Appropriate motorcycle design is essential to mitigate the discomfort and fatigue that a rider may experience. This can be achieved by combining computer-aided engineering and digital human modeling to investigate interactions between motorcycles and riders prior to developing physical prototypes. When predicting riding postures for novel designs, it is useful to use optimization-based predictive models. However, to effectively use optimization, it is important to know what objective function(s) and associated weightings are necessary to predict realistic riding behaviors. The purpose of this analysis was to identify the objective function weightings that best predict preferred riding postures. A scoping review was conducted to identify preferred riding postures based on experimental data. Santos Pro™ was used in manual manipulation mode to recreate a preferred (gold standard) riding posture. Posture prediction mode was then used to predict riding postures using various objective functions which can be applied and weighted in Santos Pro™. However, it is unclear which weightings would predict the closest posture to the gold standard. Therefore, a response surface methodology was used to compute joint angle errors between the gold standard and predicted postures. The predicted postures used combinations of three minimization objective functions: (1) discomfort, (2) joint displacement, and (3) maximum joint torque, at varying weights (0-100%). Both 50th and 95th percentile males and females were analyzed. Error results were fit with a multivariate model, which was minimized to estimate the objective function weights that resulted in the lowest error between the gold standard and predicted postures. When averaging the best objective function weighting results across all avatars, the estimated best objective function weighting combination was 100%, 24%, and 0% for discomfort, joint displacement, and maximum joint torque objective functions, respectively. These results indicate that the best way to model comfortable riding postures is to weight the minimize discomfort objective highly. The response surface method was able to provide an empirical means to identify the best objective function weights. By determining the best weighting combinations needed to model rider postures, end-users can quickly evaluate the influence of a structural design change within a virtual environment.
{"title":"Identifying the best objective function weightings to predict comfortable motorcycle riding postures","authors":"J. Davidson, S. Fischer","doi":"10.17077/dhm.31744","DOIUrl":"https://doi.org/10.17077/dhm.31744","url":null,"abstract":"Appropriate motorcycle design is essential to mitigate the discomfort and fatigue that a rider may experience. This can be achieved by combining computer-aided engineering and digital human modeling to investigate interactions between motorcycles and riders prior to developing physical prototypes. When predicting riding postures for novel designs, it is useful to use optimization-based predictive models. However, to effectively use optimization, it is important to know what objective function(s) and associated weightings are necessary to predict realistic riding behaviors. The purpose of this analysis was to identify the objective function weightings that best predict preferred riding postures. A scoping review was conducted to identify preferred riding postures based on experimental data. Santos Pro™ was used in manual manipulation mode to recreate a preferred (gold standard) riding posture. Posture prediction mode was then used to predict riding postures using various objective functions which can be applied and weighted in Santos Pro™. However, it is unclear which weightings would predict the closest posture to the gold standard. Therefore, a response surface methodology was used to compute joint angle errors between the gold standard and predicted postures. The predicted postures used combinations of three minimization objective functions: (1) discomfort, (2) joint displacement, and (3) maximum joint torque, at varying weights (0-100%). Both 50th and 95th percentile males and females were analyzed. Error results were fit with a multivariate model, which was minimized to estimate the objective function weights that resulted in the lowest error between the gold standard and predicted postures. When averaging the best objective function weighting results across all avatars, the estimated best objective function weighting combination was 100%, 24%, and 0% for discomfort, joint displacement, and maximum joint torque objective functions, respectively. These results indicate that the best way to model comfortable riding postures is to weight the minimize discomfort objective highly. The response surface method was able to provide an empirical means to identify the best objective function weights. By determining the best weighting combinations needed to model rider postures, end-users can quickly evaluate the influence of a structural design change within a virtual environment.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116063467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents PhD research conducted at Loughborough University in the UK, into flesh deformation of the buttocks in a seated posture. Due to a lack of detailed understanding of how the soft tissues of humans behave when in contact with a seat surface, this research aims to explore the deformation behaviour of these tissues across the sitting task. In particular the research aims to understand the relationships between the three main degrees of freedom: compression (C), anterior-posterior spread (AP), and lateral-medial spread (LM). The paper presents the analysis of C, LM and AP deformation behaviour from a study of 42 participants. Data were collected using motion capture markers attached to tight fitting clothing across one buttock of each participant via the Codamotion system. A rigid platform was used to act as a ‘seat’. Participants were suspended via a hoist such that they could adopt a seated posture just short of the seat surface. Data were then captured through the sitting process from first contact to fully deformed. The resulting coordinate changes throughout this process were captured and analysed. In addition to buttock deformation data, a range of anthropometric data were captured from each participant to explore correlations between anthropometric measures and deformation behaviour to inform any later modelling activity. Findings identify clear deformation behaviour types for AP and LM spread and that participants can display predominant deformation behaviour in one axis. Typically, AP spread is greater than LM spread, and the maximum deformations occur in the lower regions of the buttocks closer to the seat surface. The development of useful models of deformation behaviour is ongoing.
{"title":"Understanding buttock deformation in a seated posture","authors":"R. Marshall, M. Harry, M. Fray","doi":"10.17077/dhm.31777","DOIUrl":"https://doi.org/10.17077/dhm.31777","url":null,"abstract":"This paper presents PhD research conducted at Loughborough University in the UK, into flesh deformation of the buttocks in a seated posture. Due to a lack of detailed understanding of how the soft tissues of humans behave when in contact with a seat surface, this research aims to explore the deformation behaviour of these tissues across the sitting task. In particular the research aims to understand the relationships between the three main degrees of freedom: compression (C), anterior-posterior spread (AP), and lateral-medial spread (LM). The paper presents the analysis of C, LM and AP deformation behaviour from a study of 42 participants. Data were collected using motion capture markers attached to tight fitting clothing across one buttock of each participant via the Codamotion system. A rigid platform was used to act as a ‘seat’. Participants were suspended via a hoist such that they could adopt a seated posture just short of the seat surface. Data were then captured through the sitting process from first contact to fully deformed. The resulting coordinate changes throughout this process were captured and analysed. In addition to buttock deformation data, a range of anthropometric data were captured from each participant to explore correlations between anthropometric measures and deformation behaviour to inform any later modelling activity. Findings identify clear deformation behaviour types for AP and LM spread and that participants can display predominant deformation behaviour in one axis. Typically, AP spread is greater than LM spread, and the maximum deformations occur in the lower regions of the buttocks closer to the seat surface. The development of useful models of deformation behaviour is ongoing.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"367 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
3D body scanning is well known in various application areas such as medicine, automotive, sports, clothing, product design and gaming. These models have some limitations in that they are unable to capture dynamic poses that can provide more information about real-time tasks and interactions with a real-life object, machine or environment. As a result, in the literature, to provide a more realistic movement of static shape models, researchers provided an idea of attribute kinematic capturing or "skeletal animation" as Biovision Hierarchy (BVH) file using a wearable inertial mocap system applied to a 3D statistical shape model, obtaining a "moving statistical shape" using exchange format in open source software like Blender. But in this case, the attribution was not a perfect attribution of the real-time capturing of a dynamic 3D body shape in real-time Nowadays, 4D body scanning can perform 4D measurements in real-time of dynamic body shape without using any wearable inertial mocap system that can occlude the scanning surface and represent a comfortable solution without influencing the performance of the user. In addition, 3D and 4D can be used in open and closed source software using specific file exchange formats for modeling and animation or interaction and integration with other devices, e.g., synchronization with pressure mat and force platform. In particular, open-source software represents a more intuitive, fast and inexpensive platform for performing animation, modeling, and file exchange formats in a multidisciplinary approach. Based on the previous assumptions, in this study, we will provide an overview of open and closed source software along with file exchange formats in 3D and 4D body scanning, looking at the advantages and disadvantages of their use in different fields of applications. Future research will focus on studying the interoperability of data interchange formats utilizing 4D scanning technology, with an emphasis on developing and validating a methodology using a universal skeleton capable of representing and rigging a real population capture.
{"title":"Overview of software and file exchange formats in 3D and 4D body shape scanning","authors":"S. Scataglini, S. Truijen","doi":"10.17077/dhm.31757","DOIUrl":"https://doi.org/10.17077/dhm.31757","url":null,"abstract":"3D body scanning is well known in various application areas such as medicine, automotive, sports, clothing, product design and gaming. These models have some limitations in that they are unable to capture dynamic poses that can provide more information about real-time tasks and interactions with a real-life object, machine or environment. As a result, in the literature, to provide a more realistic movement of static shape models, researchers provided an idea of attribute kinematic capturing or \"skeletal animation\" as Biovision Hierarchy (BVH) file using a wearable inertial mocap system applied to a 3D statistical shape model, obtaining a \"moving statistical shape\" using exchange format in open source software like Blender. But in this case, the attribution was not a perfect attribution of the real-time capturing of a dynamic 3D body shape in real-time Nowadays, 4D body scanning can perform 4D measurements in real-time of dynamic body shape without using any wearable inertial mocap system that can occlude the scanning surface and represent a comfortable solution without influencing the performance of the user. In addition, 3D and 4D can be used in open and closed source software using specific file exchange formats for modeling and animation or interaction and integration with other devices, e.g., synchronization with pressure mat and force platform. In particular, open-source software represents a more intuitive, fast and inexpensive platform for performing animation, modeling, and file exchange formats in a multidisciplinary approach. Based on the previous assumptions, in this study, we will provide an overview of open and closed source software along with file exchange formats in 3D and 4D body scanning, looking at the advantages and disadvantages of their use in different fields of applications. Future research will focus on studying the interoperability of data interchange formats utilizing 4D scanning technology, with an emphasis on developing and validating a methodology using a universal skeleton capable of representing and rigging a real population capture.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127508550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nitesh Bhatia, Ciara Pike-Burke, E. Normando, O. Matar
Digital Human Modelling (DHM) is rapidly emerging as one of the most cost-effective tools for generating computer-based virtual human-in-the-loop simulations. These help better understand individual and crowd behaviour under complex situations. For tasks such as target search and wayfinding, the eye is the primary channel for processing perceptual information and decision making. Existing experimental human studies in the literature have highlighted the relationship between the field of vision, visual acuity, accommodation, and its effect on visual search performance. This paper presents a methodology for the simulation of visual behaviour in target search and a wayfinding task by employing DHM as a reinforcement learning agent with functional vision characteristics. We used Unity 3D game engine to build the DHM and virtual workspace, Unity ML-Agents package to realise its connection with TensorFlow, and the Proximal Policy Optimization (PPO) algorithm to train DHM in finding a target through intensive reinforcement learning (RL). For the functional vision system, we have considered three human-inspired vision personas: (i) ‘good vision’, (ii) ‘poor vision’ type 1 (low acuity like), and (iii) ‘poor vision’ type 2 (high myopia like). We have compared the emergent behaviour of DHM for each of the three personas and RL training performance. The results conclude that simulating reinforcement learning agents with varying vision characteristics can evaluate their impact on visual task performance.
{"title":"Reinforcement learning with digital human models of varying visual characteristics","authors":"Nitesh Bhatia, Ciara Pike-Burke, E. Normando, O. Matar","doi":"10.17077/dhm.31782","DOIUrl":"https://doi.org/10.17077/dhm.31782","url":null,"abstract":"Digital Human Modelling (DHM) is rapidly emerging as one of the most cost-effective tools for generating computer-based virtual human-in-the-loop simulations. These help better understand individual and crowd behaviour under complex situations. For tasks such as target search and wayfinding, the eye is the primary channel for processing perceptual information and decision making. Existing experimental human studies in the literature have highlighted the relationship between the field of vision, visual acuity, accommodation, and its effect on visual search performance. This paper presents a methodology for the simulation of visual behaviour in target search and a wayfinding task by employing DHM as a reinforcement learning agent with functional vision characteristics. We used Unity 3D game engine to build the DHM and virtual workspace, Unity ML-Agents package to realise its connection with TensorFlow, and the Proximal Policy Optimization (PPO) algorithm to train DHM in finding a target through intensive reinforcement learning (RL). For the functional vision system, we have considered three human-inspired vision personas: (i) ‘good vision’, (ii) ‘poor vision’ type 1 (low acuity like), and (iii) ‘poor vision’ type 2 (high myopia like). We have compared the emergent behaviour of DHM for each of the three personas and RL training performance. The results conclude that simulating reinforcement learning agents with varying vision characteristics can evaluate their impact on visual task performance.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129198911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Uriel, A. Ruescas, Sofía Iranzo, A. Ballester, E. Parrilla, Alfredo Remón, S. Alemany
Anthropometric data can be measured manually, through traditional methods, or obtained from a 3D body scan. In both cases, anthropometric dimensions are measured in a static posture (e.g. standing, sitting) however, people interact with products and environments in movement. Anthropometry applied to the ergonomic design of spaces (e.g. workplace, cockpits) includes measurements of reaches and considers dynamic anthropometry, that is the functional ranges of movements of the limbs. In the case of wearables, products that are worn in contact to the body (e.g. clothing, protective gear), the variability of the shape and dimensions during the moment is crucial information to achieve a good fitting, comfort and performance. The appearance of new 4D body scanning technology enables the generation of digital human models in movement which reproduce the actual body shape in motion. Anthropometry in movement is a new category of body metrics that can be obtained from a sequence of scans. In this paper, the variability of eight anthropometric dimensions (neck to waist length, back length, arm length, thigh girth, crotch length, arm girth, waist girth and hip girth) is analyzed in different movements. For this purpose, ten subjects, with a variety of morphotypes, have been measured performing different movements using a 4D scanning system. The methodology to process the sequence of body scans is described to obtain automatically anatomical references of the anthropometric measurements along the movement. The results presented show the evolution of the eight anthropometric dimensions during the movement for the different subjects and movements. The mean ranges of variation are also reported and can reach values between 2-14 cm that will be relevant information for wearable design. Anthropometric dimensions in movement is a new body metric that require further research to establish new protocols, better anthropometric definitions and the creation of new datasets.
{"title":"A methodology to obtain anthropometric measurements from 4D scans","authors":"J. Uriel, A. Ruescas, Sofía Iranzo, A. Ballester, E. Parrilla, Alfredo Remón, S. Alemany","doi":"10.17077/dhm.31758","DOIUrl":"https://doi.org/10.17077/dhm.31758","url":null,"abstract":"Anthropometric data can be measured manually, through traditional methods, or obtained from a 3D body scan. In both cases, anthropometric dimensions are measured in a static posture (e.g. standing, sitting) however, people interact with products and environments in movement. Anthropometry applied to the ergonomic design of spaces (e.g. workplace, cockpits) includes measurements of reaches and considers dynamic anthropometry, that is the functional ranges of movements of the limbs. In the case of wearables, products that are worn in contact to the body (e.g. clothing, protective gear), the variability of the shape and dimensions during the moment is crucial information to achieve a good fitting, comfort and performance. The appearance of new 4D body scanning technology enables the generation of digital human models in movement which reproduce the actual body shape in motion. Anthropometry in movement is a new category of body metrics that can be obtained from a sequence of scans. In this paper, the variability of eight anthropometric dimensions (neck to waist length, back length, arm length, thigh girth, crotch length, arm girth, waist girth and hip girth) is analyzed in different movements. For this purpose, ten subjects, with a variety of morphotypes, have been measured performing different movements using a 4D scanning system. The methodology to process the sequence of body scans is described to obtain automatically anatomical references of the anthropometric measurements along the movement. The results presented show the evolution of the eight anthropometric dimensions during the movement for the different subjects and movements. The mean ranges of variation are also reported and can reach values between 2-14 cm that will be relevant information for wearable design. Anthropometric dimensions in movement is a new body metric that require further research to establish new protocols, better anthropometric definitions and the creation of new datasets.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Hanson, D. Högberg, A. Brolin, E. Brolin, Mikael Lebram, Aitor Iriondo Pascual, A. Lind, Niclas Delfs
In the design process of products and production systems, the activity to systematically evaluate initial alternative design concepts is an important step. The digital human modelling (DHM) tools include several different types of assessment methods in order to evaluate product and production systems. Despite this, and the fact that a DHM tool in essence is a computer supported design and analysis tool, none of the DHM tools provide the functionality to, in a systematic way, use the results generated in the DHM tool to compare design concepts between each other. The aim of this paper is to illustrate how a systematic concept evaluation method is integrated in a DHM tool, and to exemplify how it can be used to systematically assess design alternatives. Pugh´s method was integrated into the IPS software with LUA scripting to systematically compare design concepts. Four workstation layout concepts were generated by four engineers. The four concepts were systematically evaluated with 2 methods focus on human well-being, 2 methods focus on system performance and cost. The result is very promising. The demonstrator illustrates that it is possible to perform a systematic concept evaluation based on both human well-being, overall system performance, and other parameters, where some of the data is automatically provided by the DHM tool and other manual. The demonstrator can also be used to evaluate only one design concept, where it provides the software user and the decision maker with an objective and visible overview of the success of the design proposal from the perspective of several evaluation methods
{"title":"Design concept evaluation in digital human modeling tools","authors":"L. Hanson, D. Högberg, A. Brolin, E. Brolin, Mikael Lebram, Aitor Iriondo Pascual, A. Lind, Niclas Delfs","doi":"10.17077/dhm.31747","DOIUrl":"https://doi.org/10.17077/dhm.31747","url":null,"abstract":"In the design process of products and production systems, the activity to systematically evaluate initial alternative design concepts is an important step. The digital human modelling (DHM) tools include several different types of assessment methods in order to evaluate product and production systems. Despite this, and the fact that a DHM tool in essence is a computer supported design and analysis tool, none of the DHM tools provide the functionality to, in a systematic way, use the results generated in the DHM tool to compare design concepts between each other. The aim of this paper is to illustrate how a systematic concept evaluation method is integrated in a DHM tool, and to exemplify how it can be used to systematically assess design alternatives. Pugh´s method was integrated into the IPS software with LUA scripting to systematically compare design concepts. Four workstation layout concepts were generated by four engineers. The four concepts were systematically evaluated with 2 methods focus on human well-being, 2 methods focus on system performance and cost. The result is very promising. The demonstrator illustrates that it is possible to perform a systematic concept evaluation based on both human well-being, overall system performance, and other parameters, where some of the data is automatically provided by the DHM tool and other manual. The demonstrator can also be used to evaluate only one design concept, where it provides the software user and the decision maker with an objective and visible overview of the success of the design proposal from the perspective of several evaluation methods","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"14 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113976740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Abdel-Malek, R. Bhatt, Chris Murphy, Marco Tena Salais
{"title":"Santos and Sophia predict human behavior","authors":"K. Abdel-Malek, R. Bhatt, Chris Murphy, Marco Tena Salais","doi":"10.17077/dhm.31790","DOIUrl":"https://doi.org/10.17077/dhm.31790","url":null,"abstract":"","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122455680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aitor Iriondo Pascual, Elia Mora, D. Högberg, L. Hanson, Mikael Lebram, Dan Lämkull
Simulation using virtual models is used widely in industries because it enables efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulation is also used in the design of workstations to assess worker well-being by using digital human modelling (DHM) tools. DHM tools typically include musculoskeletal risk assessment methods, such as RULA, REBA, OWAS, and NIOSH Lifting Equation, that can be used to study, analyse, and evaluate the risk of work-related musculoskeletal disorders of different design solutions in a proactive manner. However, most musculoskeletal risk assessment methods implemented in DHM tools are in essence made to assess static instances only. Also, the methods are typically made to support manual observations of the work rather than by algorithms in a software. This means that, when simulating full work sequences to evaluate manikins’ well-being, using these methods becomes problematic in terms of the legitimacy of the evaluation results. In addition to that, to consider objectives in optimizations they should be measurable with real numbers, which most of musculoskeletal risk assessment methods cannot provide when simulating full work sequences. In this study, we implemented the musculoskeletal risk assessment method OWAS in a digital tool connected to the DHM tool IPS IMMA. We applied the Lundqvist index on top of the OWAS whole body risk category score
{"title":"Using time-based musculoskeletal risk assessment methods to assess worker well-being in optimizations in a welding station design","authors":"Aitor Iriondo Pascual, Elia Mora, D. Högberg, L. Hanson, Mikael Lebram, Dan Lämkull","doi":"10.17077/dhm.31746","DOIUrl":"https://doi.org/10.17077/dhm.31746","url":null,"abstract":"Simulation using virtual models is used widely in industries because it enables efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulation is also used in the design of workstations to assess worker well-being by using digital human modelling (DHM) tools. DHM tools typically include musculoskeletal risk assessment methods, such as RULA, REBA, OWAS, and NIOSH Lifting Equation, that can be used to study, analyse, and evaluate the risk of work-related musculoskeletal disorders of different design solutions in a proactive manner. However, most musculoskeletal risk assessment methods implemented in DHM tools are in essence made to assess static instances only. Also, the methods are typically made to support manual observations of the work rather than by algorithms in a software. This means that, when simulating full work sequences to evaluate manikins’ well-being, using these methods becomes problematic in terms of the legitimacy of the evaluation results. In addition to that, to consider objectives in optimizations they should be measurable with real numbers, which most of musculoskeletal risk assessment methods cannot provide when simulating full work sequences. In this study, we implemented the musculoskeletal risk assessment method OWAS in a digital tool connected to the DHM tool IPS IMMA. We applied the Lundqvist index on top of the OWAS whole body risk category score","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123011992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hamidreza Mortazavy Beni, M. S. Islam, Gunther Paul
Dynamic modeling of body organs has become an elementary part of modern digital human modeling (DHM), where advanced biomedical models incorporate biomechanical behavior of tissues down to the cell level. While the biomechanical response of organs to impact and trauma has traditionally been considered an important aspect in developing safety related models such as for vehicle crash simulation, organ behavior is now also reflected in models used for medical purposes, such as the simulation of breathing or cardiovascular circulation. All human body cells have in vivo nonlinear viscoelastic properties. Moreover, body tissue is composed of cells wrapped in an extracellular matrix (ECM). Body tissue in vivo nonlinear viscoelastic properties depend on its function in an organ system, which directly affects the tissue viscoelasticity modulus. For advanced perfusion or fluid passage simulation, we propose to represent the nonlinear viscoelastic behavior of the body tissue in a solid boundary condition using the moving deforming mesh (MDM) method. The MDM method considers the viscoelastic perfusion wall during transient fluid flow responding to the pressure pulse from the human organ systems as the lung or heart. Also, changing the volume fraction of the ECM constituents due to aging or diseases like cancer leads to changes in the viscous modulus (loss modulus) and elastic modulus (storage modulus) of organ tissue. Therefore, the MDM method can produce a reliable result that corresponds to reality by considering the precise viscoelastic properties of the fluid passage wall. In this study, we use the MDM method to examine two organ geometries from the respiratory and cardiovascular systems. Although the simulation effort using this method is more time-consuming, the simulation outcomes are expected to be in better accordance with the real organs when compared to simulation results using the computational fluid dynamic (CFD) modeling leads to pre-visualizing in surgical planning to define the best favorable reformative techniques to determine the most probable patient condition consequences.
{"title":"Moving deforming mesh modeling of human organ systems","authors":"Hamidreza Mortazavy Beni, M. S. Islam, Gunther Paul","doi":"10.17077/dhm.31776","DOIUrl":"https://doi.org/10.17077/dhm.31776","url":null,"abstract":"Dynamic modeling of body organs has become an elementary part of modern digital human modeling (DHM), where advanced biomedical models incorporate biomechanical behavior of tissues down to the cell level. While the biomechanical response of organs to impact and trauma has traditionally been considered an important aspect in developing safety related models such as for vehicle crash simulation, organ behavior is now also reflected in models used for medical purposes, such as the simulation of breathing or cardiovascular circulation. All human body cells have in vivo nonlinear viscoelastic properties. Moreover, body tissue is composed of cells wrapped in an extracellular matrix (ECM). Body tissue in vivo nonlinear viscoelastic properties depend on its function in an organ system, which directly affects the tissue viscoelasticity modulus. For advanced perfusion or fluid passage simulation, we propose to represent the nonlinear viscoelastic behavior of the body tissue in a solid boundary condition using the moving deforming mesh (MDM) method. The MDM method considers the viscoelastic perfusion wall during transient fluid flow responding to the pressure pulse from the human organ systems as the lung or heart. Also, changing the volume fraction of the ECM constituents due to aging or diseases like cancer leads to changes in the viscous modulus (loss modulus) and elastic modulus (storage modulus) of organ tissue. Therefore, the MDM method can produce a reliable result that corresponds to reality by considering the precise viscoelastic properties of the fluid passage wall. In this study, we use the MDM method to examine two organ geometries from the respiratory and cardiovascular systems. Although the simulation effort using this method is more time-consuming, the simulation outcomes are expected to be in better accordance with the real organs when compared to simulation results using the computational fluid dynamic (CFD) modeling leads to pre-visualizing in surgical planning to define the best favorable reformative techniques to determine the most probable patient condition consequences.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127652012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To understand system performance, it is rational to consider all system components, including the humans involved in the control or maintenance of the system. Previous research has included human performance by modeling human tasks as events within Discrete Event Simulation (DES) models. These models typically represent the variability of task performance times and error rates by calculating the mean and variance across multiple individuals. Such approaches assume independence of task performance measures between individuals, but evidence exists which indicates that task performance measures are correlated between individuals. The current research seeks to understand methods to account for performance variability within DES models. A taxonomy of potential methods to address variability in DES models is developed and discussed. Among the findings derived through development of this taxonomy is the need to differentiate models of performance envelopes from models of average system performance and alternatives for modeling the human when predicting each class of performance.
{"title":"Methods for including human variability in system performance models","authors":"Randall J. Hodkin Jr., Michael E. Miller","doi":"10.17077/dhm.31789","DOIUrl":"https://doi.org/10.17077/dhm.31789","url":null,"abstract":"To understand system performance, it is rational to consider all system components, including the humans involved in the control or maintenance of the system. Previous research has included human performance by modeling human tasks as events within Discrete Event Simulation (DES) models. These models typically represent the variability of task performance times and error rates by calculating the mean and variance across multiple individuals. Such approaches assume independence of task performance measures between individuals, but evidence exists which indicates that task performance measures are correlated between individuals. The current research seeks to understand methods to account for performance variability within DES models. A taxonomy of potential methods to address variability in DES models is developed and discussed. Among the findings derived through development of this taxonomy is the need to differentiate models of performance envelopes from models of average system performance and alternatives for modeling the human when predicting each class of performance.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115435786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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