New Technologies to Improve Mood by Eliciting Autobiographical Memories in Older Adults

Selva, Jorge; Aguilar, L.F.; Ros, Laura; Trives, J. Ricarte; López, Marta Nieto; Postigo, José Miguel Latorre

doi:10.1093/geroni/igx004.2696

Cited by 1 publication

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“…Unfortunately, few efforts have been made to regulate the ageing adults' emotional condition (Castillo et al, ; Fernández‐Caballero, Latorre, Pastor, & Fernández‐Sotos, ) or improve their autobiographical memory (Ros et al, ; Serrano et al, ), which would play a key role in health and wellness promotion. However, the affective computing paradigm enables to decide an adequate response to human emotional stimuli (Peralta, Fernández‐Caballero, Latorre, Olivas, & Conde, ; Poria, Cambria, Bajpai, & Hussain, ; Sokolova & Fernández‐Caballero, ).…”

Section: Introductionmentioning

confidence: 99%

Film mood induction and emotion classification using physiological signals for health and wellness promotion in older adults living alone

et al. 2019

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This paper introduces a wearable hardware/software system specifically tailored to detect seven emotions (neutral, tenderness, amusement, anger, disgust, fear, and sadness) aimed at promoting health and wellness in older adults living alone at home. The complete software and hardware architectures acquiring and processing electrodermal activity and photoplethysmography signals are introduced. The wearable emotion detection system is trained by eliciting the desired emotions on 39 older adults through a film mood induction procedure. Seventeen features are calculated on skin conductance response and heart rate variability data, grouped into five statistical, four temporal, and eight morphological features. Then, these features are used to run emotion classification considering support vector machines, decision trees, and quadratic discriminant analysis. In line with psychological findings, the results offer a global accuracy of 82% in negative emotion (anger, disgust, fear, and sadness) classification. For positive emotions (tenderness and amusement), also in conformity with previous psychological outcomes, amusement shows the highest ratio of hits (92%) but tenderness the lowest one (66%). These results demonstrate that our wearable emotion detection system can be used by ageing adults, especially for detecting negative emotions that usually damage health and wellness and lead to social isolation.

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