Jörn Rickert
University of Freiburg
36 Papers
79 Citations
Jörn Rickert is an academic researcher from University of Freiburg. The author has contributed to research in topics: Computer science & Local field potential. The author has an hindex of 9, co-authored 35 publications.
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Papers
Inference of hand movements from local field potentials in monkey motor cortex
Carsten Mehring,Jörn Rickert,Eilon Vaadia,Simone Cardoso de Oliveira,Ad Aertsen,Stefan Rotter +5 more
TL;DR: It is shown that hand movement target and velocity can be inferred from multiple local field potentials (LFPs) in single trials approximately as efficiently as from multiple single-unit activity recorded from the same electrodes.
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Encoding of movement direction in different frequency ranges of motor cortical local field potentials.
Jörn Rickert,Simone Cardoso de Oliveira,Eilon Vaadia,Ad Aertsen,Stefan Rotter,Carsten Mehring +5 more
TL;DR: Using the different frequency components in the LFP is useful in improving inference of movement parameters from local field potentials, with the best performance achieved by the combination of different frequency ranges.
359
Adaptive Classification for Brain Computer Interfaces
Julie Blumberg,Jörn Rickert,Stephan Waldert,Andreas Schulze-Bonhage,Ad Aertsen,Carsten Mehring +5 more
- 22 Oct 2007
TL;DR: This paper evaluates the performance of a new adaptive classifier for the use within a brain computer-interface (BCI) and suggests an approach to strongly improve the precision and the time needed to gain accurate control in future BCI applications.
95
An online brain–machine interface using decoding of movement direction from the human electrocorticogram
Tomislav Milekovic,Jörg Fischer,Tobias Pistohl,Johanna Ruescher,Johanna Ruescher,Andreas Schulze-Bonhage,Andreas Schulze-Bonhage,Ad Aertsen,Jörn Rickert,Tonio Ball,Tonio Ball,Carsten Mehring +11 more
TL;DR: The results demonstrate the feasibility of an online BMI using decoding of movement direction from human ECoG signals and shows that the same approach can be realized using brain activity measured directly from the surface of the human cortex using electrocorticography (ECoG).
78
Invasive brain–machine interfaces: a survey of paralyzed patients’ attitudes, knowledge and methods of information retrieval
Jacob Lahr,Christina Schwartz,Bernhard Heimbach,Ad Aertsen,Jörn Rickert,Tonio Ball,Tonio Ball +6 more
TL;DR: The attitudes of paralyzed patients eligible for BMIs, particularly patients affected by amyotrophic lateral sclerosis, are investigated, indicating that paralyzed patients are indeed interested in BMIs and the Internet is an important source of information on ATDs.
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