ABSTRACT. Johan Iraeus

Chalmers University of Technology, Mechanics and Maritime Sciences, Vehicle Safety, Injury Prevention

Johan’s research is focused on biomechanics, with emphasis on car crashes. The research is mainly carried out using computer simulations with human body models, but also includes database studies. A field of specialization is population based simulations, i.e. how system changes influence a population. The goal is to be able to predict the effect of new countermeasures in terms of saved lives/reduced harm, before the system is on the market. Johan defended his PhD thesis in 2015 and before that he worked for more than ten years with computer aided vehicle development, primarily crashworthiness.

ABSTRACT. Many digital human model applications are based on optimal control simulations of the musculoskeletal system. These simulations usually involve the derivatives of the underlying kinematic and dynamic model, which are in general not easy to derive analytically. In the direct transcription method DMOCC, we use the discrete Euler-Lagrange equations together with a discrete null space matrix and a nodal reparametrization, which are embedded into a constrained optimization problem. The abstract and formalizable structure of this method offers many possibilities for automation. Therefore, we use the CasADi nonlinear optimization and algorithmic differentiation tool to automatically derive the discrete Euler-Lagrange equation and a valid discrete null space matrix. This allows us an efficient and easy implementation of the DMOCC method for large multibody systems.

ABSTRACT. In IPS-IMMA the operation sequence planning tool offers an easy and powerful way to construct, analyze, and simulate sequences of human operations. So far, the simulations created using this tool have been quasi-static solutions to the operation sequence. In this paper we present new functionality for motion planning of digital human operation sequences which also takes the dynamics of the human into consideration. The new functionality is based discrete mechanics and optimal control, and will be seamlessly integrated into to the IPS-IMMA software through the operation sequence planning tool. First, the user constructs an operation sequence using the operation sequence tool in IPS-IMMA. The operation sequence is then converted into a discrete optimal control problem which is solved using a nonlinear programming solver. Finally, the solution can be played back and analyzed in the graphical interface of IPS-IMMA. In order to obtain physically correct solutions to complex sequences consisting of several consecutive and dependent operations, we view the digital human as a hybrid system, i.e. a system containing both continuous and discrete dynamic behavior. In particular, the optimal control problem is divided into multiple continuous phases, connected by discrete events. The variational integrators used in discrete mechanics are particularly well suited for modelling the dynamics of constrained mechanical systems, which is almost always the case when considering complex human models interacting with the environment. However, special care must be taken in order to maintain good results when connecting several dynamic phases with discrete events. To demonstrate this new functionality, we model and solve several industrial cases, with particular focus on cases where the dynamics of the system plays an important part in the solution.

ABSTRACT. For virtual evaluation of universal design products, it is necessary to synthesize natural grasps for various hands including those with disability. As one of the disabilities, we focused on the limitation of the thumb's range of motion (ROM). For example, carpal tunnel syndrome (CTS) is a typical disease that limits thumb's ROM. Though there is no doubt that the range of motion affects the whole grasp, detailed grasp strategy has not been studied so far due to the difficulties in collecting data from such patients. Therefore, in this paper, we propose to synthesize grasping postures by the thumb's ROM-limited digital hands based on the observation of an actual subject whose hand is artificially-disabled. The synthesized postures of the healthy hand and the thumb's ROM-limited hand were obviously different. We applied a contact-region-based method for grasp synthesis for ROM-limited hand and succeeded in synthesizing the grasping postures that reflect the features of the thumb's ROM-limited hands' grasps.

ABSTRACT. Temporomandibular disorder (TMD) is a prevalent dental disease in common with dental caries and periodontitis. The major symptoms of TMD are masticatory muscle pain, temporomandibular joint (TMJ) pain and impairment of jaw movement due to the pain and pathologic derangement of TMJs. However, there are few studies using TMD patient-specific motion data to drive the musculoskeletal model that can elucidate kinematic and biomechanical characteristics of the patient. The purpose of this study is to develop the workflow of musculoskeletal modeling of the mandible with jaw motion data obtained from a TMD patient. This involves the establishment of patient-specific boundary conditions representing the characteristics of the TMJ. The jaw motion of a TMD patient was recorded and used as an input for driving the model.

ABSTRACT. We propose an evidence-based methodology for the systematic analysis and cognitive characterisation of multimodal interactions in naturalistic roadside situations. Founded on basic human modalities of embodied (inter)action, the proposed methodology utilises three key characteristics crucial to roadside (multimodal) interaction, namely: explicit and implicit mode of deliverance, formal and informal signalling, and levels of visual attention in a given context. Motivated by the fine-grained modelling of human interactions in naturalistic virtual settings, we present an application of the proposed model by examples from a work-in-progress dataset consisting of multimodal interaction scenarios (and variations built there- from) with a particular emphasis on: (i) joint attention between participating roadside stakeholders; and (ii) diversity of modalities employed during the course of an interaction.

ABSTRACT. Industry 4.0 and the Smart Factory promise a connected product life cycle that links data driven development of future products to the manufacturing and support enterprise.

As with the previous three industrial transformations, these changes to manufacturing and product technology have profound impact on customers and workers. Production is, by definition, a highly physical activity in which human workers, tooling, machines and various levels of automation works in coordination to perform processes with the aim of producing a product meeting its defined specifications. Further digitalization is in progress also for the production processes which creates new challenges for both human centric assembly line management and individual assembly operators. By providing an efficient platform and ‘virtual assembly line twin’ the collaboration between Manufacturing Engineering and Production Operations can be significantly improved providing an efficient platform for assembly validation, ramp-up, operator guidance and virtual try-outs of improvements and changes to the assembly line.

The main target is to provide a further strengthened platform for Human Centric Experiential Discovery and Validation, providing a rich virtual twin of the assembly environment, thus enabling efficient and reliable decision making by the key stakeholders involved in the manufacturing engineering, ramp-up and production operation processes, while providing digital continuity with upstream and downstream workflows for efficient integration within the customer processes.

This session highlights most valuable IC.IDO themes supporting the virtual validation of human centric processes in the production line, supporting our customers to increase productivity while ensuring worker health and safety, minimizing waste (Muda) and human error throughout the product lifecycle fulfilled with some proven customer examples. The session will also highlight customer requirements from innovation perspective to improve future workflows to generate a higher level of working efficiency.

ABSTRACT. To provide better support in the development process of ergonomic design and enhance a deeper understanding of the digital human modeling (DHM) tool’s functionality and its output, DHM technology could be combined with Virtual Reality (VR). The envisioned VR with DHM technology could be operated in a more natural way of interaction and present more representative simulations. To gain a deeper understanding of how various aspects of users’ experiences in DHM works in VR, a pilot study was conducted where participants observed a simulated humanoid robot hand’s reaching and grasping task, i.e. representing a pick-and-place (PAP) action. Preliminary findings suggest that proactive eye gaze (PEG) happened sooner with a self-propelled condition, contrary to previous research in the real world . We suggest that these findings could be related to the experience of being situated in the virtual world and the representativeness of the simulated PAP action. Our purpose is to conduct an elaborated study to investigate these user experience aspects in further detail. In the long run, we hope that our research will have implications for studying VR in DHM, and contributing to the wellbeing of operators that collaborate with robots in the factories of the future.

ABSTRACT. The precision of human movements within the gripping space has been poorly described, but could play an important role, particularly in the simulation of human movements or in virtual interactions. We therefore describe an experiment in which virtual target points need to be reached. The targets are visualized in the three-dimensional gripping space using the HTC-Vive pro and participant movements are recorded using an optical motion-capturing system. The targets consist of 60 spheres which appear at different ranges, height angles and side angles. The target vanishes if the participant holds the HTC controller for two seconds within the required point. We measured 43 test subjects in three test conditions (fast as possible, precise as possible, fast and precise). We measured two forms of human movement precision: static holding precision and dynamic reaching precision. As a result, the static and dynamic precision is described in terms of the speed, the distance between the hand and the virtual target, as well as the position within the gripping space. Fast movements seem to be more precise at the end of the movement phase (26 mm deviation). Precise movements result in better dynamic precision at the end of the adjustment (7 mm deviation) and holding precision (5 mm deviation). Future works involve the evaluation of movement strategies.

ABSTRACT. Observational ergonomic evaluation methods have inherent subjectivity. Observers’ assessment results might differ even with the same dataset. While motion capture (MOCAP) systems have improved the speed and the accuracy of motion-data gathering, the algorithms used to compute assessments seem to rely on predefined conditions to perform them. Moreover, the authoring of these conditions is not always clear. Making use of artificial intelligence (AI), along with MOCAP systems, computerized ergonomic assessments can become more alike to human observation and improve over time, given proper training datasets. AI can assist ergonomic experts with posture detection, useful when using methods that require posture definition, such as Ovako Working Posture Assessment System (OWAS). This study aims to prove the usefulness of an AI model when performing ergonomic assessments and to prove the benefits of having a specialized database for current and future AI training. Several algorithms are trained, using Xsens MVN MOCAP datasets, and their performance within a use case is compared. AI algorithms can provide accurate posture predictions. The developed approach aspires to provide with guidelines to perform AI-assisted ergonomic assessment based on observation of multiple workers.

ABSTRACT. In virtual modelling of exoskeletons, the human-exoskeleton interface is often simplified by modelling the interface forces at a single point instead of contact forces due to the straps or cuffs. In the past, force-generating elements (FGEs) have been used to predict ground reaction forces. However, unlike the ground, which is a planar surface, the human-exoskeleton interface presents curved surfaces. This work discusses the modifications required for using the FGEs for predicting the curved human-exoskeleton interface forces of a passive lower-limb exoskeleton, the Chairless Chair. A pressure mat was positioned at the human-exoskeleton interface to measure the area of contact and the centre of pressure (CoP) in three different sitting conditions. The strength of the FGEs was analysed in detail and its optimization based on the model outputs is discussed. The strength affects the model assistance and the CoP, and these outputs could be used to identify the optimal value of the strength. The strength of the FGEs affects the biomechanical outputs from the model also. Therefore, it is crucial to select the correct value of the strength. The results of this work would be useful for the detailed modelling of the human-exoskeleton interface.

ABSTRACT. Digital human models (DHM) are widely used in automotive industry to simulate the driver in a very early stages of production, where no physical prototypes of the car exist. In case of crash simulation, detailed finite element models of the human body are used to simulate the highly dynamic impact and the resulting injuries in the human body. Models with multibody kinematics are widely used, when the reachability and the ergonomic assessment of the driver is investigated. These kind of models are only used in quasit static scenarios where the car is standing or driving with constant velocity. In dynamic driving scenarios like cornering, sudden breaking or pre-crash scenarios, both types of models are not applicable. The FEM models are much too time consuming, because in contradiction to crash simulation the simulated time span is bigger. Also these models are difficult to control. The kinematic models are not able to take into account dynamic loads and contact forces. Also the motion generation is difficult, because the usually base on forward or inverse kinematics. In this work we will present an approach, how to enhance a multibody based DHM to generate human like motion for dynamic driving maneuvers. Therefore, the human is modeled as a multibody system, where the limbs are the rigid bodies, which are connected via joints. Hill muscles are used to actuated the multibody system. These are digital versions of the real muscles in the human body. To generate the dynamic human motion an optimal control algorithm is developed, which is able to handle opening and close contacts. These enables to simulate the dynamic interaction of the DHM with the car interior like seat, pedals or steering wheel. In this approach only some basic boundary conditions must be described, like at the start the human is sitting at a certain positon with two hands on the steering wheel and the trajectory of the car. With a certain objective function, the optimal control approach than generates the desired control (muscle actuation) and the human motion. Topics: Musculoskeletal human models, Posture and motion simulation, DHM in safety applications, Biomechanical modelling

ABSTRACT. Active human body models (AHBM) are essential engineering tools to provide further biomechanical knowledge. For example, to predict injury risks and kinematic behaviour in a wide range of possible scenarios such as low-g and multiaxial loading scenarios where muscle activity has shown to affect head and neck kinematics. The validation of the AHBM, in particular, the tuning and selection of an appropriate control strategy is a significant challenge. There are two main contributions of this paper. First, a Driver-in-the-Loop (DiL) simulator, used for reproducible and safe data acquisitions of human behaviour, is presented. Second, subject-specific control parameter identification to replicate the unique behaviour of each subject by using a modular calibration approach. The DiL setup is modelled in Madymo using the active human model (AHM) as a representation of the human. The Matlab/Simulink interface of Madymo is extended to implement in Matlab two new individual muscle control strategies for the head-neck region of the AHM; (i) PD controllers based on the muscle length – motivated by the equilibrium point control theory and (ii) the in-vivo stretch reflex – based on the strain measuring capabilities of the muscle spindles. Any optimization procedure available in Matlab, i.e. a particle swarm optimizer, can be used to calibrate the control parameters to achieve a good agreement between DiL measurement data and the simulation output. Finally, this modular workflow is used to identify two subject-specific sets of control parameters. These subject-specific parameters play an important role in a robust representation of human occupants.

ABSTRACT. Patients with chronic disability, or in a transient disability state post-surgery may require a mobility device for their safety and convenience. Patients with a low to mid-level severe mobility impairment are mostly comfortable to leave hospital in a factory wheelchair without further modifications, however in particular chronically disabled wheelchair bound patients require wheelchair cushion modifications specifically designed for their condition. Such personalized cushions minimise pain from sitting, avoid pressure ulcers, and correct patient posture to prevent musculoskeletal and spinal damage. To identify physical properties of a complex seat cushion design with multiple layers, for the simulation of optimum seat cushions for mobility impaired users, long-term testing was undertaken with multiples of different layer combination samples. Physical indentation results for reorganised cushions were obtained and further evaluated. We present the first study where a complex, multi-layered foam cushion structure is cycle-tested using a custom-specific human-shape indenter, derived from 3-D body scanning of a 95th percentile stature subject. The test provides physical material properties of the complex foam structure under realistic human shape indentation for the selected anthropometry. The test results feed and validate a realistic material model, and confirm durability and stability over time of the complex foam.

ABSTRACT. For the aerospace industry, cockpit innovations are centered around comfort, pilot ergonomics and accessibility. Pilots spend a lot of time on a seat during a flight. If seats are uncomfortable and pilots are in a wrong posture, risks of injuries and fatigue increase a lot. All these expectations make the pilot cabin design very challenging. Moreover, due to very strict aeronautics certifications and standards, gaps can occur between concept design and seat development. The requested innovations to address this kind of issues can’t rely on a classical trial-and-error approach during testing on real prototypes with human volunteers. This way of working presents several disadvantages, such as repeatability and subjectivity issues. During real tests, volunteers’ morphology, posture and mood could change and sometimes don’t represent occupant diversity. As tests happen late in the development process at a time where there are very few flexibilities to improve the seat and cockpit designs or propose fully innovative solutions, it becomes very complicated for engineers to reach their initial objectives. To avoid all issues linked to real tests, OEMs and suppliers are beginning to change their development process and are adopting alternative ways to iterate earlier in the conception phase. In the scope of a pilot cabin development project done with aerospace actors Safran & Dassault Aviation and ESI-Group, a tool for aircraft pilot seat certification assessment has been developed to integrate earlier in the industrial process comfort aspects and seat integration inside the cockpit. This paper will describe the “virtual prototyping” and how designers can virtually create a seat model right from the early design phases and fully ensure performances thanks to human models. Seating simulations have been performed with dedicated models to evaluate their capabilities to highlight static, postural and vibratory comfort. New functionalities have been also tested like seat inclinations and thermal comfort. And finally, these results have been compared to real measurements and have proven predictability of ESI Seat and Interior Solution.

ABSTRACT. Driver posture monitoring is beneficial for identifying driver physical state as well as for optimizing passive safety systems to mitigate injury outcomes during collisions. In recent years, depth cameras are increasingly used to monitor driver’s posture. However, good driver posture data is missing for developing accurate posture recognition methods. In this study, we introduce a method to build an in-vehicle driver posture database for training posture recognition algorithms based on a depth camera. Driver motion data were collected from 23 participants performing both driving and non-driving activities by an optical motion capture system Vicon. Motions were reconstructed by creating personalized digital human skeletons and applying inverse kinematics approach. By taking advantage of the techniques developed in computer graphics, a recorded driver motion can be retargeted to a variety of virtual humans efficiently to build a large database including synthetic depth images, ground truth labels of body segments and skeletal joint centers. Examples from motion reconstruction, data augmentation and preliminary posture prediction results are given.

ABSTRACT. Foot positioning has a significant impact on human body stability control when completing a manufacturing task. In classical Digital Human Models (DHM), the use of stepping strategies to generate stable postures relies on simplistic models, which generally locate the DHM center of mass (COM) at half distance between feet contact or limit the zero moment point (ZMP) projection within the base of support (BOS). Developing more comprehensive stepping models requires rigorous experimental studies to extract human movement coordination strategies during manufacturing tasks, which can be used to validate DHM models. The objective of this study is to develop an experimental test bench representing industrial conditions and to carry out experiments to provide these DHM models with parameters of postural stability. The assessed postural stability parameters in this study were the support length which is a variation of the step length, and the ZMP position with respect to the BOS. Results obtained from a pilot subject showed that the contralateral and ipsilateral legs move respectively to expand the BOS in the direction of ZMP displacement to maximize stability.

ABSTRACT. Current finite element (FE) approaches to model clothing on the human body in terms of personal protective equipment (PPE) are mainly bound to the discretization of the outer element layer of the human body model (HBM) and the given posture. Costs for PPE prototyping could be lowered drastically if an efficient and posture-independent clothing modeling method would be available, so that the effectiveness of PPE in terms of injury risk mitigation could be assessed in a donned configuration. In the present study, an FE modeling method was developed to map 2D planar clothing structures on arbitrary 3D human body contours. The method was successfully applied to the GHBMC M50-PS with a modular design based ballistic vest including all components, joints and fasteners. The 3D shaped clothing models in combination with arbitrary HBM allow to analyze the structural interaction of protective clothing with the human body in unforeseen dangerous situations. The presented method facilitates the building of full featured FE models of PPE in donned configurations.

ABSTRACT. The human hand has a complex musculoskeletal structure which acts as an effective end-effector to perform grasping effectively. Optimal control is a productive method to execute predictive simulations for many biomechanical activities. Optimal control for grasping simulations has been demonstrated for precision grasps for two fingers. However, the procedure to expand it to a full hand is laborious, primarily due to a large computational cost. Furthermore, a full hand performs with a high degree of coordination. These issues  can be challenged by the inclusion of kinematic or postural synergies in the multibody framework. In this work, we implement the modelling of kinematic synergies to perform grasping simulations. The quality of the grasps are compared with an non-synergy actuated hand model.

ABSTRACT. This paper presents a method to calculate spatiotemporal parameters using a chest-worn accelerometer. Accuracy was compared with an optical system that consists of a walkway of transmitting and receiving bars (Microgait, Optogait, Bolzano, Italy). To this purpose, seventeen healthy male wore a smart shirt based worn accelerometer performing five meters of walkway delimited by five meters of optical bars OptoGait ™ (Microgait, Bolzano, Italy) for three times. Spatiotemporal parameters such as gait cycle and gait phases were analysed and compared using the two systems. Smart shirt based on chest-worn accelerometer revealed to be a non-intrusive way of calculating gait cycle, phases and sub-phases. In addition, the inverted pendulum model based on chest body-worn accelerometer revealed to be a good model for calculating step length variation and consequently the speed. Our results, are in line with previous literature presenting an average of 60.247 % of stance phase, 39.752% of swing phase, a foot flat subphase of 17.60%, a terminal stance subphase of 21.42%, a pre-swing subphase of 10.65%, a step length of 0.75 m for an average speed of 1.38 m/s using the smart shirt.