Evidence map›Paper›PMID 42022748›Full record

ArticleNature chemical engineering2025

Neural network-assisted personalized handwriting analysis for Parkinson's disease diagnostics.

Guorui Chen, Trinny Tat, Yihao Zhou, Zhaoqi Duan, Junkai Zhang, Kamryn Scott, Xun Zhao, Zeyang Liu, Wei Wang, Song Li and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature chemical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Artificial Intelligence-Driven Soft Bioelectronics for Self-Powered Respiration Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  10. Article
  11. Multitype hand writing as a digital marker for Parkinson's disease.Clinical parkinsonism & related disorders · 2026
    Article
  12. Article
  13. 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

12 authors.

Guorui ChenDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Trinny TatDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Yihao ZhouDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Zhaoqi DuanDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Junkai ZhangDepartment of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA.
Kamryn ScottDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Xun ZhaoDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.ORCID 0000-0001-5543-0081
Zeyang LiuDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Wei WangDepartment of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA.
Song LiDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-4760-8828
Katy A CrossDepartment of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
Jun ChenDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-3439-0495

Funding

Multimodal wireless electrical stimulation for tissue regenerationR01NS126918 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Song Li, John Rogers · 2022 to 2026
$2.4M
Caltech/UCLA Individualized Theranostic Engineering to Advance Metabolic System (iTEAM)T32EB027629 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Dino Di Carlo, Azita Emami · 2020 to 2026
$2.0M
Magnetoelastic Vascular GraftsR01HL175135 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Jun Chen · 2025 to 2026
$1.1M
A soft magnetoelastic microneedle patch for rapid skin cancer screeningR01CA287326 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Jun Chen · 2024 to 2026
$1.1M
American Heart Association-American Stroke Association 23IPA1054908American Heart Association-American Stroke Association 23SCEFIA1157587American Heart Association-American Stroke Association 23TPA1141360NCI NIH HHS R01 CA287326NHLBI NIH HHS R01 HL175135NIBIB NIH HHS T32 EB027629NINDS NIH HHS R01 NS126918
6 · The paper itself

Abstract

Diagnosing Parkinson's disease (PD) promptly, accessibly and effectively is crucial for improving patient outcomes, yet reaching this goal remains a challenge. Here we developed a diagnostic pen featuring a soft magnetoelastic tip and ferrofluid ink, capable of sensitively and quantitatively converting both on-surface and in-air writing motions into high-fidelity, analyzable signals for self-powered PD diagnostics. The diagnostic pen's working mechanism is based on the magnetoelastic effect in its magnetoelastic tip and the dynamic movement of the ferrofluid ink. To validate the clinical potential, a pilot human study was conducted, incorporating both patients with PD and healthy participants. The diagnostic pen accurately recorded handwriting signals, and a onedimensional convolutional neural network-assisted analysis successfully distinguished patients with PD with an average accuracy of 96.22%. Our development of the diagnostic pen represents a low-cost, widely disseminable and reliable technology with the potential to improve PD diagnostics across large populations and resource-limited areas.

Identifiers

PMID42022748
PMCPMC13098994

What OpenQuestion holds

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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.