Study of Ageing in Complex Interface Interaction Tasks: Based on Combined Eye-Movement and HRV Bioinformatic Feedback

Ting Huang, Chengmin Zhou (), Xin Luo and Jake Kaner
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Ting Huang: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China
Chengmin Zhou: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China
Xin Luo: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China
Jake Kaner: School of Art and Design, Nottingham Trent University, Nottingham NG1 4FQ, UK

IJERPH, 2022, vol. 19, issue 24, 1-12

Abstract: Human–computer interaction tends to be intelligent and driven by technological innovation. However, there is a digital divide caused by usage barriers for older users when interacting with complex tasks. To better help elderly users efficiently complete complex interactions, a smart home’s operating system’s interface is used as an example to explore the usage characteristics of elderly users of different genders. This study uses multi-signal physiological acquisition as a criterion. The results of the study showed that: (1) Older users are more attracted to iconic information than textual information. (2) When searching for complex tasks, female users are more likely to browse the whole page before locating the job. (3) Female users are more likely to browse from top to bottom when searching for complex tasks. (4) Female users are more likely to concentrate when performing complex tasks than male users. (5) Males are more likely to be nervous than females when performing complex tasks.

Keywords: complex interaction tasks; age-friendly interface; eye tracking; multi-physiological signals (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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