Publications

 

Motor Imagery Virtual Reality Neurorehabilitation with BCI Functional electrical stimulation Robotic rehabilitation

 

Irimia, D.C., Ortner, R., Poboroniuc, M.S., Ignat, B.E. and Guger, C., 2018. High classification accuracy of a motor imagery based brain-computer interface for stroke rehabilitation training. Frontiers in Robotics and AI, 5, p.130.

Guger, C., Millán, J.D.R., Mattia, D., Ushiba, J., Soekadar, S.R., Prabhakaran, V., Mrachacz-Kersting, N., Kamada, K. and Allison, B.Z., 2018. Brain-computer interfaces for stroke rehabilitation: summary of the 2016 BCI Meeting in Asilomar. Brain-Computer Interfaces, 5(2-3), pp.41-57.

Irimia, D. C., Cho, W., Ortner, R., Allison, B. Z., Ignat, B. E., Edlinger, G., & Guger, C. (2017). Brain‐computer interfaces with multi‐sensory feedback for stroke rehabilitation: a case study. Artificial organs, 41(11), E178-E184.

Cho W, Heilinger A, Xu R, Zehetner M, Schobesberger S, et al. (2017) Hemiparetic Stroke Rehabilitation Using Avatar and Electrical Stimulation Based on Non-invasive Brain Computer Interface. International Journal of Physical Medicine and Rehabilitation 5:411.

Huggins, J. E., Guger, C., Ziat, M., Zander, T. O., Taylor, D., Tangermann, M., ... & Ruffini, G. (2017). Workshops of the Sixth International Brain–Computer Interface Meeting: brain–computer interfaces past, present, and future. Brain-Computer Interfaces, 1-34.

Xu R., Allison B. Z., Ortner R., Irimia D. C., Espinosa A., Lechner A., & Guger C. (2017). How Many EEG Channels Are Optimal for a Motor Imagery Based BCI for Stroke Rehabilitation?. In Converging Clinical and Engineering Research on Neurorehabilitation II (pp. 1109-1113). Springer International Publishing.

Cho W., Sabathiel N., Ortner R., Lechner A., Irimia D.C., Allison B.Z., Edlinger G. and Guger C., 2016. Paired Associative Stimulation using Brain-Computer Interfaces for Stroke Rehabilitation: A Pilot study. European Journal of Translational Myology, 26(3).

C. Guger, C. Kapeller, R. Ortner, K. Kamada, Motor Imagery with Brain-Computer Interface Neurotechnology (pp. 61-79), in: Motor Imagery: Emerging Practices, Role in Physical Therapy and Clinical Implications, edited by B.M Garcia, 2015. 

R. Ortner, J. Scharinger, A. Lechner, C. Guger (2015). How many people can control a motor imagery based BCI using common spatial patterns?, in: 7th International IEEE/EMBS Conference on Neural Engineering (NER) 2015, pp. 202-205.

Rupert Ortner, Alexander Lechner, Christoph Guger (2015): Stroke Rehabilitation assisted by a Brain-Computer Interface (BCI) and multimodal feedback: First results. In proccedings of the European Stroke Conference, 15.05.2015, Vienna, AT. Poster.

D. C. Irimia, M. S. Poboroniuc and R. Ortner, “Improved Method to Perform FES & BCI Based Rehabilitation,” in The 4th IEEE International Conference on E-Health and Bioengineering, 2013.

C. Guger, H. Ramoser and G. Pfurtscheller, “Real-Time EEG Analysis with Subject-Specific Spatial Patterns for a Brain–Computer Interface (BCI),” IEEE Trans. Rehab. Eng, vol. 8, pp. 447-456, 2000.

K. Shindo, K. Kawashima and e. a. Ushiba, “Effects of neurofeedback training with an electroencephalogram-based brain-computer interface for hand paralysis in patients with chronic stroke: a preliminary case series study,” J Rehabil Med, pp. 951-957, 43(10) 2011.

J.C. Moreno, J. L. Pons, E. Gruenbacher, C. Guger (2010). BCI-driven stroke rehabilitation; the concept of the BETTER project..

C. Guger, W. Harkam, C. Hertnaes, G. Pfurtscheller (1999). Prosthetic control by an EEG-based brain-computer interface (BCI). 5th European Conference for the Advancement of Assitive Technolgoy Düsseldorf, Germany, AAATE.

G. Pfurtscheller, C. Guger (1999). "Brain-computer communication system: EEG-based control of hand orthosis in a tetraplegic patient." Acta Chir. Austriaca 31(159): pp. 23 - 25. Brain-computer communication system.

R. Ortner, D. Ram, A. Kollreider, H. Pitsch, J. Wojtowicz, and G. Edlinger, “Human-computer confluence for rehabilitation purposes after stroke,” in Virtual, Augmented and Mixed Reality. Systems and Applications, Springer, 2013, pp. 74–82.

R. Ortner, D.-C. Irimia, C. Guger, and G. Edlinger, “Human Computer Confluence in BCI for Stroke Rehabilitation,” in Foundations of Augmented Cognition, Springer, 2015, pp. 304–312.

A. Ramos-Murguialday, D. Broetz, M. Rea, L. Läer, O. Yilmaz, F. L. Brasil, G. Liberati, M. R. Curado, E. Garcia-Cossio, A. Vyziotis, W. Cho, M. Agostini, E. Soares, S. Soekadar, A. Caria, L. G. Cohen, and N. Birbaumer, “Brain-machine-interface in chronic stroke rehabilitation: A controlled study.,” Ann Neurol. 2013, p. doi: 10.1002/ana.23879, 2013.

Cho, W., Vidaurre, C., Hoffmann, U., Birbaumer, N., & Ramos-Murguialday, A. (2011, August). Afferent and efferent activity control in the design of brain computer interfaces for motor rehabilitation. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE (pp. 7310-7315). IEEE.

#Advisory-Board "Advisory-Board"

Advisory Board of recoveriX

 

The advisory board consists of international key experts in the fields of neuroscience, neurology and neurosurgery who are continuously contributing their experiences and clinical needs into the research, development and application of recoveriX by using the system in their clinical and research environment. These experts have a crucial interest in optimizing motor rehabilitation and maximizing the positive outcome of stroke therapy.

 

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Brendan Allison, PhD

Allison Consulting, San Diego

 

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Prof. Marian Poboroniuc, PhD

Technical University of Iasi, Romania

 

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Milena Korostenskaja, MD, PhD

Florida Hospital for Children, US

 

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Vivek Prabhakaran, MD, PhD

University of Wisconsin, US

 

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Tetsuo Ota, MD, PhD

Asahikawa Medical University, Japan

 

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Rossella Spataro, MD, PhD

University of Palermo, Italy

 

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Kyosuke Kamada, MD, PhD

Mengumino Hospital, Sapporo, Japan

 

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Adam Hebb, MD, PhD

St. Joseph's Hospital, Denver, US