Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.

ABSTRACT:

Background

The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa response (LR). Assessment of Movement Disorder Society's Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) is a key step in ALCT, which is some extent subjective and inconvenience.

Methods

This study developed a machine learning method based on instrumented Timed Up and Go (iTUG) test to evaluate the patients' response to levodopa and compared it with classic ALCT. Forty-two patients with parkinsonism were recruited and administered with levodopa. MDS-UPDRS III and the iTUG were conducted in both OFF-and ON-medication state. Kinematic parameters, signal time and frequency domain features were extracted from sensor data. Two XGBoost models, levodopa response regre

SUBMITTER: He J 

PROVIDER: S-EPMC11409684 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature