Related papers: Mobile-Based Experience Sampling for Behaviour Res…
This paper reviews research methods used to understand the user experience of mobile technology. The paper presents an improvement of the Experience Sampling Method and case studies supporting its design. The paper concludes with an agenda…
Mobile sensing plays a crucial role in generating digital traces to understand human daily lives. However, studying behaviours like mood or sleep quality in smartphone users requires carefully designed mobile sensing strategies such as…
In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never…
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness, unobtrusiveness, and ecological validity.…
In the past years we have witnessed the emergence of the new discipline of computational social science, which promotes a new data-driven and computation-based approach to social sciences. In this article we discuss how the availability of…
Emotion prediction is a key emerging research area that focuses on identifying and forecasting the emotional state of a human from multiple modalities. Among other data sources, physiological data can serve as an indicator for emotions with…
A pro-environmental attitude in the general population is essential to combat climate change. Society as a whole has the power to change economic processes through market demands and to exert pressure on policymakers - both are key social…
Human decision-making heavily relies on active sensing, a well-documented cognitive behaviour for evidence gathering to accommodate ever-changing environments. However, its operational mechanism in the real world remains non-trivial.…
Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces…
In this paper we discuss the use of sensors incorporated in mobile devices as possible mobile laboratories at the service of teaching experimental sciences. Mobile devices, smartphones, tablets, laptops, microbit cards, are a resource for…
Emergence of smartphone and the participatory sensing (PS) paradigm have paved the way for a new variant of pervasive computing. In PS, human user performs sensing tasks and generates notifications, typically in lieu of incentives. These…
Promoting healthy lifestyle behaviors remains a major public health concern, particularly due to their crucial role in preventing chronic conditions such as cancer, heart disease, and type 2 diabetes. Mobile health applications present a…
Students' mental well-being is vital for academic success, with activities such as studying, socializing, and sleeping playing a role. Current mobile sensing data highlight this intricate link using statistical and machine learning…
Data volume grows explosively with the proliferation of powerful smartphones and innovative mobile applications. The ability to accurately and extensively monitor and analyze these data is necessary. Much concern in mobile data analysis is…
In transport modeling and prediction, trip purposes play an important role since mobility choices (e.g. modes, routes, departure times) are made in order to carry out specific activities. Activity based models, which have been gaining…
There is an increasing interest in exploiting mobile sensing technologies and machine learning techniques for mental health monitoring and intervention. Researchers have effectively used contextual information, such as mobility,…
The growth of mobile sensor technologies have made it possible for city councils to understand peoples' behaviour in urban spaces which could help to reduce stress around the city. We present a quantitative approach to convey a collective…
Despite the advent of wearable devices and the proliferation of smartphones, there still is no ideal platform that can continuously sense and precisely collect all available contextual information. Ideally, mobile sensing data collection…
Advances in mobile computing have paved the way for the development of several health applications using smartphone as a platform for data acquisition, analysis and presentation. Such areas where mhealth systems have been extensively…
Mobile phones are quickly becoming the primary source for social, behavioral, and environmental sensing and data collection. Today's smartphones are equipped with increasingly more sensors and accessible data types that enable the…