Evidence map›Paper›PMID 39578241›Full record

ArticleAdvanced healthcare materials2025

Kirigami-Inspired Stretchable Piezoelectret Sensor for Analysis and Assessment of Parkinson's Tremor.

Qisen Xie, Liuyang Han, Jie Liu, Wenjie Zhang, Liuyan Zhao, Yuhan Liu, Yanru Chen, Yuzhen Li, Qian Zhou, Ying Dong and 1 more

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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  7. FromMaterials today. Bio · 2025
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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

11 authors.

Qisen XieTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Liuyang HanTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Jie LiuTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Wenjie ZhangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Liuyan ZhaoTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Yuhan LiuTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Yanru ChenTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Yuzhen LiTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Qian ZhouTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
Ying DongTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.ORCID 0000-0002-6413-8653
Xiaohao WangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.

Funding

National Natural Science Foundation of China 61971262Shenzhen Science and Technology Innovation Program JCYJ20220818101005011
6 · The paper itself

Abstract

Human muscle activity contains rich information that can reflect human movement patterns and conditions of diseases or physical abnormalities. Flexible pressure sensors enable the assessment of muscle tremors in Parkinson's disease (PD) through Force Myography (FMG). Here, an easily fabricated, ultra-sensitive, and stretchable piezoelectret pressure sensor is presented. Utilizing an effective integration of Kirigami structure and piezoelectret air gap, the sensor achieved a dynamic sensitivity of ≈725 pC/N (@5 Hz), measurement repeatability of <2.5%, measurement hysteresis of <1%, a pressure detection limit of <15 Pa, a response time of ≈2.5 ms, stable output within ±3% over 40 000 cycles, and output decay of <2.5% after 1000 cycles of complex deformation, meeting non-distorted measurement conditions up to 20 Hz. Successful monitoring and assessment of hand muscle tremors are demonstrated. Furthermore, using a 1×3 sensor array enabled tremor localization, achieving a high accuracy rate of 99.5% with machine learning algorithms. Additionally, the sensor facilitated the experimental quantification and assisted scoring of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), with an accuracy of ≈85%. The sensor demonstrates potential for assisting in the diagnosis and rehabilitation monitoring of Parkinson's disease.

Indexed as

Parkinson DiseaseTremorHumansMaleMyographyPressureWearable Electronic Devicesforce myographykirigami structuremuscle tremorParkinson disease, piezoelectret sensor

Identifiers

PMID39578241
PMCPMC11694081

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.