Evidence map›Paper›PMID 40690754›Full record

SynthesisJournal of medical Internet research2025

Evaluating the Utility of Wearable Sensors for the Early Diagnosis of Parkinson Disease: Systematic Review.

Hai Li, Massimiliano Zecca, Jiajun Huang

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
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

3 authors.

Hai LiCollege of Sport, Neijiang Normal University, Neijiang, China.ORCID https://orcid.org/0000-0002-1160-3777
Massimiliano ZeccaSchool of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, United Kingdom.ORCID https://orcid.org/0000-0003-4741-4334
Jiajun HuangDepartment of Neurology, The Second People's Hospital of Neijiang, Neijiang, China.ORCID https://orcid.org/0009-0004-0058-8550

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly diagnosis is crucial for ensuring that patients with Parkinson disease (PD) receive timely treatment, which can improve their quality of life and prolong lifespan. Wearable sensors have emerged as promising tools for early PD diagnosis, offering noninvasive, continuous symptom monitoring.

objectiveThis review aimed to evaluate how wearable sensors have been applied in early diagnosis of PD over the past decade, focusing on sensor types, methods, findings, and limitations.

methodsThe systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were sourced from PubMed, IEEE Xplore, Scopus, and Web of Science and screened based on predefined criteria. The inclusion criteria were as follows: (1) the study was observational or experimental, (2) wearable sensors were applied for the early diagnosis of PD, (3) participants were diagnosed with early-stage or prodromal PD, (4) the study included at least 10 participants with PD, and (5) the article was published between 2013 and 2023. Studies were excluded if they focused solely on treatment, rehabilitation, symptom monitoring, or nonwearable devices; lacked diagnostic clarity; were not published in English; or were not primary research articles. All the selected studies were assessed for quality using the Quality Assessment of Diagnostic Accuracy Studies-2, the quality assessment tool recommended by the Cochrane Collaboration.

resultsOverall, 1888 records were retrieved from the selected databases, with 1044 records remaining after duplicate removal. Following the screening of titles and abstracts, 949 ineligible records were excluded, leaving 95 articles for eligibility. Eventually, of the 1044 studies, 12 (1.12%) met the inclusion criteria, validating the feasibility of wearable sensors in the early diagnosis of PD. Most (10/12, 83%) were cross-sectional studies, with 1 longitudinal and 1 mixed-design study. Of the 12 studies, 4 (33%) focused on identification diagnosis, 2 (17%) addressed the staged diagnosis of PD, and 1 (8%) focused on the identification of specific symptoms. Of the 12 studies, 5 (42%) assessed the overall feasibility and performance of wearable sensors in early PD detection without targeting specific classification purposes. The main wearable sensors used were inertial measurement units (8/12, 67%) and accelerometers (4/12, 33%), which primarily captured motion-related data. While initial findings suggest that wearable sensors are feasible for early PD diagnosis, the evidence is still limited by small sample sizes and short study durations.

conclusionsWearable sensors show promise in supporting the early diagnosis of PD, particularly for motor symptoms monitoring. However, several limitations remain in validating and applying wearable sensors in clinical contexts, including cross-sectional designs and limited diagnostic standardization. More diverse studies are needed to further validate these findings and address existing shortcomings to better advance the use of wearable sensors in the early diagnosis of PD.

trial registrationPROSPERO CRD42024544198; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024544198.

Indexed as

Parkinson DiseaseWearable Electronic DevicesEarly DiagnosisHumansdigital biomarkersearly diagnosismotor symptomsParkinson diseasewearable sensor

Identifiers

PMID40690754
PMCPMC12322615

What OpenQuestion holds

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LicenceCC BY
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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.