Inspiratory Muscle Training Reduces Sympathetic Nervous Activity and Improves Inspiratory Muscle Weakness and Quality of Life in Patients With Chronic Heart Failure A CLINICAL TRIAL

PURPOSE: To evaluate the effect of inspiratory muscle training (IMT) on cardiac autonomic modulation and on peripheral nerve sympathetic activity in patients with chronic heart failure (CHF). METHODS: Functional capacity, low-frequency (LF) and high-frequency (HF) components of heart rate variability, muscle sympathetic nerve activity inferred by microneurography, and quality of life were determined in 27 patients with CHF who had been sequentially allocated to 1 of 2 groups: (1) control group (with no intervention) and (2) IMT group. Inspiratory muscle training consisted of respiratory exercises, with inspiratory threshold loading of seven 30-minute sessions per week for a period of 12 weeks, with a monthly increase of 30% in maximal inspiratory pressure (PImax) at rest. Multivariate analysis was applied to detect differences between baseline and followup period. RESULTS: Inspiratory muscle training significantly increased PImax (59.2 +/- 4.9 vs 87.5 +/- 6.5 cmH(2)O, P = .001) and peak oxygen uptake (14.4 +/- 0.7 vs 18.9 +/- 0.8 mL.kg(-1).min(-1), P = .002); decreased the peak ventilation (V. E) +/- carbon dioxide production (V-CO2) ratio (35.8 +/- 0.8 vs 32.5 +/- 0.4, P = .001) and the (V) over dotE +/-(V) over dotCO(2) slope (37.3 +/- 1.1 vs 31.3 +/- 1.1, P = .004); increased the HF component (49.3 +/- 4.1 vs 58.4 +/- 4.2 normalized units, P = .004) and decreased the LF component (50.7 +/- 4.1 vs 41.6 +/- 4.2 normalized units, P = .001) of heart rate variability; decreased muscle sympathetic nerve activity (37.1 +/- 3 vs 29.5 +/- 2.3 bursts per minute, P = .001); and improved quality of life. No significant changes were observed in the control group. CONCLUSION: Home-based IMT represents an important strategy to improve cardiac and peripheral autonomic controls, functional capacity, and quality of life in patients with CHF.

The Effectiveness of a Voice Training Program for Telemarketers

Purpose. To use a randomized design to evaluate the effectiveness of voice training programs for telemarketers via multidimensional analysis. Methods. Forty-eight telemarketers were randomly assigned to two groups: voice training group (n = 14) who underwent training over an 8-week period and a nontraining control group (n = 34). Before and after training, recordings of the sustained vowel /epsilon/ and connected were collected for acoustic and perceptual analyses. Results. Based on pre- and posttraining comparisons, the voice training group presented with a significant reduction in percent jitter (P = 0.044). No other significant differences were observed, and inter-rater reliability varied from poor to fair. Conclusions. These findings suggest that voice training improved a single acoustic dimension, but do not change perceptual dimension of telemarketers' voices.

Academic and clinical preparation in speech-language pathology and audiology: a global training consortium

ABSTRACT: Purpose: To describe a research-based global curriculum in speech-language pathology and audiology that is part of a funded cross-linguistic consortium among 2 U.S. and 2 Brazilian universities. Method: The need for a global curriculum in speechlanguage pathology and audiology is outlined, and different funding sources are identified to support development of a global curriculum. The U.S. Department of Education’s Fund for the Improvement of Post-Secondary Education (FIPSE), in conjunction with the Brazilian Ministry of Education (Fundacao Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior; CAPES), funded the establishment of a shared research curriculum project, “Consortium for Promoting Cross-Linguistic Understanding of Communication Disabilities in Children” for East Tennessee State University and the University of Northern Iowa and 2 Brazilian universities (Universidade Federal de Santa Maria and Universidade de São Paulo-Baurú). Results: The goals and objectives of the research-based global curriculum are summarized, and a description of an Internet-based course, “Different Languages, One World,” is provided Conclusion: Partnerships such as the FIPSE–CAPES consortium provide a foundation for training future generations of globally and research-prepared practitioners in speechlanguage pathology and audiology.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

From inverted pendulum to N-link chain: inertial sensors-based assessment of movement kinematics and dynamics for functional evaluation and rehabilitation

Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

Antarctic cloud spectral emission from ground-based measurements, a focus on far infrared signatures

The present work belongs to the PRANA project, the first extensive field campaign of observation of atmospheric emission spectra covering the Far InfraRed spectral region, for more than two years. The principal deployed instrument is REFIR-PAD, a Fourier transform spectrometer used by us to study Antarctic cloud properties. A dataset covering the whole 2013 has been analyzed and, firstly, a selection of good quality spectra is performed, using, as thresholds, radiance values in few chosen spectral regions. These spectra are described in a synthetic way averaging radiances in selected intervals, converting them into BTs and finally considering the differences between each pair of them. A supervised feature selection algorithm is implemented with the purpose to select the features really informative about the presence, the phase and the type of cloud. Hence, training and test sets are collected, by means of Lidar quick-looks. The supervised classification step of the overall monthly datasets is performed using a SVM. On the base of this classification and with the help of Lidar observations, 29 non-precipitating ice cloud case studies are selected. A single spectrum, or at most an average over two or three spectra, is processed by means of the retrieval algorithm RT-RET, exploiting some main IR window channels, in order to extract cloud properties. Retrieved effective radii and optical depths are analyzed, to compare them with literature studies and to evaluate possible seasonal trends. Finally, retrieval output atmospheric profiles are used as inputs for simulations, assuming two different crystal habits, with the aim to examine our ability to reproduce radiances in the FIR. Substantial mis-estimations are found for FIR micro-windows: a high variability is observed in the spectral pattern of simulation deviations from measured spectra and an effort to link these deviations to cloud parameters has been performed.

Content and English Language Integrated Learning: The use of Moodle in Aircraft Maintenance Training Programs

The aim of this work is to develop a prototype of an e-learning environment that can foster Content and Language Integrated Learning (CLIL) for students enrolled in an aircraft maintenance training program, which allows them to obtain a license valid in all EU member states. Background research is conducted to retrace the evolution of the field of educational technology, analyzing different learning theories – behaviorism, cognitivism, and (socio-)constructivism – and reflecting on how technology and its use in educational contexts has changed over time. Particular attention is given to technologies that have been used and proved effective in Computer Assisted Language Learning (CALL). Based on the background research and on students’ learning objectives, i.e. learning highly specialized contents and aeronautical technical English, a bilingual approach is chosen, three main tools are identified – a hypertextbook, an exercise creation activity, and a discussion forum – and the learning management system Moodle is chosen as delivery medium. The hypertextbook is based on the technical textbook written in English students already use. In order to foster text comprehension, the hypertextbook is enriched by hyperlinks and tooltips. Hyperlinks redirect students to webpages containing additional information both in English and in Italian, while tooltips show Italian equivalents of English technical terms. The exercise creation activity and the discussion forum foster interaction and collaboration among students, according to socio-constructivist principles. In the exercise creation activity, students collaboratively create a workbook, which allow them to deeply analyze and master the contents of the hypertextbook and at the same time create a learning tool that can help them, as well as future students, to enhance learning. In the discussion forum students can discuss their individual issues, content-related, English-related or e-learning environment-related, helping one other and offering instructors suggestions on how to improve both the hypertextbook and the workbook based on their needs.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

Is hypoxia training good for muscles and exercise performance?

Altitude training has become very popular among athletes as a means to further increase exercise performance at sea level or to acclimatize to competition at altitude. Several approaches have evolved during the last few decades, with "live high-train low" and "live low-train high" being the most popular. This review focuses on functional, muscular, and practical aspects derived from extensive research on the "live low-train high" approach. According to this, subjects train in hypoxia but remain under normoxia for the rest of the time. It has been reasoned that exercising in hypoxia could increase the training stimulus. Hypoxia training studies published in the past have varied considerably in altitude (2300-5700 m) and training duration (10 days to 8 weeks) and the fitness of the subjects. The evidence from muscle structural, biochemical, and molecular findings point to a specific role of hypoxia in endurance training. However, based on the available performance capacity data such as maximal oxygen uptake (Vo(2)max) and (maximal) power output, hypoxia as a supplement to training is not consistently found to be advantageous for performance at sea level. Stronger evidence exists for benefits of hypoxic training on performance at altitude. "Live low-train high" may thus be considered when altitude acclimatization is not an option. In addition, the complex pattern of gene expression adaptations induced by supplemental training in hypoxia, but not normoxia, suggest that muscle tissue specifically responds to hypoxia. Whether and to what degree these gene expression changes translate into significant changes in protein concentrations that are ultimately responsible for observable structural or functional phenotypes remains open. It is conceivable that the global functional markers such as Vo(2)max and (maximal) power output are too coarse to detect more subtle changes that might still be functionally relevant, at least to high-level athletes.

Secondary prevention through cardiac rehabilitation: physical activity counselling and exercise training: key components of the position paper from the Cardiac Rehabilitation Section of the European Association of Cardiovascular Prevention and Rehabilitation

Cardiac patients after an acute event and/or with chronic heart disease deserve special attention to restore their quality of life and to maintain or improve functional capacity. They require counselling to avoid recurrence through a combination of adherence to a medication plan and adoption of a healthy lifestyle. These secondary prevention targets are included in the overall goal of cardiac rehabilitation (CR). Cardiac rehabilitation can be viewed as the clinical application of preventive care by means of a professional multi-disciplinary integrated approach for comprehensive risk reduction and global long-term care of cardiac patients. The CR approach is delivered in tandem with a flexible follow-up strategy and easy access to a specialized team. To promote implementation of cardiac prevention and rehabilitation, the CR Section of the EACPR (European Association of Cardiovascular Prevention and Rehabilitation) has recently completed a Position Paper, entitled 'Secondary prevention through cardiac rehabilitation: A condition-oriented approach'. Components of multidisciplinary CR for seven clinical presentations have been addressed. Components include patient assessment, physical activity counselling, exercise training, diet/nutritional counselling, weight control management, lipid management, blood pressure monitoring, smoking cessation, and psychosocial management. Cardiac rehabilitation services are by definition multi-factorial and comprehensive, with physical activity counselling and exercise training as central components in all rehabilitation and preventive interventions. Many of the risk factor improvements occurring in CR can be mediated through exercise training programmes. This call-for-action paper presents the key components of a CR programme: physical activity counselling and exercise training. It summarizes current evidence-based best practice for the wide range of patient presentations of interest to the general cardiology community.

Structural plasticity in the language system related to increased second language proficiency

While functional changes linked to second language learning have been subject to extensive investigation, the issue of learning-dependent structural plasticity in the fields of bilingualism and language comprehension has so far received less notice. In the present study we used voxel-based morphometry to monitor structural changes occurring within five months of second language learning. Native English-speaking exchange students learning German in Switzerland were examined once at the beginning of their stay and once about five months later, when their German language skills had significantly increased. We show that structural changes in the left inferior frontal gyrus are correlated with the increase in second language proficiency as measured by a paper-and-pencil language test. Contrary to the increase in proficiency and grey matter, the absolute values of grey matter density and second language proficiency did not correlate (neither on first nor on second measurement). This indicates that the individual amount of learning is reflected in brain structure changes, regardless of absolute proficiency.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.