526 research outputs found
Proceedings, MSVSCC 2019
Old Dominion University Department of Modeling, Simulation & Visualization Engineering (MSVE) and the Virginia Modeling, Analysis and Simulation Center (VMASC) held the 13th annual Modeling, Simulation & Visualization (MSV) Student Capstone Conference on April 18, 2019.
The Conference featured student research and student projects that are central to MSV. Also participating in the conference were faculty members who volunteered their time to impart direct support to their students’ research, facilitated the various conference tracks, served as judges for each of the tracks, and provided overall assistance to the conference.
Appreciating the purpose of the conference and working in a cohesive, collaborative effort, resulted in a successful symposium for everyone involved. These proceedings feature the works that were presented at the conference.
Capstone Conference Chair: Dr. Yuzhong Shen Capstone Conference Student Chair: Daniel Pere
Deep Learning Based Malware Classification Using Deep Residual Network
The traditional malware detection approaches rely heavily on feature extraction procedure, in this paper we proposed a deep learning-based malware classification model by using a 18-layers deep residual network. Our model uses the raw bytecodes data of malware samples, converting the bytecodes to 3-channel RGB images and then applying the deep learning techniques to classify the malwares. Our experiment results show that the deep residual network model achieved an average accuracy of 86.54% by 5-fold cross validation. Comparing to the traditional methods for malware classification, our deep residual network model greatly simplify the malware detection and classification procedures, it achieved a very good classification accuracy as well. The dataset we used in this paper for training and testing is Malimg dataset, one of the biggest malware datasets released by vision research lab of UCSB
Development of a sub-miniature acoustic sensor for wireless monitoring of heart rate
This thesis presents the development of a non-invasive, wireless, low-power, phonocardiographic (PCG) or heart sound sensor platform suitable for long-term monitoring of heart function. The core of this development process involves a study of the feasibility of this conceptual system and the development of a prototype mixed-signals integrated circuit (IC) to form the integral component of the proposed sensor.
The feasibility study of the proposed long-term monitoring sensor is divided into two main parts. The first part of the study investigates the technological aspect of the conceptual system, via a system level design. This is to prove the technological or operational feasibility of the system, where the system can be built completely using discrete, off-the-shelf electronics components to satisfy the size, power consumption, battery life and operational requirements of the sensor platform. The second part of the study concentrates on the post-processing of the heart sounds and murmurs or PCG data recorded. This is where a number of different de-noising algorithms are studied and their relative performance compared when applied to a variety of different noisy heart sound signals that would likely be acquired using the proposed sensor in everyday life. This was done to demonstrate the functional feasibility of the proposed system, where the ambient acoustic noise in the recorded PCG data can be effectively suppressed and therefore meaningful analysis of heart function i.e. heart rate, can be performed on the data.
After the feasibility of the conceptual system has been demonstrated, the final part of this thesis discusses the synthesis and testing of a 0.35 μm CMOS technology prototype mixed analog-digital integrated circuit (IC) to miniaturise part of this sensor platform outlined in the system level design, conducted in the earlier part of this thesis, to achieve the objective specifications – in terms of the size and power consumption. A new implementation of the multi-tanh triplet transconductor is introduced to construct a pair of 100 nW analogue 4th order Gm-C signal conditioning filters. Furthermore, a 7 μW digital circuit was designed to drive the analog-to-digital conversion cycle of the Linear Technology LTC1288 ADC and synchronise the ADC’s output to generate the Manchester encoded data compatible with the Holt Integrated Circuit HI-15530 Manchester Encoder/Decoder
Telemedicine
Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios
Dynamics, Electromyography and Vibroarthrography as Non-Invasive Diagnostic Tools: Investigation of the Patellofemoral Joint
The knee joint plays an essential role in the human musculoskeletal system. It has evolved to withstand extreme loading conditions, while providing almost frictionless joint movement. However, its performance may be disrupted by disease, anatomical deformities, soft tissue imbalance or injury. Knee disorders are often puzzling, and accurate diagnosis may be challenging. Current evaluation approach is usually limited to a detailed interview with the patient, careful physical examination and radiographic imaging. The X-ray screening may reveal bone degeneration, but does not carry sufficient information of the soft tissue conditions. More advanced imaging tools such as MRI or CT are available, but expensive, time consuming and can be used only under static conditions. Moreover, due to limited resolution the radiographic techniques cannot reveal early stage arthritis. The arthroscopy is often the only reliable option, however due to its semi-invasive nature, it cannot be considered as a practical diagnostic tool. Therefore, the motivation for this work was to combine three scientific methods to provide a comprehensive, non-invasive evaluation tool bringing insight into the in vivo, dynamic conditions of the knee joint and articular cartilage degeneration.
Electromyography and inverse dynamics were employed to independently determine the forces present in several muscles spanning the knee joint. Though both methods have certain limitations, the current work demonstrates how the use of these two methods concurrently enhances the biomechanical analysis of the knee joint conditions, especially the performance of the extensor mechanism. The kinetic analysis was performed for 12 TKA, 4 healthy individuals in advanced age and 4 young subjects. Several differences in the knee biomechanics were found between the three groups, identifying age-related and post-operative decrease in the extensor mechanism efficiency, explaining the increased effort of performing everyday activities experienced by the elderly and TKA subjects.
The concept of using accelerometers to assess the cartilage degeneration has been proven based on a group of 23 subjects with non-symptomatic knees and 52 patients suffering from knee arthritis. Very high success (96.2%) of pattern classification obtained in this work clearly demonstrates that vibroarthrography is a promising, non-invasive and low-cost technique offering screening capabilities
Extraction and Detection of Fetal Electrocardiograms from Abdominal Recordings
The non-invasive fetal ECG (NIFECG), derived from abdominal surface electrodes, offers novel diagnostic possibilities for prenatal medicine. Despite its straightforward applicability, NIFECG signals are usually corrupted by many interfering sources. Most significantly, by the maternal ECG (MECG), whose amplitude usually exceeds that of the fetal ECG (FECG) by multiple times. The presence of additional noise sources (e.g. muscular/uterine noise, electrode motion, etc.) further affects the signal-to-noise ratio (SNR) of the FECG. These interfering sources, which typically show a strong non-stationary behavior, render the FECG extraction and fetal QRS (FQRS) detection demanding signal processing tasks.
In this thesis, several of the challenges regarding NIFECG signal analysis were addressed. In order to improve NIFECG extraction, the dynamic model of a Kalman filter approach was extended, thus, providing a more adequate representation of the mixture of FECG, MECG, and noise. In addition, aiming at the FECG signal quality assessment, novel metrics were proposed and evaluated. Further, these quality metrics were applied in improving FQRS detection and fetal heart rate estimation based on an innovative evolutionary algorithm and Kalman filtering signal fusion, respectively. The elaborated methods were characterized in depth using both simulated and clinical data, produced throughout this thesis. To stress-test extraction algorithms under ideal circumstances, a comprehensive benchmark protocol was created and contributed to an extensively improved NIFECG simulation toolbox. The developed toolbox and a large simulated dataset were released under an open-source license, allowing researchers to compare results in a reproducible manner.
Furthermore, to validate the developed approaches under more realistic and challenging situations, a clinical trial was performed in collaboration with the University Hospital of Leipzig. Aside from serving as a test set for the developed algorithms, the clinical trial enabled an exploratory research. This enables a better understanding about the pathophysiological variables and measurement setup configurations that lead to changes in the abdominal signal's SNR. With such broad scope, this dissertation addresses many of the current aspects of NIFECG analysis and provides future suggestions to establish NIFECG in clinical settings.:Abstract
Acknowledgment
Contents
List of Figures
List of Tables
List of Abbreviations
List of Symbols
(1)Introduction
1.1)Background and Motivation
1.2)Aim of this Work
1.3)Dissertation Outline
1.4)Collaborators and Conflicts of Interest
(2)Clinical Background
2.1)Physiology
2.1.1)Changes in the maternal circulatory system
2.1.2)Intrauterine structures and feto-maternal connection
2.1.3)Fetal growth and presentation
2.1.4)Fetal circulatory system
2.1.5)Fetal autonomic nervous system
2.1.6)Fetal heart activity and underlying factors
2.2)Pathology
2.2.1)Premature rupture of membrane
2.2.2)Intrauterine growth restriction
2.2.3)Fetal anemia
2.3)Interpretation of Fetal Heart Activity
2.3.1)Summary of clinical studies on FHR/FHRV
2.3.2)Summary of studies on heart conduction
2.4)Chapter Summary
(3)Technical State of the Art
3.1)Prenatal Diagnostic and Measuring Technique
3.1.1)Fetal heart monitoring
3.1.2)Related metrics
3.2)Non-Invasive Fetal ECG Acquisition
3.2.1)Overview
3.2.2)Commercial equipment
3.2.3)Electrode configurations
3.2.4)Available NIFECG databases
3.2.5)Validity and usability of the non-invasive fetal ECG
3.3)Non-Invasive Fetal ECG Extraction Methods
3.3.1)Overview on the non-invasive fetal ECG extraction methods
3.3.2)Kalman filtering basics
3.3.3)Nonlinear Kalman filtering
3.3.4)Extended Kalman filter for FECG estimation
3.4)Fetal QRS Detection
3.4.1)Merging multichannel fetal QRS detections
3.4.2)Detection performance
3.5)Fetal Heart Rate Estimation
3.5.1)Preprocessing the fetal heart rate
3.5.2)Fetal heart rate statistics
3.6)Fetal ECG Morphological Analysis
3.7)Problem Description
3.8)Chapter Summary
(4)Novel Approaches for Fetal ECG Analysis
4.1)Preliminary Considerations
4.2)Fetal ECG Extraction by means of Kalman Filtering
4.2.1)Optimized Gaussian approximation
4.2.2)Time-varying covariance matrices
4.2.3)Extended Kalman filter with unknown inputs
4.2.4)Filter calibration
4.3)Accurate Fetal QRS and Heart Rate Detection
4.3.1)Multichannel evolutionary QRS correction
4.3.2)Multichannel fetal heart rate estimation using Kalman filters
4.4)Chapter Summary
(5)Data Material
5.1)Simulated Data
5.1.1)The FECG Synthetic Generator (FECGSYN)
5.1.2)The FECG Synthetic Database (FECGSYNDB)
5.2)Clinical Data
5.2.1)Clinical NIFECG recording
5.2.2)Scope and limitations of this study
5.2.3)Data annotation: signal quality and fetal amplitude
5.2.4)Data annotation: fetal QRS annotation
5.3)Chapter Summary
(6)Results for Data Analysis
6.1)Simulated Data
6.1.1)Fetal QRS detection
6.1.2)Morphological analysis
6.2)Own Clinical Data
6.2.1)FQRS correction using the evolutionary algorithm
6.2.2)FHR correction by means of Kalman filtering
(7)Discussion and Prospective
7.1)Data Availability
7.1.1)New measurement protocol
7.2)Signal Quality
7.3)Extraction Methods
7.4)FQRS and FHR Correction Algorithms
(8)Conclusion
References
(A)Appendix A - Signal Quality Annotation
(B)Appendix B - Fetal QRS Annotation
(C)Appendix C - Data Recording GU
Estrazione non invasiva del segnale elettrocardiografico fetale da registrazioni con elettrodi posti sull’addome della gestante (Non-invasive extraction of the fetal electrocardiogram from abdominal recordings by positioning electrodes on the pregnant woman’s abdomen)
openIl cuore è il primo organo che si sviluppa nel feto, particolarmente nelle primissime settimane di
gestazione. Rispetto al cuore adulto, quello fetale ha una fisiologia ed un’anatomia significativamente
differenti, a causa della differente circolazione cardiovascolare. Il benessere fetale si valuta
monitorando l’attività cardiaca mediante elettrocardiografia fetale (ECGf). L’ECGf invasivo (acquisito
posizionando elettrodi allo scalpo fetale) è considerato il gold standard, ma l’invasività che lo
caratterizza ne limita la sua applicabilità . Al contrario, l’uso clinico dell’ECGf non invasivo (acquisito
posizionando elettrodi sull’addome della gestante) è limitato dalla scarsa qualità del segnale risultante.
L’ECGf non invasivo si estrae da registrazioni addominali, che sono corrotte da differenti tipi di rumore,
fra i quali l’interferenza primaria è rappresentata dall’ECG materno. Il Segmented-Beat Modulation
Method (SBMM) è stato da me recentemente proposto come una nuova procedura di filtraggio basata
sul calcolo del template del battito cardiaco. SBMM fornisce una stima ripulita dell’ECG estratto da
registrazioni rumorose, preservando la fisiologica variabilità ECG del segnale originale. Questa
caratteristica è ottenuta grazie alla segmentazione di ogni battito cardiaco per indentificare i segmenti
QRS e TUP, seguito dal processo di modulazione/demodulazione (che include strecciamento e
compressione) del segmento TUP, per aggiustarlo in modo adattativo alla morfologia e alla durata di
ogni battito originario. Dapprima applicato all’ECG adulto al fine di dimostrare la sua robustezza al
rumore, l’SBMM è stato poi applicato al caso fetale. Particolarmente significativi sono i risultati relativi
alle applicazioni su ECGf non invasivo, dove l’SBMM fornisce segnali caratterizzati da un rapporto
segnale-rumore comparabile a quello caratterizzante l’ECGf invasivo. Tuttavia, l’SBMM può
contribuire alla diffusione dell’ECGf non invasiva nella pratica clinica.The heart is the first organ that develops in the fetus, particularly in the very early stages
of pregnancy. Compared to the adult heart, the physiology and anatomy of the fetal heart
exhibit some significant differences. These differences originate from the fact that the fetal
cardiovascular circulation is different from the adult circulation. Fetal well-being
evaluation may be accomplished by monitoring cardiac activity through fetal
electrocardiography (fECG). Invasive fECG (acquired through scalp electrodes) is the
gold standard but its invasiveness limits its clinical applicability. Instead, clinical use of
non-invasive fECG (acquired through abdominal electrodes) has so far been limited by its
poor signal quality. Non-invasive fECG is extracted from the abdominal recording and is
corrupted by different kind of noise, among which maternal ECG is the main interference.
The Segmented-Beat Modulation Method (SBMM) was recently proposed by myself as a
new template-based filtering procedure able to provide a clean ECG estimation from a
noisy recording by preserving physiological ECG variability of the original signal. The
former feature is achieved thanks to a segmentation procedure applied to each cardiac
beat in order to identify the QRS and TUP segments, followed by a
modulation/demodulation process (involving stretching and compression) of the TUP
segments to adaptively adjust each estimated cardiac beat to the original beat morphology
and duration. SBMM was first applied to adult ECG applications, in order to demonstrate
its robustness to noise, and then to fECG applications. Particularly significant are the
results relative to the non-invasive applications, where SBMM provided fECG signals
characterized by a signal-to-noise ratio comparable to that characterizing invasive fECG.
Thus, SBMM may contribute to the spread of this noninvasive fECG technique in the
clinical practice.INGEGNERIA DELL'INFORMAZIONEAgostinelli, AngelaAgostinelli, Angel
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