Multimodal Assessment of Emotion in Aging and Dementia: A Laboratory-Based Protocol

Dementia affects millions worldwide and challenges emotional and social functioning. However, emotional experiences in dementia remain poorly understood. To help better understand this complex phenomenon, the component process model (CPM) was used, which views emotion as a changing process involving appraisal, expression, physiology, motivation, and feeling. It demands a multimodal approach to measure its components. A protocol was developed that combines physiological, facial, vocal, linguistic, and self-report measures, and its feasibility was assessed. The protocol was piloted using iMotions on two older adults with caregiving experience and one with expertise in neuropsychology. Adjustments to instructions, mock tests to familiarize participants with the tasks, and session duration were implemented for a subsequent sample of healthy participants (3 young and 4 older adults) and for 1 older adult diagnosed with dementia due to probable Alzheimer's disease. Participants were screened for impairments in hearing, vision, cognition, and language, as well as psychological distress. The final tasks required watching validated film clips to elicit joy, anger, and sadness. Recorded data according to the CPM included facial movements and voice (expression), electrodermal activity and heart rate (physiology), discourse content, and CoreGRID questionnaire (appraisal; feeling; motivation). Protocol feasibility was assessed by documenting the number of completed tasks, collecting participant feedback via the Post-Study System Usability Questionnaire with comments, and extracting data quality metrics from iMotions for facial expressions and galvanic skin response (percentage of usable data; signal-to-noise ratio). All participants completed the tasks and reported positive feedback on the usability questionnaire. Automated facial expression data were analyzable for all participants, and galvanic skin response recordings were obtained for all participants, with 10 of 11 recordings meeting the predefined signal-to-noise criterion. This protocol was feasible to administer in the tested sample. Further evaluation in larger and more diverse dementia samples is needed.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2026-10-27
DOI
https://doi.org/10.3791/73521
Primary Topic
Emotion and Mood Recognition
Type
article
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article

Multimodal Assessment of Emotion in Aging and Dementia: A Laboratory-Based Protocol

Nathalie H. Gosselin, Anna Zumbansen, Sina Shafiyan, Carol Léonard
Journal of Visualized Experiments
Emotion and Mood Recognition
article

Multimodal Assessment of Emotion in Aging and Dementia: A Laboratory-Based Protocol

Nathalie H. Gosselin, Anna Zumbansen, Sina Shafiyan, Carol Léonard
article en

Abstract

Dementia affects millions worldwide and challenges emotional and social functioning. However, emotional experiences in dementia remain poorly understood. To help better understand this complex phenomenon, the component process model (CPM) was used, which views emotion as a changing process involving appraisal, expression, physiology, motivation, and feeling. It demands a multimodal approach to measure its components. A protocol was developed that combines physiological, facial, vocal, linguistic, and self-report measures, and its feasibility was assessed. The protocol was piloted using iMotions on two older adults with caregiving experience and one with expertise in neuropsychology. Adjustments to instructions, mock tests to familiarize participants with the tasks, and session duration were implemented for a subsequent sample of healthy participants (3 young and 4 older adults) and for 1 older adult diagnosed with dementia due to probable Alzheimer's disease. Participants were screened for impairments in hearing, vision, cognition, and language, as well as psychological distress. The final tasks required watching validated film clips to elicit joy, anger, and sadness. Recorded data according to the CPM included facial movements and voice (expression), electrodermal activity and heart rate (physiology), discourse content, and CoreGRID questionnaire (appraisal; feeling; motivation). Protocol feasibility was assessed by documenting the number of completed tasks, collecting participant feedback via the Post-Study System Usability Questionnaire with comments, and extracting data quality metrics from iMotions for facial expressions and galvanic skin response (percentage of usable data; signal-to-noise ratio). All participants completed the tasks and reported positive feedback on the usability questionnaire. Automated facial expression data were analyzable for all participants, and galvanic skin response recordings were obtained for all participants, with 10 of 11 recordings meeting the predefined signal-to-noise criterion. This protocol was feasible to administer in the tested sample. Further evaluation in larger and more diverse dementia samples is needed.

Journal of Visualized Experiments(236)
University of Ottawa (CA), Université de Montréal (CA)
Openalex Percentile: Top 8%
Emotion and Mood Recognition
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