ASTM F3771-25

1.1 This practice provides information about utilizing human digital modeling in the design and evaluation of exoskeletons. This practice specifies:

• 1.1.1 Basic terminology, definitions, principles, methods, inputs, and expected outputs of digital human modeling (DHM) methods.
• 1.1.2 Principles of modeling methods and expected outputs for designing new exoskeletons or for new work processes, or both.
• 1.1.3 Principles of modeling methods and expected outputs for evaluating existing exoskeleton devices and human-exoskeleton collaborative/teaming tasks.
• 1.1.4 Recommendations of modeling methods and expected outputs for consumers to estimate the benefit of using exoskeleton products in their domain.

1.2 The practice does not describe all the details about the model establishment and parameter determination. Instead, this practice provides audiences with necessary modeling procedures and precautions, and results in an interpretation specifically for device design or evaluation purposes.

1.3 The values stated in SI units are to be regarded as the standard. The values given in the examples are not precisely validated, are provided for information only, and are not considered standard.

1.4 Table of Contents:

5.1 This practice guides the user through a selection of digital human modeling methods, various modeling focuses, and available outcomes for use in evaluating the performance of existing exoskeletons and predicting/simulating the performance of exoskeleton concept designs. Fig. 1 shows a flow chart for developing a digital human-exoskeleton model for a different purpose.

Overall, there are two major usages of DHM in the application of human-exoskeleton interaction.

• First, DHM can be used to simulate an expected task, a specific expected exoskeleton design, and predict expected workloads on users. The results from this type of DHM can be used to virtually design a new exoskeleton device or design/evaluate new human-exoskeleton interaction scenarios.
• The second typical use of DHM is for the evaluation of real human-exoskeleton interactive tasks. Data required to build such DHM are mainly from real data collection where users’ anthropometry, motion, external forces, as well as kinematics of the exo devices are collected from a simulated task in a laboratory environment or a real task in the field. Further details can be found in Section 7.

Two major applications of DHM (that is, simulation and evaluation) are illustrated using separate colors.

5.2 The benefits of using DHM in understanding the teaming operation between users and exoskeletons mainly include:

1. (1) reduce time and costs of the equipment development cycle, no real prototype is needed, and all the design/redesign procedures can be completed virtually and efficiently with good flexibility of the design procedure;
2. (2) avoid potential risks due to uncertainty while exploring various exoskeleton design ideas and human-exoskeleton interaction scenarios;
3. (3) DHM can also provide an offline estimation of internal loads placed on users during real human-exoskeleton interaction, identifying potential risks associated with posture, loads, and other human-exoskeleton interaction;
4. (4) DHM can be used as a surveillance solution to provide real-time workloads estimations and risks identification.

The detailed model components and modeling procedure are explained in Sections 6 and 7.

5.3 This practice is expected to provide guidance for many, although not all, estimations and evaluations of human-exoskeleton interaction activities. The method described in this practice can be used as a basic method of DHM or as guidance for developing additional and advanced DHM of human-exoskeleton interaction.