Workload and Performance: Associations, Insensitivities, and Dissociations

2018 ◽  
Vol 61 (3) ◽  
pp. 374-392 ◽  
Author(s):  
P. A. Hancock ◽  
Gerald Matthews
Keyword(s):  
Subjective Experience ◽  
Conscious Experience ◽  
Physiological Reactivity ◽  
Human Machine Interaction ◽  
Objective Performance ◽  
Self Reports ◽  
Practical Design ◽  
Future Prediction ◽  
And Performance ◽  
Machine Interaction

Objective: The aim of this study was to distill and define those influences under which change in objective performance level and the linked cognitive workload reflections of subjective experience and physiological variation either associate, dissociate, or are insensitive, one to another. Background: Human factors/ergonomics frequently employs users’ self-reports of their own conscious experience, as well as their physiological reactivity, to augment the understanding of changing performance capacity. Under some circumstances, these latter workload responses are the only available assessment information to hand. How such perceptions and physiological responses match, fail to match, or are insensitive to the change in primary-task performance can prove critical to operational success. The reasons underlying these associations, dissociations, and insensitivities are central to the success of future effective human–machine interaction. Method: Using extant research on the relations between differing methods of workload assessment, factors influencing their association, dissociation, and insensitivity are identified. Results: Dissociations and insensitivities occur more frequently than extant explanatory theories imply. Methodological and conceptual reasons for these patterns of incongruity are identified and evaluated. Application: We often seek convergence of results in order to provide coherent explanations as bases for future prediction and practical design implementation. Identifying and understanding the causes as to why different reflections of workload diverge can help practitioners toward operational success.

scholarly journals Empathy and Human-Machine Interaction

2013 ◽  
Vol 4 (2) ◽  
pp. 8-21
Author(s):  
Florence Gouvrit
Keyword(s):  
Human Machine Interaction ◽  
Presence And Absence ◽  
And Performance ◽  
Machine Interaction

This paper presents the framework of the author’s practice and research exploring empathy and human-machine interaction in projects involving robotic art and video installations and performance. The works investigate emotions and embodiment, presence and absence, relationships and loss, and ways to implicate these ideas in encounters between technology-based artwork and the viewer.

Social stress and performance in human-machine interaction: a neglected research field

Ergonomics ◽  
2019 ◽  
Vol 62 (11) ◽  
pp. 1377-1391 ◽  
Author(s):  
Juergen Sauer ◽  
Sven Schmutz ◽  
Andreas Sonderegger ◽  
Nadine Messerli
Keyword(s):  
Social Stress ◽  
Research Field ◽  
Human Machine Interaction ◽  
And Performance ◽  
Machine Interaction

Designing Artificial Agents as Social Companions

2017 ◽  
Vol 61 (1) ◽  
pp. 1604-1608 ◽  
Author(s):  
Eva Wiese ◽  
Tyler Shaw ◽  
Daniel Lofaro ◽  
Carryl Baldwin
Keyword(s):  
Social Robotics ◽  
Social Connection ◽  
Artificial Agents ◽  
Human Machine Interaction ◽  
Mind Perception ◽  
Social Partners ◽  
Internal States ◽  
And Performance ◽  
Machine Interaction ◽  
Do So

When we interact with others, we make inferences about their internal states (i.e., intentions, emotions) and use this information to understand and predict their behavior. Reasoning about the internal states of others is referred to as mentalizing, and presupposes that our social partners are believed to have a mind. Seeing mind in others increases trust, prosocial behaviors and feelings of social connection, and leads to improved joint performance. However, while human agents trigger mind perception by default, artificial agents are not automatically treated as intentional entities but need to be designed to do so. The panel addresses this issue by discussing how mind attribution to robots and other automated agents can be elicited by design, what the effects of mind perception are on attitudes and performance in human-robot and human-machine interaction and what behavioral and neuroscientific paradigms can be used to investigate these questions. Application areas covered include social robotics, automation, driver-vehicle interfaces, and others.

scholarly journals Performance Analysis of Urban Cleaning Devices Using Human–Machine Interaction Method

2021 ◽  
Vol 13 (11) ◽  
pp. 5846
Author(s):  
María Alonso-García ◽  
Ana García-Sánchez ◽  
Paula Jaén-Moreno ◽  
Manuel Fernández-Rubio
Keyword(s):  
Performance Analysis ◽  
Well Being ◽  
Working Environment ◽  
Interaction Method ◽  
Human Machine Interaction ◽  
Complex Interactions ◽  
Limited Company ◽  
Cleaning Device ◽  
And Performance ◽  
Machine Interaction

Presently, several jobs require the collaboration of humans and machines to perform different services and tasks. The ease and intuitiveness of the worker when using each machine will not only improve the worker’s experience but also improve the company’s productivity and the satisfaction that all users have. Specifically, electromechanical devices used to provide cleaning services require complex interactions. These interactions determine the usability and performance of devices. Therefore, devices must have appropriate ergonomic arrangements for human–machine interactions. Otherwise, the desired performance cannot be achieved. This study analyzes the performance of an urban cleaning device (pressure washer on a power take-off van) using human–machine interaction method. The method measures visceral and behavioral levels (set by Norman) and service times. Using these measurements, the usability of the pressure washer is determined according to different factors that facilitate the operator’s well-being in the working environment. A pressure washer from Feniks Cleaning and Safety, Limited Company, has been studied. Sixteen errors related to ergonomics, usability and safety were identified in this machine, which operates in more than 40 locations in Spain. Therefore, this study provides valuable information on the usability and performance of pressure washers, as well as possibilities for improvement.

scholarly journals An Argument for Trust Assessment in Human-Machine Interaction: Overview and Call for Integration

2021 ◽  
Author(s):  
Nathan Tenhundfeld ◽  
Mustafa Demir ◽  
Ewart de Visser
Keyword(s):  
Future Development ◽  
Human Factors Engineering ◽  
Physiological Measures ◽  
Human Machine Interaction ◽  
Assessment Technique ◽  
Foundational Principle ◽  
Great Utility ◽  
Self Reports ◽  
Assessment Techniques ◽  
Machine Interaction

Trust is a foundational principle in Human Factors Engineering. While an understanding of trust can help predict and alter much of human-machine interactions (HMI), assessment of trust is underutilized in the field. We make the argument that trust assessment provides great utility for anyone interested in HMI, followed by an overview of the various trust assessment techniques which exist. With each broad assessment technique, we evaluate the benefits and drawbacks of its use. We then apply those shortcomings in a call for future development of new trust assessment techniques, be they subjective self-reports, behavioral, or physiological measures. For scientists and practitioners alike, trust assessment provides a substantial opportunity for greater understanding of the human in human-machine interactions.

scholarly journals Augmenting Visual Image Configuration in a Simulated Digital Periscope Human-Machine Interface

2021 ◽  
Author(s):  
Stephanie Michailovs ◽  
Jessica Irons ◽  
Zachary L Howard ◽  
Stephen Pond ◽  
Megan Schmitt ◽  
...  
Keyword(s):  
Visual Information ◽  
Visual Image ◽  
Human Machine Interaction ◽  
Analysis Tools ◽  
Perceived Workload ◽  
Machine Interface ◽  
Perceived Usability ◽  
And Performance ◽  
Digital Human ◽  
Machine Interaction

Advances in opto-electronics enables replacement of traditional periscopes which display only a portion of the horizon, with digital periscopes, which can potentially display a full 360° panoramic digital representation of the horizon. The advantages of an increased field of view (FOV) might include reducing memory requirements and being better able to integrate visual information over time. Another potential advantage of moving to digital human-machine interaction concepts is that they can be paired with digital aids that can replace or simplify tasks traditionally performed manually. This study compared a low- FOV visual concept to a high-FOV concept (Experiment 1), and then traditional analysis tools with digitized analysis tools (Experiment 2). The high-FOV concept and digitized tools provided a range of perceived workload, perceived usability, and performance benefits, and we conclude that digitally augmenting the periscope concept, including exploiting a panoramic display and digitized analysis tools, can support key submariner tasks.

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

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