Dataset Information

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

ABSTRACT: Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively evaluated every minute. We acquired a dataset of 8,661?minutes of IMU data from 30 patients, with annotations about the motor state (OFF,ON, DYSKINETIC) based on MDS-UPDRS global bradykinesia item and the AIMS upper limb dyskinesia item. Using a 1-minute window size as an input for a convolutional neural network trained on data from a subset of patients, we achieved a three-class balanced accuracy of 0.654 on data from previously unseen subjects. This corresponds to detecting the OFF, ON, or DYSKINETIC motor state at a sensitivity/specificity of 0.64/0.89, 0.67/0.67 and 0.64/0.89, respectively. On average, the model outputs were highly correlated with the annotation on a per subject scale (r?=?0.83/0.84; p?

SUBMITTER: Pfister FMJ

PROVIDER: S-EPMC7125162 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

Pfister Franz M J FMJ Um Terry Taewoong TT Pichler Daniel C DC Goschenhofer Jann J Abedinpour Kian K Lang Muriel M Endo Satoshi S Ceballos-Baumann Andres O AO Hirche Sandra S Bischl Bernd B Kulić Dana D Fietzek Urban M UM

Scientific reports 20200403 1

Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively evaluated every minute. We acquired a dataset of 8,661 minutes of IMU data from 30 patients, with ann ...[more]

PMID: 32246097

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Dataset Information

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

Publications

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

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