Concept
Ivresse
Publications associées (19)
Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life
A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...
EPFL2024Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety
Jeffrey Huang, Simon Elias Bibri
In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...
Springernature2024Impaired cognitive flexibility and heightened urgency are associated with increased alcohol consumption in rodent models of excessive drinking
Alcohol use disorder (AUD) is characterized by impairments in decision-making that can exist as stable traits or transient states. Cognitive inflexibility reflects an inability to update information that guides decision-making and is thought to contribute ...
WILEY2021Understanding Eating And Drinking In Context From Crowdsourced Data
With the increasing rate of urbanization, understanding food and beverage consumption, including alcohol drinking behaviour with its consequences, is relevant in such a megacity in the future. Especially, investigation of alcohol drinking is necessary for ...
EPFL2020Youth nightlife at home: towards a feminist conceptualisation of home
Daniel Gatica-Perez, Darshan Santani
This paper explores home as a space of youth nightlife and drinking through a feminist lens. It draws on feminist geographical scholarship on home and 40 semi-structured interviews with young people aged 16–25 in Switzerland in the context of a larger inte ...
2020Learning Urban Nightlife Routines from Mobile Data
Daniel Gatica-Perez, Thanh Trung Phan
The use of smartphone sensing for public health studies is appealing to understand routines. We present an approach to learn nightlife routines in a smartphone sensing dataset volunteered by 184 young people (1586 weekend nights with location data captured ...
ACM2020Understanding Heavy Drinking at Night through Smartphone Sensing and Active Human Engagement
Daniel Gatica-Perez, Skanda Muralidhar, Thanh Trung Phan
Heavy alcohol consumption can lead to many severe consequences. In this paper, we study the phenomenon of heavy drinking at night (4+ drinks for women or 5+ for men on a single evening), using a smartphone sensing dataset depicting about nightlife and drin ...
ACM2020The contexts of heavy drinking: A systematic review of the combinations of context-related factors associated with heavy drinking occasions
Background
The amount of alcohol consumed during an occasion can be influenced by physical and social attributes of the setting, characteristics and state of individuals, and the interactions of these components. This systematic review identifies and desc ...
2019#Drink Or #Drunk: Multimodal Signals and Drinking Practices on Instagram
Daniel Gatica-Perez, Skanda Muralidhar, Thanh Trung Phan
The understanding of alcohol consumption patterns, especially those indicating negative drinking behavior, is an important issue to researchers and health policymakers. On social media, people share daily activities, including alcohol consumption, represen ...
2019What Reminds Young People That They Drank More Than Intended on Weekend Nights: An Event-Level Study
Objective:
Young people often drink more alcohol than intended over the course of a night. This study investigates individual and night-specific factors predicting young people’s acknowledgment of having drunk more than intended.
Method:
Using the Yout ...
2018