Wearable sensor-based gait analysis to discriminate early Parkinson's disease from essential tremor.

ABSTRACT:

Background

Differentiating early-stage Parkinson's disease (PD) from essential tremor (ET) is challenging since they have some overlapping clinical features. Since early-stage PD may present with slight gait impairment and ET generally does not, gait analysis could be used to differentiate PD from ET using machine learning.

Objective

To differentiate early-stage PD from ET via machine learning using gait and postural transition parameters calculated using the raw kinematic signal captured from inertial measurement unit (IMU) sensors.

Methods

Gait and postural transition parameters were collected from 84 early-stage PD and 80 ET subjects during the Time Up and Go (TUG) test. We randomly split our data into training and test data. Within the training data, we separated

SUBMITTER: Lin S 

PROVIDER: S-EPMC10025195 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature