Selection of entropy based features for the analysis of the Archimedes' spiral applied to essential tremor

Abstract

Biomedical systems are regulated by interacting mechanisms that operate across multiple spatial and temporal scales and produce biosignals with linear and non-linear information inside. In this sense entropy could provide a useful measure about disorder in the system, lack of information in time-series and/or irregularity of the signals. Essential tremor (ET) is the most common movement disorder, being 20 times more common than Parkinson's disease, and 50-70% of this disease cases are estimated to be genetic in origin. Archimedes spiral drawing is one of the most used standard tests for clinical diagnosis. This work, on selection of nonlinear biomarkers from drawings and handwriting, is part of a wide-ranging cross study for the diagnosis of essential tremor in BioDonostia Health Institute. Several entropy algorithms are used to generate nonlinear feayures. The automatic analysis system consists of several Machine Learning paradigms.

Selection of Entropy Based Features for Automatic Analysis of Essential Tremor

“…The PE based features improve the CER (%) rates in most of the cases. The best results are obtained for m " 7 and t " 7, which improve the previous references for MLP and SVM and are equal to the k-NN system [14].…”

“…Written informed consent, fully approved by the local ethics committee at the Donostia University Hospital, was obtained from all participants in this new study. Table 1 summarizes the features of the group with ET with regard to EPT, diagnosis and demography [13,14]. In addition to the standard clinical exploration (Neuropsychological and Electrophysiological Studies), evaluation of ET was carried out by recording the drawing of an Archimedes' spiral.…”

“…For instance, people diagnosed with AD produce softer and simpler strokes, and people with ET are less stable. ET and Parkinson's disease are other examples [13,14,[23][24][25]. For example, in [18], they have reported the proficiency of writers with regard to the length of the in-air trajectories and the pressure of their handwritings [26].…”

“…It is part of a wider study focused on early ET detection. Feature search in this work aims at preclinical evaluation in order to define useful tests for ET diagnosis [5,13,14].…”

“…We also use the measurement automatically provided by WEKA "Coverage of cases" (0.95 level); that is, the confidence interval at 95% level. Despite the small sample size that could point to the use of Leave One Out Cross-Validation (LOOC), we were oriented to the selected k-fold cross-validation by the model number, the sample richness and previous works [14,22].…”