10^th World Congress on Healthcare & Technologies July 17-18, 2017 Lisbon, Portugal

Beth Bock is a Professor in the department of Psychiatry & Human Behavior at Brown University Medical School and a Senior Research Scientist at the Centers for Behavioral and Preventive Medicine at the Miriam Hospital. Dr. Bock’s primary research interests are in developing and testing innovative interventions for addictions, particularly tobacco and alcohol use, and interventions to promote physical activity. She has been Principal Investigator on over 18 and co-investigator on 33 research studies funded by the US National Institutes of Health. Her most recent work includes 1) research examining the efficacy of physically active video games for exercise adoption and maintenance among adults, 2) developing and testing a mobile program for alcohol safety among community college students and 3) research testing the efficacy of an intervention for smoking cessation delivered through text messaging.

Statement of the Problem: Numerous interventions have been developed to be delivered through mobile technologies such as mobile phones. Few studies have considered that the relationship of the individual to their mobile phone may have an important impact on intervention acceptability and outcomes. There are existing surveys to assess this relationship, however they tend to focus on negative constructs such as “addiction” or “dependence”. Since mobile technologies can be beneficial (e.g., health tracking, disease management, work productivity), there is a need for a more balanced instrument that reflects both these positive and negative aspects. This research developed and validated the Mobile Phone Affinity Scale (MPAS). rnMethodology: Participants (n=1058, mean age = 32.5 years + 10.3; 50% female) were recruited in a national (USA) sample using Amazon Mechanical Turk to complete the MPAS survey along with surveys assessing demographic data, anxiety, depressive symptoms and resilience. Confirmatory factor analyses examined factor loadings and sub-structures within the instrument. rnFindings: Analyses produced a final 6-factor model that fit well (RMSEA=0.059, CFI=0.941, TLI=0.931, SRMR-0.042) consisting of 24 items measuring: Connectedness, Productivity, Empowerment/Safety, Anxious attachment, Addiction, and Continuous use. Subscales demonstrated strong internal consistency (coefficient alpha range = 0.76 to 0.88, M=0.83), and high item factor loadings (range=0.57 to 0.87, M=0.75). Analyses demonstrated support for the individuals subscales. Attachment and Addiction subscales correlated significantly and positively with symptoms of depression and anxiety and negatively with resilience, while Productivity was positively correlated with resilience. rnConclusion & Significance: The MPAS is a reliable, valid assessment of both positive and negative characteristics associated with the individual’s relationship to their mobile phone. Mobile phone affinity may have an important impact on the efficacy and effectiveness of mobile health interventions. Research is needed to assess the predictive ability of the MPAS within health behavior change interventions delivered through the mobile phone. rn

Andrea Silvello has over 15 years of experience in business & strategy consulting in multinationals like BCG and Bain & Company. He is founder of Business Support (a business consulting firm) and 2 insurtech startups: Neosurance and Digital Tech. He is also a columnist at The Indian Economist - online journal on business & economics, policy, politics and culture & society, guest contributor at Insurance Thought Leadership, InsurTechNews and Fùture Inese. He is 50insurtech influencer according to insurtechnews.com and top fintech influencer in Italy according to letstalkpayments.com.

The health insurance sector is getting a considerable amount of attention all around the world and in particular in developed countries. This is partly because of the ever growing costs related to certain health issues like ageing and chronic disease and, on the other hand, due to the reshaping of Public Welfare. The common factor at an international level is that the Insurers are trying to move from a simple “Payer role” to become a reference point (a “Player”) for all the health-related needs of their customers. In light of the above, Health telematics presents great potential for the insurer. Such potential should be harnessed in a profitable way by targeting less risky clients and presenting them with an improved, better-priced value proposition. For this to happen, Insurance Companies will have to seek partners from both the technological innovation sphere and medical providers, keeping in mind that its role in the health system is changing from “payer” to “pivot”. The trend is now clear as Companies are becoming more of a 360° health “counsellor” that assists the insured in taking the best decisions based on digital solutions. There are five main value creation levers to take into consideration: 1) Risk selection, enhancing the underwriting phase with a temporary monitoring based on dedicated devices; 2) Loyalty and behaviour modification programs, leading the client toward risk free behaviour; 3) Value added services, developing client tailored ancillary services that allow the Insurer to play as an omni-channel medical concierge; 4) Loss control, developing a broad approach to mitigate claims; 5) Risk based pricing, developing insurance policies with pricing linked to client behaviours. \r\nThe winning insurance value propositions will that which is able to propose to its customer’s insurance components together with “e/m health” modular services made available in a single complete UX accessible via mobile app: wellness, medical network access and medical services. \r\n

Tatiana Egorovna Popova is a neurologist and professor in the Department of neurology and psychiatry at the North-Eastern Federal University in Yakutsk. Scientific interest is devoted to the study of demyelinating diseases, epilepsy, neurodegenerative diseases. Tatyana Popova has made a significant contribution to the improvement of the diagnosis of sensory predominant chronic polyneuropathy on an outpatient care setting.

Motor disturbances and coordination disorders take a predominant place among the causes of restriction of patients’ vital activity chronic peripheral polyneuropathies, including sensory predominant chronic inflammatory demyelinating polyneuropathy (SP-CIDP). A leading symptom of motor SP-CIDP disorders is sensory ataxia, which is displayed by instability strengthening at eyes close position. Due to various sensitive systems (vestibular, proprioceptive and visual) brain receives the information about the process deviation from the vertical. Stabilometry is the most exact method, allowing making an assessment of body balance, to investigate quality of balance function, to study the contribution of various systems to maintenance of vertical position: vestibular mechanisms of deduction of balance and motor activity, function of proprioceptive system, visual evaluator and other systems of organism expressly or by implication influencing on postural reaction. \r\nResearch Aim: To estimate expressiveness of sensory ataxia in patients with sensory predominant chronic inflammatory demyelinating polyneuropathy in two regions of the Russian Federation: Republic of Sakha (Yakutia) and Krasnoyarsk region. \r\nMaterials and Methods: A group of healthy volunteers (24 people, median age 33 [23.5; 47] years) and patients with SP-CIDP from Republic of Sakha (Yakutia) (42 people, median age 43 [30; 48] years) and Krasnoyarsk region (87 people, median age 28 [22; 35] years). Diagnostics methods: Neurological examination and stabilometry had been conducted in all patients. \r\nResults: The results of stabilometry in patients with SP-CIDP have revealed area expansion of pressure centre in phases “eyes open” and “eyes close” with deflection the pressure center forward by anteropulsion type among patients with SP-CIDP from Republic of Sakha (Yakutia). Also in the Yakut group has been noted to have severer clinical course in comparison with inhabitants of Krasnoyarsk region. \r\nConclusion: The method of computer stabilometry allows estimating objectively presence and degree of manifestation of sensitive ataxia in patients with SP-CIDP. \r\n

Alexey Alexeyevich Tappakhov is a neurologist and postgraduate student in the Department of neurology and psychiatry at the North-Eastern Federal University in Yakutsk. Scientific interest is devoted to the study of neurodegenerative diseases and movement disorders. Alexey Tappakhov study of epidemiologic, genetic and clinical features of Parkinson’s disease in the Sakha (Yakutia) Republic. He is looking for reliable neuroimaging, neurophysiological biomarkers of Parkinson\'s disease.

Postural balance is the ability to stand upright and perform motor acts without jiggle and falls. It enables the integration of information in the central nervous system received from the visual, vestibular and proprioceptive analyzers. Violations of postural functions are one of the cardinal symptoms of Parkinson\'s disease (PD) - a chronic brain disease characterized by degeneration of the substantia nigra in the midbrain. Postural disorders are one of the most negative factors of PD. It causes a loss of the patient\'s independence, increases the risk of trauma and significantly increases the degree of disability. In addition to falling postural disorders are characterized by changes in muscle tone, leading to the development of flexion postures (\"supplicant posture\"), in severe cases, may develop prosternation - pronounced tilt torso forward. Stabilometry is one of the highly informative methods of studying postural functions. The purpose of the research is to assess the degree of postural disorders in patients with PD. Material and methods: we have examined 30 patients with PD (average age – 65.97±8,33 years) and 30 volunteers (average age – 62.5 ± 6.95 years). Stabilometry was carried all surveyed persons. We calculated the average position of the center of pressure (CP) in the frontal and sagittal plane the velocity of CP, area of statokineziogramm and quotient of Romberg. It was revealed that in PD significantly increases area of statokineziogramm and velocity of CP. Significant differences between the other parameters had not been found. Thus, in patients with PD were found evidence of moderate postural disorders. These results are likely to be related to the study in the on-period when symptoms of PD (slowness of movement and muscular rigidity) minimally. \r\nConclusion: Stabilometry allows to objectively identifying postural disorders in patients with PD. \r\n

Sang Hyun Jo has his expertise in studying a mobile healthcare service. He has been investigating what people intend to use the service and differences by ages and countries. Nowadays, he has tried to find out the possibilities of mobile healthcare services as a tool for preventive healthcare based on his previous work (Lee, Han and Jo, 2017).

The old people after retirement have more chronic diseases and they are getting susceptible to diseases. These factors make them to concentrate on health management (Quality Improvement in Healthcare) and they want to save the health cost (Saving cost) (Slingerland et al. 2007). On the contrary, the young people rarely have time to see health-related professionals in order to manage their health, so they get interested in mHealth services with the feature of non-limitations of space and time (pwc 2012). This paper will verify the following hypothesis. People who have regular health check-up, do regular exercise, and take vitamin/supplements for health management will be interested in some characteristics of mHealth services like quality improvement in healthcare, non-limitation in spatial/temporal coverage, and saving cost moderating by disease experiences from oneself, family and acquaintance (Rice 2006). Then, people with many disease experiences will put value on the usefulness of the services providing quality improvement to manage their health (Xue et al. 2012; Lisban et al. 2009), no spatial and temporal limitation to have health information and medical services (Yoon & Kim 2007; Ybarra & Suman 2008), saving cost when they have health information or they consume medical services through mHealth services (Pagani 2004; Sweeney and Soutar 2001). In addition, this study will take a look that privacy would affect the intention to use the mHealth services. mHealth services are provide through mobile devices connecting to the network so that people would worry about leaking their personal information (Yang et al. 2005). This study will show the factors and differences of adoption to the mHealth services in two different age groups.

Guram Beraia is a third year student of Tbilisi State Medical University on MD faculty. He is doing a research in oscillatory hemodynamics. New approach has a different way of focusing about altering blood flow and explains the reason of resistive factors in arterial circulation, indicates the reason for separation of venous and lymphatic circulations. For the advanced views he is awarded with the gold medal in I-SWEEEP 2012, Houston, USA. Diploma for attendance in EU contest for young inventors Prague, Czech Republic 2013 and European congress of Radiology 2015. He took part in health care summit London, 2016. His works are openly published in different journals.

Purpose of the Study: Is to identify the reason for the formation of the resistive factors in blood flow: Inertial flow and turbulence in large arteries and increasing viscosity in the venous blood. \r\nMethods and Materials: Blood flow velocities were studied in the different sites of the large vessels in 35 normal adults (15 men 20 women, age 21 - 49 years) with the use of Magnetic Resonance Angiography. Blood radiodensity (HU) was measured by the CT scanner. Blood flow pulsatility, resistivity indexes were carried out with the Duplex US. \r\nResults: Resistive and pulsatility indexes for the ascending aorta are 0.96±0.07 and 3.14.±1.7, abdominal aorta 0.91±0.07 and 2.7±1.3, carotid artery 0.74±0.07 and 2.04±0.53, pulmonary trunk 0.74±0.11 and 1.49±0.37, inferior vena cava 0.32±0.21 and 0.69±0.37. Blood radiodensity (in HU) in the ascending aorta is 57.3±3.5, distal thoracic aorta 25.7±3.1, inferior vena cava 59.3±3.3. Pulsation of the peak velocity is expressed at the external wall of the isthmus of aorta at the end of systole. \r\nConclusion: Heart energy is stored in the elastic deformation of the blood cells and arterial walls, in kinetic energy of the blood flow entropy of the system. Inertial blood flow due to the frequency dispersion in the arteries, transforms to the flow with the high fluidity in capillaries. Gibbs free energy increases, enabling spontaneous chemical reaction to proceed across the cell membrane. Process is altered in the venous blood. Changes in resistance express transformation of the energy in the substance. \r\n

John-Jules Ch. Meyer studied Mathematics with Computer Science and Digital Signal Processing at Leyden University. He obtained his Ph.D. from the Vrije Universiteit in Amsterdam on a subject in theoretical computer science. Since 1993 he has been a full professor of computer science, and artificial intelligence in particular, at Utrecht University. At the moment he is heading the Artificial Intelligence Division within the Department of Information and Computing Sciences and is programme leader of the AI Master of the UU. Currently he is also the CSO of the Alan Turing Institute Almere, which specializes in multi-disciplinary research for the health sciences, and the CEO of Companion Diagnostics ltd. as a part of Emotional Brain ltd. He has over 500 peer-reviewed publications in international journals and conference proceedings. In 2005 he was appointed as a Fellow of the European Coordinating Committee for Artificial Intelligence.

Artificial Intelligence (AI) is becoming more and more ubiquitous, and AI also invades health care and related fields ever more. And I believe this is a good thing. Primarily inspired by work we have done at the Alan Turing Institute Almere (ATIA) and Utrecht University (UU), in this invited talk I’ll review a number of applications of AI in health care and medicine. I’ll talk about advanced diagnostic techniques based on machine learning, modeling techniques and also artificial companions to assist with the care of patients in a hospital or home setting. These companions are able to monitor the behavior of patients, help them remind of taking medication, but also can have conversations with them giving them the feeling that they are cared for. This is important in times where health care is economized upon like we face in The Netherlands. Moreover, so-called serious games can be used to train health care professionals. In Utrecht we have worked on the personalization of this type of games involving automatic adaptation to knowledge and skills of the user / trainee. I also speak on the work we have done in Utrecht on emotion modeling, a relatively new subject in AI. By studying psychological literature we have extracted logical models of various aspects of emotions, in particular triggering / appraisal of emotions. I’ll review what we have done in the past decade or so on logics of emotions. The aim is to put these formal models at work in systems where (emotional) software agents steering virtual characters can render these more believable. I believe that these models can also increase the efficacy of the above-mentioned companions in human-robot interactions.

Striking advances in modern computer power, broadband communication and digital sensor technologies have led to an unprecedented flood of health and biomedical data in our surrounding. Handling and processing this big data pose a serious problem for healthcare systems designers and managers. \r\nThe most frequently used is the classical data based computational approach. Although it is generally recognized that human-like cognitive or information based processing is much more suitable for big data managing tasks, the lack of a proper definition of what is information leads to a persistent misuse and misappropriation of big data processing enterprises. \r\nTo meet the requirement for a fitting information definition, I have proposed (a couple of years ago) a new definition of information derived from Kolmogorov’s notion of complexity. In its last and upgraded version, my definition sounds like this: “Information is a linguistic description of structures observable in a given data set”. \r\nWhat follows immediately from this definition is that information is a complex notion composed of Physical and Semantic information staying for Real and Imagery components of the expression. What follows from this is that semantic information (the crucial player in data analysis and meaningful data processing) has to be expressed as a text hierarchy, a story, a narrative. And meaningful data processing turns out to be a text processing paradigm. \r\nWhat follows from this is that semantic information (the referenced knowledge base of the system) cannot be learned autonomously and must be always provided (granted, donated) from the outside. A whole package of unusual innovations stems from this new information definition (which strikingly separates information from data). But abstract space restrictions preclude further exploration of this very important data-information challenge.\r\n