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Person re-identification is a critical privacy breach in publicly shared healthcare data. We investigate the possibility of a new type of privacy threat on publicly shared privacy insensitive large scale wearable sensing data. In this…
Predicting an individual's aging trajectory is a central challenge in preventative medicine and bioinformatics. While machine learning models can predict chronological age from biomarkers, they often fail to capture the dynamic,…
Wearable devices with a wide range of sensors have contributed to the rise of the Quantified Self movement, where individuals log everything ranging from the number of steps they have taken, to their heart rate, to their sleeping patterns.…
The analysis of human motion as a clinical tool can bring many benefits such as the early detection of disease and the monitoring of recovery, so in turn helping people to lead independent lives. However, it is currently under used.…
The research on human activity recognition has provided novel solutions to many applications like healthcare, sports, and user profiling. Considering the complex nature of human activities, it is still challenging even after effective and…
The increased worldwide prevalence of obesity has sparked the interest of the scientific community towards tools that objectively and automatically monitor eating behavior. Despite the study of obesity being in the spotlight, such tools can…
Digital phenotyping enables continuous passive monitoring of behavior and physiology, offering a promising paradigm for early detection of psychotic relapse. In this work, we develop and systematically study two smartwatch-based frameworks…
We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from…
The unprecedented extension of the human lifespan necessitates a parallel evolution in how we quantify the quality of aging and its socioeconomic impact. Traditional metrics focusing on Healthspan (years free of disease) overlook the…
Nitrogen isotope analysis of bone collagen has been used to reconstruct the breastfeeding practices of archaeological human populations. However, weaning ages have been estimated subjectively because of a lack of both information on…
Demand for smartwatches has taken off in recent years with new models which can run independently from smartphones and provide more useful features, becoming first-class mobile platforms. One can access online banking or even make payments…
The human spine is a complex structure composed of 33 vertebrae. It holds the body and is important for leading a healthy life. The spine is vulnerable to age-related degenerations that can be identified through magnetic resonance imaging…
Simulating prospective magnetic resonance imaging (MRI) scans from a given individual brain image is challenging, as it requires accounting for canonical changes in aging and/or disease progression while also considering the individual…
The UK Biobank dataset follows over 500,000 volunteers and contains a diverse set of information related to societal outcomes. Among this vast collection, a large quantity of telemetry collected from wrist-worn accelerometers provides a…
The recent development of smartphone and wearable sensor technologies enable general public to carry self-tracking tasks more easily. Much work has been devoted to life data collection and visualisation to help people with better…
Understanding physiological responses during running is critical for performance optimization, tailored training prescriptions, and athlete health management. We introduce a comprehensive framework -- what we believe to be the first capable…
Wearable devices, such as smartwatches and head-mounted displays, are increasingly used for prolonged tasks like remote learning and work, but sustained interaction often leads to user fatigue, reducing efficiency and engagement. This study…
Rapid developments in streaming data technologies have enabled real-time monitoring of human activity that can deliver high-resolution data on health variables over trajectories or paths carved out by subjects as they conduct their daily…
Personalized Active Learner (PAL) is a wearable system for real-time, personalized, and context-aware health and cognition support. PAL's system consists of a wearable device, mobile app, cloud database, data visualization web app, and…
We investigate the use of musically structured, closed-loop vibration patterns as a passive biofeedback intervention for relaxation and sleep initiation. By encoding rhythmic meter structures into smartwatch vibrations and adapting their…