Improving Social Acceptance of Orthopedic Foot Orthoses Through Image-Generative AI in Product Design

The lack of social acceptability for wearable devices such as orthopedic foot orthoses can lead to irregular usage and missed health benefits, as shown in prior studies. While AI-generated designs have been explored for prototyping aesthetic hand orthoses, their impact on social acceptability, particularly for foot orthoses, remains unknown. The current state of research is limited, as no empirical evidence exists on whether AI-designed orthoses influence acceptance, nor has the role of customized generative pre-trained transformers (GPTs) and specific prompting strategies been examined in this context. To address these gaps, we conducted two mixed-methods studies to investigate (1) the impact of AI-generated orthosis designs on social acceptability compared to existing orthopedic products and development concepts and (2) how a customized GPT and different prompt keywords influence acceptance. Our results show that AI-generated designs significantly enhance social acceptance across orthotic categories. Furthermore, we found that personalized GPTs and targeted prompt keywords significantly influence user perception. Overall, our findings highlight the potential of using AI to create socially acceptable design solutions for wearable technology and offer new applications for future smart devices. We contribute to generative AI in product design and provide concrete recommendations for optimizing prompting strategies to enhance social acceptance.

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Publication Details

Journal
Applied Sciences
Published
2025-04-09
DOI
https://doi.org/10.3390/app15084132
Citations
5
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.27
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article

Improving Social Acceptance of Orthopedic Foot Orthoses Through Image-Generative AI in Product Design

Stefan Resch, Diana Völz, Valentin Schwind, Daniel Morillo et al.
5 citations
Applied Sciences
Artificial Intelligence in Healthcare and Education
3.27
article

Improving Social Acceptance of Orthopedic Foot Orthoses Through Image-Generative AI in Product Design

Stefan Resch, Diana Völz, Valentin Schwind, Daniel Morillo, Jakob Schauer
article en
5 citations

Abstract

The lack of social acceptability for wearable devices such as orthopedic foot orthoses can lead to irregular usage and missed health benefits, as shown in prior studies. While AI-generated designs have been explored for prototyping aesthetic hand orthoses, their impact on social acceptability, particularly for foot orthoses, remains unknown. The current state of research is limited, as no empirical evidence exists on whether AI-designed orthoses influence acceptance, nor has the role of customized generative pre-trained transformers (GPTs) and specific prompting strategies been examined in this context. To address these gaps, we conducted two mixed-methods studies to investigate (1) the impact of AI-generated orthosis designs on social acceptability compared to existing orthopedic products and development concepts and (2) how a customized GPT and different prompt keywords influence acceptance. Our results show that AI-generated designs significantly enhance social acceptance across orthotic categories. Furthermore, we found that personalized GPTs and targeted prompt keywords significantly influence user perception. Overall, our findings highlight the potential of using AI to create socially acceptable design solutions for wearable technology and offer new applications for future smart devices. We contribute to generative AI in product design and provide concrete recommendations for optimizing prompting strategies to enhance social acceptance.

Applied SciencesVol. 15(8)
Goethe University Frankfurt (DE), Universidad de Cádiz (ES), Biomedical Research and Innovation Institute of Cadiz (ES), Frankfurt University of Applied Sciences (DE)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
3.27
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Improving Social Acceptance of Orthopedic Foot Orthoses Through Image-Generative AI in Product Design — Stefan Resch, Diana Völz, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS