Differentiation of Saccadic Eye Movement Signals.

Saccadic electrooculograms are discrete biosignals that contain the instantaneous angular position of the human eyes as a response to saccadic visual stimuli. These signals are essential to monitor and evaluate several neurological diseases, such as Spinocerebellar Ataxia type 2 (SCA2). For this, biomarkers such as peak velocity, latency and duration are computed.

A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis.

Medical data are often tricky to get mined for patterns even by the generally demonstrated successful modern methodologies of deep learning. This paper puts forward such a medical classification task, where patient registers of two of the categories are sometimes hard to be distinguished because of samples showing characteristics of both labels in turn in several repetitions of the screening procedure. To this end, the current research appoints a pre-processing clustering step (through self-organizing maps) to group the data based on shape similarity and relabel it accordingly.