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Investigating the Overall Experience of Wearable Robots during Prototype-Stage Testing
Jinlei Wang1,2, Suihuai Yu1,2, Xiaoqing Yuan3
1Key Laboratory of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel, Switzerland)
|November 11, 2022
Summary
This study introduces a new model to evaluate user experience with wearable robots (WRs) during prototyping. The model effectively predicts overall user experience, guiding future WR development and testing.
Area of Science:
- Human-Robot Interaction
- Robotics Engineering
- User Experience Research
Background:
- Wearable robots (WRs) show potential for collaborative tasks with humans.
- Limited user experience (UX) data exists for WRs, particularly during early prototyping.
- Understanding UX is crucial for effective WR development and adoption.
Purpose of the Study:
- To develop and validate an exploratory research model for assessing WR user experience during the prototyping phase.
- To identify key factors influencing the overall experience of using wearable robots.
- To provide a quantitative framework for predicting user experience in interactive robotic systems.
Main Methods:
- Quantitative empirical research was conducted.
- A theoretical model incorporating usability, hedonic quality, and attitude toward use was proposed.
- Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for data analysis.
Main Results:
- The proposed research model demonstrated medium predictive power, explaining 53.2% of the variance in overall WR user experience.
- Significant correlations were found between the latent variables within the model.
- The model provides a validated approach for quantifying user experience.
Conclusions:
- A novel quantitative research model effectively explains and predicts the overall user experience of wearable robots during prototyping.
- This model is valuable for iterative design and testing of WRs.
- The findings contribute to a better understanding of human-robot interaction in the context of wearable technologies.
