Biomedical subjects

Dimitrios I Fotiadis

Publications and source records attributed to Dimitrios I Fotiadis.

18 recordsLinked to original sources

PubMed2026

The effect of dietetic counseling combined with digital tools intervention on hemodynamic markers in Greek adults: The GATEKEEPER Study.

BACKGROUND AND AIM: Hypertension is a leading cardiovascular risk factor with substantial global impact on morbidity, mortality, and healthcare costs. While lifestyle interventions remain central to management, mHealth technologies offer promising adjunctive support, though their clinical effectiveness remains uncertain. This study evaluated whether combining dietetic counseling with digital tools improves hemodynamic markers in adults aged ≥55 years with increased cardiometabolic risk. METHODS AND RESULTS: This 3-month RCT (NCT05031299) included 954 adults with at least one metabolic syndrome risk factor, allocated 1:1:1 to Standard Care (dietetic counseling), Platform (counseling plus web-based platform), or Platform + Devices (counseling plus platform plus wearables). Outcomes included anthropometrics, lifestyle characteristics, blood pressure, pulse pressure, and estimated pulse wave velocity, analyzed using linear mixed-effects models adjusted for age and sex. All groups improved over 3 months. Waist circumference decreased by -6.29, -4.92, and -4.69 cm across Standard Care, Platform, and Platform + Devices groups respectively, and systolic blood pressure declined by -4.84 to -7.15 mmHg across groups. The Platform + Devices group showed greater increases in physical activity (94.62 MET-min/week; 95% CI 66.49 to 122.76) and greater reductions in pulse pressure (-3.90 mmHg; -6.58 to -1.22) versus Standard Care. Weight loss was associated with lower odds of hypertension (OR 0.4; 95% CI 0.2-0.7), greater likelihood of hypertension reversal (OR 3.6; 1.2-10.3), and higher probability of achieving normal pulse pressure (OR 1.8; 1.1-3.1). CONCLUSIONS: Dietary lifestyle intervention improved cardiometabolic outcomes, with limited added benefit from digital tools. Weight loss was the primary driver of hemodynamic improvement.

Aged↗

PubMed2006

An integrated telemedicine platform for the assessment of affective physiological states.

AUBADE is an integrated platform built for the affective assessment of individuals. The system performs evaluation of the emotional state by classifying vectors of features extracted from: facial Electromyogram, Respiration, Electrodermal Activity and Electrocardiogram. The AUBADE system consists of: (a) a multisensorial wearable, (b) a data acquisition and wireless communication module, (c) a feature extraction module, (d) a 3D facial animation module which is used for the projection of the obtained data through a generic 3D face model; whereas the end-user will be able to view the facial expression of the subject in real time, (e) an intelligent emotion recognition module, and (f) the AUBADE databases where the acquired signals along with the subject's animation videos are saved. The system is designed to be applied to human subjects operating under extreme stress conditions, in particular car racing drivers, and also to patients suffering from neurological and psychological disorders. AUBADE's classification accuracy into five predefined emotional classes (high stress, low stress, disappointment, euphoria and neutral face) is 86.0%. The pilot system applications and components are being tested and evaluated on Maserati's car racing drivers.

Journal Article↗

PubMed2006

Association of endothelial shear stress with plaque thickness in a real three-dimensional left main coronary artery bifurcation model.

We report for the first time a real three-dimensional reconstruction of the left main coronary artery, left main bifurcation, left anterior descending coronary artery and left circumflex coronary artery using biplane angiography and intravascular ultrasound imaging in a patient with a proximal stenosis in the left anterior descending coronary artery. By using computational fluid dynamics in the three-dimensional luminal model we computed endothelial shear stress, while plaque thickness was calculated as the difference between the three-dimensional lumen and outer vessel wall; plaque thickness was found to be inversely related to endothelial shear stress in the left main coronary artery and bifurcation. The application of our methodology for real three-dimensional reconstruction of the left main coronary artery and bifurcation is useful for investigating the relationship of hemodynamic parameters with plaque thickness in this critical coronary region.

Coronary Artery Disease↗

PubMed2006

Guided ultrasound wave propagation in intact and healing long bones.

Ultrasonic evaluation of bone fracture healing has been traditionally based on the measurement of the propagation velocity of the first arriving signal (FAS). However, the FAS in general corresponds to a lateral wave that propagates along the bone's subsurface. In this work, we study guided ultrasound propagation in intact and healing bones. We developed a 2-D model of a bone-mimicking plate in which the healing process was simulated as a 7-stage process, and we also carried out ex vivo experiments on an intact tibia. Guided waves were represented in the time-frequency (t-f) domain of the signal by incorporating the Lamb wave theory. Three t-f distribution functions were examined, namely the reassigned Spectrogram, the smoothed-pseudo Wigner-Ville, and the reassigned version of it. For the intact plate case, we found that the S2, A3 Lamb modes were the dominant waves for a broadband 1-MHz excitation, and the S2, S0 for a 500-kHz excitation. During the simulated healing process, the mechanical and geometrical callus properties affected the theoretically anticipated Lamb modes. The propagation of guided waves throughout the thickness of the cortical bone and their sensitivity to both the mechanical and structural changes during healing can supplement velocity measurements so as to enhance the monitoring capabilities of ultrasonic evaluation. Nevertheless, the applicability of the Lamb wave theory to real bones has several limitations mostly associated with neglecting the inhomogeneity, anisotropy and irregular geometry of bone.

Acoustics↗

PubMed2006

An association rule mining-based methodology for automated detection of ischemic ECG beats.

Currently, an automated methodology based on association rules is presented for the detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The proposed approach consists of three stages. 1) Preprocessing: Noise is removed and all the necessary ECG features are extracted. 2) Discretization: The continuous valued features are transformed to categorical. 3) CLASSIFICATION: An association rule extraction algorithm is utilized and a rule-based classification model is created. According to the proposed methodology, electrocardiogram (ECG) features extracted from the ST segment and the T-wave, as well as the patient's age, were used as inputs. The output was the classification of the beat as ischemic or not. Various algorithms were tested both for discretization and for classification using association rules. To evaluate the methodology, a cardiac beat dataset was constructed using several recordings of the European Society of Cardiology ST-T database. The obtained sensitivity (Se) and specificity (Sp) was 87% and 93%, respectively. The proposed methodology combines high accuracy with the ability to provide interpretation for the decisions made, since it is based on a set of association rules.

Arrhythmias, Cardiac↗

PubMed2006

EEG transient event detection and classification using association rules.

In this paper, a methodology for the automated detection and classification of transient events in electroencephalographic (EEG) recordings is presented. It is based on association rule mining and classifies transient events into four categories: epileptic spikes, muscle activity, eye blinking activity, and sharp alpha activity. The methodology involves four stages: 1) transient event detection; 2) clustering of transient events and feature extraction; 3) feature discretization and feature subset selection; and 4) association rule mining and classification of transient events. The methodology is evaluated using 25 EEG recordings, and the best obtained accuracy was 87.38%. The proposed approach combines high accuracy with the ability to provide interpretation for the decisions made, since it is based on a set of association rules.

Algorithms↗

PubMed2005

Transosseous application of low-intensity ultrasound for the enhancement and monitoring of fracture healing process in a sheep osteotomy model.

The purpose of this study is twofold: (a) to investigate the application of transosseous low-intensity pulsed ultrasound (LiUS) on the enhancement of fracture healing and (b) to demonstrate the ability of transosseous ultrasound propagation to monitor the healing process. A midshaft tibial osteotomy model was used on 40 skeletally mature sheep, and an external fixator was applied to maintain the reduction and stabilization of the osteotomy. Two ultrasound transducers were implanted into the fracture site in contact with the bone. For investigating the efficacy of LiUS, the animals were randomly divided in two equal groups: the treatment group and the control group. The LiUS-treated animals received 200-micros bursts of 1-MHz sine waves with a pulse repetition rate of 1 kHz and average intensity of 30 mW/cm2, for 20 min daily. For monitoring purposes, an ultrasound dataset was constructed consisting of serial ultrasound measurements obtained from healing bones. Animals' sacrifice took place on the 100th post-operative day. The effect of LiUS on fracture healing was evaluated using radiographs, destructive three-point bending testing and quantitative CT-based bone mineral density (BMD) measurements. Survival analysis using Kaplan-Meier curves showed significantly higher probability of radiographic healing for the animals in the treatment group (P = 0.009). Statistical significance was also observed for callus BMD (P = 0.003, Wilcoxon nonparametric test), the breaking load (P = 0.001), extrinsic stiffness (P = 0.019), Young's modulus (P = 0.043) and ultimate strength (P = 0.051) in favor of the LiUS-treated limbs. Analysis of the obtained ultrasonic measurements showed that the propagation velocity across healing bones constitutes a significant feature able to early distinguish between healed and nonhealed bones (area under ROC curve was 0.810 and 0.841 on the 80th and 100th post-operative days, respectively). Both the LiUS application and the ultrasonic measurements are supported by an integrated telemedicine system which also incorporates an ultrasound wearable device and a patient management system.

Animals↗

PubMed2005

A method for 3D reconstruction of coronary arteries using biplane angiography and intravascular ultrasound images.

The aim of this study is to describe a new method for the three-dimensional reconstruction of coronary arteries and its quantitative validation. Our approach is based on the fusion of the data provided by intravascular ultrasound images (IVUS) and biplane angiographies. A specific segmentation algorithm is used for the detection of the regions of interest in intravascular ultrasound images. A new methodology is also introduced for the accurate extraction of the catheter path. In detail, a cubic B-spline is used for approximating the catheter path in each biplane projection. Each B-spline curve is swept along the normal direction of its X-ray angiographic plane forming a surface. The intersection of the two surfaces is a 3D curve, which represents the reconstructed path. The detected regions of interest in the IVUS images are placed perpendicularly onto the path and their relative axial twist is computed using the sequential triangulation algorithm. Then, an efficient algorithm is applied to estimate the absolute orientation of the first IVUS frame. In order to obtain 3D visualization the commercial package Geomagic Studio 4.0 is used. The performance of the proposed method is assessed using a validation methodology which addresses the separate validation of each step followed for obtaining the coronary reconstruction. The performance of the segmentation algorithm was examined in 80 IVUS images. The reliability of the path extraction method was studied in vitro using a metal wire model and in vivo in a dataset of 11 patients. The performance of the sequential triangulation algorithm was tested in two gutter models and in the coronary arteries (marked with metal clips) of six cadaveric sheep hearts. Finally, the accuracy in the estimation of the first IVUS frame absolute orientation was examined in the same set of cadaveric sheep hearts. The obtained results demonstrate that the proposed reconstruction method is reliable and capable of depicting the morphology of coronary arteries.

Algorithms↗

PubMed2005

Endothelin receptor--a blockade decreases ventricular arrhythmias after myocardial infarction in rats.

OBJECTIVE: Endothelin-1 (ET-1) production increases during acute myocardial infarction (MI) and may contribute to the genesis of ventricular tachycardia (VT) and ventricular fibrillation (VF). However, the antiarrhythmic effects of ET-1 receptor blockade, examined shortly after MI, have been debated. In the present study, we examined the effects of such treatment on VT/VF during the first 24 h post-MI. METHODS: Thirty-five Wistar rats (223+/-22 g) were randomly allocated to either the ET-1 receptor-A (ETA) antagonist BQ-123 (0.4 mg/kg, BQ-123 group, n=17), or normal saline (control group, n=18) and were subjected to coronary artery ligation. A single-lead electrocardiogram was continuously recorded for 24 h post-MI, using an implanted telemetry system, and episodes of VT/VF were analyzed. Monophasic action potential (MAP) recordings were obtained from the left (LV) and right (RV) ventricular epicardium at baseline, 5 min after treatment and 24 h post-MI. RESULTS: There were 15.94+/-19.35 episodes/h/rat of VT/VF in the control group and 1.66+/-2.22 in the BQ-123 group (p=0.010), resulting in a lower (p=0.030) arrhythmic mortality in treated animals. The mean episode duration was 7.40+/-7.16 s for the control group and 2.30+/-1.37 s for the BQ-123 group (p=0.011). The maximum decrease in VT/VF was observed during the 1st, 5th and 6th hours post-MI. In the control group, LV MAP duration increased 24 h post-MI, displaying an increased beat-to-beat variation, but remained unchanged in the BQ-123 group. CONCLUSION: Acute ETA blockade reduces the incidence of VT/V F during the first 24-h post-MI in the rat, through a decrease in the dispersion of repolarization.

Action Potentials↗

PubMed2005

Motif-based protein sequence classification using neural networks.

We present a system for multi-class protein classification based on neural networks. The basic issue concerning the construction of neural network systems for protein classification is the sequence encoding scheme that must be used in order to feed the neural network. To deal with this problem we propose a method that maps a protein sequence into a numerical feature space using the matching scores of the sequence to groups of conserved patterns (called motifs) into protein families. We consider two alternative ways for identifying the motifs to be used for feature generation and provide a comparative evaluation of the two schemes. We also evaluate the impact of the incorporation of background features (2-grams) on the performance of the neural system. Experimental results on real datasets indicate that the proposed method is highly efficient and is superior to other well-known methods for protein classification.

Algorithms↗

PubMed2005

An ultrasound wearable system for the monitoring and acceleration of fracture healing in long bones.

An ultrasound wearable system for remote monitoring and acceleration of the healing process in fractured long bones is presented. The so-called USBone system consists of a pair of ultrasound transducers, implanted into the fracture region, a wearable device and a centralized unit. The wearable device is responsible to carry out ultrasound measurements using the axial-transmission technique and initiate therapy sessions of low-intensity pulsed ultrasound. The acquired measurements and other data are wirelessly transferred from the patient-site to the centralized unit, which is located in a clinical setting. The evaluation of the system on an animal tibial osteotomy model is also presented. A dataset was constructed for monitoring purposes consisting of serial ultrasound measurements, follow-up radiographs, quantitative computed tomography-based densitometry and biomechanical data. The animal study demonstrated the ability of the system to collect ultrasound measurements in an effective and reliable fashion and participating orthopaedic surgeons accepted the system for future clinical application. Analysis of the acquired measurements showed that the pattern of evolution of the ultrasound velocity through healing bones over the postoperative period monitors a dynamic healing process. Furthermore, the ultrasound velocity of radiographically healed bones returns to 80% of the intact bone value, whereas the correlation coefficient of the velocity with the material and mechanical properties of the healing bone ranges from 0.699 to 0.814. The USBone system constitutes the first telemedicine system for the out-hospital management of patients sustained open fractures and treated with external fixation devices.

Animals↗

PubMed2005

Semantics-based information modeling for the health-care administration sector: the citation platform.

An information brokerage environment for effective information structuring, indexing, and retrieval in the health-care administration sector is presented. The system is based on ontology modeling, natural language processing, extensible markup language, semantics analysis, and behavioral description. Semantics-based information acquisition is achieved through the uniform modeling, representation, and handling of domain-specific knowledge, both content-based and procedural. The system has been validated using information located on several repositories in the web and its performance is reported in terms of precision and recall.

Artificial Intelligence↗

PubMed2004

Automatic arrhythmia detection based on time and time-frequency analysis of heart rate variability.

We have developed an automatic arrhythmia detection system, which is based on heart rate features only. Initially, the RR interval duration signal is extracted from ECG recordings and segmented into small intervals. The analysis is based on both time and time-frequency (t-f) features. Time domain measurements are extracted and several combinations between the obtained features are used for the training of a set of neural networks. Short time Fourier transform and several time-frequency distributions (TFD) are used in the t-f analysis. The features obtained are used for the training of a set of neural networks, one for each distribution. The proposed approach is tested using the MIT-BIH arrhythmia database and satisfactory results are obtained for both sensitivity and specificity (87.5 and 89.5%, respectively, for time domain analysis and 90 and 93%, respectively, for t-f domain analysis).

Arrhythmias, Cardiac↗

PubMed2004

Automated ischemic beat classification using genetic algorithms and multicriteria decision analysis.

Cardiac beat classification is a key process in the detection of myocardial ischemic episodes in the electrocardiographic signal. In the present study, we propose a multicriteria sorting method for classifying the cardiac beats as ischemic or not. Through a supervised learning procedure, each beat is compared to preclassified category prototypes under five criteria. These criteria refer to ST segment changes, T wave alterations, and the patient's age. The difficulty in applying the above criteria is the determination of the required method parameters, namely the thresholds and weight values. To overcome this problem, we employed a genetic algorithm, which, after proper training, automatically calculates the optimum values for the above parameters. A task-specific cardiac beat database was developed for training and testing the proposed method using data from the European Society of Cardiology ST-T database. Various experimental tests were carried out in order to adjust each module of the classification system. The obtained performance was 91% in terms of both sensitivity and specificity and compares favorably to other beat classification approaches proposed in the literature.

Age Factors↗

PubMed2004

An automated method for lumen and media-adventitia border detection in a sequence of IVUS frames.

In this paper, we present a method for the automated detection of lumen and media-adventitia border in sequential intravascular ultrasound (IVUS) frames. The method is based on the use of deformable models. The energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. A simulated annealing scheme is included to ensure convergence at a global minimum. The method overcomes distortions in the expected image pattern, due to the presence of calcium, employing a specialized structure of the neural network and boundary correction schemas which are based on a priori knowledge about the vessel geometry. The proposed method is evaluated using sequences of IVUS frames from 18 arterial segments, some of them indicating calcified regions. The obtained results demonstrate that our method is statistically accurate, reproducible, and capable to identify the regions of interest in sequences of IVUS frames.

Algorithms↗

PubMed2003

Greedy mixture learning for multiple motif discovery in biological sequences.

MOTIVATION: This paper studies the problem of discovering subsequences, known as motifs, that are common to a given collection of related biosequences, by proposing a greedy algorithm for learning a mixture of motifs model through likelihood maximization. The approach adds sequentially a new motif to a mixture model by performing a combined scheme of global and local search for appropriately initializing its parameters. In addition, a hierarchical partitioning scheme based on kd-trees is presented for partitioning the input dataset in order to speed-up the global searching procedure. The proposed method compares favorably over the well-known MEME approach and treats successfully several drawbacks of MEME. RESULTS: Experimental results indicate that the algorithm is advantageous in identifying larger groups of motifs characteristic of biological families with significant conservation. In addition, it offers better diagnostic capabilities by building more powerful statistical motif-models with improved classification accuracy.

Algorithms↗

PubMed2002

An ischemia detection method based on artificial neural networks.

An automated technique was developed for the detection of ischemic episodes in long duration electrocardiographic (ECG) recordings that employs an artificial neural network. In order to train the network for beat classification, a cardiac beat dataset was constructed based on recordings from the European Society of Cardiology (ESC) ST-T database. The network was trained using a Bayesian regularisation method. The raw ECG signal containing the ST segment and the T wave of each beat were the inputs to the beat classification system and the output was the classification of the beat. The input to the network was produced through a principal component analysis (PCA) to achieve dimensionality reduction. The network performance in beat classification was tested on the cardiac beat database providing 90% sensitivity (Se) and 90% specificity (Sp). The neural beat classifier is integrated in a four-stage procedure for ischemic episode detection. The whole system was evaluated on the ESC ST-T database. When aggregate gross statistics was used the Se was 90% and the positive predictive accuracy (PPA) 89%. When aggregate average statistics was used the Se became 86% and the PPA 87%. These results are better than other reported.

Automation↗

PubMed2002

Use of a novel rule-based expert system in the detection of changes in the ST segment and the T wave in long duration ECGs.

The development of a new fast and robust computerised system is examined in detecting electrocardiogram (ECG) changes in long duration ECG recordings. The system distinguishes these changes between ST-segment deviation and T-wave alterations and can support the produced diagnosis by providing explanations for the decisions made. The European Society of Cardiology ST-T Database was used for evaluating the performance of the system. Sensitivity and positive predictive accuracy were the performance measures used and the proposed system scored 92.02% and 93.77%, respectively, in detecting ST-segment episodes and 91.09% and 80.09% in detecting T-wave episodes. By using the chi-square test we also compared the performance of the system between ECG recordings with minimal and substantial amount of noise. The sensitivity of the proposed system is higher than of other algorithms reported in the literature and the positive predictive accuracy is comparable to, or better than, most of them.

Algorithms↗