Understanding the Preferences for Lower-Limb Prosthesis: A Think-Aloud Study during User-Guided Auto-Tuning

Author:

Yuan Jing1,Bai Xiaolu1,Alili Abbas2,Liu Ming2,Feng Jing1,Huang He2

Affiliation:

1. department of Psychology, North Carolina State University, NC, USA

2. Joint Department of Biomedical Engineering, North Carolina State University, University of North Carolina - Chapel Hill, NC, USA

Abstract

Prostheses help amputees to maintain physical health and quality of life. Prosthesis wearers’ satisfaction and adherence to the prosthesis are closely related to the preferences for prosthesis tuning settings. However, the underlying factors that contribute to the preferences were under-explored. In this study, two able-bodied participants were asked to change the robotic prosthesis settings to their preferred state and the think-aloud technique with a mixed-method approach was used to reveal the contributing factors of preferences. We found that physical perception (e.g., positions of the prosthetic foot, balance, and stability) and subjective feelings (e.g., comfortableness, satisfaction, confidence, and worries) were two major factors. Experiences with the intact leg and other profiles were used as anchors for their preference levels. Preferences may also differ with situational context such as walking speed. The saturation points were reached with no strong approach motivation. The implications for prosthesis design and research were discussed.

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Finding a Natural Fit: A Thematic Analysis of Amputees’ Prosthesis Setting Preferences during User-Guided Auto-Tuning;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2023-11-27

2. A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2023

3. Data-efficient human walking speed intent identification;Wearable Technologies;2023

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