A versatile computational algorithm for time-series data analysis and machine-learning models.

ABSTRACT: Here we introduce Local Topological Recurrence Analysis (LoTRA), a simple computational approach for analyzing time-series data. Its versatility is elucidated using simulated data, Parkinsonian gait, and in vivo brain dynamics. We also show that this algorithm can be used to build a remarkably simple machine-learning model capable of outperforming deep-learning models in detecting Parkinson's disease from a single digital handwriting test.

SUBMITTER: Chomiak T 

PROVIDER: S-EPMC8578326 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature