Estimating motor symptom presence and severity in Parkinson’s disease from wrist accelerometer time series using ROCKET and InceptionTime

Estimating motor symptom presence and severity in Parkinson’s disease from wrist accelerometer time series using ROCKET and InceptionTime

Abstract Parkinson’s disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques have demonstrated limited efficacy in mon...

Full description

Saved in:
Bibliographic Details
Main Authors: Cedric Donié, Neha Das, Satoshi Endo, Sandra Hirche
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Parkinson’s disease
InceptionTime
ROCKET
Time series classification
IMU
Accelerometer
Online Access:https://doi.org/10.1038/s41598-025-04263-2
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-04263-2

Similar Items