Summary of open projects (Spring 2024)
Open positions for student projects will be listed here when available:
- Master thesis: Implementation of teleoperation with force feedback for a neuroendovascular robotic system
- Master thesis or Semester Project: Comparison of balance metrics for autonomyo exoskeleton
- Master thesis or Internship: Fall detection with an active hip exoskeleton
- Master thesis or Semester Project: Development and validation of an automated calibration and multisite spinal cord stimulation system
- Master thesis or Semester Project: Multisite Transcutaneous Spinal Cord Stimulation and analysis of the selectivity of muscle recruitment during gait
To apply, please send an email to the responsible person for the project with your CV and briefly describe your relevant experience.
Implementation of teleoperation with force feedback for a neuroendovascular robotic system
Category: Master thesis
Keywords: Ischemic stroke, Teleoperation, Surgical Robotics
Type: 70% programming, 30% experimentation+validation
Responsible: Evgenia Roussinova (MED 3 1115, [email protected])
Description: Stroke is the 2nd leading cause of death worldwide. In ischemic stroke (the most common), a blood clot blocks an artery in the brain and thus prevents the neural tissue from getting oxygen and nutrients. We are working on a teleoperated neuroendovascular robotic system whose aim is to assist the doctor in performing the medical procedure of mechanical thrombectomy (“clot extraction”). Teleoperation is interesting for several reasons: 1) The procedure is currently performed under X-rays which are harmful for the body. Therefore, we would like to enable the doctor to operate from a distance; 2) Teleoperation allows for shared control strategies (benefitting from robotic precision and human experience/supervision); 3) With a teleoperated system we can improve the safety by providing an amplified force feedback to the operator.
In this context, we are looking for a master thesis student who will improve the basic teleoperation which is currently implemented on the system by adding reliable force feedback and implementing different teleoperation modes. Then the implementations will have to be tested with our collaborators from the Geneva University Hospitals in an in vitro setup.
Skills: C/C++ programming (preferably with experience with Qt and multithreading), Haptics
Comparison of balance metrics for autonomyo exoskeleton
Category: Semester project or Master thesis
Keywords: Gait analysis, Balance metrics, robotics, lower-limb exoskeletons
Type: 10% theory, 30% experimentation, 60% data analysis
Responsible: Zeynep Özge Orhan (MED 3 1015, [email protected]
This project concerns the analysis of several metrics of the balance of exoskeleton users of the autonomyo lower-limb exoskeleton. Autonomyo is developed for people who have walking impairments due to muscular weakness or motor deficits. The laboratory BIOROB and the research group REHAssist have established expertise in human locomotion and lower limb exoskeletons. Autonomyo has been designed at EPFL.
Currently, Center of Pressure (CoP) based metrics are used to investigate the balance of different locomotion tasks. However, by using an external measurement system we can also investigate center of mass (CoM) based metrics as well.
This project involves different steps:
– Familiarization with existing hardware/software and firmware of the exoskeleton
– Conduct experiments with autonomyo
– Prepare functional code blocks that is synchronizing two measurement systems
– Analyze the collected data for various balance metrics
Skills:
– Experience with Matlab for data analysis
– Experience with C++
References:
Gordon, D. F., Henderson, G., & Vijayakumar, S. (2018). Effectively quantifying the performance of lower-limb exoskeletons over a range of walking conditions. Frontiers in Robotics and AI, 5. https://doi.org/10.3389/frobt.2018.00061
Fall detection with an active hip exoskeleton
Category: Master thesis or internship
Keywords: Balance control, data processing, dynamics model, experiments, locomotion, machine learning, robotics, treadmill, kinematics
Type: 70% programming, 10% hardware, 20% theory
Responsible: Giulia Ramella (MED 3 1015, [email protected])
Description: Exoskeletons have experienced unprecedented growth in recent years and portable exoskeletons have demonstrated the possibility to increase the endurance, reduce energetic expenditure, and increase performance during walking. In our lab, a hip-joint active hip orthosis (“eWalk”) has been prototyped and tested in recent years.
In order to have correct coordination between human and robot, exoskeletons must be able to detect changes in the gait pattern and provide assistance accordingly. To this day, fall detection and prevention have not been addressed by many wearable devices. This project intends to address this challenge by designing, implementing, and validating a novel algorithm.
If interested, please send an email with your CV and previous experiences that could be relevant to the project.
Development and validation of an automated calibration and multisite spinal cord stimulation system
Category: Semester project or Master thesis
Type: 20% hardware, 40% software, 40% experimentation
Responsible: Mouhamed Zorkot (MED 3 1115, [email protected])
Transcutaneous spinal cord stimulation (tSCS) is a recent and promising approach that has the potential to promote improved motor control for both upper and lower limbs, voluntary movement, and spinal cord modulation for various pathologies. However, the setup for performing the protocol requires specialized knowledge for the application of the electrode position on the vertebrae in the spinal cord and stimulation current. This setup depends on the analysis of the electromyographic (EMG) responses of the muscles. In this context, aiming to facilitate clinical applications and improve the configuration of stimulation parameters for each patient, the objective of this work is to develop a multi-site and automated tSCS setup combining a set of electrodes positioned on the vertebrae of the spinal cord, synchronized EMG recordings and an automated stimulation algorithm (protocol). The protocol aims to analyze the selectivity of the tSCS, test electrode locations, and stimulation amplitudes in real-time, and classify the posterior root muscle reflexes nos musculos dos membros inferiores.
This project involves different steps:
– tSCS and electrophysiological tests
– Development of an automated calibration algorithm using EMG and tSCS
– Experiments and data analysis
Skills:
– Knowledge in programming
– Machine learning
– Data analysis
– Experience with Qt
Reference:
Salchow-Hömmen C, Schauer T, Müller P, Kühn AA, Hofstoetter US, Wenger N. Algorithms for Automated Calibration of Transcutaneous Spinal Cord Stimulation to Facilitate Clinical Applications. Journal of Clinical Medicine. 2021; 10(22):5464. https://doi.org/10.3390/jcm10225464
Multisite Transcutaneous Spinal Cord Stimulation and analysis of the selectivity of muscle recruitment
during gait
Category: Semester project or Master thesis
Type: 40% hardware, 40% software, 20% experimentation
Responsible: Mouhamed Zorkot (MED 3 1115, [email protected])
Transcutaneous spinal cord stimulation (tSCS) is a recent and promising approach that has the potential to promote improved motor control for both upper and lower limbs, voluntary movement, and spinal cord modulation for various pathologies. However, when compared to more invasive protocols, tSCS may not present the same selectivity in muscle recruitment and, consequently, limit motor control benefits. In this context, the objective of this work is to analyze muscle recruitment according to the variation of stimulator parameters and the position of the active electrode in the spinal cord. In other words, we aim to develop a protocol for stimulation of the spinal cord with different channels and to analyze the correlation of the stimulator parameters with the extension and flexion movements of the main muscles involved in gait. This project involves conducting experiments and developing techniques for tSCS during walking, with the aim of achieving greater selectivity in the recruitment of flexor and extensor muscles. This will be done by analyzing the electromyographic (EMG) response elicited by stimulation of a given position of the electrode on the vertebra and different parameters of the stimulator during gait.
This project involves different steps:
– tSCS and electrophysiological tests
– Development of an automated calibration algorithm using EMG and tSCS
– Experiments and data analysis
Skills:
– Knowledge in programming
– Machine learning
– Data analysis
If none of the projects are suitable for you, but you are interested in gait rehabilitation technologies, please contact us to discuss possible opportunities.