Emotional Self-Regulation of Individuals with Autism Spectrum Disorders: Smartwatches for Monitoring and Interaction
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In this paper, we analyze the needs of individuals with Autism Spectrum Disorders (ASD) to have a pervasive, feasible and non-stigmatizing form of assistance in their emotional self-regulation, in order to ease certain behavioral issues that undermine their mental health throughout their life. We argue the potential of recent widespread wearables, and more specifically smartwatches, to achieve this goal. Then, a smartwatch system that implements a wide range of self-regulation strategies and infers outburst patterns from physiological signals and movement is presented, along with an authoring tool for smartphones that is to be used by caregivers or family members to create and edit these strategies, in an adaptive way. We conducted an intensive experiment with two individuals with ASD who showed varied, representative behavioral responses to their emotional dysregulation. Both users were able to employ effective, customized emotional self-regulation strategies by means of the system, recovering from the majority of mild stress episodes and temper tantrums experienced in the nine days of experiment in their classroom.
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Using physiological and movement metrics from a smartwatch to infer outburst patterns, real-time, self-regulation exercises are sent as smartwatch notifications as a just-in-time intervention.
“Using physiological and movement metrics from a smartwatch to infer outburst patterns, real-time, self-regulation exercises are sent as smartwatch notifications as a just-in-time intervention.”
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- Authors
- Torrado, J. C., Gomez, J., & Montoro, G.
- Affiliations
- Universidad Autónoma de Madrid (ES)
- Department of Computer Engineering, Universidad Autónoma de Madrid, Madrid 28049, Spain
- Corresponding author
- Torrado, Juan C.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2017-06-11
- Volume
- 17
- Issue
- 6
- Pages
- 1359
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC5492838
- OpenAlex
- W2624259507
- Cited by
- 130
- References
- 90
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 14 · 2023: 13 · 2022: 21 · 2021: 18 · 2020: 18 · 2019: 10 · 2018: 10
- FWCI
- 5.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion)
- Tesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Hispana (submittedVersion)
- Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, public-domain)
- Funders
- Fundación Orange
- e-Training y e-Coaching para la integración socio-laboral (TIN2013--44586--R)
- eMadrid-CM: Investigación y Desarrollo de Tecnologías Educativas en la Comunidad de Madrid (S2013/ICE-2715)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- autism spectrum disorder, emotion regulation, smartwatches, wearable devices, physiological signals, motion detection, tantrums
- MeSH terms
- Autism Spectrum Disorder, Smartphone, Emotions, Humans
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