human-robot fluency. As part of this effort, we have developed a number of metrics to evaluate…

Enabling Effective Programming and Flexible Management of Efficient Body Sensor Network Applications

Giancarlo Fortino, Roberta Giannantonio, Raffaele Gravina et al. · 24 Dec 2012

Wireless body sensor networks (BSNs) possess enormous potential for changing people's daily lives. They can enhance many human-centered application domains such as m-Health, sport and wellness, and human-centered applications that involve physical/virtual social interactions. However, there are still challenging issues that limit their wide diffusion in real life: primarily, the programming complexity of these systems,…

Human Interaction With Robot Swarms: A Survey

Andreas Kolling, Phillip Walker, Nilanjan Chakraborty et al. · 15 Oct 2015

Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth of these advances are systems comprised of large numbers of robots that collaborate autonomously in diverse applications. Research on effective autonomous control of such systems, commonly called swarms, has increased dramatically in recent years and received attention from many domains,…

IEEE Transactions on Human-Machine Systems template — frequently asked questions

How do I write a paper in the IEEE Transactions on Human-Machine Systems format?
In DocuGuru you write your manuscript in a normal editor — no LaTeX setup required — and select the IEEE Transactions on Human-Machine Systems template. When you export, DocuGuru compiles the paper into the official IEEE format and hands you a submission-ready PDF along with the editable LaTeX source.
What reference style does IEEE Transactions on Human-Machine Systems use?
IEEE Transactions on Human-Machine Systems uses Numbered (IEEE) references, shown as numbered [1], [2] markers in the text. DocuGuru formats every in-text citation and the reference list in this exact style automatically. A reference appears like this: [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Human-Machine Systems, vol. 12, no. 3, pp. 45–58, 2023.
Do I need to know LaTeX to submit to IEEE Transactions on Human-Machine Systems?
No. DocuGuru generates the IEEEtran LaTeX class and compiles the PDF for you in the background, so you get a IEEE-ready IEEE Transactions on Human-Machine Systems document without writing any LaTeX. If you do want it, the LaTeX source is included in the export.
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Who publishes IEEE Transactions on Human-Machine Systems?
IEEE Transactions on Human-Machine Systems is a engineering and computer science journal published by IEEE. DocuGuru's IEEE Transactions on Human-Machine Systems template matches IEEE's official submission format.
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