ArticleNPJ Parkinson's disease2024
The digital signature of emergent tremor in Parkinson's disease.
Article in NPJ Parkinson's disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Cell-based regenerative interventions in Parkinson's disease: Overcoming pharmacological limitations.Acta pharmaceutica Sinica. B · 2026Review
- Remote real time digital monitoring fills a critical gap in the management of Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Closing the loop in DBS: A data-driven approach.Parkinsonism & related disorders · 2025Review
- Development of a Tremor Detection Algorithm for Use in an Academic Movement Disorders Center.Sensors (Basel, Switzerland) · 2024Article
- Comprehensive real time remote monitoring for Parkinson's disease using Quantitative DigitoGraphy.NPJ Parkinson's disease · 2024Article
- Quantitative DigitoGraphy: a Comprehensive Real-Time Remote Monitoring System for Parkinson's Disease.Research square · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Emergent tremor in Parkinson's disease (PD) can occur during sustained postures or movements that are different from action tremor. Tremor can contaminate the clinical rating of bradykinesia during finger tapping. Currently, there is no reliable way of isolating emergent tremor and measuring the cardinal motor symptoms based on voluntary movements only. In this study, we investigated whether emergent tremor during repetitive alternating finger tapping (RAFT) on a quantitative digitography (QDG) device could be reliably identified and distinguished from voluntary tapping. Ninety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and the Movement Disorders Society - Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III). Visual identification of tremor during QDG-RAFT was labeled by an experienced movement disorders specialist. Two methods of identifying tremor were investigated: 1) physiologically informed temporal thresholds 2) XGBoost model using temporal and amplitude features of tapping. The XGBoost model showed high accuracy for identifying tremor (area under the precision-recall curve of 0.981) and outperformed temporal-based thresholds. Percent time duration of classifier-identified tremor showed significant correlations with MDS-UPDRS III tremor subscores (r = 0.50, p < 0.0001). There was a significant change in QDG metrics for bradykinesia, rigidity, and arrhythmicity after tremor strikes were excluded (p < 0.01). The results demonstrate that emergent tremor during QDG-RAFT has a unique digital signature and the duration of tremor correlated with the MDS-UPDRS III tremor items. When involuntary tremor strikes were excluded, the QDG metrics of bradykinesia and rigidity were significantly worse, demonstrating the importance of distinguishing tremor from voluntary movement when rating bradykinesia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.