Related papers: Quantified-Self 2.0: Using Context-Aware Services …

Human cognitive performance is an underlying factor in most of our daily lives, and numerous factors influence cognitive performance. In this work, we investigate how changes in sleep quality influence cognitive performance, measured from a…

In this work we investigate intra-day patterns of activity on a population of 7,261 users of mobile health wearable devices and apps. We show that: (1) using intra-day step and sleep data recorded from passive trackers significantly…

The quality of sleep has a deep impact on people's physical and mental health. People with insufficient sleep are more likely to report physical and mental distress, activity limitation, anxiety, and pain. Moreover, in the past few years,…

Recommender Systems have not been explored to a great extent for improving health and subjective wellbeing. Recent advances in mobile technologies and user modelling present the opportunity for delivering such systems, however the key issue…

Human cognitive performance is critical to productivity, learning, and accident avoidance. Cognitive performance varies throughout each day and is in part driven by intrinsic, near 24-hour circadian rhythms. Prior research on the impact of…

The sedentary lifestyle increases individuals' risks of developing chronic diseases. To support individuals to be more physically active, we propose a mobile system, MotionShift, that presents users with step count data alongside contextual…

Social media enjoys a growing popularity as a platform to seek and share personal health information. For sleep studies using data from social media, most researchers focused on inferring sleep-related artifacts from self-reported anecdotal…

Users install many apps on their smartphones, raising issues related to information overload for users and resource management for devices. Moreover, the recent increase in the use of personal assistants has made mobile devices even more…

Wearable devices offer detailed sleep-tracking data. However, whether this information enhances our understanding of sleep or simply quantifies already-known patterns remains unclear. This work explores the relationship between subjective…

We propose a model of the situational context of a person and show how it can be used to organize and, consequently, reason about massive streams of sensor data and annotations, as they can be collected from mobile devices, e.g.…

Sleep constitutes a key indicator of human health, performance, and quality of life. Sleep deprivation has long been related to the onset, development, and worsening of several mental and metabolic disorders, constituting an essential…

Sleep is critical to human function, mediating factors like memory, mood, energy, and alertness; therefore, it is commonly conjectured that a good night's sleep is important for job performance. However, both real-world sleep behavior and…

Wearable devices record physiological and behavioral signals that can improve health predictions. While foundation models are increasingly used for such predictions, they have been primarily applied to low-level sensor data, despite…

For improving e-health services, we propose a context-aware framework to monitor the activities of daily living of dependent persons. We define a strategy for generating long-term realistic scenarios and a framework containing an adaptive…

Smartphones enable understanding human behavior with activity recognition to support people's daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly…

We introduce a new dynamic model with the capability of recognizing both activities that an individual is performing as well as where that ndividual is located. Our model is novel in that it utilizes a dynamic graphical model to jointly…

Smartphone apps provide a vitally important opportunity for monitoring human mobility, human experience of ubiquitous information aids, and human activity in our increasingly well-instrumented spaces. As wireless data capabilities move…

Context-awareness in smart mobile applications is a growing area of study, because of it's intelligence in the applications. In order to build context-aware intelligent applications, mining contextual behavioral rules of individual…

In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her check-in records on a location-based…

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…