Evaluation method of design elements for scoliosis orthoses based on three-dimensional perspective tracking data

Product kansei image evaluation is crucial for optimizing product design elements. Developing methods for evaluating kansei image will improve user satisfaction. Traditional methods of assessing kansei image primarily use two-dimensional images, limited by their single perspective and one-sided interaction. To overcome these limitations, this paper proposes a product kansei image evaluation method incorporating three-dimensional perspective tracking data. This study used scoliosis orthosis as an experimental sample and focused on the kansei image word “hidden.” Through kansei image evaluation, we identified the product design elements that most influence the perception of “hidden”, optimizing the design to increase the product’s hiddenness. First, we created an interactive three-dimensional simulation space and placed a three-dimensional model of a scoliosis orthosis inside it. Through this setup, participants could interact in three dimensions with the product, enabling the collection of three-dimensional perspective data. Meanwhile, we divided the scoliosis orthosis into Areas of Interest (AOI) based on the product’s functional regions and acquired eye-tracking data as participants interacted with the product model in the three-dimensional simulation space. The eye-tracking and three-dimensional perspective data were matched with the AOI regions. Finally, we weighted the eye-tracking data with the three-dimensional perspective tracking data to calculate the weighted value of each design element of the scoliosis orthosis associated with the kansei image word “hidden,” thus optimizing the design based on their priority. The results demonstrate that evaluating kansei images with three-dimensional perspective tracking data is more accurate than with eye tracking alone. Further analysis reveals that: (1) Constructing a three-dimensional simulation space to display the product model and enable human–computer interaction provides more accurate experimental data than traditional single-perspective two-dimensional images, better reflecting real user-product interactions. (2) Regarding the weight calculation of design elements, three-dimensional perspective tracking data is incorporated based on eye-tracking data, and a weighted method is used for the calculation. This includes visual data obtained by observing the product from different fixation points, providing more information and improving the results’ authenticity. (3) Eye-tracking data combined with three-dimensional perspective tracking enables designers to make quick decisions on design elements that need to be optimised. Consequently, designers can adjust scoliosis orthoses promptly, improving patient compliance and orthopedic effectiveness. In this study, we propose a new quantitative method for evaluating kansei images in products and provide new insights into the perceptual design of scoliosis orthoses.