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Friedrich-Alexander-Universität Assistive Intelligent Robotics Lab AIROB
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Artificial Intelligence in Biomedical Engineering
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Artificial Intelligence in Biomedical Engineering
Friedrich-Alexander-Universität Assistive Intelligent Robotics Lab AIROB
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The Assistive Intelligent Robotics Lab

Ideas, in motion, for people.

In page navigation: Education
  • Lectures, seminars and laboratories
  • Student Theses and Jobs
    • Benchmarking of an IMU-based kinematics tracker - Paid position
    • FAU - DLR: Shared Autonomy in Advanced Humanoid Teleoperation for Intuitive and Reliable Grasping
    • Force Myography as an intent prediction and feedback mechanism for a functional electrical stimulation setup
    • Force output based calibration of a muscular electrical stimulation array
    • Functional Electric Stimulation for the Operation Room
    • Intuitive Control for Industrial Setups
    • Investigate, design and implement a versatile force myography sensor in cooperation with Ottobock
    • Master Thesis: Shallow and deep unsupervised methods for myoelectric control of upper limb prostheses
    • R/B/M: Development and investigation of virtual prosthesis performance evaluations a robotic engine (MuJoCo)
    • Student Assistent for IntelliMan - Biosignal Analysis, Machine Learning and VR (HiWi)
    • Student Assistent for IntelliMan - VR for Upper Limb Prostheses (HiWi)
    • Electromyography-Based Control of a Finger-Hand Exoskeleton
    • Software Development Student Assistant

Master Thesis: Shallow and deep unsupervised methods for myoelectric control of upper limb prostheses

The AIROB Lab has 1 open position for Master’s project to investigate shallow and deep unsupervised methods for myoelectric control of ULP.

In this research project, the student will investigate shallow and deep unsupervised approaches to myoelectric control of upper limb prostheses. To this end, the student will become familiar with possible methods and architectures. A method will be chosen and implemented in such a way that it can run in (semi-) real-time. After the development and training phase, the system will be tested online on healthy participants.

The tasks include, among others:

  • Reasearch
  • Implementation and training of selected methods
  • Testing control in real-time
  • Post-analysis

Required Qualifications

  • Experience with Python
  • (basic) Experience with DL/ML
  • (basic) Experience with C#
The Assistive Intelligent Robotics (AIROB) Laboratory
Friedrich-Alexander-Universität Erlangen-Nürnberg

Nürnberger Str. 74
91052 Erlangen
Germany
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