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Institute of Robotics and Intelligent Systems D-HEST

AcronymIRIS
Homepagehttp://www.iris.ethz.ch/
CountrySwitzerland
ZIP, City 
Address
Phone
TypeAcademy
Top-level organizationETH Zurich
Parent organizationDepartment of Health Sciences and Technology
Current organizationInstitute of Robotics and Intelligent Systems D-HEST
Child organizations
  • Biomedical and Mobile Health Technology Lab
  • Mobile Health Systems Laboratory
  • Neuroengineering Lab
  • Rehabilitation Engineering Lab
  • Sensory-Motor Systems Lab
Members
  • Institute of Robotics and Intelligent Systems D-MAVT
Memberships
  • Institute of Robotics and Intelligent Systems D-MAVT


Open Opportunities

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Klinisches Forschungspraktikum/Masterarbeit am USZ zum Visual Snow Syndrom

  • ETH Zurich
  • Rehabilitation Engineering Lab

Liebe Masterstudierende Die Forschungsgruppe des neuroradiologischen Departementes des Universitätsspitals Zürich (Leitung: PD Dr. Lars Michels) sucht ab Juni 2022 ein*e Forschungspraktikant*in mit Option auf Masterarbeit. In dieser Studie untersuchen wir die bisher wenig erforschte neurologische Erkrankung Visual Snow und die Möglichkeit von fMRI Neurofeedback Training als Therapiemethode. Das Projekt beinhaltet fMRI, DTI, MR-Spektroskopie Messungen (MRS) und psychophysische Tests.

  • Biomedical Engineering, Neurosciences, Psychology
  • Internship, Master Thesis, Semester Project

First measurements with an instrumented campus board

  • ETH Zurich
  • Sensory-Motor Systems Lab

Climbers train their finger strength on the campus board. If the forces at the bars are measured, performance analysis becomes possible. In a recent bachelor thesis, we designed an instrumentation for a campus board which should now be further developed to run first experiments in campus board training.

  • Engineering and Technology, Human Movement and Sports Science
  • Bachelor Thesis, Internship, Master Thesis, Semester Project

MOVEMENTS CLASSIFICATION BASED ON PRESSURE-SENSING MATTRESS DATA

  • ETH Zurich
  • Sensory-Motor Systems Lab

This Master Thesis aims to develop an algorithm to classify different movements that could occur during sleep. Data is readily available from previous recordings but can be extended using additional measurements.

  • Engineering and Technology
  • Master Thesis

Closed-loop optimization of vagus nerve stimulation for functionally selective neuromodulation

  • ETH Zurich
  • Neuroengineering Lab

Development of a closed-loop machine learning algorithm to extend the therapeutical uses of vagus nerve stimulation by improving the selectivity of electrical nerve stimulation, trained on a computational model and validated against experimental data.

  • Biomedical Engineering
  • Master Thesis, Semester Project

Ultrasound-driven (Micro-) Robotics for Healthcare Applications

  • ETH Zurich
  • Acoustic Robotics for Life Sciences and Healthcare (ARSL)

Wireless empowered micro/-nanorobotic systems enable novel and innovative medical therapeutics and diagnostics such as minimal-invasive surgery, targeted drug delivery, or enhanced imaging of diseased tissue. Immense research is conducted using various different external field-driven robot actuation methods, including magnetic, pneumatic, optical, and electric fields. Each technique brings its advantages and limitations that are matched for addressing one specific medical task. At the Acoustic Robotics and Systems Lab (ARSL), we focus on acoustically based robotic systems for life sciences and healthcare applications. Activation by ultrasound is attractive because ultrasound is safe to most biological systems, non-invasive, penetrates deep into the body of an animal model, and is widely spread in clinical institutions.

  • Biology, Engineering and Technology, Physics
  • Collaboration, Master Thesis, Semester Project

Development of machine learning models of peripheral nerve stimulation integrated into an online 3D platform for neuroprosthetic applications

  • ETH Zurich
  • Neuroengineering Lab

Computational modeling of the PNS is a complex tool whose domain spans several physical scales. The long time and cost of their execution can be immensely reduced by the use of AI estimators, which will enable the development of an online 3D platform for real-time model manipulation and computation.

  • Biomedical Engineering, Computer Graphics, Simulation and Modelling
  • Master Thesis, Semester Project

Development of smart garments to monitor the frontal plane knee angle for sports and medical applications

  • ETH Zurich
  • Biomedical and Mobile Health Technology Lab

The aim of this project is to develop an unobtrusive wearable for the measurement of the frontal plane knee angle. Measurements made by such a device can be used for the assessment of anterior cruciate ligament (ACL) injuries, for rehabilitation, or to prevent injuries in sports.

  • Engineering and Technology, Information, Computing and Communication Sciences
  • Collaboration, Master Thesis, Semester Project

Wearable Technology for Back Movement Monitoring in Patients with Low Back Pain

  • ETH Zurich
  • Biomedical and Mobile Health Technology Lab

This project aims to develop light and unobtrusive wearable technologies using thread-like sensors to monitor back movements. The information provided by the developed technologies will be used to address a major health issue, i.e., low back pain, through its prevention or rehabilitation.

  • Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
  • Collaboration, Master Thesis, Semester Project

Machine Learning for Healthcare: Signal Quality Assessment of Biosignals

  • ETH Zurich
  • Biomedical and Mobile Health Technology Lab

We aim to develop an efficient algorithm able to run in real-time within a mobile phone, to collect high-quality electrocardiogram (ECG) and photoplethysmogram (PPG) signals.

  • Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Medical and Health Sciences
  • Bachelor Thesis, Master Thesis, Semester Project

Machine Learning Evaluation of A Multi-User High-Performance Computer

  • ETH Zurich
  • Biomedical and Mobile Health Technology Lab

Explore how machine learning algorithms are impacted by the several choices of general-purpose computing capable (not only graphics) of our GPU station to produce a high computation environment with minimal cost. More importantly, our system will be recommended to facilitate computational tasks of research projects for faculty members and students.

  • Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Physics
  • Bachelor Thesis, Master Thesis, Semester Project
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