Mood😆 and eating 🍱 are two prominent factors that shape our daily life, health, and well-being. While the intersection of
#Mood and
#EatingBehavior has been extensively studied, it remains poorly understood through
#SmartphoneSensor data, captured in
#MobileFoodDiaries and
#DigitalHealth applications.
Our new paper takes a deeper look into this research gap by developing machine learning models using over 24K mood-while-eating reports captured from more than 700 participants across 8 countries🌍📊, via a mobile app📱 in the context of the
#DiversityOne study.
Read the paper here:
dl.acm.org/doi/10.1145/37230…
Learn more about
#DiversityOne dataset here:
dl.acm.org/doi/10.1145/37122…
This long and rewarding collaboration, which spanned over two years from ideation to publication, was made possible with the help of Wageesha Bangamuarachchi (
@WageeshaErangi) and Anju Chamantha (
@a_chamantha) who lead the work, and also other amazing collaborators Haeeun Kim, Salvador Ruiz-Correa (
@SalvadorRu78223), Indika Perera, and Daniel Gatica-Perez (
@dgaticaperez).
Department of Computer Science & Engineering, University of Moratuwa (
@cse_uom), University of Moratuwa (
@MoratuwaUni), University of Utah (
@UUtah), IPICyT (
@IPICYTciencia), ETH Zürich (
@ETH,
@ETH_en,
@HEST), Idiap Research Institute (
@Idiap_ch), EPFL (
@EPFL,
@EPFL_en)
#digitalhealth #mobilehealth #mhealth #ehealth #smartphonesensing #ubicomp #mobilesensing #multimodalsensing #mobilefooddiaries #fooddiary #eatingbehavior #behaviormodeling #healthcare