Carlo Menon: Catalogue data in Autumn Semester 2024 |
| Name | Prof. Dr. Carlo Menon |
| Field | Biomedical and Mobile Health Technology |
| Address | Biomedical and Mobile Health Tech ETH Zürich Lengghalde 5 8008 Zürich SWITZERLAND |
| carlo.menon@hest.ethz.ch | |
| URL | https://bmht.ethz.ch/ |
| Department | Health Sciences and Technology |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||
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| 151-0623-00L | ETH Zurich Distinguished Seminar in Robotics, Systems and Controls  | 1 credit | 1S | B. Nelson, M. Hutter, R. Katzschmann, C. Menon, R. Riener, R. Siegwart | |||||||||||||||||||||||||||||||||||||||||
| Abstract | This course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls. | ||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | 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. | ||||||||||||||||||||||||||||||||||||||||||||
| Content | 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. | ||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | 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 credits | 3G | C. Menon, C. Ahmadizadeh, C. Otesteanu | |||||||||||||||||||||||||||||||||||||||||
| Abstract | The course introduces concepts about wearable and unobtrusive technologies for sport and health data collection. Tools for analysing this data and evaluating the performance of these systems are introduced. Topics such as monitoring movement and muscle activation, mental focus, stress, and heart health are covered. | ||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Objective 1: Acquire knowledge about wearable and unobtrusive technologies and skills to process data acquired using wearable technologies. Objective 2: Provide students with hands-on experience using various wearable technologies, including textile-based stretchable sensors, electromyography (EMG), electroencephalogram (EEG) and electrocardiogram (ECG). | ||||||||||||||||||||||||||||||||||||||||||||
| Content | The course consists of the following modules: Module 0: Fundamentals This module briefly reviews time-frequency domains, transforms and filtering. Module 1: Movement. This module provides the scientific background needed to understand the principles that current technologies investigating movement rely on. It provides an overview of wearable technologies for monitoring overall body movement as well as for tracking motion parameters (e.g. gait, running, posture). Technologies such as inertial measurement units, electromyography, optical motion capture systems, and others are covered. The latest updates on wearable-related (e.g., textile-based) technologies are also introduced. Students are involved in labs/assignments to put into practice the knowledge and skills acquired during this module. Module 2: Brain. This module briefly introduces brain functions and provides an overview of related wearable technologies. Topics covered may include electroencephalograms, transcranial magnetic stimulation, and galvanic vestibular stimulation. Data processing techniques such as common spatial patterns, principal component analysis, and linear discriminant analysis are introduced. Students are given a practical assignment to put into practice the knowledge and skills acquired during this module. Module 3: Cardiac. This module focuses on wearable technologies for monitoring cardiac health. The module starts by providing information on cardiac physiology and introduces wearable technologies for the heart. Topics such as electrocardiography, photoplethysmography, light sensing, and contactless physiology monitoring are introduced. Data analysis techniques for cardiac data including heart-rate variability, Poincare plots, and wavelet transforms are discussed. Students will be given an assignment to put into practice the knowledge and skills acquired during this module. | ||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | - Students should be proficient in programming (any language). - Note: assignments will be in Python. Students are expected to learn Python 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) | ||||||||||||||||||||||||||||||||||||||||||||
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