Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Controls in Experiments01:13

Controls in Experiments

7.7K
When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
7.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A multimodal dataset for human robot collaborative systems: Experimental data.

Data in brief·2025
Same author

Use of Raman spectroscopy and PLS for the quantification of critical quality attributes in biopharmaceutical products.

Journal of pharmaceutical and biomedical analysis·2025
Same author

Machine learning performance in EEG-based mental workload classification across task types: a systematic review.

Frontiers in neuroergonomics·2025
Same author

Monitoring Visual Fatigue with Eye Tracking in a Pharmaceutical Packing Area.

Sensors (Basel, Switzerland)·2025
Same author

How does Prognostics and Health Management (PHM) develop in the engineering domain: A bibliometric analysis with critical review.

Heliyon·2025
Same author

A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications.

Frontiers in robotics and AI·2024
Same journal

Geochemistry and X-ray diffraction data from rock salts and saltwork wastes of Canada: data compilation.

Data in brief·2026
Same journal

Unique GNSS data from the Eastern Betic Tectonic Arc (Western Mediterranean), covering almost 28 years of campaign observations.

Data in brief·2026
Same journal

A national peatland database for the Republic of Ireland.

Data in brief·2026
Same journal

Dataset on criteria for evaluating teaching quality in blended learning environments: Evidence from a Vietnamese university.

Data in brief·2026
Same journal

Whole-genome sequence data of a multidrug-resistant <i>Klebsiella pneumoniae</i> strain KP-S-66 isolated from cattle shed soil.

Data in brief·2026
Same journal

Updating "A nationally representative dataset of 1549 Americans aged 18 to 94 on interest in, experience with, and barriers to cogeneration, defined as working with older and younger people for social good" with data on religious identity and service attendance.

Data in brief·2026
See all related articles
  1. Home
  3. Experiment Data: Human-in-the-loop Decision Support In Process Control Rooms.
  1. Home
  3. Experiment Data: Human-in-the-loop Decision Support In Process Control Rooms.

Related Experiment Video

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.0K

Experiment data: Human-in-the-loop decision support in process control rooms.

Chidera Winifred Amazu1,2, Joseph Mietkiewicz2,3, Ammar N Abbas2,4

  • 1Politecnico di Torino, Corso, Duca degli Abruzzi, 24, Turin 10129, Italy.

Data in Brief
|March 5, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study analyzed multi-modal data from 92 participants in a simulated formaldehyde plant, evaluating decision support tools to enhance operator performance and safety in control rooms.

Keywords:
BiometricsDecision supportDesign of experimentHuman–machine interactionProcess industrySafetySimulated studySurveys

More Related Videos

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K
Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories
04:15

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

Published on: February 23, 2024

1.0K

Related Experiment Videos

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.0K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K
Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories
04:15

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

Published on: February 23, 2024

1.0K

Area of Science:

  • Human-Computer Interaction
  • Cognitive Engineering
  • Process Safety

Background:

  • Cognitive states like workload, situational awareness, stress, and fatigue are critical in industrial control room operations.
  • Existing multi-modal data collection methods provide insights into operator performance.
  • Human-in-the-loop systems require effective decision support tools for optimal operator functioning.

Purpose of the Study:

  • To collect and analyze multi-modal data assessing operator performance under varying decision support conditions.
  • To evaluate the impact of different decision support tools on cognitive states and task execution.
  • To provide a dataset for optimizing control room design and validating new safety solutions.

Main Methods:

  • Collected objective (eye-tracking, EEG, Health Monitoring Watch) and subjective (NASA-TLX, SART, surveys) data from 92 participants.
  • Participants engaged in a simulated formaldehyde production plant control task with alarm handling and process control.
  • Tested combinations of decision support tools: alarm prioritization, digital vs. paper procedures, and AI recommendations.

    • Main Results:

    • Statistical analysis performed to compare outcomes across four participant groups with different decision support tool configurations.
    • Identified impacts of decision support tools on operator performance and cognitive states.
    • Dataset enables comparison of current industry practices against proposed solutions.

    Conclusions:

    • The collected dataset is valuable for understanding operator performance in complex industrial environments.
    • Findings can inform control room design, optimization, and the development of enhanced safety protocols.
    • Applicable for process safety, system, and human factors engineers, as well as researchers in related fields.