I completed my secondment at TNO Soesteberg (The Netherlands) under the supervision of Dr Anne-Marie Brouwer with whom I share a vivid interest for Brain Computer Interfaces (BCI). The secondment took place on several weeks during year 2 and 3 of my PhD for a total of 1 month (31 days). We planned my first visit to be from 21st August 2016 to 31st August 2016. The aim of this first contact was to familiarise myself with the literature on the topic of movement prediction using EEG, the lab and possibly collect some pilot data. The second visit was planned for 23rd February to March 4th 2017 with the aim of collecting data for the experiment. Finally, data analysis was carried out during my last visit from 14th to 22nd January 2018.
The main objective of the secondment was for me to collaborate and help out in the several steps needed to carry out to completion an on-going experiment at TNO. The experiment aimed, briefly, to investigate accuracy and timing of self-paced movement prediction using EEG in the context of BCI. Personally, I saw this opportunity as a way of deepening my understanding of EEG techniques, which I had used already during my undergraduate and postgraduate studies. As my main research topic is linked to BCI application in the clinical and rehabilitation setting, the secondment also offered me the chance to see how the same techniques can be applied in the wider context of the general public.
During the first visit, I was able to carry out a literature search on the topic, helping me not only understand the background of the research but also giving me the chance to further my knowledge in an area of BCI I had yet to encounter before. In general, the topic of movement prediction with EEG is extremely versatile and can be tailored for most BCI applications, whether it being clinical or recreational. In the span of the 10 first days I spent at TNO we were also able to collect some pilot data. This allowed us to agree on a methodology to follow for the actual data collection and produce initial evidence of the validity of our research rationale that were presented at a lunchtime seminar at the end of the week. Additionally, at this stage I was able to get familiar again with the use of EEG that I had left at the end of my postgraduate studies to move on to a different brain imaging technique (fMRI) for my PhD.
In my second visit, we completed data collection of 20 participants chosen from a wide range of ages, sexes and occupations. Results from a preliminary data analysis, carried out by TNO, converged in a conference paper published later on in March 2017 (Brouwer et al., 2017).
Finally, during my last visit we completed data analysis on EEG specific traces and components that investigate further the accuracy and feasibility of using this brain imaging technique in self-paced movement prediction for EEG-based BCIs.
In conclusion, this was overall a great opportunity that has significantly improved my experience as a student part of the PACE network both on a work related but also personal level. I thoroughly enjoyed my time at TNO and I think that the collaboration was a true success on my part as it gave me the chance to not only gain a little more experience in the research field but also, given the peculiar and independent nature of the institution, to get in contact with a professional work environment that is extremely different from what I was used to so far.
Brouwer, A.M., Van der Waa, J.S., Hogervorst, M.A., Cacace, A., and Stokking, H. (2017). A feasible BCI in real life: using predicted head rotation to improve HMD imaging. BCIforReal ’17 Proceedings of the 2017 ACM Workshop on An Application-oriented Approach to BCI out of the laboratory, 35-38.