Dataset Information

K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.

ABSTRACT: With the popularization of low-cost mobile and wearable sensors, several studies have used them to track and analyze mental well-being, productivity, and behavioral patterns. However, there is still a lack of open datasets collected in real-world contexts with affective and cognitive state labels such as emotion, stress, and attention; the lack of such datasets limits research advances in affective computing and human-computer interaction. This study presents K-EmoPhone, a real-world multimodal dataset collected from 77 students over seven days. This dataset contains (1) continuous probing of peripheral physiological signals and mobility data measured by commercial off-the-shelf devices, (2) context and interaction data collected from individuals' smartphones, and (3) 5,582 self-reported affect states, including emotions, stress, attention, and task disturbance, acquired by the experience sampling method. We anticipate the dataset will contribute to advancements in affective computing, emotion intelligence technologies, and attention management based on mobile and wearable sensor data.

SUBMITTER: Kang S

PROVIDER: S-EPMC10238385 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.

Kang Soowon S Choi Woohyeok W Park Cheul Young CY Cha Narae N Kim Auk A Khandoker Ahsan Habib AH Hadjileontiadis Leontios L Kim Heepyung H Jeong Yong Y Lee Uichin U

Scientific data 20230602 1

With the popularization of low-cost mobile and wearable sensors, several studies have used them to track and analyze mental well-being, productivity, and behavioral patterns. However, there is still a lack of open datasets collected in real-world contexts with affective and cognitive state labels such as emotion, stress, and attention; the lack of such datasets limits research advances in affective computing and human-computer interaction. This study presents K-EmoPhone, a real-world multimodal ...[more]

PMID: 37268686

Similar Datasets

Project description:BackgroundMany adolescent mothers are parenting young children under highly stressful conditions as they are managing first-time parenthood, poverty, lack of housing, school and work, and challenging peer and familial relationships. Mobile health (mHealth) technology has the potential to intervene at various points in the emotion regulation process of adolescent mothers to provide them support for more adaptive emotional and behavioral regulation in the course of their daily life.ObjectiveThe goal of this study was to examine the acceptability, feasibility, use patterns, and mechanisms by which a mobile technology used as an adjunct to in-person, provider-delivered sessions fostered adolescent mothers' adaptive emotion regulation strategies under real-life conditions.MethodsParticipants (N=49) were enrolled in the intervention condition of a larger pilot study of homeless adolescent mothers living in group-based shelters. The mHealth technology. Calm Mom, consisted of a mobile app and a wrist-worn sensorband for the ambulatory measurement and alerting of increased electrodermal activity (EDA), a physiological measurement of stress. We examined logs of mobile app activity and conducted semistructured qualitative interviews with a subsample (N=10) of participants. Qualitative data analysis was guided by the theoretical frames of the intervention and a technology acceptance model and included an analysis of emerging themes and concepts.ResultsOverall, participants indicated that one or more of the elements of Calm Mom supported their ability to effectively regulate their emotions in the course of their daily life in ways that were consonant with the intervention's theoretical model. For many adolescent mothers, the app became an integral tool for managing stress. Due to technical challenges, fewer participants received sensorband alerts; however, those who received alerts reported high levels of acceptability as the technology helped them to identify their emotions and supported them in engaging in more adaptive behaviors during real-life stressful situations with their children, peers, and family members.ConclusionsCalm Mom is a promising technology for providing theoretically driven behavioral intervention strategies during real-life stressful moments among a highly vulnerable population. Future research efforts will involve addressing technology challenges and refining tailoring algorithms for implementation in larger-scale studies.

Dataset Information

K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.

Publications

K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets