A herniated intervertebral disc (HIVD) is a disease caused by the prolapse of the nucleus pulposus of the intervertebral disc due to aging and repeated damage. To treat this, artificial nucleus replacement (ANR) is used to restore the height and flexibility of the reduced intervertebral disc by replacing a portion of the aged nucleus pulposus with an artificial one. However, few studies provide quantitative criteria for partial nucleus pulposus removal. Therefore, through finite element model (FEM) simulation of the lumbar spine (L4-L5), we obtained the optimal location and rate of nucleus pulposus removal and analyzed the movement of the model after ANR in this study. We modeled the FEM in which 60%, 80%, 87%, and 93% of the total nucleus pulposus were replaced by the artificial nucleus pulposus in each of the four directions (left, right, anterior, posterior). Then, a z-axis load of 400N was applied to the model to obtain an axial compression displacement, and a y-axis moment of -6 Nm~+6 Nm was applied to the model to analyze a flexion-extension range of motion (ROM). As a result, regardless of the location of the remaining nucleus pulposus, the compression displacement of the 80% and 87% nucleus pulposus removed model was restored to about 98% of that of the intact model. In addition, the ROM of the 87% nucleus pulposus removed model was restored in 96% of that of the intact model. It is expected that the data obtained through this study can be utilized in digital twin research to predict the prognosis of ANR and to improve surgical techniques.
{"title":"Optimization of nucleus pulposus removal rate in the intervertebral disc during artificial nucleus replacement using lumbar finite element model simulation","authors":"Yeeun Kang, Jaemin Kim, Junghwa Hong","doi":"10.17077/dhm.31778","DOIUrl":"https://doi.org/10.17077/dhm.31778","url":null,"abstract":"A herniated intervertebral disc (HIVD) is a disease caused by the prolapse of the nucleus pulposus of the intervertebral disc due to aging and repeated damage. To treat this, artificial nucleus replacement (ANR) is used to restore the height and flexibility of the reduced intervertebral disc by replacing a portion of the aged nucleus pulposus with an artificial one. However, few studies provide quantitative criteria for partial nucleus pulposus removal. Therefore, through finite element model (FEM) simulation of the lumbar spine (L4-L5), we obtained the optimal location and rate of nucleus pulposus removal and analyzed the movement of the model after ANR in this study. We modeled the FEM in which 60%, 80%, 87%, and 93% of the total nucleus pulposus were replaced by the artificial nucleus pulposus in each of the four directions (left, right, anterior, posterior). Then, a z-axis load of 400N was applied to the model to obtain an axial compression displacement, and a y-axis moment of -6 Nm~+6 Nm was applied to the model to analyze a flexion-extension range of motion (ROM). As a result, regardless of the location of the remaining nucleus pulposus, the compression displacement of the 80% and 87% nucleus pulposus removed model was restored to about 98% of that of the intact model. In addition, the ROM of the 87% nucleus pulposus removed model was restored in 96% of that of the intact model. It is expected that the data obtained through this study can be utilized in digital twin research to predict the prognosis of ANR and to improve surgical techniques.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"28 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":"122993305","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}
S. Summerskill, R. Marshall, Allan Paterson, Anthony Eland
Accidents between vulnerable road users and trucks have been linked to the inability of drivers to directly see the areas in close proximity to the front and sides of the vehicle cab. The lack of direct vision is mitigated through the use of mirrors. The coverage requirements of mirrors are standardized in a UNECE standard. Direct Vision for trucks is not currently standardized in any way. Research by the authors identified key requirements for a Direct Vision Standard (DVS) which was subsequently designed. The method used to quantify direct vison measures the volume of space that is visible, of an assessment volume around the vehicle cab, from a driver's eye point. The result is a volumetric score in m 3 . This standard is now being applied in London, England, and a UNECE version is in development. This paper describes how DHM was used to provide a measure of real-world performance which correlates to a high level with the volumetric score, and an automated version of this process that is being used in the UNECE version.
{"title":"The use of DHM to quantify the a measure of direct vision performance in trucks","authors":"S. Summerskill, R. Marshall, Allan Paterson, Anthony Eland","doi":"10.17077/dhm.31756","DOIUrl":"https://doi.org/10.17077/dhm.31756","url":null,"abstract":"Accidents between vulnerable road users and trucks have been linked to the inability of drivers to directly see the areas in close proximity to the front and sides of the vehicle cab. The lack of direct vision is mitigated through the use of mirrors. The coverage requirements of mirrors are standardized in a UNECE standard. Direct Vision for trucks is not currently standardized in any way. Research by the authors identified key requirements for a Direct Vision Standard (DVS) which was subsequently designed. The method used to quantify direct vison measures the volume of space that is visible, of an assessment volume around the vehicle cab, from a driver's eye point. The result is a volumetric score in m 3 . This standard is now being applied in London, England, and a UNECE version is in development. This paper describes how DHM was used to provide a measure of real-world performance which correlates to a high level with the volumetric score, and an automated version of this process that is being used in the UNECE version.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"4 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":"128663394","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 study examines the biomechanical effects of idealized multi-joint exoskeleton assistances on hip, knee, and ankle joints. We conducted predictive simulations of walking without assistance and with seven different assistance cases including assistance to each joint, assistance to any two joints, and assistance to all three joints. A 2D musculoskeletal model with 10 degrees of freedom and 18 muscles was used and the OpenSim Moco optimal control solver was employed for all predictive simulations, which aimed to minimize the weighted sum of several objectives including metabolic cost, muscle activation, joint coordinate acceleration, motion tracking, and whole-body center of mass (COM) acceleration. The results showed that all assistance cases changed the joint kinematics of the walking motion to different degrees and for most cases the exoskeleton assistance reduced muscle effort substantially. By comparing with the unassisted case, we found that the two cases with assistance to all three joints and to the hip-ankle joints both provided more than 50% reduction in metabolic cost of transport (COT), followed by assistance to hip-knee and knee-ankle joints with less than 40% reduction. As for the single joint assistance cases, assistance to the hip joint appeared to be the most effective with around 34% reduction in COT, followed by the assistance to the ankle joint with around 22% reduction, whereas the assistance to the knee joint was much less effective (with less than 10%).
{"title":"Prediction of walking kinematics and muscle activities under idealized lower limb exoskeleton assistances","authors":"Neethan Ratnakumar, Vinay Devulapalli, Niranjan Deepak, Xianlian Zhou","doi":"10.17077/dhm.31769","DOIUrl":"https://doi.org/10.17077/dhm.31769","url":null,"abstract":"This study examines the biomechanical effects of idealized multi-joint exoskeleton assistances on hip, knee, and ankle joints. We conducted predictive simulations of walking without assistance and with seven different assistance cases including assistance to each joint, assistance to any two joints, and assistance to all three joints. A 2D musculoskeletal model with 10 degrees of freedom and 18 muscles was used and the OpenSim Moco optimal control solver was employed for all predictive simulations, which aimed to minimize the weighted sum of several objectives including metabolic cost, muscle activation, joint coordinate acceleration, motion tracking, and whole-body center of mass (COM) acceleration. The results showed that all assistance cases changed the joint kinematics of the walking motion to different degrees and for most cases the exoskeleton assistance reduced muscle effort substantially. By comparing with the unassisted case, we found that the two cases with assistance to all three joints and to the hip-ankle joints both provided more than 50% reduction in metabolic cost of transport (COT), followed by assistance to hip-knee and knee-ankle joints with less than 40% reduction. As for the single joint assistance cases, assistance to the hip joint appeared to be the most effective with around 34% reduction in COT, followed by the assistance to the ankle joint with around 22% reduction, whereas the assistance to the knee joint was much less effective (with less than 10%).","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"63 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":"114621515","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}
The ability to predict human postures when simulating interactions with different workspaces and objects is valuable for effective proactive ergonomic evaluation. Using previously collected human motions to predict postures appears to be one effective method; however, when modeling more unique postures, optimization approaches may be useful. Optimization-based predictive modeling is rooted in optimal control theory principles, which are built on the assumption that humans adopt movement strategies that minimize or maximize some underlying performance criteria (e.g., minimize joint torques). Santos Pro™ is an optimization-based digital human model that uses multiple objective functions to predict postures. However, it is unclear which objective functions and associated weightings are ideal for predicting probable human postures. The purpose of this research was to develop a response surface methodology approach to optimize objective function weighting to predict realistic floor-to-shoulder lifts. Three minimization objective functions were evaluated to demonstrate this quantitative method: (1) discomfort, (2) total joint torque, and (3) maximum joint torque. Ten participants completed box lifting from floor to shoulder while their motion was tracked using motion capture. Postures for the initiation (origin) and end (destination) of the lift were extracted and mapped onto anthropometrically matched avatars. Separately, avatar lifting postures were also predicted using the built-in multi-objective optimization. The avatar’s hands and feet were constrained to match a human participant’s hand and foot location. The remaining degrees of freedom on the avatar were predicted using the various objective functions and their associated weightings. Three objective functions were weighted systematically at 10% weighting increments to predict 1,331 postures from the various weighting combinations. Joint angle errors were calculated between the motion capture data and each predicted posture. The resultant error surface (error as a function of objective function weighting) was then fit with a multivariate function and subsequently minimized to estimate the objective function weighting combination that best predicted the true participant postures. Discomfort alone tended to best predict lift origin and destination postures. Thus, minimizing discomfort may be an important objective for predicting un-fatigued lifting. The response surface methodology provides a quantifiable method to estimate the best objective function weighting to predict task-focused human behaviors.
{"title":"Developing a response surface methodology to determine the best objective function weightings for predicting probable postures","authors":"J. Davidson, Joshua G. A. Cashaback","doi":"10.17077/dhm.31792","DOIUrl":"https://doi.org/10.17077/dhm.31792","url":null,"abstract":"The ability to predict human postures when simulating interactions with different workspaces and objects is valuable for effective proactive ergonomic evaluation. Using previously collected human motions to predict postures appears to be one effective method; however, when modeling more unique postures, optimization approaches may be useful. Optimization-based predictive modeling is rooted in optimal control theory principles, which are built on the assumption that humans adopt movement strategies that minimize or maximize some underlying performance criteria (e.g., minimize joint torques). Santos Pro™ is an optimization-based digital human model that uses multiple objective functions to predict postures. However, it is unclear which objective functions and associated weightings are ideal for predicting probable human postures. The purpose of this research was to develop a response surface methodology approach to optimize objective function weighting to predict realistic floor-to-shoulder lifts. Three minimization objective functions were evaluated to demonstrate this quantitative method: (1) discomfort, (2) total joint torque, and (3) maximum joint torque. Ten participants completed box lifting from floor to shoulder while their motion was tracked using motion capture. Postures for the initiation (origin) and end (destination) of the lift were extracted and mapped onto anthropometrically matched avatars. Separately, avatar lifting postures were also predicted using the built-in multi-objective optimization. The avatar’s hands and feet were constrained to match a human participant’s hand and foot location. The remaining degrees of freedom on the avatar were predicted using the various objective functions and their associated weightings. Three objective functions were weighted systematically at 10% weighting increments to predict 1,331 postures from the various weighting combinations. Joint angle errors were calculated between the motion capture data and each predicted posture. The resultant error surface (error as a function of objective function weighting) was then fit with a multivariate function and subsequently minimized to estimate the objective function weighting combination that best predicted the true participant postures. Discomfort alone tended to best predict lift origin and destination postures. Thus, minimizing discomfort may be an important objective for predicting un-fatigued lifting. The response surface methodology provides a quantifiable method to estimate the best objective function weighting to predict task-focused human behaviors.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"39 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":"127071046","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}
Changing mobility scenarios are leading to innovative vehicle concepts. The absence of the driver has opened up a wide range of modified interiors and seating configurations for highly automated vehicles, which are the focus of research. With the ongoing automatization in the car industry, new questions arise about human factors. From SAE level 3, conditional driving automation allows the driver to disengage from the driving task without the need for supervision. With an increasing degree of automation, the active vehicle driver is transformed into a passive vehicle passenger. This gives the driver the possibility to deal with non-driving related activities and tasks (NDRA, NDRT) whenever the automation is active. The question of what people are likely to do during an automated ride has mostly been addressed via online surveys or by analyzing other means of transportation like train and bus. Various studies examining train or bus journeys using different methods such as (online) surveys or observation of passengers in different means of transport show a wide variety of activities such as listening to music, looking at the surroundings, relaxing, talking on the phone, reading or working, and the use of electronic devices such as laptops, tablets and smartphones [1-2]. Other studies additionally examined seating parameters such as seat and recline angle [3-8]. However, knowing about desired activities allows researchers and developers to design future car interior including seat and seating position, internal HMI, air-conditioning and the automated driving functions according to user needs. Highly automated and autonomous vehicles enable different seating postures. Space in front of the seat allows the passenger more range for movement and postures [4]. Moreover, several studies contribute to the space managements of interior design in the future and show significant effects of NDRTs on driving postures concerning the seat positions and backrest angles [3,8].
{"title":"Analysis of the influence of non-driving-related activities on seat parameters and sitting posters","authors":"Manuel Kipp","doi":"10.17077/dhm.31745","DOIUrl":"https://doi.org/10.17077/dhm.31745","url":null,"abstract":"Changing mobility scenarios are leading to innovative vehicle concepts. The absence of the driver has opened up a wide range of modified interiors and seating configurations for highly automated vehicles, which are the focus of research. With the ongoing automatization in the car industry, new questions arise about human factors. From SAE level 3, conditional driving automation allows the driver to disengage from the driving task without the need for supervision. With an increasing degree of automation, the active vehicle driver is transformed into a passive vehicle passenger. This gives the driver the possibility to deal with non-driving related activities and tasks (NDRA, NDRT) whenever the automation is active. The question of what people are likely to do during an automated ride has mostly been addressed via online surveys or by analyzing other means of transportation like train and bus. Various studies examining train or bus journeys using different methods such as (online) surveys or observation of passengers in different means of transport show a wide variety of activities such as listening to music, looking at the surroundings, relaxing, talking on the phone, reading or working, and the use of electronic devices such as laptops, tablets and smartphones [1-2]. Other studies additionally examined seating parameters such as seat and recline angle [3-8]. However, knowing about desired activities allows researchers and developers to design future car interior including seat and seating position, internal HMI, air-conditioning and the automated driving functions according to user needs. Highly automated and autonomous vehicles enable different seating postures. Space in front of the seat allows the passenger more range for movement and postures [4]. Moreover, several studies contribute to the space managements of interior design in the future and show significant effects of NDRTs on driving postures concerning the seat positions and backrest angles [3,8].","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"101 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":"127510993","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}
T. Xia, P. Ziarati, Simon Kudernatsch, Donald H. Peterson
It is well known that overhead work is associated with musculoskeletal disorders in the upper extremities. Arm-supporting exoskeletons (ArmExos) help to reduce mechanical load to the shoulder joint and subsequently risk of injury in the area. The ArmExos are adopted rapidly by industries such as car and airplane manufacturers, although there lack studies examining the effectiveness of the ArmExos in these industry settings as the associated overhead tasks often involve use of power hand tools. To simulate overhead tasks with use of power hand tools, an electromagnetic shaker was hung from the ceiling and produced a random vibration spectrum modified from the ISO 10819. In this posture the ArmExos exerted the highest torque to the upper arm when it was flexed 90 degrees. As comparison, the shaker was also placed in front of the body, in which the ArmExos produced minimum torque to the upper arm when it was hanging down along the body. Vibration transmissibility along the arm and the spine was monitored using accelerometers. Activity of the shoulder muscles was obtained using surface electromyography. The grip force was assessed in the shaker handle while the push force was assessed using a force plate placed under subject’s feet. Live feedback was shown on a computer monitor for the subjects to maintain an average grip force at 30 N and an average push force at 50 N. The data demonstrated that wearing ArmExos didn’t alter vibration transmissibility along the body. Wearing ArmExos led to lower shoulder muscle activities. The agonist muscle activities in the overhead posture were higher when compared to the front-of-body posture. Antagonist muscle activities tended to increase with vibration turned on. The existence of vibration significantly increased the peak grip force and push force, indicating a higher mechanical load to the shoulder. These findings suggest that the impact of ArmExo use in overhead tasks involving power tools is complex. Shoulder joint load analysis using advanced musculoskeletal models is recommended to understand the effectiveness of ArmExos in such industry settings. work posture, vibration, muscle activity.
{"title":"Experimental assessment of effectiveness of arm-supporting exoskeleton for overhead work","authors":"T. Xia, P. Ziarati, Simon Kudernatsch, Donald H. Peterson","doi":"10.17077/dhm.31770","DOIUrl":"https://doi.org/10.17077/dhm.31770","url":null,"abstract":"It is well known that overhead work is associated with musculoskeletal disorders in the upper extremities. Arm-supporting exoskeletons (ArmExos) help to reduce mechanical load to the shoulder joint and subsequently risk of injury in the area. The ArmExos are adopted rapidly by industries such as car and airplane manufacturers, although there lack studies examining the effectiveness of the ArmExos in these industry settings as the associated overhead tasks often involve use of power hand tools. To simulate overhead tasks with use of power hand tools, an electromagnetic shaker was hung from the ceiling and produced a random vibration spectrum modified from the ISO 10819. In this posture the ArmExos exerted the highest torque to the upper arm when it was flexed 90 degrees. As comparison, the shaker was also placed in front of the body, in which the ArmExos produced minimum torque to the upper arm when it was hanging down along the body. Vibration transmissibility along the arm and the spine was monitored using accelerometers. Activity of the shoulder muscles was obtained using surface electromyography. The grip force was assessed in the shaker handle while the push force was assessed using a force plate placed under subject’s feet. Live feedback was shown on a computer monitor for the subjects to maintain an average grip force at 30 N and an average push force at 50 N. The data demonstrated that wearing ArmExos didn’t alter vibration transmissibility along the body. Wearing ArmExos led to lower shoulder muscle activities. The agonist muscle activities in the overhead posture were higher when compared to the front-of-body posture. Antagonist muscle activities tended to increase with vibration turned on. The existence of vibration significantly increased the peak grip force and push force, indicating a higher mechanical load to the shoulder. These findings suggest that the impact of ArmExo use in overhead tasks involving power tools is complex. Shoulder joint load analysis using advanced musculoskeletal models is recommended to understand the effectiveness of ArmExos in such industry settings. work posture, vibration, muscle activity.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"41 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":"130212440","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}
Manual material handling such as box lifting is a very common task that is used in the industrial and medical fields. It is widely accepted that manual lifting can potentially lead to low back injury. Asymmetric lifting, which involves twisting of the trunk, shifts trunk muscle activation and can increase the lower back loading on the spine thus further increasing the likelihood of injury. Other researchers have explored asymmetric lifting but have not considered the effects of handedness. Sex has also been considered as a factor related to low back injury, but majority of research work include only male subjects in literature. This work aims to examine the effects of sex, handedness, box load, and box origin on the maximum lumbar flexion/extension L5-S1 joint moments generated during two-handed box lifting so that safer lifting recommendations can be made for those tasks. Eight participants (sex: 4 women, 4 men; age: 28.62 ± 4.53 years; height: 170.00 ± 7.45 cm; body mass: 72.36 ± 8.97 kg; handedness: 4 left-dominant, 4 right-dominant) performed two-handed box lifts with five different box origins (two left lifts, one sagittally symmetric lift, and two right lifts) and three different box weights (1.20 kg, 5.74 kg, 10.27 kg). Motion data was collected using a motion capture system and force plates. There were no clear trends for the effect of sex, but our results suggest that individuals should lift from their dominant-hand side when performing asymmetric two-handed lifting tasks. Future work which will incorporate the use multiscale modeling (musculoskeletal modeling and finite element modeling) to perform a deeper analysis of spine biomechanics during these lifts at the muscle and tissue levels, respectively.
{"title":"The effects of sex and handedness on lumbar kinetics during asymmetric lifting tasks: A pilot study","authors":"Jazmin Cruz, James Yang","doi":"10.17077/dhm.31748","DOIUrl":"https://doi.org/10.17077/dhm.31748","url":null,"abstract":"Manual material handling such as box lifting is a very common task that is used in the industrial and medical fields. It is widely accepted that manual lifting can potentially lead to low back injury. Asymmetric lifting, which involves twisting of the trunk, shifts trunk muscle activation and can increase the lower back loading on the spine thus further increasing the likelihood of injury. Other researchers have explored asymmetric lifting but have not considered the effects of handedness. Sex has also been considered as a factor related to low back injury, but majority of research work include only male subjects in literature. This work aims to examine the effects of sex, handedness, box load, and box origin on the maximum lumbar flexion/extension L5-S1 joint moments generated during two-handed box lifting so that safer lifting recommendations can be made for those tasks. Eight participants (sex: 4 women, 4 men; age: 28.62 ± 4.53 years; height: 170.00 ± 7.45 cm; body mass: 72.36 ± 8.97 kg; handedness: 4 left-dominant, 4 right-dominant) performed two-handed box lifts with five different box origins (two left lifts, one sagittally symmetric lift, and two right lifts) and three different box weights (1.20 kg, 5.74 kg, 10.27 kg). Motion data was collected using a motion capture system and force plates. There were no clear trends for the effect of sex, but our results suggest that individuals should lift from their dominant-hand side when performing asymmetric two-handed lifting tasks. Future work which will incorporate the use multiscale modeling (musculoskeletal modeling and finite element modeling) to perform a deeper analysis of spine biomechanics during these lifts at the muscle and tissue levels, respectively.","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":"130290829","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}
A hand with 25 degrees of freedom (DOF) was proposed with forward and inverse kinematics for all fingers, with a realistic virtual simulation. However, the wrist is not in the model. Today, several authors have proposed in the literature that the wrist has a relative movement between the two rows of bones with eight bones. Some authors discuss a comparison of four joint coordinate systems previously described in the literature. Others propose a helical movement of wrist bones in distal movements. Objective: A new design the hand model of 25 DOF adding a movement of two rows and eight bones of the wrist. Methods: Once we locate a new coordinates system in the end of the radius close to the scaphoid, we apply Denavit-Hartenberg for all joints. Forward and inverse kinematics are applied. We include ten ligaments to apply restrictions in the wrist movement, which affects fingertip position. Results: A new model of a virtual human hand with more accuracy is presented and validated with a Cyberglove™ and Leap Motion. Conclusions: This new model that includes wrist movement yields a more accurate virtual human hand. New DOFs are added to the 25-DOF hand model.
{"title":"Wrist model for the whole human hand","authors":"Esteban Peña-Pitarch","doi":"10.17077/dhm.31766","DOIUrl":"https://doi.org/10.17077/dhm.31766","url":null,"abstract":"A hand with 25 degrees of freedom (DOF) was proposed with forward and inverse kinematics for all fingers, with a realistic virtual simulation. However, the wrist is not in the model. Today, several authors have proposed in the literature that the wrist has a relative movement between the two rows of bones with eight bones. Some authors discuss a comparison of four joint coordinate systems previously described in the literature. Others propose a helical movement of wrist bones in distal movements. Objective: A new design the hand model of 25 DOF adding a movement of two rows and eight bones of the wrist. Methods: Once we locate a new coordinates system in the end of the radius close to the scaphoid, we apply Denavit-Hartenberg for all joints. Forward and inverse kinematics are applied. We include ten ligaments to apply restrictions in the wrist movement, which affects fingertip position. Results: A new model of a virtual human hand with more accuracy is presented and validated with a Cyberglove™ and Leap Motion. Conclusions: This new model that includes wrist movement yields a more accurate virtual human hand. New DOFs are added to the 25-DOF hand model.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"307 5 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":"121163461","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}
Lucas Fonseca Alexandre de Oliveira, M. Meywerk, L. Schories, Maria Meier, Ramakrishna Nanjundaiah, Paulthi B. Victor, Francesco Foglino, Mark Carroll, Arunaachalam Muralidharan
Pedestrian safety is a central topic in the automotive industry because of the high number of deaths in car-to-pedestrian accidents. Different systems have been developed to protect pedestrians and other vulnerable road users. So-called Active Safety Systems are used to avoid possible collisions with the VRU or to mitigate injury severity by reducing the collision speed in case the collision can't longer be prevented. The autonomous emergency braking system (AEB) is one of these systems and aims to intervene in conflict situations by stopping the car, Haus et al. (2019). The performance assessment of the AEB System can be done via virtual simulation. One crucial aspect is the modeling of pedestrian behavior. Current studies use a simple pedestrian behavior model, sometimes called a trajectory-based model, in which the pedestrian moves with constant speed on a given path and without any interaction with the environment. This study investigates how the AEB Performance in virtual environments is influenced by using a more realistic pedestrian behavior model based on reinforcement learning approach, a particular Machine Learning branch perfectly suited for modeling decision-making processes. For that, a generic AEB-System, the trajectory-based pedestrian model, and the reinforcement learning model were implemented in CARLA Simulator. A scenario catalog was created by varying some parameters and used to evaluate the front collisions with and without the AEB system. The study indicates that due to some pedestrian reactions of the reinforcement learning model, like unexpected stopping in front of the car, the performance of the AEB-System is reduced.
{"title":"Influence of different pedestrian behavior models on the performance assessment of autonomous emergency braking (AEB) systems via virtual simulation","authors":"Lucas Fonseca Alexandre de Oliveira, M. Meywerk, L. Schories, Maria Meier, Ramakrishna Nanjundaiah, Paulthi B. Victor, Francesco Foglino, Mark Carroll, Arunaachalam Muralidharan","doi":"10.17077/dhm.31753","DOIUrl":"https://doi.org/10.17077/dhm.31753","url":null,"abstract":"Pedestrian safety is a central topic in the automotive industry because of the high number of deaths in car-to-pedestrian accidents. Different systems have been developed to protect pedestrians and other vulnerable road users. So-called Active Safety Systems are used to avoid possible collisions with the VRU or to mitigate injury severity by reducing the collision speed in case the collision can't longer be prevented. The autonomous emergency braking system (AEB) is one of these systems and aims to intervene in conflict situations by stopping the car, Haus et al. (2019). The performance assessment of the AEB System can be done via virtual simulation. One crucial aspect is the modeling of pedestrian behavior. Current studies use a simple pedestrian behavior model, sometimes called a trajectory-based model, in which the pedestrian moves with constant speed on a given path and without any interaction with the environment. This study investigates how the AEB Performance in virtual environments is influenced by using a more realistic pedestrian behavior model based on reinforcement learning approach, a particular Machine Learning branch perfectly suited for modeling decision-making processes. For that, a generic AEB-System, the trajectory-based pedestrian model, and the reinforcement learning model were implemented in CARLA Simulator. A scenario catalog was created by varying some parameters and used to evaluate the front collisions with and without the AEB system. The study indicates that due to some pedestrian reactions of the reinforcement learning model, like unexpected stopping in front of the car, the performance of the AEB-System is reduced.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"75 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":"122535776","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}
Observational postural assessment methods which are commonly used in industry are time consuming and have issues of inter- and intra-rater reliability. Computer vision (CV) based methods have been proposed, but they have mainly been tested inside lab environments. This study aims to develop and evaluate an upper body postural assessment system in a real industry environment using a single depth camera and OpenPose for the task of forklift driving. The results were compared with XSens, an Inertial Measurement Unit (IMU) based system. Data from three forklift drivers performing seven indoor and outdoor tasks were recorded with a depth camera and XSens sensors. The data were then analyzed with OpenPose with additional custom processing. The angles calculated by the computer vision system showed small errors compared to the XSens system and generally followed the trend of the XSens system joint angle values. However, the results after applying ergonomic thresholds were vastly different and the two systems rarely agreed. These findings suggest that the CV system needs further study to improve the robustness on self-occlusion and angle calculations. Also, XSens needs further study to assess its consistency and reliability in industrial environments.
{"title":"Evaluation of upper body postural assessment of forklift driving using a single-depth camera","authors":"Veeresh Elango, Simona Petravic, L. Hanson","doi":"10.17077/dhm.31780","DOIUrl":"https://doi.org/10.17077/dhm.31780","url":null,"abstract":"Observational postural assessment methods which are commonly used in industry are time consuming and have issues of inter- and intra-rater reliability. Computer vision (CV) based methods have been proposed, but they have mainly been tested inside lab environments. This study aims to develop and evaluate an upper body postural assessment system in a real industry environment using a single depth camera and OpenPose for the task of forklift driving. The results were compared with XSens, an Inertial Measurement Unit (IMU) based system. Data from three forklift drivers performing seven indoor and outdoor tasks were recorded with a depth camera and XSens sensors. The data were then analyzed with OpenPose with additional custom processing. The angles calculated by the computer vision system showed small errors compared to the XSens system and generally followed the trend of the XSens system joint angle values. However, the results after applying ergonomic thresholds were vastly different and the two systems rarely agreed. These findings suggest that the CV system needs further study to improve the robustness on self-occlusion and angle calculations. Also, XSens needs further study to assess its consistency and reliability in industrial environments.","PeriodicalId":111717,"journal":{"name":"Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022) and Iowa Virtual Human Summit 2022 -","volume":"86 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":"133018106","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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