Monitoring and detection of agitation in dementia: towards real-time and big-data solutions

The changing demographic profile of the population has potentially challenging social, geopolitical, and financial consequences for individuals, families, the wider society, and governments globally. The demographic change will result in a rapidly growing elderly population with healthcare implications which importantly include Alzheimer type conditions (a leading cause of dementia). Dementia requires long term care to manage the negative behavioral symptoms which are primarily exhibited in terms of agitation and aggression as the condition develops. This paper considers the nature of dementia along with the issues and challenges implicit in its management. The Behavioral and Psychological Symptoms of Dementia (BPSD) are introduced with factors (precursors) to the onset of agitation and aggression. Independent living is considered, health monitoring and implementation in context-aware decision-support systems is discussed with consideration of data analytics. Implicit in health monitoring are technical and ethical constraints, we briefly consider these constraints with the ability to generalize to a range of medical conditions. We postulate that health monitoring offers exciting potential opportunities however the challenges lie in the effective realization of independent assisted living while meeting the ethical challenges, achieving this remains an open research question remains.Peer ReviewedPostprint (author's final draft

Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.Comment: ACM Multimedia 2014, November 3-7, 2014, Orlando, Florida, US

The development of a rich multimedia training environment for crisis management: using emotional affect to enhance learning

PANDORA is an EU FP7-funded project developing a novel training and learning environment for Gold Commanders, individuals who carry executive responsibility for the services and facilities identified as strategically critical e.g. Police, Fire, in crisis management strategic planning situations. A key part of the work for this project is considering the emotional and behavioural state of the trainees, and the creation of more realistic, and thereby stressful, representations of multimedia information to impact on the decision-making of those trainees. Existing training models are predominantly paper-based, table-top exercises, which require an exercise of imagination on the part of the trainees to consider not only the various aspects of a crisis situation but also the impacts of interventions, and remediating actions in the event of the failure of an intervention. However, existing computing models and tools are focused on supporting tactical and operational activities in crisis management, not strategic. Therefore, the PANDORA system will provide a rich multimedia information environment, to provide trainees with the detailed information they require to develop strategic plans to deal with a crisis scenario, and will then provide information on the impacts of the implementation of those plans and provide the opportunity for the trainees to revise and remediate those plans. Since this activity is invariably multi-agency, the training environment must support group-based strategic planning activities and trainees will occupy specific roles within the crisis scenario. The system will also provide a range of non-playing characters (NPC) representing domain experts, high-level controllers (e.g. politicians, ministers), low-level controllers (tactical and operational commanders), and missing trainee roles, to ensure a fully populated scenario can be realised in each instantiation. Within the environment, the emotional and behavioural state of the trainees will be monitored, and interventions, in the form of environmental information controls and mechanisms impacting on the stress levels and decisionmaking capabilities of the trainees, will be used to personalise the training environment. This approach enables a richer and more realistic representation of the crisis scenario to be enacted, leading to better strategic plans and providing trainees with structured feedback on their performance under stress

Naturalistic monitoring of the affect-heart rate relationship: A Day Reconstruction Study

Objective: Prospective studies have linked both negative affective states and trait neuroticism with hypertension, cardiovascular disease, and mortality. However, identifying how fluctuations in cardiovascular activity in day-to-day settings are related to changes in affect and stable personality characteristics has remained a methodological and logistical challenge. Design - In the present study, we tested the association between affect, affect variability, personality and heart rate (HR) in daily life. Measures: We utilized an online day reconstruction survey to produce a continuous account of affect, interaction, and activity patterns during waking hours. Ambulatory HR was assessed during the same period. Consumption, activity, and baseline physiological characteristics were assessed in order to isolate the relationships between affect, personality and heart rate. Results: Negative affect and variability in positive affect predicted an elevated ambulatory HR and tiredness a lower HR. Emotional stability was inversely related to HR, whereas agreeableness predicted a higher HR. Baseline resting HR was unrelated to either affect or personality. Conclusion: The results suggest that both state and trait factors implicated in negative affectivity may be risk factors for increased cardiovascular reactivity in everyday life. Combining day reconstruction with psychophysiological and environmental monitoring is discussed as a minimally invasive method with promising interdisciplinary relevance.heart rate, negative affect, affect variability, Big Five, Day Reconstruction Method

Engineering Advanced Training Environment for Crisis Management: The Pandora Project

The paper describes the technical framework of a near real-life training environment for learning activities suitable for training in crisis scenarios. The underlying architecture features a design that makes provision for a learning environment capable of training collaborative, as well as independent, decision making skills among crisis managers in potential crisis situations. Modelling the training scenarios takes into consideration both the pragmatic nature of responding to crisis, as well as the human behavioural factors involved in dealing with situations of chaos and uncertainty. This work is part of ongoing research on the Pandora1 project, which aims to provide a near-real training environment at affordable cost

Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial

The multitasking framework: the effects of increasing workload on acute psychobiological stress reactivity

A variety of techniques exist for eliciting acute psychological stress in the laboratory; however, they vary in terms of their ease of use, reliability to elicit consistent responses and the extent to which they represent the stressors encountered in everyday life. There is, therefore, a need to develop simple laboratory techniques that reliably elicit psychobiological stress reactivity that are representative of the types of stressors encountered in everyday life. The multitasking framework is a performance-based, cognitively demanding stressor, representative of environments where individuals are required to attend and respond to several different stimuli simultaneously with varying levels of workload. Psychological (mood and perceived workload) and physiological (heart rate and blood pressure) stress reactivity was observed in response to a 15-min period of multitasking at different levels of workload intensity in a sample of 20 healthy participants. Multitasking stress elicited increases in heart rate and blood pressure, and increased workload intensity elicited dose–response increases in levels of perceived workload and mood. As individuals rarely attend to single tasks in real life, the multitasking framework provides an alternative technique for modelling acute stress and workload in the laboratory