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Sensory-Motor Systems Lab

AcronymSMS
Homepagehttp://www.sms.hest.ethz.ch/
CountrySwitzerland
ZIP, City 
Address
Phone
TypeAcademy
Top-level organizationETH Zurich
Parent organizationInstitute of Robotics and Intelligent Systems D-HEST
Current organizationSensory-Motor Systems Lab
Memberships
  • Max Planck ETH Center for Learning Systems
  • ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC)


Open Opportunities

Master Thesis / Project - SENSEI: Sensor Teaching in Multi-Activity classification from Video and Wearables for Wheelchair Users

  • ETH Zurich
  • Sensory-Motor Systems Lab Other organizations: ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC), Spinal Cord Injury & Artificial Intelligence Lab

In this project, we focus on continuous and quantitative monitoring of activities of daily living (ADL) in SCI individuals with the goal of identifying cardiovascular events and PI-related risk behaviors. ADLs specific to SCI patients and their lifestyles shall be discussed and narrowed down in the scope of this work, therefore an autonomous camera-based system is proposed to classify ADLs. The Current work builds on a previous project where a SlowFast network [1] was trained to identify SCI-specific classes and we aim to further improve the classification and temporal resolution for transferring to wearables' time-series data.

  • Computer Vision, Health Information Systems (incl. Surveillance), Intelligent Robotics, Knowledge Representation and Machine Learning, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition
  • Bachelor Thesis, Course Project, ETH for Development (ETH4D) (ETHZ), ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project

Master Thesis: Development of a Customized Knee Orthosis for Osteoarthritis

  • ETH Zurich
  • Spinal Cord Injury & Artificial Intelligence Lab Other organizations: Sensory-Motor Systems Lab

Osteoarthritis (OA) presents a significant challenge in healthcare, necessitating innovative solutions to alleviate pain, enhance mobility. This thesis documents the research and development journey of an OA knee orthosis within the Spinal Cord and Artificial Intelligence Lab (SCAI-Lab) at ETH Zurich. This thesis is a close collaboration between the ORTHO-TEAM Group and the SCAI-Lab at ETH Zurich. The collaboration offers a unique exchange of expertise and resources between industry and academia. Together, we aim to make meaningful progress in the field of and empower students to make valuable contributions to their academic pursuits.

  • Biomechanics, Biomedical Engineering
  • ETH Zurich (ETHZ), Master Thesis

Master Thesis: Contact force evaluation of robotic endoscopic system based on Series Elastic Actuation

  • University of Basel
  • Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab) Other organizations: Sensory-Motor Systems Lab

In the BIROMED-Lab we have been developing an endoscopic system for safer neurosurgeries with inspiration from human finger anatomy. Its two degrees of freedom allow the endoscope to investigate areas of the brain that would be inaccessible with standard rigid endoscopes. Thanks to springs in the transmission between the motors and the movable endoscope tip, the interaction forces between the instrument and the brain tissue can be reduced. Furthermore the interaction forces can be estimated by measuring the deflection of the spring. To make the telemanipulation of the endoscope safer and more intuitive for the surgeon, force feedback was also implemented.

  • Biomedical Engineering
  • Master Thesis

Master Thesis: Vibro-tactile feedback in ventricle puncturing during External Ventricular Drain (EVD) procedure

  • University of Basel
  • Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab) Other organizations: Sensory-Motor Systems Lab

EVD is a common procedure in Neurosurgery, nevertheless its placement is non-ideal in up to 40% of the cases because of lack of hands-on experience of residents. To try and solve the issue we propose a medical simulator that will merge haptic feedback with hardware components. Vibro-tactile feedback has been proven useful in medical simulations and could give a more complete and realistic experience to the training surgeon, either as supplementary information to the force feedback or as stand alone information. In order to feed back the vibro-tactile information to the user, the haptic device has to be instrumentalized with appropriate custom-made hardware.

  • Biomedical Engineering
  • Master Thesis

Research Assistant in Biosensing for Robotics Care and Body Simulation (~12 months)

  • ETH Zurich
  • Spinal Cord Injury & Artificial Intelligence Lab Other organizations: ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC), Sensory-Motor Systems Lab

Join a team of scientists improving the long-term prognosis and treatment of Spinal Cord Injury (SCI) through mobile and wearable systems and personalized health monitoring. Joining the SCAI Lab part of the Sensory-Motor Systems Lab at ETH, you will have the unique opportunity of working at one of the largest and most prestigious health providers in Switzerland: Swiss Paraplegic Center (SPZ) in Nottwil (LU).

  • Artificial Intelligence and Signal and Image Processing, Computer Software, Data Format, Information Systems
  • ETH Zurich (ETHZ), Internship, Lab Practice, Student Assistant / HiWi

Master's Thesis: AI-powered nap detection from Fitbit data

  • ETH Zurich
  • Spinal Cord Injury & Artificial Intelligence Lab Other organizations: Sensory-Motor Systems Lab

The uprise of consumer-grade fitness trackers has opened the doors to long-term activity monitoring in the wild in research and clinics. However, Fitbit does not identify napping episodes shorter than 90 minutes. Hence, there is a need to establish a robust algorithm to detect naps.

  • Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Biosensor Technologies, Electrical and Electronic Engineering
  • Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis

A Bayesian sensor fusion and machine learning approach for robust hand gesture decoding with application to stroke rehabilitation.

  • ETH Zurich
  • Sensory-Motor Systems Lab

About the project: This thesis aims to design a framework for robust fine-motor action decoding using multi-modal (sEMG and depth sensing camera) Bayesian sensor fusion and machine learning approach

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

Master Thesis: Data Analysis of Wearable and Nearable Sensors Data for Classification of Activities of Daily Living

  • ETH Zurich
  • Spinal Cord Injury & Artificial Intelligence Lab Other organizations: Sensory-Motor Systems Lab

This project aims to develop a novel algorithm for tracking a person's health condition changes using daily life wearable sensor data, biosignals, and information from nearable sensors. With the Life-long-logging system, we want to provide meaningful data for medical staff and directly engage patients and their caregivers.

  • Artificial Intelligence and Signal and Image Processing, Engineering and Technology
  • Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project

Master Thesis: Data Analysis of Wearable and Nearable Sensors Data within the StrongAge Cohort Study

  • ETH Zurich
  • Spinal Cord Injury & Artificial Intelligence Lab Other organizations: Sensory-Motor Systems Lab

The StrongAge Dataset, collected over one year, provides a rich data repository from unobtrusive, contactless technologies combined with validated mood and cognition questionnaires. This project aims to uncover digital biomarkers that can transform elderly care, addressing critical research questions related to sleep, cognition, physical activity, and environmental influences.

  • Biomechanical Engineering, Signal Processing
  • Bachelor Thesis, ETH Zurich (ETHZ), Internship, Lab Practice, Master Thesis, Semester Project, Student Assistant / HiWi

A generalized sEMG-based gesture recognition framework using deep learning approach

  • ETH Zurich
  • Sensory-Motor Systems Lab

This thesis aims to develop a generalizable (user-invariant and session-invariant) gesture recognition framework using deep neural networks

  • Engineering and Technology, Information, Computing and Communication Sciences
  • Master Thesis
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