Carlo Menon: Katalogdaten im Herbstsemester 2023

Name	Herr Prof. Dr. Carlo Menon
Lehrgebiet	Biomedizinische und Mobile Gesundheitstechnologien
Adresse	Biomedical and Mobile Health Tech ETH Zürich Lengghalde 5 8008 Zürich SWITZERLAND
E-Mail	carlo.menon@hest.ethz.ch
URL	https://bmht.ethz.ch/
Departement	Gesundheitswissenschaften und Technologie
Beziehung	Ordentlicher Professor

Nummer	Titel	ECTS	Umfang	Dozierende
151-0623-00L	ETH Zurich Distinguished Seminar in Robotics, Systems and Controls	1 KP	1S	B. Nelson, M. Hutter, R. Katzschmann, C. Menon, R. Riener, R. Siegwart
Kurzbeschreibung	This course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
Lernziel	Obtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see http://www.msrl.ethz.ch/education/distinguished-seminar-in-robotics--systems---controls--151-0623-0.html for a list of upcoming lectures.
Inhalt	This course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls. MSc students in Robotics, Systems, and Controls are required to attend every lecture. Attendance will be monitored. If for some reason a student cannot attend one of the lectures, the student must select another ETH or University of Zurich seminar related to the field and submit a one page description of the seminar topic. Please see http://www.msrl.ethz.ch/education/distinguished-seminar-in-robotics--systems---controls--151-0623-0.html for a suggestion of other lectures.
Voraussetzungen / Besonderes	Students are required to attend all seven lectures to obtain credit. If a student must miss a lecture then attendance at a related special lecture will be accepted that is reported in a one page summary of the attended lecture. No exceptions to this rule are allowed.
376-1176-00L	Wearable and Mobile Technologies of the Future - Focus on Sports and Health	4 KP	3G	C. Menon, C. Ahmadizadeh, M. Elgendi
Kurzbeschreibung	This course focuses on the progress in the field of wearable and unobtrusive technologies for sports and health. Topics as monitoring heart health and blood pressure, biofeedback and improvement of motor skills and performance are covered. The focus lies on learning about the principles and design of the new generation of non-invasive technologies in fitness-, athletic and medical applications.
Lernziel	Objective 1: Acquire knowledge about the latest technological advancements in wearable and unobtrusive technologies for sport and health. Objective 2: Acquire skills to design novel non-invasive technologies for sport and health.
Inhalt	The course consists of two modules. Module 1: Movement. This module provides the scientific background needed to understand the principles that current technologies investigating movement rely on. The latest technological advancements to track parameters of gait and running, improve posture as well as to monitor overall body movement and provide feedback on motion during sport, rehabilitation or at work will be investigated. The focus will be on wearable-related (e.g., textile-based) technologies. Module 2: Cardiac. This module focuses on the latest technologies for monitoring the cardiac cycle and blood pressure. The module starts by succinctly providing background information on cardiac physiology and then briefly introduces conventional technologies used in daily practice. This module subsequently focuses on the latest technologies and the latest data analysis techniques to monitor the cardiac cycle for assisting individuals in sport activities or monitoring their health conditions.
Voraussetzungen / Besonderes	- Students should be proficient in programming (any language). - Note: assignments will be in MATLAB. Students are expected to learn MATLAB on their own if not experienced with this programming language. - Course prerequisites:  For Biomedical Engineering Master’s: none  For ITET Master’s: none  For D-MAVT Master’s: none  For D-HEST Master’s and PhD students: • If BSc in electrical/mechanical engineering or computer science: none • If any other BSc program: 376-0022-00L (Imaging and Computing in Medicine) or 376-1983-00L (Foundations of Data Science)