Exploring unconscious user responses to affective computing in interactive prototypes: a consumer neuroscience study

Affective Computing (AC) has gained increasing attention for its potential to enrich Human-Computer Interaction by enabling technologies to recognise and respond to human emotions. However, there is limited research on how users unconsciously react to AC-based interactive prototypes at a physiological level during interaction. This study examines user cognitive and affective responses to two interactive AC-based Prototypes using consumer neuroscience techniques - Electroencephalogram (EEG), Galvanic Skin Response (GSR), and Eye-tracking - to capture unconscious physiological responses. Two laboratory experiments were conducted with a total sample of 34 participants, each experiment employing a different interactive AC-based prototype. The objective is to explore how users engage in cognitive and affective responses, as well as visual behaviour, through unconscious physiological responses generated during interactions with AC-based Prototypes. Results indicate that AC-based Prototypes exhibit greater engagement, cognitive load, and emotional impact on users compared to conventional technology. This study contributes to the field by providing evidence on how AC Prototypes influence user responses at an unconscious level, offering insights into how these technologies can enhance human-computer interactions. These findings indicate that AC technology enables more personalized and emotionally adaptive interactions between humans and machines by responding to users' affective states.

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Publication Details

Journal
Behaviour and Information Technology
Published
2025-05-18
DOI
https://doi.org/10.1080/0144929x.2025.2504514
Citations
4
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
8.47

Funders

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article

Exploring unconscious user responses to affective computing in interactive prototypes: a consumer neuroscience study

Mónica Cortiñas, Natalia Rubio, Álvaro Saavedra, Raquel Chocarro
4 citations
Behaviour and Information Technology
Emotion and Mood Recognition
8.47
article

Exploring unconscious user responses to affective computing in interactive prototypes: a consumer neuroscience study

Mónica Cortiñas, Natalia Rubio, Álvaro Saavedra, Raquel Chocarro
article en
4 citations

Abstract

Affective Computing (AC) has gained increasing attention for its potential to enrich Human-Computer Interaction by enabling technologies to recognise and respond to human emotions. However, there is limited research on how users unconsciously react to AC-based interactive prototypes at a physiological level during interaction. This study examines user cognitive and affective responses to two interactive AC-based Prototypes using consumer neuroscience techniques - Electroencephalogram (EEG), Galvanic Skin Response (GSR), and Eye-tracking - to capture unconscious physiological responses. Two laboratory experiments were conducted with a total sample of 34 participants, each experiment employing a different interactive AC-based prototype. The objective is to explore how users engage in cognitive and affective responses, as well as visual behaviour, through unconscious physiological responses generated during interactions with AC-based Prototypes. Results indicate that AC-based Prototypes exhibit greater engagement, cognitive load, and emotional impact on users compared to conventional technology. This study contributes to the field by providing evidence on how AC Prototypes influence user responses at an unconscious level, offering insights into how these technologies can enhance human-computer interactions. These findings indicate that AC technology enables more personalized and emotionally adaptive interactions between humans and machines by responding to users' affective states.

Behaviour and Information TechnologyVol. 44(20)
Universidad Pública de Navarra (UPNA) (ES), Universidad Autónoma de Madrid (ES)
European Commission, Ministerio de Ciencia e Innovación, Universidad Pública de Navarra, Agencia Estatal de Investigación
Openalex Percentile: Top 3%
Emotion and Mood Recognition
8.47
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