Advances in biofeedback and neurofeedback studies on smoking.

Smoking is a leading cause of morbidity and premature death constituting a global health challenge. Although, pharmacological and behavioral approaches comprise the mainstay of smoking cessation interventions, the efficacy and safety of pharmacotherapy is not demonstrated for some populations. Non-pharmacological approaches, such as biofeedback (BF) and neurofeedback (NF) could facilitate self-regulation of predisposing factors of relapse such as craving and stress. The current review aims to aggregate the existing evidence regarding the effects of BF and NF training on smokers. Relevant studies were identified through searching in Scopus, PubMed and Cochrane Library, and through hand-searching the references of screened articles. Peer-reviewed controlled and uncontrolled studies, where BF and/or NF training was administered, were included and evaluated according to PICOS framework. Narrative qualitative synthesis of ten eligible studies was performed, aggregated into three categories according to training provided. BF outcomes seem to be affected by smoking behavior prior to training; individualized EEG NF training holds promise for modulating craving-related response while minimizing the required number of sessions. Real-time fMRI NF studies concluded that nicotine-dependent individuals could modulate craving-related brain responses, while mixed results were revealed regarding smokers' ability to modulate brain responses related to resistance towards the urge to smoke. BF and NF training seem to facilitate modulation of autonomous and/or central nervous system activity while also transferring this learned self-regulation to behavioral outcomes. BF and NF training should a) address remaining issues on specificity and scientific validity, b) target diverse demographics, and c) produce robust reproducible methodologies and clinical guidelines for relevant health care providers, in order to be considered as viable complementary tools to standard smoking cessation care.

The Reference Site Collaborative Network of the European Innovation Partnership on Active and Healthy Ageing.

Seventy four Reference Sites of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) have been recognised by the European Commission in 2016 for their commitment to excellence in investing and scaling up innovative solutions for active and healthy ageing. The Reference Site Collaborative Network (RSCN) brings together the EIP on AHA Reference Sites awarded by the European Commission, and Candidate Reference Sites into a single forum. The overarching goals are to promote cooperation, share and transfer good practice and solutions in the development and scaling up of health and care strategies, policies and service delivery models, while at the same time supporting the action groups in their work. The RSCN aspires to be recognized by the EU Commission as the principal forum and authority representing all EIP on AHA Reference Sites. The RSCN will contribute to achieve the goals of the EIP on AHA by improving health and care outcomes for citizens across Europe, and the development of sustainable economic growth and the creation of jobs.

A review of physical and cognitive interventions in aging.

Maintaining a healthy brain is a critical factor for the quality of life of elderly individuals and the preservation of their independence. Challenging aging brains through cognitive training and physical exercises has shown to be effective against age-related cognitive decline and disease. But how effective are such training interventions? What is the optimal combination/strategy? Is there enough evidence from neuropsychological observations, animal studies, as well as, structural and functional neuroimaging investigations to interpret the underlying neurobiological mechanisms responsible for the observed neuroplasticity of the aging brain? This piece of work summarizes recent findings toward these questions, but also highlights the role of functional brain connectivity work, an emerging discipline for future research in healthy aging and the study of the underlying mechanisms across the life span. The ultimate aim is to conclude on recommended multimodal training, in light of contemporary trends in the design of exergaming interventions. The latter issue is discussed in conjunction with building up neuroscientific knowledge and envisaged future research challenges in mapping, understanding and training the aging brain.

Social Media for the Promotion of Holistic Self-Participatory Care: An Evidence Based Approach. Contribution of the IMIA Social Media Working Group.

OBJECTIVES: As health information is becoming increasingly accessible, social media offers ample opportunities to track, be informed, share and promote health. These authors explore how social media and holistic care may work together; more specifically however, our objective is to document, from different perspectives, how social networks have impacted, supported and helped sustain holistic self-participatory care. METHODS: A literature review was performed to investigate the use of social media for promoting health in general and complementary alternative care. We also explore a case study of an intervention for improving the health of Greek senior citizens through digital and other means. RESULTS: The Health Belief Model provides a framework for assessing the benefits of social media interventions in promoting comprehensive participatory self-care. Some interventions are particularly effective when integrating social media with real-world encounters. Yet not all social media tools are evidence-based and efficacious. Interestingly, social media is also used to elicit patient ratings of treatments (e.g., for depression), often demonstrating the effectiveness of complementary treatments, such as yoga and mindfulness meditation. CONCLUSIONS: To facilitate the use of social media for the promotion of complementary alternative medicine through self-quantification, social connectedness and sharing of experiences, exploration of concrete and abstract ideas are presented here within. The main mechanisms by which social support may help improve health - emotional support, an ability to share experiences, and non-hierarchal roles, emphasizing reciprocity in giving and receiving support - are integral to social media and provide great hope for its effective use.

Experience in the use of social media in medical and health education. Contribution of the IMIA Social Media Working Group.

OBJECTIVES: Social media are online tools that allow collaboration and community building. Succinctly, they can be described as applications where "users add value". This paper aims to show how five educators have used social media tools in medical and health education to attempt to add value to the education they provide. METHODS: We conducted a review of the literature about the use of social media tools in medical and health education. Each of the authors reported on their use of social media in their educational projects and collaborated on a discussion of the advantages and disadvantages of this approach to delivering educational projects. RESULTS: We found little empirical evidence to support the use of social media tools in medical and health education. Social media are, however, a rapidly evolving range of tools, websites and online experiences and it is likely that the topic is too broad to draw definitive conclusions from any particular study. As practitioners in the use of social media, we have recognised how difficult it is to create evidence of effectiveness and have therefore presented only our anecdotal opinions based on our personal experiences of using social media in our educational projects. CONCLUSION: The authors feel confident in recommending that other educators use social media in their educational projects. Social media appear to have unique advantages over non-social educational tools. The learning experience appears to be enhanced by the ability of students to virtually build connections, make friends and find mentors. Creating a scientific analysis of why these connections enhance learning is difficult, but anecdotal and preliminary survey evidence appears to be positive and our experience reflects the hypothesis that learning is, at heart, a social activity.

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.

Are females more responsive to emotional stimuli? A neurophysiological study across arousal and valence dimensions.

Men and women seem to process emotions and react to them differently. Yet, few neurophysiological studies have systematically investigated gender differences in emotional processing. Here, we studied gender differences using Event Related Potentials (ERPs) and Skin Conductance Responses (SCR) recorded from participants who passively viewed emotional pictures selected from the International Affective Picture System (IAPS). The arousal and valence dimension of the stimuli were manipulated orthogonally. The peak amplitude and peak latency of ERP components and SCR were analyzed separately, and the scalp topographies of significant ERP differences were documented. Females responded with enhanced negative components (N100 and N200), in comparison to males, especially to the unpleasant visual stimuli, whereas both genders responded faster to high arousing or unpleasant stimuli. Scalp topographies revealed more pronounced gender differences on central and left hemisphere areas. Our results suggest a difference in the way emotional stimuli are processed by genders: unpleasant and high arousing stimuli evoke greater ERP amplitudes in women relatively to men. It also seems that unpleasant or high arousing stimuli are temporally prioritized during visual processing by both genders.

Revisiting Information Technology tools serving authorship and editorship: a case-guided tutorial to statistical analysis and plagiarism detection.

With the number of scientific papers published in journals, conference proceedings, and international literature ever increasing, authors and reviewers are not only facilitated with an abundance of information, but unfortunately continuously confronted with risks associated with the erroneous copy of another's material. In parallel, Information Communication Technology (ICT) tools provide to researchers novel and continuously more effective ways to analyze and present their work. Software tools regarding statistical analysis offer scientists the chance to validate their work and enhance the quality of published papers. Moreover, from the reviewers and the editor's perspective, it is now possible to ensure the (text-content) originality of a scientific article with automated software tools for plagiarism detection. In this paper, we provide a step-bystep demonstration of two categories of tools, namely, statistical analysis and plagiarism detection. The aim is not to come up with a specific tool recommendation, but rather to provide useful guidelines on the proper use and efficiency of either category of tools. In the context of this special issue, this paper offers a useful tutorial to specific problems concerned with scientific writing and review discourse. A specific neuroscience experimental case example is utilized to illustrate the young researcher's statistical analysis burden, while a test scenario is purpose-built using open access journal articles to exemplify the use and comparative outputs of seven plagiarism detection software pieces.

Biomedical real-time monitoring in restricted and safety-critical environments.

Biomedical signal monitoring can counteract the risk of human operator error due to inattention or fatigue in safetycritical and restrictive environments, such as in aviation, space, automobile and heavy industrial machinery operation. Real-time biomedical data acquisition is changing through advances in microelectronics fabrication, bio-MEMS and power micro-generators. Such data acquisition and processing systems are becoming increasingly miniaturised, flexible and pervasive, while data is being collected from inside the human body as well as around it. In this paper we review two related research projects exploiting this technological convergence, discuss its implications and suggest future innovation prospects through further similar cross-disciplinary synergies.

An e-learning platform for aerospace medicine.

The appeal of online education and distance learning as an educational alternative is ever increasing. To support and accommodate the over-specialized knowledge available by different experts, information technology can be employed to develop virtual distributed pools of autonomous specialized educational modules and provide the mechanisms for retrieving and sharing them. New educational standards such as SCORM and Healthcare LOM enhance this process of sharing by offering qualities like interoperability, accessibility, and reusability, so that learning material remains credible, up-to-date and tracks changes and developments of medical techniques and standards through time. Given that only a few e-learning courses exist in aerospace medicine the material of which may be exchanged among teachers, the aim of this paper is to illustrate the procedure of creating a SCORM compliant course that incorporates notions of recent advances in social web technologies. The course is in accordance with main educational and technological details and is specific to pulmonary disorders in aerospace medicine. As new educational trends place much emphasis in continuing medical education, the expansion of a general practitioner's knowledge in topics such as aviation and aerospace pulmonary disorders for crew and passengers becomes a societal requirement.

The therapeutic benefits of gravity in space and on earth.

The traditional scientific approach of investigating the role of a variable on a living organism is to remove it or the ability of the organism to sense it. Gravity is no exception. Access to space has made it possible for us to begin the exploration of how gravity has influenced our evolution, our genetic make-up and our physiology. Identifying the thresholds at which each body system perceives, how much, how often, how long the gravity stimulus is needed and in which direction should it be presented for maximum effectiveness, is fundamental knowledge required for using artificial gravity as a therapeutic or maintenance countermeasure treatment in exploration missions. Here on earth, although surrounded by gravity we are negligent in using gravity as it was intended, to maintain the level of health that is appropriate to living in 1G. These, changes in lifestyle or pathologies caused by various types of injury can benefit as well from artificial gravity in much the same way as we are now considering for astronauts in space.

Predicting missing values in a home care database using an adaptive uncertainty rule method.

OBJECTIVES: Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. METHODS: In this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. RESULTS: The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. CONCLUSIONS: It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

Mining association rules from clinical databases: an intelligent diagnostic process in healthcare.

Data mining is the process of discovering interesting knowledge, such as patterns, associations, changes, anomalies and significant structures, from large amounts of data stored in databases, data warehouses, or other information repositories. Mining Associations is one of the techniques involved in the process mentioned above and used in this paper. Association is the discovery of association relationships or correlations among a set of items. The algorithm that was implemented is a basic algorithm for mining association rules, known as a priori. In Healthcare, association rules are considered to be quite useful as they offer the possibility to conduct intelligent diagnosis and extract invaluable information and build important knowledge bases quickly and automatically. The problem of identifying new, unexpected and interesting patterns in medical databases in general, and diabetic data repositories in specific, is considered in this paper. We have applied the a priori algorithm to a database containing records of diabetic patients and attempted to extract association rules from the stored real parameters. The results indicate that the methodology followed may be of good value to the diagnostic procedure, especially when large data volumes are involved. The followed process and the implemented system offer an efficient and effective tool in the management of diabetes. Their clinical relevance and utility await the results of prospective clinical studies currently under investigation.

Magnetic field tomography of cortical and deep processes: examples of "real-time mapping" of averaged and single trial MEG signals.

Magnetic field tomography (MFT) provides 3-dimensional estimates of brain activity, from non-contact, non-invasive measurements of the magnetic field generated by coherent electrical activity in the brain. MFT analysis of averaged auditory "odd-ball" data show cortical and deep activation, presumably from the amygdala and hippocampus. These results are compared with MFT estimates obtained from a patient who had undergone lobectomy which removed these structures. The variability from subject to subject is confounded by variability between trials for the same subject; the relationship between the averaged and single trials is probed by bi-hemispheric simultaneous measurements performed under the same odd-ball paradigm and by MFT analysis of auditory evoked data and interictal epileptic activity.

MFT in complex partial epilepsy: spatio-temporal estimates of interictal activity.

Magnetic field tomography (MFT) displays three dimensional estimates of the distribution of the primary current density vector, Jp, as extracted from non-invasive, non-contact, magnetoencephalographic (MEG) measurements. MFT was used to study the spatiotemporal evolution of the interictal activity during single spike events of a patient with complex partial epilepsy. The sequences of events of the interictal spikes were analysed in sagittal sections, particularly at the depth of the temporal lobe. It appeared that the left-sided interictal spikes were usually initiated at the cortical level of the left temporal lobe, the activity then propagating to the left amygdaloid and hippocampal formation. However, some focal deep activity in this region was obviously initiated in the contralateral hemisphere.

Activation sequence of discrete brain areas during cognitive processes: results from magnetic field tomography.

Magnetic field tomography is a technique for extracting 3-dimensional estimates of current density in the brain, from non-contact, non-invasive measurements of the magnetic field generated by the brain. It allows visualisation of both cortical and subcortical focal activation patterns at millisecond intervals, and the relative time difference between active cortical areas. We have used this technique to study the activation history of discrete brain regions associated with the preparation for, initiation and inhibition of movement, and movement itself in a CNV paradigm. The strongest focal activities are found within well defined cortical regions, namely the auditory (A1), sensorimotor (SM1), medial parietal area (MPA) and anterior supplementary motor area (SMA). For the movement condition, activation history differs for the warning stimulus and the stimulus initiating movement.