Obiettivi Formativi

Gli obiettivi e l'ambito del corso sono gli studenti ad acquisire una migliore comprensione della biostatistica, dell'informatica e della bioingegneria di base. Acquisire abilità in merito alla descrizione di dati statistici Comprendere i fondamenti della valutazione di probabilità di un evento. Comprendere i fondamenti dell’inferenza statistica. Saper interpretare in modo appropriato i più comuni metodi e test statistici. Fornire allo studente nozioni di forze e momenti applicati in ambito biomeccanico; di equilibrio di forze e delle caratteristiche dei materiali biomeccanici. Fornire allo studente le informazioni, sia in termini di nozioni che di metodologia di lavoro, caratterizzanti l’analisi del cammino, la composizione e l’uso delle protesi, ortesi , esoscheletri ed ausili. Acquisire un insieme di competenze scientifico- disciplinari relative alla realizzazione di sistemi di elaborazione delle informazioni, nonché alla loro gestione ed utilizzazione in vari contesti applicativi. Durante il corso saranno introdotti i concetti base dell’informatica e fornite le basi teoriche sui sistemi di elaborazione delle informazioni, sulle basi di dati, sui sistemi informativi, sull’interazione uomo-macchina, e sulla codifica e rappresentazione elettronica delle informazioni. Si intende fornire le basi necessarie per: - la lettura di articoli scientifici di interesse medico; - la presentazione di semplici serie di dati; - l’interpretazione di esami e strumenti di laboratorio e test clinici; - Acquisire nozioni di Evidence-Based- Medicine.

Learning Goals

The aims and the scope of the Course is to allow the students to acquire a better understanding of the basic biostatistics, informatics and bioengineering. Acquire skills in describing statistical data Understand the basics of probability assessment of an event. Understand the basics of statistical inflection. Know how to interpret the most common methods and statistical tests appropriately. Provide the students with notions of forces and moments applied in the biomechanical field; of equilibrium of forces and characteristics of biomechanical materials. Provide the student with information, both in terms of knowledge and working methodology, characterizing path analysis, composition and use of prosthesis, orthosis, exoskeleton and aids. Acquire a set of scientific-disciplinary competencies related to the creation of information processing systems and their management and use in various application contexts. During the course, the basic concepts of information technology will be introduced and provided theoretical bases on information processing systems, data bases, information systems, human-machine interaction, and electronic coding and electronic representation of information. It is intended to provide the necessary basis for: - the reading of scientific articles of medical interest; - the presentation of simple data sets; - the interpretation of laboratory examinations and instruments and clinical tests; - Acquire knowledge of concepts of Evidence-Based Medicine.

Metodi didattici

Durante le lezioni frontali verranno illustrati e commentati gli argomenti nel programma dei modulo. Ogni argomento teorico e contenente formule matematiche verrà spiegato con l’ausilio di esempi semplici e pratici, in modo che lo studente si focalizzi maggiormente sui concetti di base piuttosto che sulle formule. Molti termini tecnici verranno riportati sia in Italiano che in Inglese, in modo che lo studente possa autonomamente leggere la letteratura scientifica internazionale.

Teaching Methods

During the front lessons, the topics in the modules programs will be illustrated and commented. Each theoretical topic containing mathematical formulas will be explained with the help of simple and practical examples, so that the student focuses more on basic concepts than on formulas. Many technical terms will be reported both in Italian and English, so that the student can read the international scientific literature independently.

Prerequisiti

Conoscenza base dell'inglese. Conoscenze di base della matematica.

Prerequisites

Basic knowledge of English language. Basic knowledge of Mathematics.

Verifiche dell'apprendimento

Test di autovalutazione. L'accertamento del raggiungimento degli obiettivi previsti dal modulo prevede una prova scritta o orale, consistente principalmente in quesiti a risposta aperta su argomenti trattati nel corso. In questo modo, verrà accertata la conoscenza e la comprensione, da parte dello studente, sia dei principi teorici che delle loro applicazioni in campo medico e biologico mediante l’uso di esempi pratici.

Assessment

Self-evaluation test. The assessment of the achievement of the objectives set out in the module provides for a written or oral test, consisting primarily of open-ended questions on topics discussed in the course. That way, it will come the student's knowledge and understanding of the theoretical principles and of their applications in the medical and biological field through the use of practical examples.

Programma del Corso

Definition of statistics, biostatistics and medical statistics. Difference between descriptive and inferential statistics. Definition of variable. The role of variables. Types of variable. Data storage (tables and databases). Types of biostatistics and medical statistics. Descriptive statistics: objectives and techniques. How to describe nominal variables (tables, histograms, pie-charts, etc). Descriptive statistics: continuous or discrete quantitative variables. Representation of variability: histograms, dispersion graphs. Summary of possible central trend measures, dispersion, symmetry and curvature for quantitative variables. The arithmetic mean. The median. Fashion. The dispersion: range of variation, interquartile range, standard deviation, variation coefficient. Box diagram (box plot). Examples: histograms, box plot. Normal distribution. Normal distribution properties. Normal and non-normal distributions: mean, median and fashion. Asymmetry and Curtosis. Tests on tests to evaluate normality. Non-normalities and graphs to represent the distribution of data. The log-normal distribution: mean and geometric standard deviation. Distinction between parametric and nonparametric inferential statistics. Normal distribution: sampling. Test hypothesis on an average. Calculation of significance. One and two tail tests. The level of significance. Type I and Type II errors. Constraints and degrees of freedom. Student's distribution t (SD of unknown population). Comparison between two mediums: Appropriate data. Non-parametric tests: introduction. The rank. Mann-Whitney test. Yates Continuity Correction. Wilkoxon Test. Correlation of Pearson and Spearman. Evidence Based Medicine. Types of statistical studies and their significance. Concepts of forces and moments applied in the biomechanical field; of equilibrium of forces and characteristics of biomechanical materials. Analysis of the path, composition and use of prostheses, orthoses, exoskelets and aids. Realization of information processing systems, their management and utilization in various application contexts. Information processing systems, data bases, information systems, man-machine interaction, and electronic coding and representation of information.

Course Syllabus

Definition of statistics, biostatistics and medical statistics. Difference between descriptive and inferential statistics. Definition of variable. The role of variables. Types of variable. Data storage (tables and databases). Types of biostatistics and medical statistics. Descriptive statistics: objectives and techniques. How to describe nominal variables (tables, histograms, pie-charts, etc). Descriptive statistics: continuous or discrete quantitative variables. Representation of variability: histograms, dispersion graphs. Summary of possible central trend measures, dispersion, symmetry and curvature for quantitative variables. The arithmetic mean. The median. Fashion. The dispersion: range of variation, interquartile range, standard deviation, variation coefficient. Box diagram (box plot). Examples: histograms, box plot. Normal distribution. Normal distribution properties. Normal and non-normal distributions: mean, median and fashion. Asymmetry and Curtosis. Tests on tests to evaluate normality. Non-normalities and graphs to represent the distribution of data. The log-normal distribution: mean and geometric standard deviation. Distinction between parametric and nonparametric inferential statistics. Normal distribution: sampling. Test hypothesis on an average. Calculation of significance. One and two tail tests. The level of significance. Type I and Type II errors. Constraints and degrees of freedom. Student's distribution t (SD of unknown population). Comparison between two mediums: Appropriate data. Non-parametric tests: introduction. The rank. Mann-Whitney test. Yates Continuity Correction. Wilkoxon Test. Correlation of Pearson and Spearman. Evidence Based Medicine. Types of statistical studies and their significance. Concepts of forces and moments applied in the biomechanical field; of equilibrium of forces and characteristics of biomechanical materials. Analysis of the path, composition and use of prostheses, orthoses, exoskelets and aids. Realization of information processing systems, their management and utilization in various application contexts. Information processing systems, data bases, information systems, man-machine interaction, and electronic coding and representation of information.