Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Spatio-temporal evolution of interictal epileptic activity : a study with unaveraged multichannel MEG data in association with MRIs.

This thesis addresses issues relating to MEG modelling, analysis and interpretation of results. A source model employing current density distributions, namely Magnetic Field Tomography (MET), is used to obtain the MEG results. The first issue of concern refers to the registration of MEG data with structural MR images in an attempt to improve the localisation capability of MEG/MET. Simulations testing some spatial and tem poral aspects of the reconstruction capability of MET are also provided. A novel way of conducting MET studies in depth is suggested and implemented: the iterative use of a source space designed to cover deep situated structures on either side of the brain. The main bulk of this thesis is concerned with research into interictal epileptic activity as recorded by means of multichannel MEG system s and analysed using MET. The major aim is to investigate whether or not MET analysis of unaveraged MEG data (single epochs) is feasible in cases of pathophysiological signals and more specifically interictal signals from patients with epilepsy of a complex partial type. The investigation is undertaken against the "traditional" view of the impropriety and absurdity of using single epoch records in the MEG analysis due to noise dominance; we provide evidence that analysis of single, unaveraged epileptic spikes is actually feasible: we demonstrate spatio-temporal coherence in the MET results of the various single interictal events and show that activity extracted from the "averaged event" is made up of activity contributions which occur intermittently and at variable latencies. Our statements are drawn from the study of both superficial and deep activity

Towards Evidence Based M-Health Application Design in Cancer Patient Healthy Lifestyle Interventions

Cancer is one of the most prevalent diseases in Europe and the world. Significant correlations between dietary habits and cancer incidence and mortality have been confirmed by the literature. Physical activity habits are also directly implicated in the incidence of cancer. Lifestyle behaviour change may be benefited by using mobile technology to deliver health behaviour interventions. M-Health offers a promising cost-efficient approach to deliver en-masse interventions. Smartphone apps with constructs such as gamification and personalized have shown potential for helping individuals lose weight and maintain healthy lifestyle habits. However, evidence-based content and theory-based strategies have not been incorporated by those apps systematically yet. The aim of the current work is to put the foundations for a methodologically rigorous exploration of wellness/health intervention literature/app landscape towards detailed design specifications for connected health m-apps. In this context, both the overall work plan is described as well as the details for the significant steps of application space and literature space review. Both strategies for research and initial outcomes of it are presented. The expected evidence based design process for patient centered health and wellness interventions is going to be the primary input in the implementation process of upcoming patient centered health/wellness m-health interventions.ENJECT COST-STSM-ECOST-STSM-TD1405-220216-07045

A review on brain computer interfaces: contemporary achievements and future goals towards movement restoration

Restoration of motor functions of patients with loss of mobility constitutes a yet unsolved medical problem, but also one of the most prominent research areas of neurosciences. Among suggested solutions, Brain Computer Interfaces have received much attention. BCI systems use electric, magnetic or metabolic brain signals to allow for control of external devices, such as wheelchairs, computers or neuroprosthetics, by disabled patients. Clinical applications includespinal cord injury, cerebrovascular accident rehabilitation, Amyotrophic Lateral Sclerosis patients. Various BCI systems are under re­search, facilitated by numerous measurement techniques including EEG, fMRI, MEG, nIRS and ECoG, each with its own advantages and disadvantages.Current research effort focuses on brain signal identification and extraction. Virtual Reality environments are also deployed for patient training. Wheelchair or robotic arm control has showed up as the first step towards actual mobility restoration. The next era of BCI research is envisaged to lie along the transmission of brain signals to systems that will control and restore movement of disabled patients via mechanical appendixes or directly to the muscle system by neurosurgical means

A proposed framework of an interactive semi-virtual environment for enhanced education of children with autism spectrum disorders

Education of people with special needs has recently been considered as a key element in the field of medical education. Recent development in the area of information and communication technologies may enable development of collaborative interactive environments which facilitate early stage education and provide specialists with robust tools indicating the person's autism spectrum disorder level. Towards the goal of establishing an enhanced learning environment for children with autism this paper attempts to provide a framework of a semi-controlled real-world environment used for the daily education of an autistic person according to the scenarios selected by the specialists. The proposed framework employs both real-world objects and virtual environments equipped with humanoids able to provide emotional feedback and to demonstrate empathy. Potential examples and usage scenarios for such environments are also described

Using affective avatars and rich multimedia content for education of children with autism

Autism is a communication disorder that mandates early and continuous educational interventions on various levels like the everyday social, communication and reasoning skills. Computer-aided education has recently been considered as a likely intervention method for such cases, and therefore different systems have been proposed and developed worldwide. In more recent years, affective computing applications for the aforementioned interventions have also been proposed to shed light on this problem. In this paper, we examine the technological and educational needs of affective interventions for autistic persons. Enabling affective technologies are visited and a number of possible exploitation scenarios are illustrated. Emphasis is placed in covering the continuous and long term needs of autistic persons by unobtrusive and ubiquitous technologies with the engagement of an affective speaking avatar. A personalised prototype system facilitating these scenarios is described. In addition the feedback from educators for autistic persons is provided for the system in terms of its usefulness, efficiency and the envisaged reaction of the autistic persons, collected by means of an anonymous questionnaire. Results illustrate the clear potential of this effort in facilitating a very promising autism intervention

Semantic web, reusable learning objects, personal learning networks in health: key pieces for digital health literacy

The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients “new habits” of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person need

The Impact of Math Anxiety on Working Memory:A Cortical Activations and Cortical Functional Connectivity EEG Study

Mathematical anxiety (MA) is defined as a feeling of tension, apprehension, or fear that interferes with mathematical performance in various daily or academic situations. Cognitive consequences of MA have been studied a lot and revealed that MA seriously affects solving the complex problem due to the corruption of working memory (WM). The corruption of WM caused by MA is well documented in behavioral level, but the involved neurophysiological processes have not been properly addressed, despite the recent attention drawn on the neural basis of MA. This is the second part of our study that intents to investigate the neurophysiological aspects of MA and its implications to WM. In the first study, we saw how MA affects the early stages of numeric stimuli processes as the WM indirectly using event-related potentials in scalp electroencephalographic (EEG) signals. This paper goes one step further to investigate the cortical activations, obtained by the multichannel EEG recordings as well as the cortical functional networks in three WM tasks with increasing difficulty. Our results indicate that the high-math anxious (HMA) group activated more areas linked with negative emotions, pain, and fear, while the low-math anxious (LMA) group activated regions related to the encoding and retrieval processes of the WM. Functional connectivity analysis also reveals that the LMAs' brain has got more structured cortical networks with increased connectivity in areas related to WM, such as the frontal cortex, while the HMAs' brain has a more diffused and unstructured network, superimposing the evidence that the structured processes of WM are corrupted