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Applied Sciences
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Human-Centred Design in Ergonomics
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Human-Centred Design in Ergonomics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 March 2027 | Viewed by 1595

Editor

Dr. Rosaria Califano

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Salerno, Italy
Interests: industrial design methods; computer-aided design; virtual prototyping; human factors and ergonomics; comfort assessment; design for ergonomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since its origins, ergonomics has focused on optimizing the interaction between humans and systems to improve safety, comfort, and performance. Over time, this vision has evolved into Human-Centred Design (HCD), a multidisciplinary framework that integrates human needs, abilities, and well-being into every stage of the design process. Today, the convergence of ergonomics with emerging digital technologies such as Artificial Intelligence (AI), Digital Twins, and smart systems offers new opportunities to simulate, predict, and enhance human–system interaction. These tools enable designers to create adaptive, data-driven, and inclusive systems, transforming HCD into an iterative and intelligent process that strengthens human safety, resilience, and reliability in complex environments. This Special Issue aims to collect innovative research, methodologies, and applications that advance the understanding and implementation of HCD in modern ergonomics. Contributions are welcome from academia and industry, addressing both theoretical insights and practical solutions that promote usability, accessibility, safety, and sustainability in products, workplaces, and environments.

Topics of interest include (but are not limited to) the following:

  • Human-centred and participatory design methods;
  • Digital Twins for ergonomic analysis and design optimization;
  • AI-driven human–system interaction and adaptive interfaces;
  • Cognitive, emotional, and safety ergonomics;
  • Inclusive and accessible design;
  • Human–robot collaboration and Industry 5.0 applications.

We invite researchers and practitioners to contribute to shaping the next generation of safe, human-centred, AI-supported ergonomic systems.

Dr. Rosaria Califano
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 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • human-centred design
  • ergonomics
  • digital twin
  • artificial intelligence
  • human–machine interaction
  • cognitive ergonomics
  • safety
  • usability
  • biomechanics
  • inclusive design
  • Industry 5.0
  • smart systems

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Published Papers (3 papers)

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Research

16 pages, 4059 KB  
Article
Leg Volume Changes During Standing Work: Effects of Posture, Flooring Surface, Insole Use, and Individual Characteristics
by Jonathan Osorio-Vasco, Jessica Rojas-Mora, Carlos Barrera-Causil and Yordán Rodríguez
Appl. Sci. 2026, 16(13), 6639; https://doi.org/10.3390/app16136639 - 2 Jul 2026
Viewed by 175
Abstract
Background: Standing work is common across a wide range of industries and service settings and has been associated with changes in leg volume. Objective: To analyze changes in leg volume across eight experimental scenarios integrating posture, flooring surface, insole use, and individual characteristics [...] Read more.
Background: Standing work is common across a wide range of industries and service settings and has been associated with changes in leg volume. Objective: To analyze changes in leg volume across eight experimental scenarios integrating posture, flooring surface, insole use, and individual characteristics associated with standing work. Methods: A controlled (23) factorial experiment was conducted across eight experimental scenarios. Thirty volunteers participated in a 120 min simulation of standing work while performing a light manual task. Leg measurements were obtained, and leg volume was calculated. Results: Static posture and body weight increase leg volume, whereas greater height is associated with lower leg volume. Conclusions: Leg volume increased across all experimental scenarios during the 120 min exposure period. The results suggest that dynamic posture involving movement greater than 20 cm at least every 5 min, together with reducing uninterrupted standing time, may help reduce increases in leg volume. Full article
(This article belongs to the Special Issue Human-Centred Design in Ergonomics)
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43 pages, 18358 KB  
Article
Mapping Smartwatches’ Aesthetic and Ergonomic Features to Perception and Preferences Among Millennials and Generation Zs Using Kansei Engineering and Eye-Tracking Approaches
by Sandra Atef, Islam Ali, Macky Kato and Amr B. Eltawil
Appl. Sci. 2026, 16(11), 5624; https://doi.org/10.3390/app16115624 - 4 Jun 2026
Viewed by 373
Abstract
Wearables design research often evaluates aesthetic and ergonomic features without capturing their emotional and cognitive effects on user experience and buying decisions. This paper investigates both dimensions for smartwatches as screen-based wrist-worn wearable devices (SBWWDs) among Millennials and Generation Z using Kansei Engineering [...] Read more.
Wearables design research often evaluates aesthetic and ergonomic features without capturing their emotional and cognitive effects on user experience and buying decisions. This paper investigates both dimensions for smartwatches as screen-based wrist-worn wearable devices (SBWWDs) among Millennials and Generation Z using Kansei Engineering to structure SBWWD design features into users’ emotional perception and affective preferences. The study examines four hypotheses: (H1a) aesthetic perception differs between Millennials and Generation Z, (H1b) aesthetic perception differs across genders within the same generation, (H2a) ergonomic perception and visual needs for smartwatches’ screen interfaces differ between Millennials and Generation Z, and (H2b) ergonomic preferences differ across genders within the same generation. The research adopts a two-phase design methodology. Phase I-A identifies key aesthetic attributes from market-leading smartwatches and develops controlled design stimuli using AI-assisted concept generation. A questionnaire-based survey captures demographic-linked aesthetic preferences and emotional responses, with emphasis on case shape, strap material, and wearable color, to psychological perception and preference in smartwatch product designs. Phase I-B examines ergonomic interface display preferences relevant to smartwatch screens, including contrast and polarity, using Likert scales and bipolar Semantic Differential Scales. Subsequently, participants evaluate the combined interface features’ stimuli through measures of task accuracy and completion, best/worst interface display selections, eye-tracking metrices analysis, as well as emotional and cognitive arousal provoked by psychological intention using the Self-Assessment Manikin. Further, a full factorial design experiment evaluates the effects of participants’ demographic variables, including generation and gender, as well as smartwatch design features, on aesthetics and ergonomics design perception and preference. Phase II applies Kansei Engineering principles by mapping design features to affective responses of Phase I. Findings provide a structured mapping of smartwatch design perception and preferences across generational and gender groups within the Egyptian market, supporting affective principles in SBWWD design guidelines. The study contributes an evidence-based framework that integrates aesthetic and ergonomic features through Kansei Engineering, aiming to enhance online purchasing in smartwatch devices. Full article
(This article belongs to the Special Issue Human-Centred Design in Ergonomics)
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17 pages, 2083 KB  
Article
Human Digital Biomechanical Twin-Driven Ergonomic Optimization of Bass-Guitar Support Systems: Predictive Design and Experimental Validation
by Rosaria Califano, Luigi Riva, Armando Russo, Gessica Campanile, Giovanni Meglio, Michele Guacci, Nicola Laiola and Alessandro Naddeo
Appl. Sci. 2026, 16(11), 5224; https://doi.org/10.3390/app16115224 - 22 May 2026
Viewed by 353
Abstract
Playing-related musculoskeletal disorders (PRMDs) are highly prevalent among bass-guitar players due to sustained asymmetrical postures, repetitive finger movements, and prolonged support of instrument weight. This study proposes a Human Digital Biomechanical Twin-driven, simulation-based approach to optimize bass-guitar support systems, integrating biomechanical modelling, motion [...] Read more.
Playing-related musculoskeletal disorders (PRMDs) are highly prevalent among bass-guitar players due to sustained asymmetrical postures, repetitive finger movements, and prolonged support of instrument weight. This study proposes a Human Digital Biomechanical Twin-driven, simulation-based approach to optimize bass-guitar support systems, integrating biomechanical modelling, motion capture, and musculoskeletal simulation. A preliminary survey among 63 Italian bass-guitar players was performed to define the experimental conditions regarding posture, instrument type, and session duration. Fifteen experienced bassists participated in laboratory trials using motion capture and postural assessment tools, including MediaPipe Pose, RULA, and AnyBody Modelling System. Baseline results highlighted significant activation of the trapezius and spinal extensor muscles (19–26% MVC), confirming high ergonomic risk. Three alternative support configurations were digitally simulated, revealing that a three-point harness system (bilateral shoulder straps plus thoracic anchoring) reduced spinal stabilizer activation by 15–25% across four anthropometric percentiles. Experimental validation confirmed enhanced comfort, reduced fatigue, and improved instrument stability, with the majority of participants preferring the ergonomic configuration. These findings demonstrate the feasibility of a simulation-based, prospective, and human-centred ergonomic design framework, offering a scalable methodology to compare and optimize adaptive instrument-support systems before physical prototyping. Full article
(This article belongs to the Special Issue Human-Centred Design in Ergonomics)
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