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F7ADIAMSD - Architecture and Methods of Data Collection and Evaluation of Behavioural Models of Every Day Activ.

Code Completion Credits Range Language
F7ADIAMSD ZK 20P+8C English
Lecturer:
Dušan Šimšík (guarantor), Alena Galajdová
Tutor:
Patrik Kutílek, Dušan Šimšík (guarantor), Alena Galajdová
Supervisor:
Department of Biomedical Technology
Synopsis:

The course will focus on methods of data collection and analysis for behavioural analysis of the human way of acting. The content will include methods and means for data collection and processing. Suitable data formats, creation of behavioural models.

Requirements:

As a standard, teaching is done in contact form and the subject is completed by oral examination, which precedes written preparation. If the number of students is less than 5, the teaching may take place in the form of a controlled self-study with regular consultations. In addition, a written study is required by a student on a given topic in the field. The condition for admission to the exam is the completion of two laboratory exercises (provided by the protocol signed by the student, the head of the exercise and the guarantor of the course). Protocols will be archived in the department for doctoral studies.

Syllabus of lectures:

Lectures:

1. Introduction to the basic topics of analysis of human behaviour.

2. Types of data, methods of data collection and analysis (duration of data, recording of time samples, frequency, event and time).

3. Scanning, signal processing and machine learning, especially in the acquisition and analysis of large amount of data on human behaviour.

4. Methods of processing large data files. Activity recognition methods including gait and standing analysis, gestures analysis and semantics of human behaviour in image sequences.

5. Experimental behavioural analysis and some of the most important areas of current laboratory research in behaviour analysis.

6. Applications in various fields of research, e.g. behaviour biometrics, artificial intelligence applied in assisted life environments.

7. Technical and computational methods that support measurement, analysis and modelling of signals describing human behaviour.

8. Getting big data. Record behavioural data as well as context/environmental measurements using sound, image, physiological and other techniques for recording data from monitoring systems in a controlled and natural environment.

9. Deriving signal descriptors that inform or indicate aspects of „who, what, when, how, where, why“ from multimodal measurements.

10. The diversity and variability of the method of data collection and use. Methods of creating and describing human behaviour between individuals and in context. Artificial intelligence techniques for behaviour analysis.

Syllabus of tutorials:

Exercises:

1.Kinematics and movement dynamics within the structural design of a monitoring system based on several accelerometers. Data processing methods and their quantitative evaluation using computer technology.

2. Examples of force and moment effects using force meters. Data processing methods and quantitative evaluation.

Study Objective:

The course will focus on methods of data collection and analysis for behavioural analysis of human way of acting. The content will include methods and means for data collection and processing. Suitable data formats, creation of behaviour models.

Study materials:

[1] ROANE, Henry S., Joel L. RINGDAHL a Terry S. FALCOMATA. Clinical and organizational applications of applied behavior analysis. San Diego, CA, USA: Elsevier/AP, Academic Press is an imprint of Elsevier, 2015. Practical resources for the mental health professional. ISBN 978-0-12-420249-8.

[2] MADDEN, Gregory J. a William V. DUBE. APA handbook of behavior analysis. Washington, DC: American Psychological Association, c2013. ISBN isbn:978-1-4338-1111-1.

Doporučená literatura:

[1] SARAFINO, Edward P. Applied behavior analysis: principles and procedures for modifying behavior. Hoboken, NJ: Wiley, 2012. ISBN isbn:9780470571521.

Note:
The course is a part of the following study plans:
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