A Versatile Computational Algorithm for Time-series Data Analysis and Machine-learning Models

Overview

Journal NPJ Parkinsons Dis

Date 2021 Nov 10

PMID 34753948

Citations 1

Authors

Taylor Chomiak

Neilen P Rasiah

Leonardo A Molina

Bin Hu

Jaideep S Bains

Tamas Fuzesi

Affiliations

Soon will be listed here.

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.

Citing Articles

Implementing Gait Kinematic Trajectory Forecasting Models on an Embedded System.

Shayne M, Molina L, Hu B, Chomiak T Sensors (Basel). 2024; 24(8).

PMID: 38676266 PMC: 11055148. DOI: 10.3390/s24082649.

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