It is a challenge to provide an efficient healthcare service for countries with continental dimensions. Mechanisms for a more efficient and better attendance of patients are necessary due to the increasing costs of health care systems. This work proposes the development of a system for monitoring vital signs (including ECG) through PDAs. Therefore, this has made possible the local attendance of patients by medical practitioners (here called health agents) with the support of specialist's physicians through a second opinion system. The proposed approach supports: recording and visualization of ECG waveforms. Moreover, patient's information can be transmitted to and from a remote health care server. In order to make easier the use by doctors and health agents, a user-friendly graphical interface has been developed. Methods for an efficient data access have been also developed to cope with storage constraints of PDAs.

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The most popular paradigm in BCIs is the steady-state visually evoked potential (SSVEP) due to their advantages, such as the high information transfer rate (ITR), the time spent on users in the training phase, and the capacity to discriminate each stimulus. One of the most influential factors in the ITR evaluation is the feature extraction methods since these can increase the accuracy. Here, we compare nine methods for the extraction of features from SSVEP signals to identify those with better performance, according to the time window (TW), its technology (equipment and number of nodes), and the value of ITR. The study identifies two groups: the first one is characterized by presenting variations of correlated component analysis (CCA), which is highly used to increase the ITR due to its efficiency in classification and its capacity of response to reduction (TW), such as MsetCCA, IT-CCA, FBCCA; the second one are the representation special based methods that consider the non-linear nature of the electroencephalogram (EEG) signal such as TRCA, CORRCA, EMD, and VMD. The results show a considerable difference between these groups. The maximum ITR value for FBCCA was 117.75 [bits/min] in a TW of 1.25s, while the VMD method achieved 3120 [bits/min] in a TW of 1s, respectively. The comparison covers signals between 0.55 and 8 seconds, taking into account visual strain, the experimental environment, and other artifacts.

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