IEEE Transactions on Affective Computing · 2022 · 19 citations · 31 references
Wearable SystemEngineeringAffective DesignWearable TechnologyDigital EthicResearch EthicsSocial SciencesPsychologyAffective ScienceDigital HealthAffective ComputingHuman Research EthicBehavioral SciencesUser ExperienceRecode HealthCompanion ChecklistEthical ConsiderationsHuman-computer InteractionEthical ReviewNew Technologies PointsEmotion
As the popularity of wearables increases, so does their utility for studying emotions. Using new technologies points to several ethical challenges to be considered to improve research designs. There are several ethical recommendations for utilizing wearables to study human emotions, but they focus on emotion recognition systems applications rather than research design and implementation. To address this gap, we have developed a perspective on wearables, especially in daily life, adapting the ReCODE Health - Digital Health Framework and companion checklist. Therefore, our framework consists of four domains: (1) participation experience, (2) privacy, (3) data management, and (4) access and usability. We identified 33 primary risks of using wearables to study emotions, including research-related negative emotions, collecting, processing, storing, sharing personal and biological information, commercial technology validity and reliability, and exclusivity issues. We also proposed possible strategies for minimizing risks. We consulted the new ethical guidelines with members of ethics committees and relevant researchers. The judges ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> = 26) positively rated our solutions and provided useful feedback that helped us refine our guidance. Finally, we summarized our proposals with a checklist for researchers' convenience. Our guidelines contribute to future research by providing improved protection of participants' and scientists' interests.
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A Survey of Wearable Devices and Challenges
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The mPower study, Parkinson disease mobile data collected using ResearchKit
Brian M. Bot, Christine Suver, Elias Chaibub Neto et al. · Scientific Data · 2016 · 620 citations · Full text