Comparison between Full Body Motion Recognition Camera Interaction and Hand Controllers Interaction used in Virtual Reality Exposure Therapy for Acrophobia.

Virtual Reality has already been proven as a useful supplementary treatment tool for anxiety disorders. However, no specific technological importance has been given so far on how to apply Virtual Reality with a way that properly stimulates the phobic stimulus and provide the necessary means for lifelike experience. Thanks to technological advancements, there is now a variety of hardware that can help enhance stronger emotions generated by Virtual Reality systems. This study aims to evaluate the feeling of presence during different hardware setups of Virtual Reality Exposure Therapy, and, particularly how the user's interaction with those setups can affects their sense of presence during the virtual simulation. An acrophobic virtual scenario is used as a case study by 20 phobic individuals and the Witmer-Singer presence questionnaire was used for presence evaluation by the users of the system. Statistical analysis on their answers revealed that the proposed full body Motion Recognition Cameras system generates a better feeling of presence compared to the Hand Controllers system. This is thanks to the Motion Recognition Cameras, which track and allow display of the user's entire body within the virtual environment. Thus, the users are enabled to interact and confront the anxiety-provoking stimulus as in real world. Further studies are recommended, in which the proposed system could be used in Virtual Reality Exposure Therapy trials with acrophobic patients and other anxiety disorders as well, since the proposed system can provide natural interaction in various simulated environments.

Personalized Virtual Reality Human-Computer Interaction for Psychiatric and Neurological Illnesses: A Dynamically Adaptive Virtual Reality Environment That Changes According to Real-Time Feedback From Electrophysiological Signal Responses.

Virtual reality (VR) constitutes an alternative, effective, and increasingly utilized treatment option for people suffering from psychiatric and neurological illnesses. However, the currently available VR simulations provide a predetermined simulative framework that does not take into account the unique personality traits of each individual; this could result in inaccurate, extreme, or unpredictable responses driven by patients who may be overly exposed and in an abrupt manner to the predetermined stimuli, or result in indifferent, almost non-existing, reactions when the stimuli do not affect the patients adequately and thus stronger stimuli are recommended. In this study, we present a VR system that can recognize the individual differences and readjust the VR scenarios during the simulation according to the treatment aims. To investigate and present this dynamically adaptive VR system we employ an Anxiety Disorder condition as a case study, namely arachnophobia. This system consists of distinct anxiety states, aiming to dynamically modify the VR environment in such a way that it can keep the individual within a controlled, and appropriate for the therapy needs, anxiety state, which will be called "desired states" for the study. This happens by adjusting the VR stimulus, in real-time, according to the electrophysiological responses of each individual. These electrophysiological responses are collected by an external electrodermal activity biosensor that serves as a tracker of physiological changes. Thirty-six diagnosed arachnophobic individuals participated in a one-session trial. Participants were divided into two groups, the Experimental Group which was exposed to the proposed real-time adaptive virtual simulation, and the Control Group which was exposed to a pre-recorded static virtual simulation as proposed in the literature. These results demonstrate the proposed system's ability to continuously construct an updated and adapted virtual environment that keeps the users within the appropriately chosen state (higher or lower intensity) for approximately twice the time compared to the pre-recorded static virtual simulation. Thus, such a system can increase the efficiency of VR stimulations for the treatment of central nervous system dysfunctions, as it provides numerically more controlled sessions without unexpected variations.

EHealth and Its Role in Supporting Audiological Rehabilitation: Patient Perspectives on Barriers and Facilitators of Using a Personal Hearing Support System With Mobile Application as Part of the EVOTION Study.

BACKGROUND: Hearing loss is a major public health challenge. Audiology services need to utilise a range of rehabilitative services and maximise innovative practice afforded by technology to actively promote personalized, participatory, preventative and predictive care if they are to cope with the social and economic burden placed on the population by the rapidly rising prevalence of hearing loss. Digital interventions and teleaudiology could be a key part of providing high quality, cost-effective, patient-centred management. There is currently very limited evidence that assesses the hearing impaired patient perspective on the acceptance and usability of this type of technology. AIM: This study aims to identify patient perceptions of the use of a hearing support system including a mobile smartphone app when used with Bluetooth-connected hearing aids across the everyday life of users, as part of the EVOTION project. METHODS: We applied a questionnaire to 564 participants in three countries across Europe and analysed the following topics: connectivity, hearing aid controls, instructional videos, audiological tests and auditory training. KEY FINDINGS: Older users were just as satisfied as younger users when operating this type of technology. Technical problems such as Bluetooth connectivity need to be minimised as this issue is highly critical for user satisfaction, engagement and uptake. A system that promotes user-controllability of hearing aids that is more accessible and easier to use is highly valued. Participants are happy to utilise monitoring tests and auditory training on a mobile phone out of the clinic but in order to have value the test battery needs to be relevant and tailored to each user, easy to understand and use. Such functions can elicit a negative as well as positive experience for each user. CONCLUSION: Older and younger adults can utilise an eHealth mobile app to complement their rehabilitation and health care. If the technology works well, is tailored to the individual and in-depth personalised guidance and support is provided, it could assist maximisation of hearing aid uptake, promotion of self-management and improving outcomes.

A Platform for Health Record Management of the Conscripts in the Hellenic Navy.

eMass project aims to digitalize the medical examination procedure of recruitment phase of conscripts in the Hellenic Navy. eMass integrates recruits' Electronic Health Record (EHR), while allows a pre-screening test, through portable telemedicine equipment. The data will be exploited to assess the individual's cardiovascular risk through appropriate digital tools and algorithms. The eMass digital platform, will be accessible to health experts involved in the recruitment procedure for further assessment and processing. Recruits' personal data is stored in the database encrypted using Advanced Encryption Standard (AES). eMass solution contributes to beneficial management and medical data analysis, preventing inessential physical or medical examinations minimizing danger of possible errors and reducing time-consuming processes. Moreover, eMass exploits Electronic Health Record data through a machine-learning based cardiovascular risk assessment tool.

Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment.

Tinnitus is a common symptom of a phantom sound perception with a considerable socioeconomic impact. Tinnitus pathophysiology is enigmatic and its significant heterogeneity reflects a wide spectrum of clinical manifestations, severity and annoyance among tinnitus sufferers. Although several interventions have been suggested, currently there is no universally accepted treatment. Moreover, there is no well-established correlation between tinnitus features or patients' characteristics and projection of treatment response. At the clinical level, this practically means that selection of treatment is not based on expected outcomes for the particular patient.The complexity of tinnitus and lack of well-adapted prognostic factors for treatment selection highlight a potential role for a decision support system (DSS). A DSS is an informative system, based on big data that aims to facilitate decision-making based on: specific rules, retrospective data reflecting results, patient profiling and predictive models. Therefore, it can use algorithms evaluating numerous parameters and indicate the weight of their contribution to the final outcome. This means that DSS can provide additional information, exceeding the typical questions of superiority of one treatment versus another, commonly addressed in literature.The development of a DSS for tinnitus treatment selection will make use of an underlying database consisting of medical, epidemiological, audiological, electrophysiological, genetic and tinnitus subtyping data. Algorithms will be developed with the use of machine learning and data mining techniques. Based on the profile features identified as prognostic these algorithms will be able to suggest whether additional examinations are needed for a robust result as well as which treatment or combination of treatments is optimal for every patient in a personalized level.In this manuscript we carefully define the conceptual basis for a tinnitus treatment selection DSS. We describe the big data set and the knowledge base on which the DSS will be based and the algorithms that will be used for prognosis and treatment selection.

Using digital watermarking to enhance security in wireless medical image transmission.

OBJECTIVES: During the last few years, wireless networks have been increasingly used both inside hospitals and in patients' homes to transmit medical information. In general, wireless networks suffer from decreased security. However, digital watermarking can be used to secure medical information. In this study, we focused on combining wireless transmission and digital watermarking technologies to better secure the transmission of medical images within and outside the hospital. METHODS: We utilized an integrated system comprising the wireless network and the digital watermarking module to conduct a series of tests. RESULTS: The test results were evaluated by medical consultants. They concluded that the images suffered no visible quality degradation and maintained their diagnostic integrity. DISCUSSION: The proposed integrated system presented reasonable stability, and its performance was comparable to that of a fixed network. This system can enhance security during the transmission of medical images through a wireless channel.

Emotional stimulation during motor exercise: An integration to the holistic rehabilitation framework.

Over the recent years, plenty of studies have been carried out concerning disabilities and rehabilitation. However, very few of them have focused on proposing or creating a holistic framework meant to maximize the merits of rehabilitation treatments. More importantly, an even smaller number has taken into consideration the immense impact of emotions and the crucial role they display concerning patients' performance during rehabilitation. The purpose of this study is to examine and highlight the direct connection of patients' performance quality with an artificially induced positive or negative emotional state. For that reason, we conducted an experiment regarding the convergence of emotions with the motor exercise. Specifically, our study was conducted with 45 participants and the GAPED database was employed as an emotional classifier. The effect of the visual stimulus was combined with a simple bicep exercise which introduces the motor element in our study. Statistical analysis of the yielding EMG & Acellerometer signals demonstrated a considerable difference in the quality of the physical activity of each subject induced by different emotional triggers. As a result, it is pivotal to integrate a holistic approach to rehabilitation in future clinical trials, aiming to reinforce the patient involvement and engagement process and thus the efficacy of the treatment.

Utilizing Key Item Method to Manage Musculoskeletal Disorders in a Hospital Workplace.

Management of musculoskeletal disorders (MSDs) is a necessity for the modern work environment. In hospitals, these disorders have a particularly high frequency among health care workers whose work entails lifting and transporting patients as well as washing, dressing and feeding them. This paper, presents an electronic application which is based on the method of basic items (KIM - Key Item Method) in order to reduce incidents of MSDs resulting from manual transport of loads in healthcare facilities. The sample consisted of 15 female hospital meal servers from Metaxa Hospital (Piraeus, Greece) in order to assess the activities of lifting, carrying, transporting, pushing and pulling of loads which are part of their daily work duties. The key requirement for the application was not only helping the risk assessment but also leading to targeted, easily applicable and low cost corrective measures. The results of this electronic tool application showed increased usability and benefits which were associated with the used database and the detailed information relatively to the corrective measures, such as training of the employees to change body posture, replacement of wheels on trolleys and redesigning of serving aisles which proved beneficial.

Evaluation for the Necessity of Medical Imaging Tests Prescription in Neurology.

The evaluation and control algorithms for the necessity of medical prescription testing, comprises useful tool for health professionals. It is beyond doubt that a connection between illness, symptoms, medical tests and prescriptions is essential and thus algorithms facilitating such approaches should be available to health professionals. Such informatics tools require the implementation of smart, interactive tools and not just linear, information storing websites. Such algorithms should be dynamic, that is their output should change based on the input as for example, in the serial input of symptoms to clinical examination to subsequent diagnosis. Slight variations in symptomatology can greatly alter diagnosis and subsequent physical testing and prescription. The present work presents a novel algorithm for the control of medical prescription testing in neurology, by utilizing decision trees for the connection of symptomatology to diagnosis and prescription for neurological conditions and disease. To the best of our knowledge this is the first time that such an approach is proposed.

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer.

BACKGROUND: In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. METHODS: We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 x 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. RESULTS: For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations to the original images. Within the proposed protocol, for human ROIs, we have found that there is a large number of texture features that showed significant differences between normal and abnormal endometrium. CONCLUSION: This study provides a standardized protocol for avoiding any significant texture feature differences that may arise due to variability in the acquisition procedure or the lack of color correction. After applying the protocol, we have found that significant differences in texture features will only be due to the fact that the features were extracted from different types of tissue (normal vs abnormal).

An Internet of Things platform architecture for supporting ambient assisted living environments.

Internet of Things (IoT) is the logical further development of today's Internet, enabling a huge amount of devices to communicate, compute, sense and act. IoT sensors placed in Ambient Assisted Living (AAL) environments, enable the context awareness and allow the support of the elderly in their daily routines, ultimately allowing an independent and safe lifestyle. The vast amount of data that are generated and exchanged between the IoT nodes require innovative context modeling approaches that go beyond currently used models. Current paper presents and evaluates an open interoperable platform architecture in order to utilize the technical characteristics of IoT and handle the large amount of generated data, as a solution to the technical requirements of AAL applications.

The EVOTION Decision Support System: Utilizing It for Public Health Policy-Making in Hearing Loss.

As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.

Multiple image watermarking applied to health information management.

Information technology advances have brought forth new challenges in healthcare information management, due to the vast amount of medical data that needs to be efficiently stored, retrieved, and distributed, and the increased security threats that explicitly have to be addressed. The paper discusses the perspectives of digital watermarking in a range of medical data management and distribution issues, and proposes a complementary and/or alternative tool that simultaneously addresses medical data protection, archiving, and retrieval, as well as source and data authentication. The scheme imperceptibly embeds in medical images multiple watermarks conveying patient's personal and examination data, keywords for information retrieval, the physician's digital signature for authentication, and a reference message for data integrity control. Experimental results indicate the efficiency and transparency of the scheme, which conforms to the strict requirements that apply to regions of diagnostic significance.

A distributed environment for the integration of multiple high-performance decision support systems into clinical workflow.

Current studies conclude that clinical decision support systems can help reduce serious medical errors. The importance of Causal Probabilistic Networks (CPNs) for constructing such systems is already well-known. However, the computational complexity of probabilistic inference, which results in unacceptably high response times, can hinder acceptance and integration into clinician workflow. This paper investigates the optimization and parallelization potential of complex CPN-based medical decision support systems and evaluates the results of implementing a parallel, high performance version of an existing decision support system concerning proper antibiotic treatment therapy. Furthermore, it discusses distributed computing techniques for making multiple high performance decision support systems available at the time and location of decision making, by exploiting computing resources residing inside, as well as outside the hospital walls optimally.

Communication protocol requirements of patient personal area networks for telemonitoring.

Continuous, remote monitoring of patients' healthcare condition, as this can be reflected by crucial vital signs supervision, is a key demand in modern healthcare provision. Towards the accomplishment of this requirement, the traditional solution of cabled sensors appears to have clear limitations and this is one of the ultimate causes of the proliferation of wireless medical sensor networks during last years. The modern trend towards this direction is the formulation of patient Personal Area Networks (pPANs), consisting of a wireless infrastructure of medical sensors, attached to patient's body, which lays the path for incessant telemonitoring of the person in mind, without discomforting them. The nature of data that these networks are set to handle, as well as the particular demands that patient telemonitoring services raise, necessitate for a thorough analysis of the design requirements of pPAN communication protocols, in order to outflank possible disadvantages appearing in protocols for different types of wireless sensor networks, without putting aside simplicity and feasibility factors. In the context of this paper, we intend to outline the most important requirements and design issues of a pPAN communication protocol, having as compass the main attributes of the most commonly used medical sensors and the typical functionality of these networks.

Using key performance indicators as knowledge-management tools at a regional health-care authority level.

The advantages of the introduction of information and communication technologies in the complex health-care sector are already well-known and well-stated in the past. It is, nevertheless, paradoxical that although the medical community has embraced with satisfaction most of the technological discoveries allowing the improvement in patient care, this has not happened when talking about health-care informatics. Taking the above issue of concern, our work proposes an information model for knowledge management (KM) based upon the use of key performance indicators (KPIs) in health-care systems. Based upon the use of the balanced scorecard (BSC) framework (Kaplan/Norton) and quality assurance techniques in health care (Donabedian), this paper is proposing a patient journey centered approach that drives information flow at all levels of the day-to-day process of delivering effective and managed care, toward information assessment and knowledge discovery. In order to persuade health-care decision-makers to assess the added value of KM tools, those should be used to propose new performance measurement and performance management techniques at all levels of a health-care system. The proposed KPIs are forming a complete set of metrics that enable the performance management of a regional health-care system. In addition, the performance framework established is technically applied by the use of state-of-the-art KM tools such as data warehouses and business intelligence information systems. In that sense, the proposed infrastructure is, technologically speaking, an important KM tool that enables knowledge sharing amongst various health-care stakeholders and between different health-care groups. The use of BSC is an enabling framework toward a KM strategy in health care.

A novel codification scheme based on the "VITAL" and "DICOM" Standards for telemedicine applications.

The field of interest discussed in this study is a novel codification scheme for (vital signs) medical device communication and patient monitoring data interchange, into the context of effective home care service provisioning. With medical technology having developed in isolation and major manufacturers developing their own proprietary communication protocols, which preclude connection to devices from different manufacturers, and with healthcare trends having evolved, pointing to primary care, telecare and home care monitoring, there is an increasing need for technical standardization in healthcare environments and the development of protocols that enable communication in a structured and open way. In this study, a novel codification scheme has been developed, based on two healthcare informatics standards, the VITAL and DICOM Sup. 30, in addressing the robust interchange of waveform and medical data for a home care application. Based on this scheme, we created a real-time facility, consisting of a base unit and a telemedicine (mobile) unit, that enables home telemonitoring, by installing the telemedicine unit at the patient's home while the base unit remains at the physician's office or hospital. The system allows the transmission of vital biosignals (3-lead ECG, pulse rate, blood pressure and SpO2) of the patient. This paper presents an object-oriented design with unified modeling language (UML) of a class hierarchy for exchanging the acquired medical data and performing alert management, and investigates the applicability of the proposed scheme into a commercial patient-connected medical device, thus addressing service and functionality requirements with focus on home-care applications. The system has been validated for technical performance over several telecommunication means and for clinical validity via real patient-involved pilot trials.

Cost-effective health services for interactive continuous monitoring of vital signs parameters--the e-Vital concept.

The objective of the e-Vital project is the validation of the market concerning the provision of a novel remote telemedicine service aimed at large sensitive parts of the European population, the "at-risk" citizens, who are usually patients with a stable medical condition that allow a near normal life but may suddenly deteriorate and put life at risk. This service will increase their quality of life and their feeling of safety concerning their health. The e-Vital project focuses on the implementation and exploitation of a modular and ambulatory secure telemedicine platform, which is using easily wearable vital signs monitoring devices, causing minimal discomfort to patients, and which transfer in real time and on-line critical vital parameters to doctors and/or medical experts/consultants, regardless of their location, while getting feedback to increase their feeling of comfort or in case of alarm. The interactive continuous monitoring promises cost effective health services, more active involvement of patients in their own care, and a new sense of realism in making a diagnosis.

RESHEN, a best practice approach for secure healthcare networks in Europe.

Electronic communication of healthcare related information (in the framework of Regional Healthcare Information Networks), introduces a number of security risks with regard to confidentiality, integrity and availability, which can become quite crucial taking into account its sensitive nature. Public Key Infrastructure (PKI) is acknowledged as an appropriate means for dealing with such risks, as long as all the involved critical factors are first practically assessed. This paper presents a best-practice approach for secure regional healthcare networks in Europe, examining all the identified crucial parameters (technical, organisational, legal/regulatory, medical and business). Our approach is conducted at two levels (the regional and the European), including the integration of PKI-aware security mechanisms (strong authentication, encryption, digital signature, time-stamping) in three regional pilot sites in Greece, Finland and Germany and demonstrating their interconnection in a pan-European architecture. Following the above approach, some major conclusions are excluded, pointing out existing open issues and possible steps forward.

Novel mobile-health technologies.

Mobile Health is fast becoming one of the fastest growing sectors of health as health tries to shift to patient-centric solutions. Putting the patients in the centre of care also forces them to take control of their wellbeing, health management and/or disease management. This is especially relevant when the management is constant as it is the case with chronic diseases.