Challenges in interaction modelling with digital human models - A systematic literature review of interaction modelling approaches

Digital human models (DHM) allow for a proactive ergonomic assessment of products by applying different models describing the user-product interaction. In engineering design, DHM tools are currently not established as computer-aided ergonomics tools, since (among other reasons) the interaction models are either cumbersome to use, unstandardised, time-demanding or not trustworthy. To understand the challenges in interaction modelling, we conducted a systematic literature review with the aim of identification, classification and examination of existing interaction models. A schematic user-product interaction model for DHM is proposed, abstracting existing models and unifying the corresponding terminology. Additionally, nine general approaches to proactive interaction modelling were identified by classifying the reviewed interaction models. The approaches are discussed regarding their scope, limitations, strength and weaknesses. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity. Practitioner summary: This contribution presents a systematic literature review conducted to identify, classify and examine existing proactive interaction modelling approaches for digital human models in engineering design. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity. Abbreviations: DHM: digital human model; CAE: computer-aided engineering; RQ: research question.

COMAP: a new computational interpretation of human movement planning level based on coordinated minimum angle jerk policies and six universal movement elements

Flash and Hogan (1985) suggested that the CNS employs a minimum jerk strategy when planning any given movement. Later, Nakano et al. (1999) showed that minimum angle jerk predicts the actual arm trajectory curvature better than the minimum jerk model. Friedman and Flash (2009) confirmed this claim. Besides the behavioral support that we will discuss, we will show that this model allows simplicity in planning any given movement. In particular, we prove mathematically that each movement that satisfies the minimum joint angle jerk condition is reproducible by a linear combination of six functions. These functions are calculated independent of the type of the movement and are normalized in the time domain. Hence, we call these six universal functions the Movement Elements (ME). We also show that the kinematic information at the beginning and end of the movement determines the coefficients of the linear combination. On the other hand, in analyzing recorded data from sit-to-stand (STS) transfer, arm-reaching movement (ARM) and gait, we observed that minimum joint angle jerk condition is satisfied only during different successive phases of these movements and not for the entire movement. Driven by these observations, we assumed that any given ballistic movement may be decomposed into several successive phases without overlap, such that for each phase the minimum joint angle jerk condition is satisfied. At the boundaries of each phase the angular acceleration of each joint should obtain its extremum (zero third derivative). As a consequence, joint angles at each phase will be linear combinations of the introduced MEs. Coefficients of the linear combination at each phase are the values of the joint kinematics at the boundaries of that phase. Finally, we conclude that these observations may constitute the basis of a computational interpretation, put differently, of the strategy used by the Central Nervous System (CNS) for motor planning. We call this possible interpretation "Coordinated Minimum Angle jerk Policy" or COMAP. Based on this policy, the function of the CNS in generating the desired pattern of any given task (like STS, ARM or gait) can be described computationally using three factors: (1) the kinematics of the motor system at given body states, i.e., at certain movement events/instances, (2) the time length of each phase, and (3) the proposed MEs. From a computational point of view, this model significantly simplifies the processes of movement planning as well as feature abstraction for saving characterizing information of any given movement in memory.

The manipulability: a new index for quantifying movement capacities of upper extremity

In this work, it is proposed to evaluate the upper-limb movements through a global index of performance borrowed from the field of robotics: the manipulability. For a given posture, this index quantifies the set of velocities that can be achieved at the wrist in all the Cartesian directions. The manipulability can be represented by an ellipsoid from which the volume and shape related parameters can be derived. During a reach to grasp movement, the ellipsoid obtained from experiment presented a flattened shape along the forearm longitudinal axis and an increased volume as the arm was extended. From this study, it is concluded that: (1) the ellipsoid volume reflects well the ability to generate speed at the wrist which is effectively maximal for an extended posture; (2) if maximal velocity is an important parameter it might be advisable to primarily move the hand perpendicularly to the forearm longitudinal axis.

PRACTITIONER SUMMARY

The interest of manipulability indices is that they evaluate globally a posture of the upper-limb in relation to a given task. This original parameter could help to design environments or devices in order that the adopted postures maximise one particular aspect of the performance, i.e. the velocity of the hand.

Effects of target location, stature and hand grip type on in-vehicle reach discomfort

In order to improve car interior design, data of perceived discomfort and reach posture were collected for 75 different target locations. Altogether, 24 males and females of different statures participated in the experiment. In addition to three-finger grip, index fingertip reach and five finger grip were also compared. The effects of target location, stature and hand grip on reach discomfort were analysed. Predictive regression equations were provided. In addition to the confirmation of target location effects, the results showed that seat back and steering wheel affected discomfort. Their effects differed according to the subject's anthropometry. A detailed analysis of possible interference between the car interior and reach movement showed that short females were more likely impeded by the seat back when a target was close to the body. A significant difference between three hand grip types could be explained by the change of hand reach distance when changing hand grip type. STATEMENT OF RELEVANCE: The present study analysed the effects of target location, stature and hand grip type on reach discomfort, based on the statistical analysis of subjective ratings when reaching a target in a vehicle. The results would help to optimise the location of automotive controls for improving car interior design.

Enhancing digital driver models: identification of distinct postural strategies used by drivers

Driver workspace design and evaluation is, in part, based on assumed driving postures of users and determines several ergonomic aspects of a vehicle, such as reach, visibility and postural comfort. Accurately predicting and specifying standard driving postures, hence, are necessary to improve the ergonomic quality of the driver workspace. In this study, a statistical clustering approach was employed to reduce driving posture simulation/prediction errors, assuming that drivers use several distinct postural strategies when interacting with automobiles. 2-D driving postures, described by 16 joint angles, were obtained from 38 participants with diverse demographics (age, gender) and anthropometrics (stature, body mass) and in two vehicle classes (sedans and SUVs). Based on the proximity of joint angle sets, cluster analysis yielded three predominant postural strategies in each vehicle class (i.e. 'lower limb flexed', 'upper limb flexed' and 'extended'). Mean angular differences between clusters ranged from 3.8 to 52.4 degrees for the majority of joints, supporting the practical relevance of the distinct clusters. The existence of such postural strategies should be considered when utilising digital human models (DHMs) to enhance and evaluate driver workspace design ergonomically and proactively. STATEMENT OF RELEVANCE: This study identified drivers' distinct postural strategies, based on actual drivers' behaviours. Such strategies can facilitate accurate positioning of DHMs and hence help design ergonomic driver workspaces.

Digital Human Modeling for Workspace Design

Digital human modeling (DHM) technology offers human factors/ergonomics specialists the promise of an efficient means to simulate a large variety of ergonomics issues early in the design of products and manufacturing workstations. It rests on the premise that most products and manufacturing work settings are specified and designed by using sophisticated computer-aided design (CAD) systems. By integrating a computer-rendered avatar (or hominoid) and the CAD-rendered graphics of a prospective workspace, one can simulate issues regarding who can fit, reach, see, manipulate, and so on. In this chapter, I briefly describe the development of various DHM methods to improve CAD systems. Past concerns about early DHM methods are discussed, followed by a description of some of the recent major developments that represent attempts by various groups to address the early concerns. In this latter context, methods are described for using anthropometric databases to ensure that population shape and size are well modeled. Efforts to integrate various biomechanical models into DHM systems also are described, followed by a section that outlines how human motions are being modeled in different DHM systems. In a final section, I discuss recent work to merge cognitive models of human performance with DHM models of manual tasks. Much has been accomplished in recent years to make digital human models more useful and effective in resolving ergonomics issues during the design of products and manufacturing processes, but much remains to be learned and applied in this rapidly evolving aspect of ergonomics.

A memory-based model for planning target reach postures in the presence of obstructions

Existing posture prediction and motion simulation models generally lack the capability of simulating human obstruction avoidance during target reach. This compromises the utility of digital human models for ergonomics, as many design problems involve interactions between humans and obstructions. To address this problem, this paper presents a novel memory-based posture planning (MBPP) model, which plans reach postures that avoid obstructions. In this model, the task space is partitioned into small regions called cells. For a given human figure, each cell is linked to a memory that stores various alternative postures for reaching the cell. When a posture planning problem is given in terms of a target and an obstruction configuration, the model examines postures belonging to the relevant cell, selects collision-free ones and modifies them to exactly meet the hand target acquisition constraint. Simulation results showed that the MBPP model is capable of rapidly and robustly planning reach postures for various scenarios.

Head movement control in visually guided tasks: postural goal and optimality

This work investigates the control of horizontal head movements in the context of unconstrained visually guided head and arm/finger aiming tasks. In a first experiment, the head was free to move while gaze was directed at randomly presented eccentric targets distributed horizontally (0 degrees-120 degrees) at eye level. In a second experiment, the horizontal head orientation was constrained to predetermined positions (0 degrees, 15 degrees, 30 degrees, 45 degrees or 60 degrees rightward) while the right index finger aimed at targets with the arm fully extended. Kinematics of head movements in gaze displacements exhibits an initial component weakly correlated with target position, followed by multiple corrections. Since the eyes are assumed to already be aimed at the target when the corrections occur, it is suggested that one goal of head movement control is to achieve a desired final orientation (posture). This hypothesis is supported by results from the second experiment that reveal an association between eye/head orientation angles and errors exhibited in the visuo-spatial representation of the environment. The minimization of error then underlies the control of head movement as a postural response optimized for a given target and task condition.

A computer algorithm for representing spatial–temporal structure of human motion and a motion generalization method

Inspired by the generalized motor program (GMP) theory, this study presents a symbolic motion structure representation (SMSR) algorithm that identifies a basic spatial-temporal structure of a human motion. The algorithm resolves each joint angle-time trajectory of a multi-joint motion into a sequence of elemental motion segments and labels each motion segment with a symbol representing its shape ("U": monotonically increasing; "D": monotonically decreasing; "S": stationary). By concatenating symbols according to their order in time, the spatial-temporal structure of a joint angle-time trajectory is represented as a symbolic string. The structure of a multi-joint motion is then represented as a set of symbolic strings. A sample motion, whose structure is identified by the SMSR algorithm, can be generalized to produce an infinite number of similar motion variants. To generate a variant of a sample motion, segment boundary points of the sample motion are first relocated to new locations in the angle-time space, and then individual motion segments of the original joint angle trajectories are shifted and proportionally rescaled to fit the new segment boundary points. This motion generalization method provides a basis for developing GMP-based motion simulation models, and exploring ideas and hypotheses related to the GMP theory through simulation. As an application of the motion generalization method, a motion modification (MoM) algorithm is presented, which adapts existing reach motions for new target locations. Some examples generated by the MoM algorithm are illustrated.

Improving digital human modelling for proactive ergonomics in design

This paper presents the need to improve existing digital human models (DHMs) so they are better able to serve as effective ergonomics analysis and design tools. Existing DHMs are meant to be used by a designer early in a product development process when attempting to improve the physical design of vehicle interiors and manufacturing workplaces. The emphasis in this paper is placed on developing future DHMs that include valid posture and motion prediction models for various populations. It is argued that existing posture and motion prediction models now used in DHMs must be changed to become based on real motion data to assure validity for complex dynamic task simulations. It is further speculated that if valid human posture and motion prediction models are developed and used, these can be combined with psychophysical and biomechanical models to provide a much greater understanding of dynamic human performance and population specific limitations and that these new DHM models will ultimately provide a powerful ergonomics design tool.