Related papers: Using Behavioral Interactions from a Mobile Device…
Context information brings new opportunities for efficient and effective applications and services on mobile devices. A wide range of research has exploited context dependency, i.e., the relations between context(s) and the outcome, to…
Smartphones are now ubiquitous, yet our understanding of user interface factors that maximize mobile user experience (UX), is still limited. This work presents a controlled experiment, which investigated factors that affect the usability…
The ubiquity and on-the-go availability of mobile devices makes them central to many tasks such as interpersonal communication and media consumption. However, despite the potential of mobile devices for on-demand exploratory data…
Usage of smartphones and tablets have been increasing rapidly with multi-touch interaction and powerful configurations. Performing tasks on mobile phones become more complex as people age, thereby increasing their cognitive workload. In…
The ability to automatically recognize a person's behavioral context can contribute to health monitoring, aging care and many other domains. Validating context recognition in-the-wild is crucial to promote practical applications that work…
User engagement is crucial to the long-term success of a mobile app. Several metrics, such as dwell time, have been used for measuring user engagement. However, how to effectively predict user engagement in the context of mobile apps is…
As mobile computing becomes central to digital interaction, researchers have turned their attention to adaptive authentication for its real-time, context- and behavior-aware verification capabilities. However, many implementations remain…
Context-awareness in personalized mobile applications is a growing area of study. Social context is one of the most important sources of information in human-activity based applications. In this paper, we mainly focus on social relational…
User mobility prediction is widely considered to be helpful for various sorts of location based services on mobile devices. A large amount of studies have explored different algorithms to predict where a user will visit in the future based…
Interaction is a fundamental part of using any computer system but it is still an issue for people with special needs. In order to improve this situation, this paper describes a new device-interaction model based on adaptation rules for…
In this paper we predict outgoing mobile phone calls using a machine learning approach. We analyze to which extent the activity of mobile phone users is predictable. The premise is that mobile phone users exhibit temporal regularity in…
Research on mobile collocated interactions has been exploring situations where collocated users engage in collaborative activities using their personal mobile devices (e.g., smartphones and tablets), thus going from personal/individual…
Mental health conditions remain under-diagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily collectible data has several important implications towards…
Navigation and positioning systems dependent on both the operating environment and the behaviour of the host vehicle or user. The environment determines the type and quality of radio signals available for positioning and the behaviour can…
In this article, we explore computer vision approaches to detect abnormal head pose during e-learning sessions and we introduce a study on the effects of mobile phone usage during these sessions. We utilize behavioral data collected from…
Quantification of human attention is key to several tasks in mobile human-computer interaction (HCI), such as predicting user interruptibility, estimating noticeability of user interface content, or measuring user engagement. Previous works…
This work investigates how context should be taken into account when performing continuous authentication of a smartphone user based on touchscreen and accelerometer readings extracted from swipe gestures. The study is conducted on the…
Mental health conditions remain underdiagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily collectible data has several important implications for the…
No two people are alike. We usually ignore this diversity as we have the capability to adapt and, without noticing, become experts in interfaces that were probably misadjusted to begin with. This adaptation is not always at the user's…
This study provides evidence that personality can be reliably predicted from activity data collected through mobile phone sensors. Employing a set of well informed indicators calculable from accelerometer records and movement patterns, we…