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Vorlesungsverzeichnis >> Technische Fakultät (TF) >>

Seminar: Biosignals in Rehabilitation Robotics (SEM-BiosigRAR)5 ECTS
(englische Bezeichnung: Seminar: Biosignals in Rehabilitation Robotics)

Modulverantwortliche/r: Claudio Castellini
Lehrende: Fabio Andre Egle


Startsemester: WS 2022/2023Dauer: 1 SemesterTurnus: halbjährlich (WS+SS)
Präsenzzeit: 20 Std.Eigenstudium: 130 Std.Sprache: Englisch

Lehrveranstaltungen:


Empfohlene Voraussetzungen:

Recommended: basic maths, especially statistics; fundamentals of signal processing and machine learning.

Inhalt:

In the seminar, students will analyse, present and discuss issues and topics concerning the usage of biological signals in rehabilitation and assistive robotics, including the correct placement and use of the associated sensors, the techniques to condition the signals, sensor fusion, feature extraction and the usage of machine learning applied to such kind of signals. Besides reflecting on contemporary literature, the students are asked to draw own conclusions and suggest directions for future research.

Lernziele und Kompetenzen:

On successful completion of the seminar, students will be familiar with sensors and signals used in rehabilitation and assistive robotics, both theoretically and practically. They will also be able to deduce potential new research lines from recent developments.

Literatur:

  • [2002] Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal, M. Zecca, S. Micera, M. C. Carrozza and P. Dario.
  • [2010] Control of Hand Prostheses Using Peripheral Information, S. Micera, J. Carpaneto and S. Raspopović.

  • [2015] A survey of sensor fusion methods in wearable robotics, D. Novak and R. Riener


Studien-/Prüfungsleistungen:

Seminar: Biosignals in Rehabilitation Robotics (Prüfungsnummer: 897650)

(englischer Titel: Seminar: Biosignals in Rehabilitation Robotics)

Seminarleistung, Dauer (in Minuten): 45, benotet
weitere Erläuterungen:
Presentation: 50%, report: 50%.
Prüfungssprache: Englisch

Erstablegung: WS 2022/20231. Wdh.: keine Wiederholung
1. Prüfer: Claudio Castellini

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