Key terms and topics of muscle-supportive and posture-corrective wearable robots for older adults using text mining and semantic network analyses

Abstract

Purpose

This study aims to conduct text mining and semantic network analysis of muscle-supportive and posture-corrective wearable robots for the elderly to understand key terms related to the topic and to identify considerations for developing these types of clothing.

Design/methodology/approach

The authors searched and identified the key terms wearable robot, muscle-supportive, posture correction and elderly using the text-mining software Textom to extract terms as well as the network analysis software UCINET 6 to process and visualize the relationships among the terms. The authors compared and analyzed the term frequency (TF), the TF-inverse document frequency and the degree centrality of the terms, and the authors visualized and summarized the terms using NetDraw.

Findings

The key terms and their relationships in 3–4 groups were identified: wearable robot, muscle-supportive, posture correction and elderly. The authors identified the aspects of designing muscle-supportive and posture-corrective wearable robots for the elderly.

Originality/value

This study contributes to the field of muscle-supportive clothing and wearable robotics by deriving insights into what people are discussing and interested in, and by offering recommendations when developing these types of clothing for the elderly.

Citation

Tang, W., Chung, J. and Koo, S. (2024), "Key terms and topics of muscle-supportive and posture-corrective wearable robots for older adults using text mining and semantic network analyses", Research Journal of Textile and Apparel, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/RJTA-08-2023-0087