Course detail

Bionics

FEKT-LBNKAcad. year: 2010/2011

Bionics - fundamental terms and principles. Substitutive medicine, biocompatibility. Human body as a system, adaptation, homeostasis, control in living organisms. Infomational and control system of human organism. Fundamentals of genetics, genetic algorithms. Technical aspects of endocrine system. Neural system - electrical characteristics, measuring NS performance - EEG, relation between neural system and artifical neural nets. Input and output units - sensory organs, loads. Hearing - principles, measuring, cochlear endoprosthesis. Vision - principles, measuring, artificial eye. Skeletal muscles - principles and measuring their performance (EMG, ENG), artificial limbs. Cardivascular system - hemodynamics, electrical characteristics, ECG.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

doc. Ing. Jiří Kozumplík, CSc.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Basic capability to interpret structure and performance of the human body subsystems from a technical standpoint. Capability to measure and interpret basic signals generated by human body (ECG, EEG, acoustically evoked potentials, EMG, etc.).

Prerequisites

The subject knowledge on the Bachelor´s degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim of the course is to provide students with basic technical and technological interpretation of structure and performance of selected subsystems of human body and applying the knowledge both to solving technical problems (genetic algorithms, artificial neural networks, visual scene analysis, ...)and choice of the correct methodology for measuring properties and state of the described systems and/or their substitutes.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

The Biomedical Engineering Handbook. J.D. Bronzino (ed.) Boca Raton, CRC Press 1995. (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-BEI , 1 year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch EE-FLE , 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Jiří Kozumplík, CSc.

Syllabus

Bionics - fundamental vocabulary, topics, aims, principles. Subsitutive medicine, biomaterials, design of artificial organs.
Human organism as a system. Informational and control system in human body.
Genetic system. Fundamentals of genetics.
Genetic algorithms (GA), aims and principles.
Introduction to the theory of GA.
Physiological system. Endocrine system.
Neural system (NS). Electrophysiology of neural system. Measuring quality of neural system.
Artificial neural networks, relation between artificial and natural neural networks.
Basic variants of artificial neural networks.
Sensory systems. Auditory system, visual system, measuring, artificial substitutes.
Skeletal muscles, physiology, measuring of myoactivity.
Alimentation system. Cardiovascular system. Electrical and mechanical processes in heart. Measuring of heart activity - ECG.

Laboratory exercise

13 hod., compulsory

Teacher / Lecturer

Ing. Jan Hrubeš

Syllabus

Genetic algorithms
Electroencephalography
Artificial neural nets
Applications of artificial neural nets
Electromyography
Electrocardiography, vectorcardiography.