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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

Force output based calibration of a muscular electrical stimulation array

The AIROB Lab has 1 open position for Master’s project or Research Internship to investigate electrode array calibration based on fingertip force output under stimulation.

The MyoCeption prototype allows to induce force output in human limbs, and therefore to control movements. At the moment, the device is normally used on the shoulder and elbow joint, and is controlled in a loop that only has feedback in body posture. This project would be focused in including force sensing modalities in the MyoCeption’s control loop, and in applying this to the control of grasping motions.  The main task of this thesis / training will be to build a testbed consisting of an electrode array to be applied on the user’s forearm, a fingertip force sensing setup (already present), and possibly a force myography sensor array (already present). This setup should then serve to create a calibration procedure which will select, among all stimulation electrodes available in the array, which ones are more directly conducive to flexion of single digits.

The tasks include, among others:

  • Building a multiplexer-controlled electrode array to be used on the forearm.
  • Interface the MyoCeption with one of our fingertip force sensing devices.
  • Finding a fitting calibration procedure which ideally associates an electrode pair with a given desired finger flexion movement.

Required Qualifications

  • (basic) Experience with C#
  • (basic) Experience with Electronics
  • (basic) Experience with optimization and calibration algorithms

 

Additional Qualifications (not required)

  • Basic knowledge in Biosignal Processing (e.g. Filtering) and Machine Learning
  • Experience with Python, Matlab, Data Analysis, Data Visualization
  • Experience with 2D-Design (e.g. Inkscape/CorelDraw)
  • Experience with LaTEX, Office programs, Technical Documentation (e.g. in a Wiki)
The Assistive Intelligent Robotics (AIROB) Laboratory
Friedrich-Alexander-Universität Erlangen-Nürnberg

Nürnberger Str. 74
91052 Erlangen
Germany
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