Facilitating Identification of Ergonomic User Needs Through AI-Assisted Observation

Abstract User needs identification is a critical early step in the engineering design process, as it defines key design opportunities and goals. Observation is one of the most widely used methods, although its effectiveness is often constrained by its time-intensive nature and susceptibility to bias. To address these challenges, this paper introduces an AI-based observation tool that analyzes videos of user activity to assist the ergonomic need identification process. With ergonomic considerations, designers can better understand and satisfy user needs, leading to novel design solutions with improved usability and inclusiveness. Using computer vision techniques, including pose estimation and object segmentation, our tool assesses user posture and interactions with objects to detect physical discomfort. A human subject experiment was conducted as a formative investigation to evaluate the tool’s impact on the user needs identification process and outcome. While the tool did not significantly affect the number or types of needs identified, it improved the level of detail and efficiency in the identification process. Additionally, when using the tool, the participants reported higher confidence in their latent need finding performance. These findings suggest that our AI-based observation tool has potential to successfully assist designers by streamlining ergonomic analysis and enhancing user-centered design practices. Future improvements will focus on expanding the tool’s capabilities to detect emotional and psychological needs and refining its user interface.