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Biomedical Sciences
Advanced Bionic Systems

Advanced Bionic Systems

Code	13523
Year	1
Semester	S2
ECTS Credits	6
Workload	TP(60H)
Scientific area	Biomedical Sciences
Entry requirements	None
Mode of delivery	Face-to-face.
Work placements	N/A.
Learning outcomes	To teach the main principles of Bionics, review the basics of the bionic systems, study the mimicry, the systems of human-machine interface and the artificial intelligence. Apply the knowledge about bionic systems. Understand the human movement patterns and the mimicry, in order to design bioinspired systems. Know the several types of man-machine interface systems. Apply different techniques of control systems. Understand the concepts of artificial intelligence and robotic systems. Use system simulation software. Understand the convergence of biological systems and technological systems. Work individually and within a team. Develop autonomy and leadership abilities. Know how to read and write scientific works.
Syllabus	1.Basic fundamentals of bionic systems, mimicry and bioinspired systems. 2.From anatomical and physiological reasoning to bionic reasoning. 3.Basic fundamentals of human-machine interface in the area of ??health and well-being. 4.Basic fundamentals of biosystems control. 5.Basic fundamentals of artificial intelligence applied to the area of ??health and well-being.
Main Bibliography	Russell Stuart & Norvig Peter, "Artificial Intelligence, A Modern Approach", Pearson Series in Artificial Intelligence, Pearson Education Inc., 2019. Subana Shanmuganathan (Ed), "Artificial Neural Network Modelling", Studies in Computational Intelligence, Springer, 2016. C Naga Bhaskar & G Vijay Kumar, "Neural Networks and Fuzzy Logic", BS Publications, 2015. S. Rajasekaran & G.A. Vijayalakshmi Pai, "Neural Networks, Fuzzy Systems and Evolutionary Algorithms, Synthesis and Applications", PHI Learning, 2017. Oliver Kramer, "Genetic Algorithm Essentials", Studies in Computational Intelligence, Springer, 2017. Tao Song (Ed), Pan Zheng (Ed), Mou Ling Dennis Wong (Ed), "Bio-Inspired Computing Models and Algorithms", WSPC, 2019. Maoguo Gong (Ed), Pan Linqiang (Ed), Song Tao (Ed), Ke Tang (Ed), Xingyi Zhang"Bio-Inspired Computing, Theories and Applications" 10th International Conference, BIC-TA 2015 Hefei, China, Proceedings, Springer, 2015.
Teaching Methodologies and Assessment Criteria	The periodic assessment consists of a project (S1+S2+S3+RF): Seminar 1 (S1) (20%) Seminar 2 (S2) (20%) Seminar 3 (S3) (40%) Final report (RF) (20%) Minimum attendance in theoretical-practical classes of 50%* *Students in special regimes must contact the teacher.
Language	Portuguese. Tutorial support is available in English.