Supporting Self-Regulation of Children with ADHD Using Wearables: Tensions and Design Challenges

The design of wearable applications supporting children with Attention Deficit Hyperactivity Disorders (ADHD) requires a deep understanding not only of what is possible from a clinical standpoint but also how the children might understand and orient towards wearable technologies, such as a smartwatch. Through a series of participatory design workshops with children with ADHD and their caregivers, we identified tensions and challenges in designing wearable applications supporting the self-regulation of children with ADHD. In this paper, we describe the specific challenges of smartwatches for this population, the balance between self-regulation and co-regulation, and tensions when receiving notifications on a smartwatch in various contexts. These results indicate key considerations—from both the child and caregiver viewpoints—for designing technological interventions supporting children with ADHD

A contribution to the incorporation of sociability and creativity skills to computers and robots

This dissertation contains the research and work completed by the PhD candidate on the incorporation of sociability and creativity skills to computers and robots. Both skills can be directly related with empathy, which is the ability to understand and share the feelings of another. In this form, this research can be contextualized in the framework of recent developments towards the achievement of empathy machines. The first challenge at hands refers to designing pioneering techniques based on the use of social robots to improve user experience interacting with them. In particular, research focus is on eliminating or minimizing pain and anxiety as well as loneliness and stress of long-term hospitalized child patients. This challenge is approached by developing a cloud-based robotics architecture to effectively develop complex tasks related to hospitalized children assistance. More specifically, a multiagent learning system is introduced based on a combination of machine learning and cloud computing using low-cost robots (Innvo labs's Pleo rb). Moreover, a wireless communication system is also developed for the Pleo robot in order to help the health professional who conducts therapy with the child, monitoring, understanding, and controlling Pleo behavior at any moment. As a second challenge, a new formulation of the concept of creativity is proposed in order to empower computers with. Based on previous well established theories from Boden and Wiggins, this thesis redefines the formal mechanism of exploratory and transformational creativity in a way which facilitates the computational implementation of these mechanisms in Creativity Support Systems. The proposed formalization is applied and validated on two real cases: the first, about chocolate designing, in which a novel and flavorful combination of chocolate and fruit is generated. The second case is about the composition of a single voice tune of reel using ABC notation.Postprint (published version

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months

The Oneiric Reality of Electronic Scents

This paper investigates the ‘oneiric’ dimension of scent, by suggesting a new design process that can be worn as a fashion accessory or integrated in textile technologies, to subtly alter reality and go beyond our senses. It fuses wearable ‘electronic scent’ delivery systems with pioneering biotechnologies as a ground-breaking ‘science fashion’ enabler. The purpose is to enhance wellbeing by reaching a day‐dream state of being through the sense of smell. The sense of smell (or olfaction) is a chemical sense and part of the limbic system which regulates emotion and memory within the brain. The power of scent makes content extremely compelling by offering a heightened sense of reality which is intensified by emotions such as joy, anger and fear. Scent helps us appreciate all the senses as we embark on a sensory journey unlike any other; it enhances mood, keeps us in the moment, diverts us from distractions, reduces boredom and encourages creativity. This paper highlights the importance of smell, the forgotten sense, and also identifies how we as humans have grown to underuse our senses. It endeavours to show how the reinvention of our sensory faculties is possible through advances in biotechnology. It introduces the new ‘data senses’ as a wearable sensory platform that triggers and fine tunes the senses with fragrances. It puts forward a new design process that is currently being developed in clothing elements, jewellery and textile technologies, offering a new method to deliver scent electronically and intelligently in fashion and everyday consumer products. It creates a personal ‘scent wave’, around the wearer, to allow the mind to wander, to give a deeper sense of life or ‘lived reality’ (verses fantasy), a new found satisfaction and confidence, and to reach new heights of creativity. By combining biology with wearable technologies, we propose a biotechnological solution that can be translated into sensory fashion elements. This is a new trend in 21st century ‘data sensing’, based on holographic biosensors that sense the human condition, aromachology (the science of the effect of fragrance and behaviour), colour-therapy, and smart polymer science. The use of biosensors in the world of fashion and textiles, enables us to act on visual cues or detect scent signals and rising stress levels, allowing immediate information to hand. An ‘oneiric’ mood is triggered by a spectrum of scents which is encased in a micro-computerised ‘scent‐cell’ and integrated into clothing elements or jewellery. When we inhale an unexpected scent, it takes us by surprise; the power of fragrance fills us with pleasurable ripples of multi‐sensations and dream‐like qualities. The aromas create a near trance‐like experience that induces a daydream state of (immediate) satisfaction, or a ‘revived reality’ in our personal scent bubble of reality. The products and jewellery items were copyrighted and designed by Slim Barrett and the technology input was from EG Technology and Epigem