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Wearable, Wireless EEG Solutions in Daily Life Applications: What are we missing?

Wearable, Wireless EEG Solutions in Daily Life Applications: What are we missing?

Monitoring human brain activity has great potential in helping us understand the functioning of our brain, as well as in preventing mental disorders and cognitive decline and improve our quality of life. To take full advantage of surface EEG recordings, EEG technology has to be advanced to a level that it can be used in daily life activities. To achieve this, EEG systems have to be transformed from stationary, wired and cumbersome systems used mostly in clinical practice today, to intelligent wearable, wireless, convenient and comfortable lifestyle solutions that provide high signal quality. Here we discuss state-of-the-art in wireless and wearable EEG solutions and a number of aspects where such solutions require improvements when handling electrical activity of the brain.

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Smart-Phone Based Recognition of States and State Changes in Bipolar Disorder Patients

Smart-Phone Based Recognition of States and State Changes in Bipolar Disorder Patients

In this article we introduce a system, which based on smartphone-sensing is able to recognize depressive and manic states and detect state changes of patients suffering from bipolar disorder. The work is motivated by the fact that the effectiveness of bipolar disorder treatment critically depends on it being administered at the beginning of a patient’s transition into a different state (e.g. from normal to depressive). Once severe symptoms have persisted for a significant time, treatment is less effective and more difficult. We have verified our approach upon a real-life dataset of 10 patients, recorded over a time-period of 12 weeks by 4 different sensing modalities we could extract features corresponding to all disease-relevant aspects in behaviour.

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Estimating Energy Expenditure Using Body-Worn Accelerometers: a Comparison of Methods, Sensors Number and Positioning

Estimating Energy Expenditure Using Body-Worn Accelerometers: a Comparison of Methods, Sensors Number and Positioning

In this paper, we compare three prevalent EE estimation methods and five body locations to provide a basis for selecting among methods, sensors number and positioning. To evaluate our approach, we implemented a study with 15 participants that wore five accelerometer sensors while performing a wide range of sedentary, household, lifestyle, and gym activities at different intensities. Indirect calorimetry was used in parallel to obtain EE reference data. Results show that activity-specific estimation methods using accelerometer features can outperform counts-based methods by 88% and activity-specific methods using METs lookup for active clusters by 23%.

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Carotid Intraplaque Neovascularization Quantification Software (CINQS)

Carotid Intraplaque Neovascularization Quantification Software (CINQS)

Patients with carotid plaques carry an increased risk of cerebrovascular events such as stroke. To prevent stroke, an early detection of plaque at risk of rupture is crucial. Currently available commercial contrast quantification tools are not applicable for quantitative analysis of carotid IPN due to substantial motion of the carotid artery, artifacts, and intermittent perfusion of plaques. We therefore developed a specialized software package called Carotid Intraplaque Neovascularization Quantification Software (CINQS). It was designed for effective and systematic comparison of sets of quantitative imaging-biomarkers. In this paper, we describe the concept, analysis tools, and performance of CINQS, and present analysis results of 45 plaques of 23 patients. The results in 45 plaques showed excellent agreement with visual IPN scores for two quantitative imaging biomarkers.

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About This Journal

IEEE Journal of Biomedical and Health Informatics (J-BHI) publishes original papers describing recent advances in the field of biomedical and health informatics where information and communication technologies intersect with health, healthcare, life sciences and biomedicine. Papers must contain original content in theoretical analysis, methods, technical development, and/or novel clinical applications of information systems.

Retitled from the IEEE Transactions on Information Technology in Biomedicine (T-ITB) in 2013, the J-BHI is one of the leading journals in computer science and information systems with a strong interdisciplinary focus and biomedical and health application emphasis. Topics covered by J-BHI include, but are not limited to: acquisition, transmission, storage, retrieval, management, processing and analysis of biomedical and health information; applications of information and communication technologies to the practice of healthcare, personal well-being, preventive care and early diagnosis of diseases, and discovery of new therapies and patient specific treatment protocols; and integration of electronic medical and health records, methods of longitudinal data analysis, data mining and knowledge discovery tools.

Manuscripts may deal with these applications and their integration, such as clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body senor networks, informatics in biological and physiological systems, personalized and pervasive health technologies (telemedicine, u-, p-, m- and e-Health) for public health, home healthcare and wellness management. Topics related to integration include interoperability, protocol-based patient care, evidence-based medicine, and methods of secure patient data.

Papers published by J-BHI are typically organised under section headings of Bioinformatics, Imaging Informatics, Sensor Informatics, Medical Informatics, and Public Health Informatics. These are complemented by managed special issues/sections covering topics that are of strategic importance to the journal, coordinated by guest editors who are leading experts in these fields. We particularly encourage large cohort studies with clearly demonstrated clinical translational values supplemented by online data sets or algorithms that can be shared by the research community.

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Call for Papers: JBHI Special Issue on Sensor Informatics and Quantified Self IEEE J-BHI Upcoming Special Issues and Supported Conferences
Call for applications: Director and Professor of Biomedical Engineering