Methods of Processing Biomedical Signals

Askaduly Kanat

The instructor profile

Description: Study of various methods of processing biomedical signals, as well as the implementation of these methods using modern software development systems. Methods of discrete data representation, the basics of digital filtering, and methods of digital spectral analysis are considered. Examples of various classes of biomedical signals and methods of their processing at various stages are given: pre-processing, digital filtering, extraction of informative features, recognition and classification of signal shapes.

Amount of credits: 6

Пререквизиты:

  • Introduction to engineering

Course Workload:

Types of classes hours
Lectures 30
Practical works 30
Laboratory works
SAWTG (Student Autonomous Work under Teacher Guidance) 30
SAW (Student autonomous work) 90
Form of final control Exam
Final assessment method

Component: Component by selection

Cycle: Profiling disciplines

Goal
  • The objectives of the development of the discipline "Methods of processing biomedical signals" are: formation of students' views on the correct use of existing mathematical methods and algorithms for analyzing experimental information of various physical nature; creation of software algorithmic and mathematical support for automated primary processing of biomedical signals; development of medical and technical requirements for the creation of new and improvement of existing medical devices and systems, designs, programs and methods of their testing.
Objective
  • The objectives of the discipline are the formation of skills and abilities in the following areas of activity: - classification and physical nature of biomedical signals; - justification of the choice of methods for the analysis of biomedical signals; - mathematical processing of signals received from primary measuring transducers using modern methods of signal analysis and conversion; - digital spectral analysis; - analysis of digital filters and functional signal processing units; - undistorted transmission of primary signals to processing and analysis tools; - general principles of automated analysis of biomedical information; - calculation of the main characteristics of biomedical signals; - rational coordination of the properties of biological objects with the parameters of technical links.
Learning outcome: knowledge and understanding
  • Know: basic concepts and mathematical methods of results processing; linear algebra; analytical geometry; differential and integral calculus; differential equations; fundamentals of the theory of functions of a complex variable; probability theory and mathematical statistics; fundamental laws of nature and basic laws in the field of mechanics, thermodynamics, electricity and magnetism; laws of applied mechanics; environmental problems, etc.
Learning outcome: applying knowledge and understanding
  • Be able to: apply methods of mathematical analysis, probability theory and mathematical statistics to study methods of signal and data processing; make differential equations of motion; apply mathematical methods, physical and chemical laws to solve practical problems. Possess: methods of solving algebraic systems and differential equations, differential and integral calculus, analytical geometry; methods of probability theory, mathematical statistics, mathematical logic and functional analysis; skills of practical application of the laws of physics, chemistry, ecology and applied mechanics.
Topics of lectures
  • Сообщения и сигналы
  • Анализ и синтез сигналов, описание сигналов
  • Гармонический анализ периодических сигналов
  • Спектр одиночного импульса
  • Описание свойств четырехполюсников
  • Дискретная обработка сигналов, обобщенный алгоритм цифровой обработки
  • Быстрое преобразование Фурье
  • Классификация фильтров, параметры фильтров
  • Цифровые фильтры
  • Огибающая и фаза, преобразование Гильберта
  • Математические вопросы, связанные с обработкой случайных сигналов (обзор)
  • Модели случайных процессов
  • Оцениванивание параметров случайных сигналов
  • Анализ числовых данных (краткий обзор)
  • Статистические методы анализа данных
Key reading
  • 1. Теория вероятностей и математическая статистика: Основы, прикладные аспекты с примерами и задачами в среде Mathcad: Учеб. пособие для вузов / Р. И. Ивановский. — СПб.: БХВ-Петербург, 2008. — 528 с.
  • 2. Гмурман В.Е. Теория вероятностей и математическая статистика. М.: Высш. шк., 2006.
  • 3. Малков П.Ю. Количественный анализ биологических данных: Учебное пособие. - Горно-Алтайск: РИО ГАГУ, 2005. - 71 с. http://window.edu.ru/resource/280/66280
  • 4. Архирейский А.А., Рассоха Е.Н. Статистическая обработка данных о надежности: Методические указания к выполнению расчетно-графической работы. - Оренбург: ГОУ ОГУ, 2004. - 35 с.
  • 5. Роганов В.Р., Роганова С.М., Новосельцева М.Е. Обработка экспериментальных данных: Учебное пособие. - Пенза: Пенз. гос. ун-т, 2007. - 171 с. http://window.edu.ru/resource/987/36987
Further reading
  • 1. Сергиенко А.Б. Цифровая обработка сигналов. - Спб: Питер, 2002
  • 2. Осипов Л.А. Обработка сигналов на цифровых процессорах. Линейно-аппроксимирующий подход. - М: Горячая линия – Телеком, 2001.
  • 3. Солонина А.И., Улахович Д.А., Яковлев Л.А. Цифровые процессоры обработки сигналов фирмы Motorola.- Спб.: БХВ – Петербург, 2000
  • 4. Рабинер Л., Гоулд Б. Теория и применение цифровой обработки сигналов. – М.: Мир - 197892. Применение цифровой обработки сигналов. Под ред. Оппенгейма Э. – М.: Мир – 1980
  • 5. Гоноровский И.С. Радиотехнические цепи и сигналы. М.: Радио и связь – 1986