Operational Performance and Subjective Preferences of Elderly Users in Intelligent Interactive Interfaces: A Systematic Review

Abstract

As the ageing population grows and information technology evolves, elderly individuals increasingly rely on interacting with intelligent interfaces in their daily activities, posing a challenge to their interaction fluency. This study aims to identify the evaluation indicators and conditions in intelligent interactive interfaces that affect the operational performance and subjective preferences of elderly users. From there, general conclusions and strategies are summarised to promote the development of age-friendly design and practice in intelligent interactive interfaces. This systematic review includes 31 studies for analysis and classifies them into four categories according to the form of interaction: gesture interaction, voice interaction, multimodal interaction, and artificial intelligence interaction. The review indicates that factors such as the simplicity and direction of gestures in gesture interaction, the fluency of user expression and system recognition in voice interaction, modalities of interface input and feedback, as well as the conversational style, appearance, and mode of artificial intelligence, all affect user performance and preferences. However, there may be inconsistencies in the performance and preferences of elderly users in almost every form of interface. Therefore, future study needs to delve into specific scenarios for analysis.

Keywords:

• Intelligent interaction
• operational performance
• subjective preference
• elderly user
• systematic review

Disclosure statement

The authors report there are no competing interests to declare.

Additional information

Funding

This paper was supported by the Major Project of the National Social Science Fund (NSSF) of China “Theoretical and Practical Innovations for Evaluation Systems of Art Theory” (Project No. 21ZD11).

Notes on contributors

Yaxi Wang

Yaxi Wang is an associate professor at the School of Art and Design, Wuhan Institute of Technology, and Head of the Department of Industrial Design. She has a PhD in design. Her research interests include human-computer interaction and service design systems innovation.

Yiliang Zhou

Yiliang Zhou is a master’s student at the School of Art and Design, Wuhan Institute of Technology. Her research interests include human-computer interaction and user experience.

Xing Chen

Xing Chen is an Associate Professor at Beihang University, and an adjunct professor at the School of Art and Design, Wuhan Institute of Technology. His research aims to develop innovative while clinically useful medical devices or instruments based on MEMS technology.

Hao Fang

Hao Fang is a professor and doctoral supervisor at the School of Art and Design, Wuhan Institute of Technology. He has a PhD in communications and information systems. His research interests include human-intelligent interaction design and VR creative engineering.