Student Projects

Currently, the following student projects are available. Please contact the responsible supervisor and apply with your CV and transcripts.

If you are looking for a Master internship HST/BWS or would like to carry out a Studies on Mechatronics project in our group, please contact the assistant working on, or closest to, the research topic you are interested in.

Hydraulic braking of two wheels with one hand

A prototype exists (Project Sdoppiatore.org) that reliable brakes two wheels with one brake. Now, a modulation of braking power between the front and rear wheel and a reduction in size and weight of the brake doubler is needed.

Keywords

cycling, hydromechanics, parathletes

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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)

Project Background

Athletes with only one functioning hand need to be able to safely brake bicycles through one brake lever that operates the front and rear wheels at the same time. Solutions exist for mechanic brakes. For hydraulic brakes, until recently, no system existed that did this job without dividing the amount of oil into half when directing it from one lever towards two brake calipers. Of course, this also effectively divides braking power into half. Sophie (in action on the second picture) and her bike mechanic have therefore developed a device that doubles the amount of oil sent into the oil circuit to which the calipers are connected. The doubling happens through a T-shaped piston inserted between a caliper circuit and a separate lever circuit. There are two remaining problems with this device, and the thesis project would be to solve these problems. The first problem is the distribution of braking power between the front and rear calipers. Because both calipers belong to the same circuit, the same pressure arrives at both simultaneously. Given that there is considerably less weight on the rear wheel of a bicycle when braking, the rear wheel blocks more easily than the front wheel. When the rear wheel blocks, the bike slides and in the worst case, the rider can lose control. Riders therefor usually brake more strongly in the front (approximately 60-70% of total braking power used) and less in the back (approximately 30-40% of total braking power used). The thesis project would thus have to find a way to adjust the distribution of braking power by modifying our existing design. Ideally, adjusting could be done flexibly by the rider. Alternatively, the device could have a fixed distribution of 60-70% of total power in the front and the rest in the back. The second problem is that the device is currently too big and too heavy to be useful also for professional athletes in racing. The final device should be as small, light, and aerodynamic as possible, and allow for an installation on the bike that does not prevent the use of other equipment on the handlebars, such as bike packing bags.

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Published since: 2025-06-04 , Earliest start: 2025-08-18 , Latest end: 2026-03-31

Applications limited to ETH Zurich

Organization Sensory-Motor Systems Lab

Hosts Wolf Peter

Topics Engineering and Technology

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

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.

Keywords

Computer vision, activity classification, video processing, Deep Learning, ADL, soft-labelling, probabilistic networks

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Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis , ETH for Development (ETH4D) (ETHZ) , ETH Zurich (ETHZ)

Project Background

In this project, we will develop an ADL monitoring system for smart wheelchairs using wearable sensors (i.e., camera, inertial measurement units). The core idea is to classify ADL by leveraging different sensing and feature computation modalities to extract relevant and complementary context bits. For example, the presence of and the interaction with distinctive objects within the camera scene provides strong cue about the ongoing user activity [1, 2, 3]. From another perspective, inertial sensors record distinct orientation and acceleration signatures of ADL-related temporal patterns [4]. Moreover, previous literature provides strong evidence that the combination of video cameras and inertial sensors improves the recognition performance compared to one or the other [5, 6]. Based on the general multi-modal activity recognition paradigm, we are seeking a novel solution tailored to the smart wheelchair. The outcome of the study will be key to analyse the expected cardiovascular function at different moments of the day in free living. 1. Bensland, S., Paul, A., Grossmann, L., Eriks-Hogland, I., Riener, R., & Paez-Granados, D. (2023). Healthcare Monitoring for SCI individuals: Learning Activities of Daily Living through a SlowFast Network. IEEE International Conference on System Integration. 2. M. Wang, C. Luo, B. Ni, J. Yuan, J. Wang and S. Yan, "First-Person Daily Activity Recognition With Manipulated Object Proposals and Non-Linear Feature Fusion," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2946-2955, Oct. 2018 3. G. Schiboni, F. Wasner and O. Amft, "A Privacy-Preserving Wearable Camera Setup for Dietary Event Spotting in Free-Living," 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2018, pp. 872-877 4. Lopez-Nava IH, Muñoz-Meléndez A. Human action recognition based on low- and high-level data from wearable inertial sensors. International Journal of Distributed Sensor Networks. 2019. 5. C. Chen, R. Jafari and N. Kehtarnavaz, "UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor," 2015 IEEE International Conference on Image Processing (ICIP), 2015, pp. 168-172 6. S. K. Yadav, K. Tiwari, H. M. Pandey, S. A. Akbar, “A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions”, Knowledge-Based Systems, 2021, Volume 223

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Published since: 2025-03-25 , Earliest start: 2025-05-01 , Latest end: 2026-02-28

Applications limited to EPFL - Ecole Polytechnique Fédérale de Lausanne , ETH Zurich , Zurich University of the Arts , Wyss Translational Center Zurich , University of Zurich , Zurich University of Applied Sciences , CERN , CSEM - Centre Suisse d'Electronique et Microtechnique , Department of Quantitative Biomedicine , Lucerne University of Applied Sciences and Arts , Institute for Research in Biomedicine , IBM Research Zurich Lab , University of St. Gallen , University of Lucerne , University of Lausanne , University of Geneva , University of Fribourg , University of Berne , University of Basel , Université de Neuchâtel , Swiss Institute of Bioinformatics , Swiss National Science Foundation , Swiss Federal Institute for Forest, Snow and Landscape Research , Institute of Robotics and Intelligent Systems D-MAVT , TU Berlin , TU Darmstadt , TU Dresden , RWTH Aachen University , Technische Universität München , Technische Universität Hamburg , Max Planck Society , University of Oxford , University of Leeds , University of Cambridge , UCL - University College London , National Institute for Medical Research , Imperial College London , Royal College of Art , Empa , Università della Svizzera italiana , Hochschulmedizin Zürich , Hong Kong University of Science and Technology , University of Washington , Tokyo Institute of Technology , The University of Tokyo

Organization Sensory-Motor Systems Lab

Hosts Paez Diego, Dr. , Paez Diego, Dr. , Paez Diego, Dr.

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Behavioural and Cognitive Sciences

Master Thesis: Development of a Customized Knee Orthosis for Osteoarthritis

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.

Keywords

Osteo Arthritis, Orthosis, Biomechanics, AI, Medical Data, Healthcare

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Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-03-25 , Earliest start: 2025-04-15 , Latest end: 2026-01-31

Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa , University of Basel , University of Berne , Zurich University of Applied Sciences , Università della Svizzera italiana , Hochschulmedizin Zürich , Lucerne University of Applied Sciences and Arts , Institute for Research in Biomedicine , CSEM - Centre Suisse d'Electronique et Microtechnique

Organization Spinal Cord Injury & Artificial Intelligence Lab

Hosts Paez Diego, Dr. , Paez Diego, Dr.

Topics Medical and Health Sciences , Engineering and Technology

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

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.

Keywords

Robotic surgery, Neurosurgery, Telemanipulation, Haptic feedback, Robotic endoscope

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Master Thesis

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Published since: 2025-03-06 , Earliest start: 2025-03-01

Organization Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab)

Hosts Ettori Sara Lisa Margherita , Gerig Nicolas, Dr. , Sommerhalder Michael

Topics Engineering and Technology

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

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.

Keywords

Vibro-tactile feedback, Haptic feedback, Medical robotics, Surgical simulators

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Master Thesis

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Published since: 2025-02-26 , Earliest start: 2025-03-01

Organization Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-Lab)

Hosts Gerig Nicolas, Dr. , Sommerhalder Michael , Ettori Sara Lisa Margherita

Topics Engineering and Technology

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

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).

Keywords

App development, Machine Learning, Data bases, Data engineering, Systems Engineering, Data Modelling

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Internship , Lab Practice , Student Assistant / HiWi , ETH Zurich (ETHZ)

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Published since: 2025-02-06 , Earliest start: 2025-03-03 , Latest end: 2026-12-31

Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , IBM Research Zurich Lab , Institute for Research in Biomedicine , Hochschulmedizin Zürich , Swiss Institute of Bioinformatics , University of Lucerne , University of Zurich , Zurich University of Applied Sciences , Zurich University of the Arts , Lucerne University of Applied Sciences and Arts , Berner Fachhochschule

Organization Spinal Cord Injury & Artificial Intelligence Lab

Hosts Paez Diego, Dr. , Paez Diego, Dr. , Paez Diego, Dr.

Topics Information, Computing and Communication Sciences

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

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.

Keywords

Data analysis, machine learning, signal processing, wearables, Fitbit, naps detection

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Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-02-06 , Earliest start: 2025-02-10 , Latest end: 2025-08-31

Organization Spinal Cord Injury & Artificial Intelligence Lab

Hosts Gnarra Oriella , Gnarra Oriella

Topics Information, Computing and Communication Sciences , Engineering and Technology

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

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

Keywords

Bayesian inference, sEMG, depth sensing camera, rehabilitation, machine learning, deep transfer learning

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Semester Project , Bachelor Thesis , Master Thesis

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Published since: 2025-02-01 , Earliest start: 2025-03-01 , Latest end: 2025-08-01

Organization Sensory-Motor Systems Lab

Hosts Dash Adyasha

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology

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

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.

Keywords

Data analysis, Machine Learning, Wearable Sensors

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Semester Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-01-22 , Earliest start: 2025-02-03 , Latest end: 2025-09-30

Organization Spinal Cord Injury & Artificial Intelligence Lab

Hosts Gnarra Oriella , Gnarra Oriella

Topics Information, Computing and Communication Sciences , Engineering and Technology

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

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.

Keywords

Data analysis, Machine learning, Wearable and Nearable Sensors Data

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Semester Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)

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Published since: 2025-01-22 , Earliest start: 2025-02-03 , Latest end: 2025-09-30

Organization Spinal Cord Injury & Artificial Intelligence Lab

Hosts Gnarra Oriella , Gnarra Oriella

Topics Information, Computing and Communication Sciences , Engineering and Technology

Your own project ideas?

It is always possible to find a project for motivated students with own ideas in the fields of assistive healthcare technologies , augmented feedback in motor learning, and sports engineering. Please send an email to the indicated contact person of our current research pillars that most closely matches your idea.