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Brain computer interfaces (BCI) that use the steady-state-visual-evoked-potential (SSVEP) as neural source, offer two main advantages over other types of BCIs: shorter calibration times and higher information transfer rates. SSVEPs elicited by high frequency (larger than30 Hz) repetitive visual stimulation are less prone to cause visualfatigue, safer, and more comfortable for the user. However in the high frequency range there is a practical limitation because only fewfrequencies can elicit sufficiently strong SSVEPs for BCI purposes.We bypass this limitation by using only one stimulation frequency and different phases. To detect the phase from the recorded SSVEP, weuse spatial filtering combined to phase synchrony analysis. We developed an online BCI implementation which was tested on six subjects and resulted on an average accuracy of 95.5% and an average bit rateof 34 bits-per-minute. Our approach has the advantage of entailing only minimal visual annoyance for the user.

This document describes the High Frequency (HF) Steady-State Visual Evoked Potential (SSVEP) based Brain Computer Interface (BCI) developed at Philips Research Europe (PRE). The interface is based on the fact that the oscillatory visual stimuli can elicit oscillatory brain activity at the same frequency or at that of higher harmonics. This signal can be detected by analyzing human electroencephalographic (EEG) recordings. This HF SSVEP BCI system is especially geared towards using high frequencies (above 30Hz) and is utilizing spatial filtering of the EEG signals in the occipital region to extract the dominant frequency component. Our HF SSVEP BCI system supports both calibration procedure and normal operation where brain signals are used for control and/or communication. The calibration is done for aparticular user and prior to the operation. The system setup includes three main components: an electronic device for EEG signal acquisition, a processing unit for EEG signal processing, and an electronic devicefor rendering oscillatory stimuli. The HF SSVEP BCI is designed with the possibility to interface with arbitrary devices or software application. This document reports on the software platform and the operation of the HF SSVEP BCI. The algorithmic details can be found in [1].

The goal of dry electrode development activity within the WP2 is tobuild a dry electrode prototype for brain wave sensing that is comfortable for the user and provides sufficient signal quality. The electrodes are to be utilized in BCI applications, namely Steady-StateVisually Evoked Potential (SSVEP),Event Related Synchronization andDe-synchronization (ERD/ERS),and P300 based BCIs. Due to the statusof the dry electrode technology and our non-encouraging results onthe evaluation of the contactless dry sensors we re-focused our efforts in developing an EEG system using dry electrodes that have galvanic contact to the human scalp. The first goal we set is to reliably detect the alpha brain rhythm (brain waves in the range from 8 to12Hz) as these brain waves are the most prominent ones in the EEG spectrum.The outcome of the evaluation presented here is that the signal quality of dry electrodes is sufficient to reliably measure alpha brainactivity. This is con-firmed through user studies with the medicallycertified amplifier - Mobi from TMSi. However, due to the skin contact problems and high input impedance, reported in the deliverable,robustness of dry-electrode (in combination with the amplifier) hasto be further improved. In particular, the dry electrode design andamplifier front end have to be further optimized.The robustness of the dry electrode-amplifier combination has to befurther improved to achieve a stable signal and reliable performancewhen measuring brain waves of people with long and thick hair. Thefollowing directions for further developments are envisioned:- Optimization of dry electrode design, focusing on- electrode material, i.e., using “bio-approved” materials such asgold and silver/silver-chloride used in this deliverable that willenable low impedance to the skin- number of pins to achieve good contact and increase the comfort- Optimization of amplifier front-end to cope with variation in input impedance- Optimize existing amplifier technology for usage with the developed dry electrodes.

Recent technological advances in the field of skin electrodes and on-body sensors indicate a possibility of having an alternative to the traditionally used conductive gel electrodes for measuring electrical signals of the brain (electroencephalogram, EEG). This paper evaluates whether water-based and dry contact electrode solutions can replace the gel ones. The quality of the obtained signal by three headsets, each using 8 electrodes of a different type, is estimated onthe steady state visual evoked potential (SSVEP) brain-computer interface (BCI) use case. The stimuli frequencies in the low (12 to 21Hz) and high (28 to 40Hz) frequency domain were used. Six people, that had different hair length and type, participated in the experiment. SSVEP response in terms of power spectra across different electrodes is compared and the impact of noise on temporal characteristics ofthe response is discussed. For people with shorter hair style the performance of water-based and dry electrodes comes close to the gelones in the optimal setting. On average, the classification accuracy of 0.63 for dry and 0.88 for water-based electrodes is achieved, compared to the 0.96 obtained for gel electrodes. The theoretical maximum of the average information transfer rate across participants was 23bpm for dry, 38bpm for water-based and 67bpm for gel electrodes. Furthermore, the convenience level of all three setups was seen as comparable. These results demonstrate that, having optimized headset and electrode design for dry and water-based electrodes for people with different hair length and type, dry and water-based electrode scan replace gel ones in BCIs and Neurofeedback applications where lower communication speed is acceptable.