Evidence map›Paper›PMID 38433871›Full record

ArticleNature electronics2024

A physicochemical-sensing electronic skin for stress response monitoring.

Changhao Xu, Yu Song, Juliane R Sempionatto, Samuel A Solomon, You Yu, Hnin Y Y Nyein, Roland Yingjie Tay, Jiahong Li, Wenzheng Heng, Jihong Min and 4 more

Open access · greenAbstract read
In one paragraph

Article in Nature electronics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
111citing papers in PubMed, 1 pooled it
59.0field-weighted citation impact, top 1% of its field
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

111 citing papers in PubMed, 1 synthesis or guideline pooled it, 320 citations in OpenAlex.

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51 more citing papers are in PubMed but not listed here.

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

14 authors at 3 institutions in 2 countries.

Changhao XuAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Yu SongAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Juliane R SempionattoAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Samuel A SolomonAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
You YuAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Hnin Y Y NyeinDepartment of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Hong Kong, China.
Roland Yingjie TayAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Jiahong LiAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Wenzheng HengAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Jihong MinAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Alison LaoAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
Tzung K HsiaiDivision of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Jennifer A SumnerDepartment of Psychology, University of California, Los Angeles, CA, USA.
Wei GaoAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
California Institute of Technology · USUniversity of California, Los Angeles · USHong Kong University of Science and Technology · HK

Funding

Intravascular Deployment of a Wirelessly Powered Micro-PacerR01HL149808 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Tzung K Hsiai · 2020 to 2026
$2.8M
Laser-Engraved Wearable Sweat Sensors to Detect and Monitor Cardiometabolic DiseaseR01HL155815 · NHLBI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI GAO, WEI · 2021 to 2025
$2.0M
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
UCLA and Caltech integrated Cardiovascular Medicine for Bioengineers (iCMB)T32HL144449 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HSIAI, TZUNG K, PAJUKANTA, PAIVI · 2020 to 2024
$1.2M
Cutaneous uric acid and metabolite monitoring to improve individual response to pharmaceutical and dietary treatment in patients with goutR21DK132666 · NIDDK · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI FITZGERALD, JOHN D, GAO, WEI · 2022 to 2023
$461k
NHLBI NIH HHS R01 HL149808NHLBI NIH HHS R01 HL155815NHLBI NIH HHS T32 HL144449NIBIB NIH HHS T32 EB027629NIDDK NIH HHS R21 DK132666
6 · The paper itself

Abstract

Approaches to quantify stress responses typically rely on subjective surveys and questionnaires. Wearable sensors can potentially be used to continuously monitor stress-relevant biomarkers. However, the biological stress response is spread across the nervous, endocrine, and immune systems, and the capabilities of current sensors are not sufficient for condition-specific stress response evaluation. Here we report an electronic skin for stress response assessment that non-invasively monitors three vital signs (pulse waveform, galvanic skin response and skin temperature) and six molecular biomarkers in human sweat (glucose, lactate, uric acid, sodium ions, potassium ions and ammonium). We develop a general approach to prepare electrochemical sensors that relies on analogous composite materials for stabilizing and conserving sensor interfaces. The resulting sensors offer long-term sweat biomarker analysis of over 100 hours with high stability. We show that the electronic skin can provide continuous multimodal physicochemical monitoring over a 24-hour period and during different daily activities. With the help of a machine learning pipeline, we also show that the platform can differentiate three stressors with an accuracy of 98.0%, and quantify psychological stress responses with a confidence level of 98.7%.

Identifiers

PMID38433871
PMCPMC10906959
OpenAlexW4391027752

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.