Konstantina Nikita

National Technical University of Athens | NTUA · School of Electrical and Computer Engineering

Background: The COVID-19 pandemic has highlighted the need for robust diagnostic tools capable of detecting the disease from diverse and evolving data sources. Machine learning models, especially convolutional neural networks (CNNs), have shown promise. However, the dynamic nature of real-world data can lead to model drift, where performance degrad...

Objective. Understanding the generative mechanism between Local Field Potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupling between LFP and spikes. However, very few have managed to predict the exact timing of...

Importance Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases. Objective To derive subgroups with common patterns of variation in participants without diagn...

Childhood obesity is a complex disease with multiple biological and psychosocial risk factors. Recently, novel digital programs were developed with growing evidence for their effectiveness in pediatric weight management studies. The ENDORSE platform consists of mobile applications, wearables, and serious games for the remote management of childhood...

Next generation wireless networks will necessitate new and wide spectrum swaths able to accommodate and support Tb/s applications and services. In this regard, frequencies above 100 GHz are anticipated to be allocated, which requires a thorough analysis of the propagation characteristics at those segments. This article presents a detailed analysis...

Background Understanding heterogeneity of structural brain changes in aging may provide insights into susceptibility to neurodegenerative diseases. We characterize the genetics underlying brain structural heterogeneity within cognitively unimpaired (CU) individuals using data‐driven machine learning applied to a diverse dataset of 27,402 individual...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective: Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. Whil...

Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during COVID-19 pandemic. The smarty4covid dataset contains audio signals of cough (4,676), regular bre...

Visual attention forms the basis of understanding the visual world. In this work we follow a computational approach to investigate the biological basis of visual attention. We analyze retinal and cortical electrophysiological data from mouse. Visual Stimuli are Natural Images depicting real world scenes. Our results show that in primary visual cort...

Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during COVID-19 pandemic. The smarty4covid dataset contains audio signals of cough (4,676), regular bre...

This paper presents a novel Procedural Content Generation (PCG) method aiming at achieving personalization and adaptation in serious games (SG) for health. The PCG method is based on a genetic algorithm (GA) and provides individualized content in the form of tailored messages and SG missions, taking into consideration data collected from health-rel...

Childhood obesity is a serious public health problem worldwide. The ENDORSE platform is an innovative software ecosystem based on Artificial Intelligence which consists of mobile applications for parents and health professionals, activity trackers, and mobile games for children. This study explores the impact of the ENDORSE platform on metabolic pa...

Citation: Zarkogianni, K.; Chatzidaki, E.; Polychronaki, N.; Kalafatis, E.; Nicolaides, N.C.; Voutetakis, A.; Chioti, V.; Kitani, R.-A.; Mitsis, K.; Perakis, K.; et al. Abstract: Childhood obesity constitutes a major risk factor for future adverse health conditions. Multicomponent parent-child interventions are considered effective in controlling w...

Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to the broader family of generative methods, which learn to generate realistic data with a probabilistic model by learning distributions from real samples. In the clinical context, GANs have shown...

This paper introduces a propagation study at sub-THz frequencies in an urban environment. Deterministic simulations are carried out utilizing a software tool and a high-resolution digital map of the area. Different scenarios and antenna configurations are examined, as well as the relative propagation mechanisms are described. The simulated path los...

BACKGROUND The potential of harnessing the plurality of available data in real time along with advanced data analytics towards the accurate prediction of influenza-like-illness (ILI) outbreaks has gained significant scientific interest. Different methodologies based on the use of machine learning techniques and traditional and alternative data sour...

Background The potential to harness the plurality of available data in real time along with advanced data analytics for the accurate prediction of influenza-like illness (ILI) outbreaks has gained significant scientific interest. Different methodologies based on the use of machine learning techniques and traditional and alternative data sources, su...

Patients usually deviate from prescribed medication schedules and show reduced adherence. Even when the adherence is sufficient, there are conditions where the medication schedule should be modified. Crucial drug–drug, food–drug, and supplement–drug interactions can lead to treatment failure. We present the development of an internet of medical thi...

Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to a broader family called generative methods, which generate new data with a probabilistic model by learning sample distribution from real examples. In the clinical context, GANs have shown enhan...

In this article, an unobtrusive and affordable sensor-based multimodal approach for real time recognition of engagement in serious games (SGs) for health is presented. This approach aims to achieve individualization in SGs that promote self-health management. The feasibility of the proposed approach was investigated by designing and implementing an...

Early detection of breast cancer is a powerful tool towards decreasing its socioeconomic burden. Although, artificial intelligence (AI) methods have shown remarkable results towards this goal, their "black box" nature hinders their wide adoption in clinical practice. To address the need for AI guided breast cancer diagnosis, interpretability method...

Carotid atherosclerosis is the major cause of ischemic stroke resulting in significant rates of mortality and disability annually. Early diagnosis of such cases is of great importance, since it enables clinicians to apply a more effective treatment strategy. This paper introduces an interpretable classification approach of carotid ultrasound images...

Challenges in the field of retinal prostheses motivate the development of retinal models to accurately simulate Retinal Ganglion Cells (RGCs) responses. The goal of retinal prostheses is to enable blind individuals to solve complex, reallife visual tasks. In this paper, we introduce the functional assessment (FA) of retinal models, which describes...

Rapid advances in antennas, propagation, electromagnetics, and materials are opening new and unexplored opportunities in body area sensing and stimulation. Next-generation wearables and implants are seamlessly providing round-the-clock monitoring. In turn, numerous applications are brought forward with the potential to ultimately transform healthca...

The curvelet transform, which represents images in terms of their geometric and textural characteristics, was investigated toward revealing differences between moderate (50%–69%, n = 11) and severe (70%–100%, n = 14) stenosis asymptomatic plaque from B-mode ultrasound. Texture features were estimated in original and curvelet transformed images of a...

We seek the development and evaluation of a fast, accurate, and consistent method for general-purpose segmentation, based on interactive machine learning (IML). To validate our method, we identified retrospective cohorts of 20 brain, 50 breast, and 50 lung cancer patients, as well as 20 spleen scans, with corresponding ground truth annotations. Uti...

The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in more than 3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to save lives during this pandemic. Since WHO declared the COVID-19 outbreak as a pandemic, several studies have been...

Purpose The purpose of this study was to investigate differences in ultrasound-based velocities and accelerations of the carotid atheromatous plaque between asymptomatic patients with moderate and severe stenosis, based on the assumption that plaque motion features are sensitive to cardiovascular health status. Methods The dataset used consists of...

Aims: Cardiac implantable electronic devices (CIEDs) are susceptible to electromagnetic interference (EMI). Smartwatches and their chargers could be a possible source of EMI. We sought to assess whether the latest generation smartwatches and their chargers interfere with proper CIED function. Methods and results: We included consecutive CIED rec...

div> Cardiovascular Disease (CVD) is an important cause of disability and death among individuals with Diabetes Mellitus (DM). International clinical guidelines for the management of Type 2 DM (T2DM) are founded on primary and secondary prevention and favor the evaluation of CVD related risk factors towards appropriate treatment initiation. CVD r...

div> Cardiovascular Disease (CVD) is an important cause of disability and death among individuals with Diabetes Mellitus (DM). International clinical guidelines for the management of Type 2 DM (T2DM) are founded on primary and secondary prevention and favor the evaluation of CVD related risk factors towards appropriate treatment initiation. CVD r...

Asynchronous movement of the carotid atheromatous plaque from B-mode ultrasound has been previously reported, and associated with higher risk of stroke, but not quantitatively estimated. Based on the hypothesis that asynchronous plaque motion is associated with vulnerable plaque, in this study, synchronisation patterns of different tissue areas wer...

IEEE Journal of Biomedical and Health Informatics July 2020, Volume 24, Number 7

Motion extracted from the carotid artery wall provides unique information for vascular health evaluation. Carotid artery longitudinal wall motion corresponds to the multiphasic arterial wall excursion in the direction parallel to blood flow during the cardiac cycle. While this motion phenomenon has been well characterized, there is a general lack o...

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for effi...

Objective: To investigate pathway-specific connectivity disrupted in psychosis. Methods: We carried out a case study of a middle-aged patient who presented with new-onset psychosis associated with a space-occupying lesion localized in the right superior colliculus/periaqueductal gray. The study sought to investigate potential connectivity defici...

Background: To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. Methods: The holistic and evidence-based CEHRES Roadmap, used to create eHealth solutions through participator...

Recent global focus on healthcare has stimulated research and development of innovative technologies which address many sustainability issues of the current healthcare provision models. Rapid advances in mobile, wireless, and sensing technologies have enabled new opportunities in healthcare, enabling cost-effective and efficient healthcare delivery...

Retinal Prosthesis (RP) is an approach to restore vision, using an implanted device to electrically stimulate the retina. A fundamental problem in RP is to translate the visual scene to retina neural spike patterns, mimicking the computations normally done by retina neural circuits. Towards the perspective of improved RP interventions, we propose a...

Unhealthy dietary habits constitute a major risk factor for the onset of chronic diseases, such as cardiovascular diseases, cancer, diabetes and other conditions linked to obesity. Effective dietary changes are of paramount importance and can be promoted through empowering individuals with Nutrition Literacy (NL) and Food Literacy (FL) skills. This...

Sitting posture recognition can be used to evaluate the awareness of a person carrying out a task, such as working or driving, and can aid in avoiding accidents or other health risks, such as musculoskeletal disorders. In addition, sitting posture can reveal wellness or unhealthiness for the elderly and mobility disabled individuals. This paper foc...

The rapid growth of information and communications technology (ICT) and the recent advances of sensors enable the acquisition, transmission, and interpretation of different vital biosigns leading to the development of two emerging scientific fields, the electronic health (e-Health) and the mobile health (m-Health). Innovative services in healthcare...

The estimation of vessel wall motion is valuable for characterising vessel status in health and disease. Following the periodic movement of the heart and the resulting blood pressure variations during the cardiac cycle, the vascular wall performs a complex three-dimensional motion. Wall motion can be quantified through the calculation of a number o...

This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition an...

Evolution of mobile technologies and their rapid penetration to people's daily lives, especially in the developing countries, have highlighted mobile health, or m-health, as a promising solution to improve health outcomes. Several studies have been conducted that characterize the impact of m-health solutions in resource-limited settings and assess...

Accurate estimation of food's macronutrient content for people with Diabetes Mellitus (DM) is of great importance, as it determines postprandial insulin dosage. This paper introduces a classification system for food images that is adjusted to the nutritional needs of people with DM. A two-level image classification scheme, exploiting Convolutional...

A method based on the combination of Local Binary Pattern operator and radial lengths is presented aiming at the identification of Architectural Distortions (ADs) in mammograms. Local Binary Pattern operator, a number of its variants, and radial lengths are combined together producing a high‐dimensional feature space. A process, based on the combin...

The aim of the present study is to comparatively assess the performance of different machine learning and statistical techniques with regard to their ability to estimate the risk of developing type 2 diabetes mellitus (Case 1) and cardiovascular disease complications (Case 2). This is the first work investigating the application of ensembles of art...

The estimation of long-term diabetes complications risk is essential in the process of medical decision making. Guidelines for the management of Type 2 Diabetes Mellitus (T2DM) advocate calculating the Cardiovascular Disease (CVD) risk to initiate appropriate treatment. The objective of this study is to investigate the use of sophisticated machine...

Computer aided diagnosis (CADx) approaches are developed towards the effective discrimination between benign and malignant clusters of microcalcifications. Different sources of information are exploited, such as features extracted from the image analysis of the region of interest, features related to the location of the cluster inside the breast, a...

Microwave radiometry is a passive technique used to measure in-depth temperature distributions inside the human body, potentially useful in clinical applications. Experimental data imply that it may provide the capability of detecting in-depth local variations of temperature and/or conductivity of excitable tissues at microwave frequencies. Specifi...

In this paper, we present the potential of a device, originally designed for energy harvesting, to form a self-powered medical implant that monitors critical parameters of the cardiovascular system. The original design consists of a coil that deforms with an artery inside magnetic field applied by two permanent magnets. We fabricated the device, an...

Though medical implantable devices are highly suitable for continuous and real time patient monitoring, their battery replacement is a costly and complicated procedure. To extend the functional life of medical implants, energy harvesting methods have been investigated that convert the motions of the cardiovascular system to electrical energy. In th...

Recent efforts on patient-specific therapeutic approaches revealed the importance of computational methods in guiding deep brain stimulation (DBS), a neuromodulation treatment initially applied to motor diseases that is fast expanding to include affective disorders, among others. In this paper, we discuss the basic principles and challenges faced b...

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthal...

Supplementary information for “Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach”. (PDF)

Minimal underlying data set. (XLSX)

The phase response curve employed in the stochastic model (evaluated according to Mauroy et al. (2014) [47]). (TIF)

Progression of the model-based direct search method for a single trial (Central -4.3mm, Right STN, case O3). (A) Cost function minimization was achieved after a total of 13 iterations and approximately 38 function evaluations. According to the algorithm, optimal stimulation settings for this particular example included a pulse width of 30μs (B), a...

Methods: A critical literature review analysis is conducted focusing on three types of in-body medical devices, i.e., a) devices that are implanted inside the human body (implantables), b) devices that are ingested like regular pills (ingestibles), and c) devices that are injected into the human body via needles (injectables). Design consideration...

The fact that carotid atherosclerosis is the most common cause of stroke, coupled with the exceptionally high levels of mortality, morbidity, and disability for stroke events, places a valid risk stratification for the disease among the major public health challenges. The unique features of ultrasound imaging have established it as the cornerstone...

Although Fourier and Wavelet Transform have been widely used for texture classification methods in medical images, the discrimination performance of FDCT has not been investigated so far in respect to breast cancer detection. Ιn this paper, three multi-resolution transforms, namely the Discrete Wavelet Transform (DWT), the Stationary Wavelet Transf...

Mammography is the main imaging technique for breast cancer diagnosis and prevention. Many image processing techniques though require the breast region to be adequately defined in order to provide reliable results. Pectoral muscle segmentation is one of the most challenging tasks in this domain since the limits between the muscle and the actual bre...

Biomedical telemetry permits the measurement of physiological signals at a distance, through either wired or wireless communication technologies. One of the latest developments in wireless biomedical telemetry is in the field of implantable medical devices (IMDs). Such devices are implanted inside the patient’s body by means of a surgical operation...