ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en BRAIN COMPUTER INTERFACES FOR BRAIN ACQUIRED DAMAGE MARC SEBASTIÁN ROMAGOSA DOCTORAL THESIS PHD IN NEUROSCIENCE 2020 DIRECTOR Esther Udina i Bonet DIRECTOR Rupert Ortner DIRECTOR AND TUTOR Xavier Navarro Acebes Medical Physiology Unit Department of Cellular Biology, Physiology and Immunology Neuroscience Institute Universitat Autònoma de Barcelona MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE Per a la meva dona, la Núria i els meus fills, l’Andreu i l’Agnès, sense vosaltres res de tot això val la pena. 2 | P a g e MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE Acknowledgments First, I would like to thank Dr. Rupert Ortner for his constant support and advice during this time, by his side I have been able to learn every day. He has been a good boss, a good partner, and a good colleague. These special thanks also go to Dr. Esther Udina for her patience and help from the beginning, for so many hours spent and always having a word of encouragement and trusting me. I am also grateful to Dr. Xavier Navarro, who together with Dr. Esther Udina were the professors of neurophysiology at the beginning of my university education, with whom I was able to discover my vocation for research in neuroscience. To Dr. Christoph Guger, for giving me the possibility to work at g.tec medical engineering, a fantastic place! I can never stop expressing my gratitude for his trust. I also thank you for giving me the possibility to do the PhD in this company and to live for a while in Austria to get the international mention. I would also like to thank the entire g.tec medical engineering team, my colleagues in Austria and especially those in Barcelona, I was able to learn a lot from them. I also thank them for all the fun moments in and out of work, which undoubtedly make it less difficult to go working every morning. My thanks for the efforts of the master's students I have had during this time (Clara Matencio, Laura Menés and Mireia Coll). I would like to make a special mention for Dr. Josep Dinarès and Javier Rodríguez for all the time they dedicated to teaching me and to discuss in front of a whiteboard full of scribbles. I am happy that those times and those scribbles have finally resulted in very good publications and projects. I must mention the help of the "Doctorats Industrials" program offered by the Generalitat de Catalunya, this thesis has been possible thanks to this project. Finalment agraeixo a la meva família, als meus pares, als meus germans i als meus avis, perquè gràcies a tots ells he pogut estudiar i créixer com a persona. A l’Andreu i l’Agnès, que sempre m’han esperat a casa per rebre’m amb rialles i amb ganes de jugar quan arribo de la feina. I finalment a tu Núria, gràcies per aguantar-me i ajudar-me dia rere dia, per aquests anys junts i per tots els que vindran, per tots els esforços que fas, i per estar sempre amb mi amb bon humor i amb alegria. Res de tot aquest esforç valdria la pena si no us tingués. Dono gràcies a Déu perquè sempre és bo amb mi. 3 | P a g e MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE Abbreviation list BCI Brain Computer Interface EEG Electroencephalography ALS Amyotrophic Lateral Sclerosis ECoG Electrocorticography MEG Magnetoencephalography fNIRS Functional Near-Infrared Spectroscopy ERPs Event-related potentials EP Evoked Potential AEP Auditory Evoked Potential VEP Visual evoked potential SSVEP Steady-State Visual Evoked Potential SCP Slow Cortical Potentials SMR Sensorimotor Rhythms MI Motor Imagery ERS Event-Related Synchronization ERD Event-Related Desynchronization CBF Cerebral Blood Flow CBV Cerebral Blood Volume GABA Gamma-Aminobutyric Acid ICH Intracranial Hemorrhage CSF Cerebrospinal Fluid MMP Matrix Metalloproteinases M1 Primary Motor Cortex CT Computational Tomography fMRI Functional Magnetic Resonance Imaging qEEG Quantitative EEG BSI Brain Symmetry Index DAR Delta Alpha Ratio PRI Power Ratio Index FFT Fast Fourier Transform FES Functional Electrical Stimulation 4 | P a g e MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE LC Laterality Coefficient AP Absolute Power RP Relative Power ESS European Stroke Scale MRC Medical Research Council MAS Modified Ashworth Scale MNN Mirror Neuron Network FMA Fugl Meyer Assessment Scale FMAue Fugl-Meyer Assessment for the upper extremity FMAle Fugl-Meyer Assessment for the lower extremity SNR Signal Noise Ratio LDA Linear Discriminant Analysis rEEG Resting EEG BBT Box and Block Test 9HPT or NHPT 9-Hole Peg Test FTRS Fahn Tremor Rating Scale MOCA Montreal Cognitive Assessment TPDT Two Point Discrimination Test SRQ Self-Rated Questionnaire BI Barthel Index IQR Inter-Quartile Rate SD Standard Deviation SWT Shapiro Wilk Test SUS System Usability Scale MWUT Mann–Whitney U test MWWT Wilcoxon Test or Mann–Whitney W test MD Mean Difference SMD Standard Mean Difference 5 | P a g e MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE Contents Chapter I - Introduction to the Brain Computer Interfaces ................................................................... 11 Background ....................................................................................................................................... 12 Brain signals...................................................................................................................................... 13 Origin of brain signals................................................................................................................... 13 Acquisition methods ..................................................................................................................... 14 Features of neural signals .............................................................................................................. 15 Neural basis of Brain Computer Interfaces in Stroke survivors ....................................................... 17 Physiology of ischemic stroke ...................................................................................................... 18 BCI and stroke recovery ................................................................................................................... 22 EEG biomarkers for stroke diagnosis and prognosis ........................................................................ 24 Improving BCI performance for neurorehabilitation ........................................................................ 25 Objectives of the thesis ..................................................................................................................... 27 Experimental design ...................................................................................................................... 27 Chapter II - Methods ............................................................................................................................. 28 Literature search protocol for the meta-analysis ............................................................................... 29 Identification and selection of trials .............................................................................................. 29 Assessment of characteristics of trials .......................................................................................... 29 Data analysis ................................................................................................................................. 31 BCI system used for the clinical trials .............................................................................................. 32 Instructions of a BCI therapy session ........................................................................................... 32 MI exercise .................................................................................................................................... 33 Motor Imagery Accuracy .............................................................................................................. 33 Clinical trial I – EEG biomarkers for stroke diagnosis and prognosis .............................................. 34 Protocol ......................................................................................................................................... 34 Assessment tests ............................................................................................................................ 35 Statistical analysis ......................................................................................................................... 36 Quantitative EEG Biomarkers ...................................................................................................... 36 Clinical trial II - Improving BCI performance with gamification ..................................................... 40 6 | P a g e MARC SEBASTIÁN ROMAGOSA BCI FOR BRAIN ACQUIRED DAMAGE Game design .................................................................................................................................