Evidence map›Paper›PMID 41820562›Full record

ArticleScientific reports2026

Wearable sensors for monitoring drug pharmacokinetics in patients with Parkinson's disease.

Yi-Jen Guo, Chia-Chen Li, Jin-An Huang, Kanishk Singh, Henny Mellini, Yu-Hsuan Lin, Cheng-Che Yu, Ting-Chun Fang, Ching-Chia Pi, Pin-Ching Chen and 6 more

Abstract read
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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Yi-Jen Guo *Centre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Chia-Chen Li *Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Jin-An Huang *Centre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Kanishk Singh *Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Henny MelliniDepartment of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Yu-Hsuan LinCentre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Cheng-Che YuInstitute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Ting-Chun FangCentre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Ching-Chia PiInstitute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Pin-Ching ChenCentre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Ching-Yi LiCentre for Parkinson and Movement Disorders, Neurological Institute, Taichung Veterans General Hospital, Taichung City, Taiwan.
Sue-Yuan FanInstitute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Wei-Chen HuangDepartment of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Tsung-Heng TsaiDepartment of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Yu-Te LiaoDepartment of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan.
Li-Chia TaiInstitute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan. j.tai@nycu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable sweat sensors have attracted significant attention in recent years due to their potential for noninvasive health monitoring and point-of-care treatment. In this study, we developed and clinically evaluated wearable electrochemical sweat sensors in 32 patients with Parkinson’s disease (PD) at Taichung Veterans General Hospital, Taiwan. PD patients were treated with standard oral L-DOPA formulations, in terms of Madopar or Sinemet. PD symptoms were assessed using standard MDS-UPDRS scores, 10 clinical movement metrics, wearable inertial measurement units (IMUs) data, and sweat L-DOPA concentration profiles. Using these multimodal measurements, we found that 79% of PD patients with sufficient sweating showed a moderate to strong negative Spearman correlation (– 1.0 < ρ < – 0.4) between their sweat L-DOPA profiles and hand tremor intensity. These results highlight the potential of wearable sweat sensors for noninvasive monitoring of L-DOPA pharmacokinetics and enabling personalized dosage optimization in PD patients.

Indexed as

Antiparkinson AgentsDrug MonitoringLevodopaParkinson DiseaseSweatWearable Electronic DevicesAgedBenserazideFemaleHumansMaleMiddle AgedAntiparkinson AgentsBenserazideLevodopa

Identifiers

PMID41820562
PMCPMC13106675

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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.