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Vorlesungsverzeichnis >> Medizinische Fakultät (Med) >>
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Wearable and Implantable Computing (WIC)- Dozentinnen/Dozenten
- Prof. Dr. Oliver Amft, und Mitarbeiter/innen
- Angaben
- Vorlesung mit Übung
4 SWS, benoteter Schein, Anwesenheitspflicht, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch, Registration via: https://www.studon.fau.de/crs2168943_join.html
Zeit und Ort: n.V.; Bemerkung zu Zeit und Ort: First lecture: 10/16/2019, 12:30-14:00 h, MVC/ZMPT, Henkestr. 91, Lecture Hall, 1st Floor, 01.020
- Studienfächer / Studienrichtungen
- WPF MT-MA-BDV ab 1 (ECTS-Credits: 5)
WPF MT-MA-MEL ab 1 (ECTS-Credits: 5)
WPF MT-MA-GPP ab 1 (ECTS-Credits: 5)
WPF MT-BA 5 (ECTS-Credits: 5)
- ECTS-Informationen:
- Credits: 5
- Prerequisites
- Useful knowledge:
Basics of Matlab/Python, Basics in signal analysis & signal processing
- Contents
- Course description:
The course provides an overview on the design of wearable and implantable computing systems. The overview is structured in three parts: context recognition, electronic systems and sensors, and additive manufacturing methods. Pattern analysis and machine learning methods to process and infer context information are discussed. On the system functional level, frequent sensors and actuators and their design for on-body and implantable systems are analysed. Powering and energy management concepts will be detailed, including processing and task scheduling, sparse sampling and sparse sample signal processing. Energy harvesting methods for wearable and implantable systems are presented. Electronic design topics will be addressed, including bioelectronics, flexible electronics, electronics textile integration, multiprocess additive manufacturing. Principles of biocompatibility and system validation for remote health monitoring are covered. In exercise blocks along the lectures concrete design problems related to context recognition, energy-efficient processing, energy harvesting, and 2D/3D printing will be demonstrated, as well as realised and discussed in prototypes.
Learning objectives:
Gain overview on context awareness, sensors and actuators for context management in digital health.
Understand design concepts and apply/analyse wearable and implantable system design methods and electronics encapsulation.
Analyse the electrical and physical principles, select and optimise on-body energy harvesting and power management techniques.
Create continuous context recognition and energy-efficient processing using sparse sampling, related signal and pattern processing methods.
Apply system evaluation methods, assess and design for biocompatibility and medical certification.
Create digital models of wearable systems.
- Literature
- Up-to-date literature recommendations are provided during the lectures.
- Zusätzliche Informationen
- Schlagwörter: WIC
Erwartete Teilnehmerzahl: 20, Maximale Teilnehmerzahl: 20
Für diese Lehrveranstaltung ist eine Anmeldung erforderlich.
Die Anmeldung erfolgt von Mittwoch, 4.9.2019, 08:00 Uhr bis Dienstag, 15.10.2019, 18:00 Uhr über: StudOn.
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2019/2020:
- Wearable and Implantable Computing (WIC)
- Institution: Lehrstuhl für Digital Health
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