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Högberg, Dan, ProfessorORCID iD iconorcid.org/0000-0003-4596-3815
Publications (10 of 163) Show all publications
Garcia Rivera, F., Lamb, M., Högberg, D. & Alenljung, B. (2025). Friction situations in real-world remote design reviews when using CAD and videoconferencing tools. Empathic Computing, 1(1), Article ID 128.
Open this publication in new window or tab >>Friction situations in real-world remote design reviews when using CAD and videoconferencing tools
2025 (English)In: Empathic Computing, Vol. 1, no 1, article id 128Article in journal (Refereed) Published
Abstract [en]

Aims: Recent world events have resulted in companies using remote meeting tools more often in design processes. The shift to remote meeting tools has had a notable impact on collaborative design activities, such as design reviews (DRs). When DRs depend on computer-aided design (CAD) software, the lack of direct support for CAD functionalities in videoconferencing applications introduces novel communication challenges, i.e. friction. This study investigates friction encountered in real world remote DRs when using a combination of standard CAD and videoconferencing applications. The objective was to understand the main sources of friction when carrying out DRs using a combination of CAD and videoconferencing applications.

Methods: At a single Swedish automobile manufacturer, 15 DRs of a fixture component were passively observed. These observations were subjected to a qualitative thematic analysis to identify categories and sources of friction during these DRs. The DRs were carried out using a combination of CATIA CAD software and Microsoft Teams for videoconferencing.

Results: The analysis of the 15 remote DRs identified four recurring friction categories: requesting specific viewpoints, indicating specific elements, expressing design change ideas, and evaluating ergonomics. Each category highlights specific challenges that were observed during the DRs and emerged due to constraints imposed by existing methods and technologies for remote meetings.

Conclusion: This study provides a framework for understanding the current sources of friction in remote DRs using videoconferencing tools. These insights can support the future development of DR software tools, guiding the integration of features that address these friction points. Additionally, the results serve as a guideline for organizations to implement methods that reduce friction in remote DRs and improve DR quality and efficacy.

Place, publisher, year, edition, pages
Science Exploration Press, 2025
Keywords
Design review, product development, remote collaboration
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-24840 (URN)10.70401/ec.2025.0001 (DOI)
Funder
Vinnova, 2022-01704
Note

CC BY 4.0

Correspondence to: Francisco Garcia Rivera, School of Engineering Science, University of Skövde, Högskolevägen, 54128 Skövde, Sweden. E-mail: francisco.garcia.rivera@his.se

This project was funded by Swedish innovation agency Vinnova in the PLENUM project (Grant Number: 2022-01704).

Available from: 2025-01-15 Created: 2025-01-15 Last updated: 2025-01-28Bibliographically approved
Perez Luque, E., Iriondo Pascual, A., Högberg, D., Lamb, M. & Brolin, E. (2025). Simulation-based multi-objective optimization combined with a DHM tool for occupant packaging design. International Journal of Industrial Ergonomics, 105, Article ID 103690.
Open this publication in new window or tab >>Simulation-based multi-objective optimization combined with a DHM tool for occupant packaging design
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2025 (English)In: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 105, article id 103690Article in journal (Refereed) Published
Abstract [en]

Occupant packaging design is usually done using computer-aided design (CAD) and digital human modelling (DHM) tools. These tools help engineers and designers explore and identify vehicle cabin configurations that meet accommodation targets. However, studies indicate that current working methods are complicated and iterative, leading to time-consuming design procedures and reduced investigations of the solution space, in turn meaning that successful design solutions may not be discovered. This paper investigates potential advantages and challenges in using an automated simulation-based multi-objective optimization (SBMOO) method combined with a DHM tool to improve the occupant packaging design process. Specifically, the paper studies how SBMOO using a genetic algorithm can address challenges introduced by human anthropometric and postural variability in occupant packaging design. The investigation focuses on a fabricated design scenario involving the spatial location of the seat and steering wheel, as well as seat angle, taking into account ergonomics objectives and constraints for various end-users. The study indicates that the SBMOO-based method can improve effectiveness and aid designers in considering human variability in the occupant packaging design process.

Place, publisher, year, edition, pages
Elsevier, 2025
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB); VF-KDO
Identifiers
urn:nbn:se:his:diva-24834 (URN)10.1016/j.ergon.2024.103690 (DOI)2-s2.0-85214303567 (Scopus ID)
Projects
adopti
Funder
Knowledge Foundation
Note

CC BY 4.0

Corresponding author: E-mail address: estela.perez.luque@his.se (E. Perez Luque).

This work has been made possible with support from the Knowledge Foundation in Sweden in the ADOPTIVE project, VF-KDO project, and by the participating organisations. This support is gratefully acknowledged.

Available from: 2025-01-13 Created: 2025-01-13 Last updated: 2025-01-14Bibliographically approved
Iriondo Pascual, A., Högberg, D., Syberfeldt, A. & Brolin, E. (2024). Development and initial usability evaluation of a digital tool for simulation-based multi-objective optimization of productivity and worker well-being. Advanced Engineering Informatics, 62, Article ID 102726.
Open this publication in new window or tab >>Development and initial usability evaluation of a digital tool for simulation-based multi-objective optimization of productivity and worker well-being
2024 (English)In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 62, article id 102726Article in journal (Refereed) Published
Abstract [en]

Engineers use modelling and simulation techniques to efficiently create, evaluate, and optimize design solutions.In an industrial production context, engineers often need to consider requirements related to both productivityand worker well-being in order to find successful design solutions. However, simulations related to productivityand worker well-being respectively, are typically carried out by different engineering roles, using different digitaltools. This lack of integrated work procedure could lead to inefficient development processes and suboptimaldesign solutions. Additionally, since performing multi-objective optimizations is likely to be seen as a complicated task by engineers in areas such as design engineering, production engineering, and ergonomics, requiringspecific knowledge and skills, such tasks are typically performed by engineers specialized on optimization. Thispaper presents the development and usability evaluation of a digital tool that supports engineers not specializedin optimization to define and perform simulation-based multi-objective optimizations of requirements related toboth productivity and worker well-being in an automated and simultaneous manner. The digital tool is the resultof research carried out over a period of four years, following an iterative development and assessment process bythe means of use cases, done in close collaboration with potential users of the digital tool, i.e. engineers at severalcompanies. The usability evaluation of the digital tool shows that potential users in the industry view the tool asa promising support for performing their engineering tasks in a more efficient and integrated manner.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Ergonomics, Digital human modelling, Productivity, Simulation, Optimization
National Category
Information Systems Production Engineering, Human Work Science and Ergonomics
Research subject
Virtual Production Development (VPD); User Centred Product Design
Identifiers
urn:nbn:se:his:diva-24410 (URN)10.1016/j.aei.2024.102726 (DOI)001279828600001 ()2-s2.0-85199261046 (Scopus ID)
Note

CC BY 4.0

Corresponding author: Aitor Iriondo Pascual

University of Skövde, School of Engineering Science, 541 28 Skövde, Sweden.

E-mail address: aitor.iriondo.pascual@his.se

Available from: 2024-08-05 Created: 2024-08-05 Last updated: 2024-10-09Bibliographically approved
Hanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871.
Open this publication in new window or tab >>Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters
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2024 (English)In: Processes, E-ISSN 2227-9717, Vol. 12, no 12, article id 2871Article in journal (Refereed) Published
Abstract [en]

Recently the concept of Industry 5.0 has been introduced, reinforcing the human-centric perspective for future industry. The human-centric scientific discipline and profession ergonomics is applied in industry to find solutions that are optimized in regard to both human well-being and overall system performance. It is found, however, that most production development and preparation work carried out in industry tends to address one of these two domains at a time, in a sequential process, typically making optimization slow and complicated. The aim of this paper is to suggest, demonstrate, and evaluate a concept that makes it possible to optimize aspects of human well-being and overall system performance in an efficient and easy parallel process. The concept enables production planning and balancing of human work in terms of two parameters: assembly time as a parameter of productivity (system performance), and risk of musculoskeletal disorders as a parameter of human well-being. A software demonstrator was developed, and results from thirteen test subjects were compared with the traditional sequential way of working. The findings show that the suggested relatively unique parallel approach has a positive impact on the expected musculoskeletal risk and does not necessarily negatively affect productivity, in terms of cycle time and time balance between assembly stations. The time to perform the more complex two-parameter optimization in parallel was shorter than the time in the sequential process. The majority of the subjects stated that they preferred the parallel way of working compared to the traditional serial way of working.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
ergonomics, human well-being, system performance, optimization, production development, balancing, productivity
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; VF-KDO
Identifiers
urn:nbn:se:his:diva-24816 (URN)10.3390/pr12122871 (DOI)001383897300001 ()2-s2.0-85213231112 (Scopus ID)
Funder
VinnovaKnowledge Foundation
Note

CC BY 4.0

Correspondence: lars.hanson@his.se

This article belongs to the Special Issue Processes in Industry 4.0/5.0: Automation, Robotics and Smart Manufacturing

This work has received support from Eureka Cluster ITEA3/Vinnova in the project MOSIM, and from the Knowledge Foundation within the Synergy Virtual Ergonomics (SVE) project and the Virtual Factories–Knowledge-Driven Optimization (VF-KDO) research profile, and from the participating organizations. This support is gratefully acknowledged.

Available from: 2025-01-03 Created: 2025-01-03 Last updated: 2025-01-07Bibliographically approved
Lind, A., Elango, V., Bandaru, S., Hanson, L. & Högberg, D. (2024). Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis. Applied Sciences, 14(22), Article ID 10736.
Open this publication in new window or tab >>Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis
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2024 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 14, no 22, article id 10736Article in journal (Refereed) Published
Abstract [en]

This paper presents a decision support approach to enable decision-makers to identify no-preference solutions in multi-objective optimization for factory layout planning. Using a set of trade-off solutions for a battery production assembly station, a decision support method is introduced to select three solutions that balance all conflicting objectives, namely, the solution closest to the ideal point, the solution furthest from the nadir point, and the one that is best performing along the ideal nadir vector. To further support decision-making, additional analyses of system performance and worker well-being metrics are integrated. This approach emphasizes balancing operational efficiency with human-centric design, aligning with human factors and ergonomics (HFE) principles and Industry 4.0–5.0. The findings demonstrate that objective decision support based on Pareto front analysis can effectively guide stakeholders in selecting optimal solutions that enhance both system performance and worker well-being. Future work could explore applying this framework with alternative multi-objective optimization algorithms.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
factory layout, optimization, decision support, Industry 4.0–5.0
National Category
Computer Sciences Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-24726 (URN)10.3390/app142210736 (DOI)001366685400001 ()2-s2.0-85210261382 (Scopus ID)
Projects
LITMUS: Leveraging Industry 4.0 Technologies for Human-Centric Sustainable Production
Funder
Knowledge Foundation, 20240013Knowledge Foundation, 2018-0011Knowledge Foundation, 20200044
Note

CC BY 4.0

Correspondence: andreas.lind@scania.com

This research was funded by Scania CV AB and the Knowledge Foundation via the University of Skövde, the research project LITMUS: Leveraging Industry 4.0 Technologies for Human-Centric Sustainable Production (20240013), the research project Virtual Factories with Knowledge-Driven Optimization (2018-0011), and the industrial graduate school Smart Industry Sweden (20200044).

Available from: 2024-11-21 Created: 2024-11-21 Last updated: 2025-01-14Bibliographically approved
Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning. Processes, 12(11), Article ID 2379.
Open this publication in new window or tab >>Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning
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2024 (English)In: Processes, E-ISSN 2227-9717, Vol. 12, no 11, article id 2379Article in journal (Refereed) Published
Abstract [en]

Planning and designing factory layouts are frequently performed within virtual environments, relying on inputs from various cross-disciplinary activities e.g., product development, manufacturing process planning, resource descriptions, ergonomics, and safety. The success of this process heavily relies on the expertise of the practitioners performing the task. Studies have shown that layout planning often hinges on the practitioners’ knowledge and interpretation of current rules and requirements. As there is significant variability in this knowledge and interpretation, there is a risk that decisions are made on incorrect grounds. Consequently, the layout planning process depends on individual proficiency. In alignment with Industry 4.0 and Industry 5.0 principles, there is a growing emphasis on providing practitioners involved in industrial development processes with efficient decision support tools. This paper presents a digital support function integrated into a virtual layout planning tool, developed to support practitioners in considering current rules and requirements for space claims in the layout planning process. This digital support function was evaluated by industry practitioners and stakeholders involved in the factory layout planning process. This initiative forms part of a broader strategy to provide advanced digital support to layout planners, enhancing objectivity and efficiency in the layout planning process while bridging cross-disciplinary gaps.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
factory layout, digital support, Industry 4.0–5.0, space claims, rules and regulations
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-24639 (URN)10.3390/pr12112379 (DOI)001365889700001 ()2-s2.0-85210245876 (Scopus ID)
Note

CC BY 4.0

Published: 29 October 2024

(This article belongs to the Special Issue Process Automation and Smart Manufacturing in Industry 4.0/5.0)

Correspondence: andreas.lind@scania.com

This research was funded by Scania CV AB and the Knowledge Foundation via the University of Skövde, the research project Virtual Factories with Knowledge‐Driven Optimization (2018‐0011), and the industrial graduate school Smart Industry Sweden (20200044).

Available from: 2024-10-29 Created: 2024-10-29 Last updated: 2025-01-14Bibliographically approved
Lind, A., Iriondo Pascual, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2024). Multi-objective optimisation of a logistics area in the context of factory layout planning. Production & Manufacturing Research, 12(1), Article ID 2323484.
Open this publication in new window or tab >>Multi-objective optimisation of a logistics area in the context of factory layout planning
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2024 (English)In: Production & Manufacturing Research, ISSN 2169-3277, Vol. 12, no 1, article id 2323484Article in journal (Refereed) Published
Abstract [en]

The manufacturing factory layout planning process is commonly supported by the use of digital tools, enabling creation and testing of potential layouts before being realised in the real world. The process relies on engineers’ experience and inputs from several cross-disciplinary functions, meaning that it is subjective, iterative and prone to errors and delays. To address this issue, new tools and methods are needed to make the planning process more objective, efficient and able to consider multiple objectives simultaneously. This work suggests and demonstrates a simulation-based multi-objective optimisation approach that assists the generation and assessment of factory layout proposals, where objectives and constraints related to safety regulations, workers’ well-being and walking distance are considered simultaneously. The paper illustrates how layout planning for a logistics area can become a cross-disciplinary and transparent activity, while being automated to a higher degree, providing objective results to facilitate informed decision-making.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2024
Keywords
factory layout, logistics area, multi-objective optimisation, simulation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-23640 (URN)10.1080/21693277.2024.2323484 (DOI)001175090400001 ()2-s2.0-85186422081 (Scopus ID)
Funder
Knowledge Foundation, 20200044Knowledge Foundation, 2018-0011
Note

CC BY 4.0

CONTACT Andreas Lind andreas.lind@his.se Global Industrial Development, Scania CV AB, Södertälje, Sweden

The authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimisation (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.

The work was supported by the Stiftelsen för Kunskaps- och Kompetensutveckling [20200044]; Stiftelsen för Kunskaps- och Kompetensutveckling [2018-0011].

Available from: 2024-02-29 Created: 2024-02-29 Last updated: 2024-11-21Bibliographically approved
Lind, A., Elango, V., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling Tool. IISE Transactions on Occupational Ergonomics and Human Factors, 12(3), 175-188
Open this publication in new window or tab >>Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling Tool
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2024 (English)In: IISE Transactions on Occupational Ergonomics and Human Factors, ISSN 2472-5838, Vol. 12, no 3, p. 175-188Article in journal (Refereed) Published
Abstract [en]

OCCUPATIONAL APPLICATIONS

In the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers’ expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices.

TECHNICAL ABSTRACT

Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross-disciplinary, and automated process. This method offers objective decision support, balancing diverse objectives concurrently. Results: The optimization results obtained from the NSGA-II and PSO algorithms represent feasible non-dominated solutions of layout proposals, with the NSGA-II algorithm finding a solution superior in all objectives compared to the expert engineer-designed start solution for the layout. This demonstrates the presented method’s capacity to refine layout planning practices significantly. Conclusions: The study validates the effectiveness of combining multi-objective optimization with digital human modeling in manufacturing layout planning, aligning with Industry 5.0’s emphasis on human-centric processes. It proves that operational efficiency and worker well-being can be simultaneously considered and presents future potential manufacturing design advancements. This approach underscores the necessity of multi-objective consideration for optimal layout achievement, marking a progressive step in meeting modern manufacturing’s complex demands.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2024
Keywords
Multi-objective, optimization, assembly, industry 5.0, factory layouts
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-23938 (URN)10.1080/24725838.2024.2362726 (DOI)001247664700001 ()38865136 (PubMedID)2-s2.0-85195777525 (Scopus ID)
Funder
Knowledge Foundation, 2018-0011
Note

CC BY 4.0

Taylor & Francis Group an informa business

CONTACT Andreas Lind andreas.lind@scania.com, alt. andreas.lind@his.se Scania CV AB, Södertälje, Sweden

The authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimization (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.

Available from: 2024-06-12 Created: 2024-06-12 Last updated: 2024-11-21Bibliographically approved
Iriondo Pascual, A., Eklund, M. & Högberg, D. (2024). Towards automated hand force predictions: Use of random forest to classify hand postures. In: : . Paper presented at The 22nd Triennial Congress of the International Ergonomics Association (IEA), August 25-29, 2024 ICC JEJU, Republic of Korea.
Open this publication in new window or tab >>Towards automated hand force predictions: Use of random forest to classify hand postures
2024 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

SUMMATIVE STATEMENT:

This paper studies the use of motion capture to record hand motions and the use of the random forest machine learning algorithm for classification of motion capture data into categories and subcategories of the HandPak ergonomics evaluation method.

KEYWORDS:

Ergonomics, Motion capture, Posture recognition, Hand evaluation, Random forest.

PROBLEM STATEMENT:

Nowadays, different technologies are available for ergonomics evaluations in the workplace. The use of technologies, such as camera-based or inertial motion unit sensors-based motion capture systems, facilitates measuring and digitalizing postures of humans over time. These motion capture systems are now being integrated in the processes of performing ergonomics evaluations in production systems to evaluate the well-being of the workers in a more efficient and objective manner (Rybnikár, Kačerová, Hořejší, & Šimon, 2023).

Ergonomics evaluation methods are commonly used in order to assess worker well-being. The use of motion capture systems enables automating assessments of posture related exposure criteria in ergonomics evaluation methods. However, the most commonly used ergonomics evaluation methods are based on observation. The observational ergonomics evaluation methods were initially created with the intention to provide a structure for risk assessment based on observations for ergonomists (Takala et al., 2010). The observational ergonomics evaluation methods therefore rely on the assessment made by ergonomist, and the criteria are often defined as a subjective measurement in the ergonomics evaluation method, often leading to subjective assessments not being consistent between different ergonomists (Nyman et al., 2023). At the same time, these subjective definitions of the criteria make it difficult to automate the criteria assessment with the data obtained from motion capture systems.

One ergonomics evaluation method for quantifying acceptable forces and torques on the forearm, wrist and hand is HandPak (Potvin, 2024). Performing a HandPak evaluation requires selecting one of the nine categories depending on the grip and force that the worker applies. Inside each category, it is necessary to define sub-categories of hand posture. For example, for the category “Torque: Wrist Flexion or Extension” there is a subcategory of “Type of Grip/Pinch” that needs to be classified in “Power Grip”, “Lateral Pinch” or “Pull Pinch”. This classification and subclassification is not easily quantifiable and cannot be defined as a logical set of rules from the joint angles of the fingers.

OBJECTIVE/QUESTION:

The objective of this article is to automatically recognize hand postures from motion capture data to help with the categorization of the hand postures in the HandPak (Potvin, 2024) ergonomics evaluation method.

METHODOLOGY:

In this paper we study the use of motion capture systems to record hand motions, and the use of the random forest (Cutler, Cutler, & Stevens, 2012) machine learning algorithm for classification of motion capture data into categories and subcategories of the HandPak ergonomics evaluation method. We created random forests for the categorization of three different hand postures based on a dataset of more than 10.000 data points.

RESULTS:

The study is ongoing and the results will be added in the full paper.DISCUSSION:The study shows that random forests can be used to classify hand postures based on hand joints angle data, coming from a motion capture system, into subcategories of the HandPak ergonomics evaluation method, without the overfitting issues that decision trees usually present. The study is limited in that it only considers three subcategories in the HandPak ergonomics evaluation method. Other subcategories in HandPak, such as the frequency or duration, present difficulties to be automated without manual input. In addition to that limitation, the training and test data was obtained from two subjects (a male and a female). Adding more subjects to consider variation of postures could improve the accuracy of the random forest model.

CONCLUSIONS:

The use of machine learning for categorization of hand postures enables partial automation of evaluation of criteria in ergonomics evaluation methods of hands such as HandPak (Potvin, 2024) that would otherwise require manual input. Reducing the need of manual input is argued to make the use ergonomics evaluation methods faster and less subjective.

REFERENCES:

Cutler, A., Cutler, D. R., & Stevens, J. R. (2012). Random Forests. In C. Zhang & Y. Ma (Eds.), Ensemble Machine Learning: Methods and Applications (pp. 157–175). New York, NY: Springer.

Douwes, M., & de Kraker, H. (2012). HARM overview and its application: Some practical examples. Work (Reading, Mass.), 41 Suppl 1, 4004–4009.

Nyman, T., Rhén, I.-M., Johansson, P. J., Eliasson, K., Kjellberg, K., Lindberg, P., Fan, X., et al. (2023). Reliability and Validity of Six Selected Observational Methods for Risk Assessment of Hand Intensive and Repetitive Work. International Journal of Environmental Research and Public Health, 20(8), 5505.

Potvin, J. R. (2024). HandPak. Retrieved March 11, 2024, from https://potvinbiomechanics.com/handpak/

Rybnikár, F., Kačerová, I., Hořejší, P., & Šimon, M. (2023). Ergonomics Evaluation Using Motion Capture Technology—Literature Review. Applied Sciences, 13(1), 162. Multidisciplinary Digital Publishing Institute.

Takala, E.-P., Pehkonen, I., Forsman, M., Hansson, G.-A., Mathiassen, S. E., Neumann, W. P., Sjøgaard, G., et al. (2010). Systematic evaluation of observational methods assessing biomechanical exposures at work. Scandinavian Journal of Work, Environment & Health, 36(1), 3–24.

Keywords
Ergonomics, Motion capture, Posture recognition, Hand evaluation, Random forest
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design
Identifiers
urn:nbn:se:his:diva-24859 (URN)
Conference
The 22nd Triennial Congress of the International Ergonomics Association (IEA), August 25-29, 2024 ICC JEJU, Republic of Korea
Available from: 2025-01-23 Created: 2025-01-23 Last updated: 2025-02-04Bibliographically approved
Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2023). Digital support for rules and regulations when planning and designing factory layouts. Paper presented at 56th CIRP International Conference on Manufacturing Systems 2023, Cape Town, 24 - 26 October 2023. Procedia CIRP, 120, 1445-1450
Open this publication in new window or tab >>Digital support for rules and regulations when planning and designing factory layouts
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2023 (English)In: Procedia CIRP, E-ISSN 2212-8271, Vol. 120, p. 1445-1450Article in journal (Refereed) Published
Abstract [en]

Factory layouts are frequently planned and designed in virtual environments, based on the experience of the layout planner. This planning and design process depends on information from several cross-disciplinary activities performed by several functions and experts, e.g., product development, manufacturing process planning, resource descriptions, ergonomics, and safety. Additionally, the layout planner also needs to consider applicable rules and regulations. This experience-based and manual approach to plan and design factory layouts, considering a multitude of inputs and parameters, is a cumbersome iterative process with a high risk of human error and faulty inputs and updates. The general trend in industry is to automate and assist users with their tasks and activities, deriving from concepts such as Industry 4.0 and Industry 5.0. This paper presents and demonstrates how digital support for rules and regulations can assist layout planners in factory layout work. The objective is to support the layout planner in accounting for area/volume reservations required to comply with rules and regulations for workers and equipment in the factory layout. This is a step in a wider initiative to provide enhanced digital support to layout planners, making the layout planning and design process more objective and efficient, and bridge gaps between cross-disciplinary planning and design activities.

Place, publisher, year, edition, pages
Elsevier, 2023
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-23532 (URN)10.1016/j.procir.2023.09.191 (DOI)2-s2.0-85184599288 (Scopus ID)
Conference
56th CIRP International Conference on Manufacturing Systems 2023, Cape Town, 24 - 26 October 2023
Funder
Knowledge Foundation
Note

CC BY-NC-ND 4.0 DEED

Corresponding author: E-mail address: andreas.lind@scania.com

The authors appreciatively thank the support from Scania CV AB, the research school Smart Industry Sweden, and the VF-KDO (Virtual Factories with Knowledge-Driven Optimization) project funded by the Knowledge Foundation in Sweden; this support made the research possible.

Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2025-01-08Bibliographically approved
Projects
SUMMIT – SUstainability, sMart Maintenance and factory design Testbed; Publications
Iriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E. & Hanson, L. (2020). Application of Multi-objective Optimization on Ergonomics in Production: A Case Study. In: Massimo Di Nicolantonio; Emilio Rossi; Thomas Alexander (Ed.), Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, July 24-28, 2019, Washington D.C., USA. Paper presented at International Conference on Applied Human Factors and Ergonomics (AHFE), Washington D.C, USA, July 24-28, 2019 (pp. 584-594). Springer, 975Perez Luque, E., Högberg, D., Iriondo Pascual, A., Lämkull, D. & Garcia Rivera, F. (2020). Motion Behavior and Range of Motion when Using Exoskeletons in Manual Assembly Tasks. In: Kristina Säfsten; Fredrik Elgh (Ed.), SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020. Paper presented at 9th Swedish Production Symposium (SPS2020), 7-8 October 2020, Jönköping, Sweden (pp. 217-228). Amsterdam: IOS PressReinhard, R., Mårdberg, P., García Rivera, F., Forsberg, T., Berce, A., Mingji, F. & Högberg, D. (2020). The Use and Usage of Virtual Reality Technologies in Planning and Implementing New Workstations. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 388-397). Amsterdam: IOS PressGarcia Rivera, F., Brolin, E., Syberfeldt, A., Högberg, D., Iriondo Pascual, A. & Perez Luque, E. (2020). Using Virtual Reality and Smart Textiles to Assess the Design of Workstations. In: Kristina Säfsten; Fredrik Elgh (Ed.), SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020. Paper presented at 9th Swedish Production Symposium (SPS2020), October 7–8, 2020  (pp. 145-154). Amsterdam: IOS Press, 13
MOSIM – Modular Simulation of Natural Human Motions; ; Publications
Hanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871. Iriondo Pascual, A. (2023). Simulation-based multi-objective optimization of productivity and worker well-being. (Doctoral dissertation). Skövde: University of SkövdeIriondo Pascual, A., Lind, A., Högberg, D., Syberfeldt, A. & Hanson, L. (2022). Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 404-414). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Smedberg, H., Högberg, D., Syberfeldt, A. & Lämkull, D. (2022). Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity. Sustainability, 14(9), Article ID 4894. Iriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E., Perez Luque, E., Hanson, L. & Lämkull, D. (2022). Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June, 2021 (pp. 374-378). Cham: SpringerIriondo Pascual, A., Högberg, D., Lämkull, D., Perez Luque, E., Syberfeldt, A. & Hanson, L. (2021). Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework. IISE Transactions on Occupational Ergonomics and Human Factors, 9(3-4), 143-153Iriondo Pascual, A., Högberg, D., Syberfeldt, A., García Rivera, F., Pérez Luque, E. & Hanson, L. (2020). Implementation of Ergonomics Evaluation Methods in a Multi-Objective Optimization Framework. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020, Skövde, Sweden (pp. 361-371). Amsterdam: IOS PressLjung, O., Iriondo Pascual, A., Högberg, D., Delfs, N., Forsberg, T., Johansson, P., . . . Hanson, L. (2020). Integration of Simulation and Manufacturing Engineering Software - Allowing Work Place Optimization Based on Time and Ergonomic Parameters. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020, Skövde, Sweden (pp. 342-347). Amsterdam: IOS PressIriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E. & Hanson, L. (2020). Optimizing Ergonomics and Productivity by Connecting Digital Human Modeling and Production Flow Simulation Software. In: Kristina Säfsten; Fredrik Elgh (Ed.), SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020. Paper presented at Swedish Production Symposium, October 7–8, 2020 (pp. 193-204). Amsterdam: IOS Press
Virtual factories with knowledge-driven optimization (VF-KDO); University of Skövde; Publications
Perez Luque, E., Iriondo Pascual, A., Högberg, D., Lamb, M. & Brolin, E. (2025). Simulation-based multi-objective optimization combined with a DHM tool for occupant packaging design. International Journal of Industrial Ergonomics, 105, Article ID 103690. Nourmohammadi, A., Fathi, M. & Ng, A. H. C. (2024). Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration. Computers & industrial engineering, 187, Article ID 109775. Lidberg, S. (2024). Decision Support Architecture: Improvement Management of Manufacturing Sites Through Multi-Level Simulation-Based Optimization. (Doctoral dissertation). Skövde: University of SkövdeHanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871. Lind, A., Elango, V., Bandaru, S., Hanson, L. & Högberg, D. (2024). Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis. Applied Sciences, 14(22), Article ID 10736. Redondo Verdú, C., Sempere Maciá, N., Strand, M., Holm, M., Schmidt, B. & Olsson, J. (2024). Enhancing Manual Assembly Training using Mixed Reality and Virtual Sensors. Paper presented at 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '23, Gulf of Naples, Italy, 12 - 14 July 2023. Procedia CIRP, 126, 769-774Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning. Processes, 12(11), Article ID 2379. Jiang, Y., Wang, W., Ding, J., Lu, X. & Jing, Y. (2024). Leveraging Digital Twin Technology for Enhanced Cybersecurity in Cyber–Physical Production Systems. Future Internet, 16(4), Article ID 134. Smedberg, H., Bandaru, S., Riveiro, M. & Ng, A. H. C. (2024). Mimer: A web-based tool for knowledge discovery in multi-criteria decision support. IEEE Computational Intelligence Magazine, 19(3), 73-87Lind, A., Iriondo Pascual, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2024). Multi-objective optimisation of a logistics area in the context of factory layout planning. Production & Manufacturing Research, 12(1), Article ID 2323484.
VIVA - the Virtual Vehicle Assembler [2018-05026]; ; Publications
Iriondo Pascual, A. (2023). Simulation-based multi-objective optimization of productivity and worker well-being. (Doctoral dissertation). Skövde: University of SkövdeHanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: SpringerGarcia Rivera, F., Högberg, D., Lamb, M. & Perez Luque, E. (2022). DHM supported assessment of the effects of using an exoskeleton during work. International Journal of Human Factors Modelling and Simulation, 7(3/4), 231-246Hanson, L., Högberg, D., Iriondo Pascual, A., Brolin, A., Brolin, E. & Lebram, M. (2022). Integrating Physical Load Exposure Calculations and Recommendations in Digitalized Ergonomics Assessment Processes. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 233-239). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E., Perez Luque, E., Hanson, L. & Lämkull, D. (2022). Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June, 2021 (pp. 374-378). Cham: SpringerGarcía Rivera, F., Lamb, M., Högberg, D. & Brolin, A. (2022). The Schematization of XR Technologies in the Context of Collaborative Design. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 520-529). Amsterdam; Berlin; Washington, DC: IOS PressGarcia Rivera, F., Brolin, A., Perez Luque, E. & Högberg, D. (2021). A Framework to Model the Use of Exoskeletons in DHM Tools. In: Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu (Ed.), Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA. Paper presented at AHFE International Conference on Human Factors and Simulation and the AHFE International Conference on Digital Human Modeling and Applied Optimization, 2021, Virtual, Online, 25 July 2021 - 29 July 2021, USA (pp. 312-319). Cham: SpringerPerez Luque, E., Högberg, D., Iriondo Pascual, A., Lämkull, D. & Garcia Rivera, F. (2020). Motion Behavior and Range of Motion when Using Exoskeletons in Manual Assembly Tasks. In: Kristina Säfsten; Fredrik Elgh (Ed.), SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020. Paper presented at 9th Swedish Production Symposium (SPS2020), 7-8 October 2020, Jönköping, Sweden (pp. 217-228). Amsterdam: IOS PressBrolin, E., Högberg, D. & Hanson, L. (2020). Skewed Boundary Confidence Ellipses for Anthropometric Data. In: Lars Hanson, Dan Högberg, Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 18-27). Amsterdam: IOS PressReinhard, R., Mårdberg, P., García Rivera, F., Forsberg, T., Berce, A., Mingji, F. & Högberg, D. (2020). The Use and Usage of Virtual Reality Technologies in Planning and Implementing New Workstations. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 388-397). Amsterdam: IOS Press
Synergy Virtual Ergonomics (SVE) [20180167]; University of Skövde; Publications
Hanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871. Iriondo Pascual, A. (2023). Simulation-based multi-objective optimization of productivity and worker well-being. (Doctoral dissertation). Skövde: University of SkövdeHanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: SpringerGarcia Rivera, F., Högberg, D., Lamb, M. & Perez Luque, E. (2022). DHM supported assessment of the effects of using an exoskeleton during work. International Journal of Human Factors Modelling and Simulation, 7(3/4), 231-246Marshall, R., Brolin, E., Summerskill, S. & Högberg, D. (2022). Digital Human Modelling: Inclusive Design and the Ageing Population (1ed.). In: Sofia Scataglini; Silvia Imbesi; Gonçalo Marques (Ed.), Internet of Things for Human-Centered Design: Application to Elderly Healthcare (pp. 73-96). Singapore: Springer NatureIriondo Pascual, A., Lind, A., Högberg, D., Syberfeldt, A. & Hanson, L. (2022). Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 404-414). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Smedberg, H., Högberg, D., Syberfeldt, A. & Lämkull, D. (2022). Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity. Sustainability, 14(9), Article ID 4894. Lamb, M., Brundin, M., Perez Luque, E. & Billing, E. (2022). Eye-Tracking Beyond Peripersonal Space in Virtual Reality: Validation and Best Practices. Frontiers in Virtual Reality, 3, Article ID 864653. Hanson, L., Högberg, D., Iriondo Pascual, A., Brolin, A., Brolin, E. & Lebram, M. (2022). Integrating Physical Load Exposure Calculations and Recommendations in Digitalized Ergonomics Assessment Processes. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 233-239). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E., Perez Luque, E., Hanson, L. & Lämkull, D. (2022). Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June, 2021 (pp. 374-378). Cham: Springer
ADOPTIVE – Automated Design & Optimisation of Vehicle Ergonomics [20200003]; University of Skövde; Publications
Perez Luque, E., Iriondo Pascual, A., Högberg, D., Lamb, M. & Brolin, E. (2025). Simulation-based multi-objective optimization combined with a DHM tool for occupant packaging design. International Journal of Industrial Ergonomics, 105, Article ID 103690. Perez Luque, E., Brolin, E., Högberg, D. & Lamb, M. (2022). Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study. In: DESIGN2022: . Paper presented at DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia (pp. 2165-2174). Cambridge University Press, 2Hanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: SpringerMarshall, R., Brolin, E., Summerskill, S. & Högberg, D. (2022). Digital Human Modelling: Inclusive Design and the Ageing Population (1ed.). In: Sofia Scataglini; Silvia Imbesi; Gonçalo Marques (Ed.), Internet of Things for Human-Centered Design: Application to Elderly Healthcare (pp. 73-96). Singapore: Springer NatureKolbeinsson, A., Brolin, E. & Lindblom, J. (2021). Data-Driven Personas: Expanding DHM for a Holistic Approach. In: Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu (Ed.), Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA. Paper presented at International Conference on Applied Human Factors and Ergonomics (AHFE 2021), USA, July 25-29, 2021. (pp. 296-303). Springer, 264Brolin, E., Högberg, D. & Hanson, L. (2020). Skewed Boundary Confidence Ellipses for Anthropometric Data. In: Lars Hanson, Dan Högberg, Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 18-27). Amsterdam: IOS PressBrolin, E., Högberg, D. & Nurbo, P. (2020). Statistical Posture Prediction of Vehicle Occupants in Digital Human Modelling Tools. In: Vincent G. Duffy (Ed.), Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Posture, Motion and Health: 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I. Paper presented at 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020 (pp. 3-17). Cham: Springer
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4596-3815

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