Sivarit Sultornsanee

TL;DR: A network approach to uncovering trends in an area of research by analyzing keywords appearing in scholarly articles, which shows that keywords organize themselves into three categories: topical keywords, complimentary keywords and, diverse keywords.

TL;DR: An EMG-based feature extraction method based on a normalized weight vertical visibility algorithm (NWVVA) for myopathy and ALS detection is proposed and implemented to detect healthy, ALS, and myopathy statuses.

TL;DR: The results indicate that the network characteristics of structured keyword system are more suitable than unstructured keyword system to analyse research trends and bring forth the emerging areas and popular research methods.

TL;DR: A novel approach for the diagnosis of neuromuscular disorders using recurrence quantification analysis and support vector machines is introduced and it is shown that the proposed method classifies these signals with significantly better accuracy than what has been reported in the literature thus far.

TL;DR: This work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly, and compares the performance of phase synchronization based MST with cross correlation based M ST along selected network measures across temporal frame that includes economically good and crisis periods.