Fractal Analysis of Cardiovascular Signals Empowering the Bioengineering Knowledge

The cardiovascular system is composed of a complex network of vessels, where highly uniform hierarchical branching structures are regulated by the anatomy and local flow requirements. Arteries bifurcate many times before they become capillaries where the scaling factor of vessel length, diameter and angle between two children branches is established at each level of recurrence. This behaviour can be easily described using a fractal scaling principle. Moreover, it was observed that the basic pattern of blood distribution is also fractal, imposed both by the anatomy of the vascular tree and the local regulation of vascular tone. In this chapter, arterial physiology was analysed, where waveform complexity of arterial pressure time series was related to arterial stiffness changes, pulse pressure variations and the presence wave reflection. Fractal dimension was used as a nonlinear measure, giving place to a ‘holistic approach of fractal dimension variations throughout the arterial network’, both in health and disease

Complex Systems with Self‐Elimination of Dissipation with Implication in Bio‐Structural Behavior Via Nondifferentiability

In the present chapter, we show that the use of the nondifferentiable mathematical procedures, developed in the Scale Relativity Theory with constant arbitrary fractal dimension, simplifies very much the dynamics analyses in the case of complex systems. By applying such a procedure to various complex systems dynamics (biological structures, ablation or discharge plasmas, etc.), we are able to observe that it starts from a steady (oscillating state) and as the external factor is varied the system undergoes significant changes. The systems evolve asymptotically through various transition, toward a chaotic regime (like bifurcations or intermittencies), but never reaching it. Another important reveal from the study of the system’s dynamics was the presence of various steady states depending on the resolution scale at which the theoretical investigations are performed

Cardiorespiratory Function in Young Adults With a History of Covid-19 Infection

Objective. Respiratory complications may persist several months into the recovery period following COVID-19 infection. This study evaluated respiratory function and oxygen saturation variability between young adults with a history of COVID-19 infection and controls. Associations between cardiorespiratory function with potential biobehavioral correlates of COVID-19 infection were also explored.Methods. 57 adults ages 18 to 65 participated in this study (24 COVID+, 33 Control). Spirometry was used to assess pulmonary function volumes of forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1/FVC and peak expiratory flow (PEF). Exhaled nitric oxide (FeNO) was measured using the NiOX VERO, a handheld electrochemical nitric oxide analyzer and taken as a proxy of airway inflammation. Systemic inflammation levels were assessed using salivary concentrations of inflammatory biomarkers. Oxygen saturation variability was quantified via extended continuous oxygen saturation (SpO2) monitoring using linear and nonlinear analyses. Network physiology analysis was conducted to evaluate cardiorespiratory control between SpO2, heart rate (HR), respiratory rate and skin temperature signals measured by continuous ambulatory monitoring with an Equivital EQO2 LifeMonitor. Physical activity levels and sedentary time were assessed using 9-day accelerometry. COVID-19 symptom severity was assessed by participant self-report via questionnaires. Results. No group differences were observed for pulmonary function of FVC (COVID+: 4.22±1.01, C: 4.43±1.06 L, p=.663), FEV1 (COVID+: 3.45±0.72, C: 3.57±0.92 L, p=.865), PEF (COVID+: 349.63±105.54, C: 373.73±140.61 L/min, p=.370), or FeNO (COVID+: 16.61±13.04, C: 20.03±20.11 ppb, p=.285). Linear and nonlinear oxygen saturation variability did not differ between adults with a history of COVID-19 infection and controls with no history of infection (p\u3e0.05). Cardiorespiratory function measured using network analysis of did not differ between recovering COVID-19 individuals and controls (p\u3e0.05). Sedentary time was inversely associated with FEV1 (r=-.392, p=.040), PEF (r=-.579, p=.003), and IL-6 concentrations (r=- .370, p=.049). COVID-19 disease severity was inversely associated with FVC (r=-.461, p=.012) and FEV1 (r=-.365, p=.040). Number of symptoms was inversely associated with FVC (r=-.404, p=.025). Conclusions. Pulmonary function, inflammation levels and oxygen saturation variability were similar between individuals with a history of COVID-19 infection and controls without a history of COVID-19 infection. Network interactions between regulatory components of the cardiorespiratory system were also similar between recovering COVID-19 individuals and controls. Findings suggest that cardiorespiratory function and dynamic control of SpO2 may not be impaired following COVID-19 infection in young adults. Moreover, increased sedentary time and disease severity may have negative effects on pulmonary function in individuals recovering from COVID-19

High Resolution Maps of the Vasculature of An Entire Organ

The structure of vascular networks represents a great, unsolved problem in anatomy. Network geometry and topology differ dramatically from left to right and person to person as evidenced by the superficial venation of the hands and the vasculature of the retinae. Mathematically, we may state that there is no conserved topology in vascular networks. Efficiency demands that these networks be regular on a statistical level and perhaps optimal. We have taken the first steps towards elucidating the principles underlying vascular organization, creating the rst map of the hierarchical vasculature (above the capillaries) of an entire organ. Using serial blockface microscopy and fluorescence imaging, we are able to identify vasculature at 5 μm resolution. We have designed image analysis software to segment, align, and skeletonize the resulting data, yielding a map of the individual vessels. We transformed these data into a mathematical graph, allowing computationally efficient storage and the calculation of geometric and topological statistics for the network. Our data revealed a complexity of structure unexpected by theory. We observe loops at all scales that complicate the assignment of hierarchy within the network and the existence of set length scales, implying a distinctly non-fractal structure of components within

Exploring the combined use of electrical and hemodynamic brain activity to investigate brain function

This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p< 0.040 and p =0.000), and relative cross mutual information (p < 0.003 and p < 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible

Advanced Ceramics and Application : new frontiers in multifunctional material science and processing : program and the book of abstracts : IV Serbian Ceramic Society Conference, Sep 21-23 September 2015, Belgrade

Program and the book of abstracts of the II Serbian Ceramic Society Conference, 21-23, September 2015, Belgrad

Poster abstract research showcase College of Science and Technology

Welcome to the College of Science and Technology Research and Innovation Showcase 2014, an event which celebrates the research achievements of our science disciplines. Our research brings together scientists from architecture and the built environment through to computing, engineering, mathematics and physics and biology, geography and environmental science. We are committed to build on our strengths, and our key vision is to drive research growth and impact through exploitation of the synergy between research, innovation and enterprise. This year’s showcase event includes over 70 posters illustrating the excellent research being pursued, a Dean's prize recognising the achievements of an early career researcher, prizes for the best student and best students’ posters and journal papers, and this proceedings of abstracts showing the high quality and range of research in the College of Science and Technology

Fractal analyses of some natural systems

Fractal dimensions are estimated by the box-counting method for real world data sets and for mathematical models of three natural systems. 1 he natural systems are nearshore sea wave profiles, the topography of Shei-pa National Park in Taiwan, and the normalised difference vegetation index (NDV1) image of a fresh fern. I he mathematical models which represent the natural systems utilise multi-frequency sinusoids for the sea waves, a synthetic digital elevation model constructed by the mid-point displacement method for the topography and the Iterated Function System (IFS) codes for the fern leaf. The results show that similar fractal dimensions are obtained for discrete sub-sections of the real and synthetic one-dimensional wave data, whilst different fractal dimensions are obtained for discrete sections of the real and synthetic topographical and fern data. The similarities and differences are interpreted in the context of system evolution which was introduced by Mandelbrot (1977). Finally, the results for the fern images show that use of fractal dimensions can successfully separate void and filled elements of the two-dimensional series

Tissue Damage Characterization Using Non-invasive Optical Modalities

The ability to determine the degree of cutaneous and subcutaneous tissue damage is essential for proper wound assessment and a significant factor for determining patient treatment and morbidity. Accurate characterization of tissue damage is critical for a number of medical applications including surgical removal of nonviable tissue, severity assessment of subcutaneous ulcers, and depth assessment of visually open wounds. The main objective of this research was to develop a non-invasive method for identifying the extent of tissue damage underneath intact skin that is not apparent upon visual examination. This work investigated the relationship between tissue optical properties, blood flow, and tissue viability by testing the hypotheses that (a) changes in tissue oxygenation and/or microcirculatory blood flow measurable by Diffuse Near Infrared Spectroscopy (DNIRS) and Diffuse Correlation Spectroscopy (DCS) differ between healthy and damaged tissue and (b) the magnitude of those changes differs for different degrees of tissue damage. This was accomplished by developing and validating a procedure for measuring microcirculatory blood flow and tissue oxygenation dynamics at multiple depths (up to 1 centimeter) using non-invasive DCS and DNIRS technologies. Due to the lack of pressure ulcer animal models that are compatible with our optical systems, a proof of concept was conducted in a porcine burn model prior to conducting clinical trials in order to assess the efficacy of the system in-vivo. A reduction in total hemoglobin was observed for superficial (5%) and deep burns (35%) along with a statistically significant difference between the optical properties of superficial and deep burns (p < 0.05). Burn depth and viable vessel density were estimated via histological samples. 42% of vessels in the dermal layer were viable for superficial burns, compared to 25% for deep burns. The differences detected in optical properties and hemoglobin content by optical measurements correlated with the extent of tissue injury observed in histological stains. After proof of concept in animals, a human study was conducted and optical data was collected from 20 healthy subjects and 8 patients at risk of developing pressure ulcers. Blood flow index (BFI) values from the sacral region of patients were compared with those of healthy volunteers. Prior to loading measurements, baseline BFI values were measured in subjects in lateral position. These values were systematically higher for patients who developed open ulcers than for the other research subjects. While under the loading position, patients who developed a pressure ulcer had a decrease in BFI from baseline values an order of magnitude larger than healthy subjects (p < 0.01) and patients whose redness dissipated (p < 0.01). The hyperemic response, when pressure was released as the patient was moved back to a lateral position, showed a decreasing trend from one session to the next for patients who developed open ulcers. Overall, this work presents a novel non-invasive method of pressure ulcer assessment and provides an improvement over current assessment methods. The obtained results suggest the system may potentially predict whether non-blanchable redness will develop into an advanced pressure ulcer within four weeks from initial observation.Ph.D., Biomedical Engineering -- Drexel University, 201

Physiological time-series investigations of cardiovascular regulation in healthy young adults during physical exercise.

Physiological parameters may be recorded non-invasively to gain information on cardiovascular function which can then characterise populations with various pathologies. Physical exercise produces specific autonomic nervous system (ANS) changes. There has been no comprehensive profiling of cardiovascular function during exercise or simultaneous characterisation of the influence of exercise on cardiac ventricular function and electrical activity. This work aims to address that, using a combination of physiological parameters. Between-lead agreement for ambulatory electrocardiographic (EGG) depolarisation-repolarisation (QT) interval was quantified during rest and exercise. In contrast to cardiac interval (RR) data, between-lead bias and limits of agreement for QT interval data should be quantified when reporting results from an ambulatory EGG system and between-gender QT differences should also be accounted for. EGG electrode location appears to significantly affect QT-RR hysteresis, the shortening of the post-exercise QT interval relative to that at similar heart rates during exercise or pre-exercise rest, further emphasising the need for standardisation of EGG electrode placement. Sample entropy (SampEn) measures data complexity. Few studies have compared SampEn of RR data (SampEn-RR) during exercise, whilst none have examined SampEn for the corresponding QT interval (SampEn-QT). Fractal analysis assesses data correlation and scaling structures. Detrended fluctuation analysis (DFA) provides a scaling exponent (a) which describes these properties. This has not been quantified for RR interval data during post-exercise recovery and has not been reported for QT interval data. Differences in a magnitudes for RR and QT data suggest that these quantities have different fractal properties. Exercise perturbs the resting QT-RR relationship via hysteresis. The QT variability index (QTVI) quantifies the relative autonomic influence on the atrial and ventricular myocardium during rest and exercise. QTVI is a consistent measure of cardiac ventricular function and as such appears to be a more useful index than other parameters based on RR or QT interval alone