Christian Laßmann
Christian Laßmann
University of Tübingen
Department of Computer Science
Computer Engineering
Sand 13
72076 Tübingen
Germany
- Lab
- Neural Interfaces and Brain Signal Decoding
- Role
- PhD student
- Telephone
- +49 - (0) 70 71 - 29 - 77347
- Telefax
- +49 - (0) 70 71 - 29 - 50 62
- Office
- Sand 14, C222
- Office hours
- By appointment
Research Interests
- Brain-Computer Interface (BCI)
- Analysis of EEG & EMG data
- Neurorehabilitation
- Machine Learning
Research projects
Neuro-muscular modelling and analysis of gait abnormalities in early hereditary spastic paraplegia (HSP)
Hereditary spastic paraplegia (HSP) is a group of hereditary, slowly progressive neurological movement disorders characterized by spastic gait disorder. Degeneration of nerve cells in the spinal cord leads on the one hand to progressive spasticity (pathological increase in muscle tension, hyperreflexia) in certain groups of the leg muscles, while other groups are affected by muscle weakness.
For a more detailed understanding of the progressive nerve degeneration and the associated movement impairments as well as the development of assistance systems such as functional electrostimulation (FES), the early, pre-clinical phase of the disease is of particular interest, when the typical clinical symptoms have not yet become visible.
Context-sensitive neural-controlled hand-exoskeleton for restoration of everyday-capability and autonomy after brain and spinal cord injuries
The development of robotic systems that interacts with the human nervous system, promise to improve the autonomy, quality of life, and capability of people with disabilities. Brain-Computer Interfaces (BCI) can be used to translate the electrical brain activity into control signals of a robotic exoskeleton. Therefore, it is possible to restore grasping movements of a paralyzed hand by interpreting the neural correlates of the movement. For lack of signal quality, BCI systems based on non-invasive methods, e.g. electroencephalography (EEG), can only be used limited in everyday situations.
In the project CONSENS-NHE we develope a non-invasive and everyday suitable neural-controlled hand-exoskeleton, targeting the compensation of a paralyzed hand, as it can occur after strokes or spinal cord injuries. Within the project the latest methods of machine learning, optical object-recognition, movement analysis, and biological inspired design for robotic systems are combined with neurorehabilitative research. The system will allow people with hand paralysis to grasp and manipulate different objects of everyday life. For direct control of the hand-exoskeleton, the grasping intention is identified based on neural signals measured on the scalp using EEG.
Teaching
Brain-Games: associated programming project for the lecture Software Engineering | Winter 2021 |
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Seminar: Machine Learning and Artificial Neural Networks in Biomedical Applications | Winter 2018 Summer 2020 Winter 2020 Summer 2021 |
Thesis Topics
Finished Thesis Topics
Publications
2019
Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis
by Meike Annika Wilke, Christian Niethammer, Britta Meyer, Dario Farina, and Strahinja DosenIn Journal of NeuroEngineering and Rehabilitation 16(155): 155, 2019. [BIB] [DOI] [ABSTRACT]
@article{MCBDS122019,
author = {Wilke, Meike Annika and Niethammer, Christian and Meyer, Britta and Farina, Dario and Dosen, Strahinja},
title = {Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis},
journal = {Journal of NeuroEngineering and Rehabilitation},
year = {2019},
month = {dec},
volume = {16},
number = {155},
pages = {155},
doi = {10.1186/s12984-019-0622-9},
month_numeric = {12}
}
2018
Robustness of single-hand classification against other-hand activity in EEG
by Christian Niethammer, Wolfgang Rosenstiel, and Martin SpülerIn Proceedings of the 7th International BCI Meeting 2018, pages 28-29, 2018. [BIB] [PDF]
@inproceedings{CWM052018,
author = {Niethammer, Christian and Rosenstiel, Wolfgang and Spüler, Martin},
title = {Robustness of single-hand classification against other-hand activity in EEG},
booktitle = {Proceedings of the 7th International BCI Meeting 2018},
year = {2018},
month = {may},
pages = {28-29},
address = {Asilomar, CA},
month_numeric = {5}
}
2015
Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity
by Martin Spüler and Christian NiethammerIn Frontiers in Human Neuroscience 9(): 155, 2015. [BIB] [DOI]
@article{MC032015,
author = {Spüler, Martin and Niethammer, Christian},
title = {Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity},
journal = {Frontiers in Human Neuroscience},
year = {2015},
month = {mar},
volume = {9},
number = {},
pages = {155},
doi = {10.3389/fnhum.2015.00155},
month_numeric = {3}
}
2014
Classification of error-related potentials in EEG during continuous feedback
by Martin Spüler, Christian Niethammer, Wolfgang Rosenstiel, and Martin BogdanIn Proceedings of the 6th International Brain-Computer Interface Conference, 2014. [BIB]
@inproceedings{MCWM092014,
author = {Spüler, Martin and Niethammer, Christian and Rosenstiel, Wolfgang and Bogdan, Martin},
title = {Classification of error-related potentials in EEG during continuous feedback},
booktitle = {Proceedings of the 6th International Brain-Computer Interface Conference},
year = {2014},
month = {sep},
month_numeric = {9}
}