Evidence map›Paper›PMID 39860736›Full record

ArticleSensors (Basel, Switzerland)2025

Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach.

Luc J W Evers, Yordan P Raykov, Tom M Heskes, Jesse H Krijthe, Bastiaan R Bloem, Max A Little

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Luc J W EversCenter of Expertise for Parkinson and Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands.ORCID 0000-0002-8241-5087
Yordan P RaykovSchool of Mathematical Sciences, University of Nottingham, Nottingham NG9 2SE, UK.ORCID 0000-0003-0753-717X
Tom M HeskesInstitute for Computing and Information Sciences, Radboud University, 6525 EC Nijmegen, The Netherlands.ORCID 0000-0002-3398-5235
Jesse H KrijthePattern Recognition & Bioinformatics Group, Delft University of Technology, 2628 XE Delft, The Netherlands.ORCID 0000-0003-3435-6358
Bastiaan R BloemCenter of Expertise for Parkinson and Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands.
Max A LittleSchool of Computer Science, University of Birmingham, Birmingham B15 2TT, UK.

Funding

Dutch Ministry of Economic Affairs (Topconsortium voor Kennis en Innovatie, Life Sciences & Health) LSHM20090Dutch Research Council ASDI.2020.060Engineering and Physical Sciences Research Council EP/T022493/1 and EP/M02315X/1Michael J. Fox Foundation 17369 and 020425NIHR BRC Imaging Center at University of Nottingham
6 · The paper itself

Abstract

Objective and continuous monitoring of Parkinson's disease (PD) tremor in free-living conditions could benefit both individual patient care and clinical trials, by overcoming the snapshot nature of clinical assessments. To enable robust detection of tremor in the context of limited amounts of labeled training data, we propose to use prototypical networks, which can embed domain expertise about the heterogeneous tremor and non-tremor sub-classes. We evaluated our approach using data from the Parkinson@Home Validation study, including 8 PD patients with tremor, 16 PD patients without tremor, and 24 age-matched controls. We used wrist accelerometer data and synchronous expert video annotations for the presence of tremor, captured during unscripted daily life activities in and around the participants' own homes. Based on leave-one-subject-out cross-validation, we demonstrate the ability of prototypical networks to capture free-living tremor episodes. Specifically, we demonstrate that prototypical networks can be used to enforce robust performance across domain-informed sub-classes, including different tremor phenotypes and daily life activities.

Indexed as

Parkinson DiseaseTremorAccelerometryActivities of Daily LivingAgedFemaleHumansMaleMiddle AgedMonitoring, PhysiologicParkinson’s diseasepassive monitoringprototype networkstremor detectiontremor modelingwearable sensors

Identifiers

PMID39860736
PMCPMC11768787

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Registered trials

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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.