Evidence map›Paper›PMID 40176780›Full record

ArticleJournal of sensor and actuator networks2025

Optimizing Sensor Locations for Electrodermal Activity Monitoring Using a Wearable Belt System.

Riley Q McNaboe, Youngsun Kong, Wendy A Henderson, Xiaomei Cong, Aolan Li, Min-Hee Seo, Ming-Hui Chen, Bin Feng, Hugo F Posada-Quintero

Abstract read
In one paragraph

Article in Journal of sensor and actuator networks, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

9 authors.

Riley Q McNaboeDepartment of Biomedical Engineering, College of Engineering, University of Connecticut, Storrs, CT 06269, USA.ORCID 0000-0002-2211-7475
Youngsun KongDepartment of Biomedical Engineering, College of Engineering, University of Connecticut, Storrs, CT 06269, USA.ORCID 0000-0001-5409-3888
Wendy A HendersonDepartment of Biobehavioral Health Sciences, School of Nursing, University of Pennsylvania, Philadelphia, PA 19104, USA.ORCID 0000-0003-3924-7118
Xiaomei CongSchool of Nursing, Yale University, Orange, CT 06477, USA.ORCID 0000-0002-4992-199X
Aolan LiDepartment of Statistics, College of Liberal Arts and Sciences, University of Connecticut, Storrs, CT 06269, USA.ORCID 0009-0009-3525-395X
Min-Hee SeoDepartment of Statistics, College of Liberal Arts and Sciences, University of Connecticut, Storrs, CT 06269, USA.
Ming-Hui ChenDepartment of Statistics, College of Liberal Arts and Sciences, University of Connecticut, Storrs, CT 06269, USA.
Bin FengDepartment of Biomedical Engineering, College of Engineering, University of Connecticut, Storrs, CT 06269, USA.ORCID 0000-0001-9277-211X
Hugo F Posada-QuinteroDepartment of Biomedical Engineering, College of Engineering, University of Connecticut, Storrs, CT 06269, USA.ORCID 0000-0003-4514-4772

Funding

Objective Integrated Multimodal Electrophysiological Index for the Quantification of Visceral PainR01DK138248 · NIDDK · UNIVERSITY OF CONNECTICUT STORRS · PI Hugo Fernando Posada-Quintero · 2024 to 2026
$1.9M
NIDDK NIH HHS R01 DK138248
6 · The paper itself

Abstract

Wearable devices for continuous health monitoring in humans are constantly evolving, yet the signal quality may be improved by optimizing electrode placement. While the commonly used locations to measure electrodermal activity (EDA) are at the fingers or the wrist, alternative locations, such as the torso, need to be considered when applying an integrated multimodal approach of concurrently recording multiple bio-signals, such as the monitoring of visceral pain symptoms like those related to irritable bowel syndrome (IBS). This study aims to quantitatively determine the EDA signal quality at four torso locations (mid-chest, upper abdomen, lower back, and mid-back) in comparison to EDA signals recorded from the fingers. Concurrent EDA signals from five body locations were collected from twenty healthy participants as they completed a Stroop Task and a Cold Pressor task that elicited salient autonomic responses. Mean skin conductance (meanSCL), non-specific skin conductance responses (NS.SCRs), and sympathetic response (TVSymp) were derived from the torso EDA signals and compared with signals from the fingers. Notably, TVSymp recorded from the mid-chest location showed significant changes between baseline and Stroop phase, consistent with the TVSymp recorded from the fingers. A high correlation (0.77-0.83) was also identified between TVSymp recorded from the fingers and three torso locations: mid-chest, upper abdomen, and lower back locations. While the fingertips remain the optimal site for EDA measurement, the mid-chest exhibited the strongest potential as an alternative recording site, with the upper abdomen and lower back also demonstrating promising results. These findings suggest that torso-based EDA measurements have the potential to provide reliable measurement of sympathetic neural activities and may be incorporated into a wearable belt system for multimodal monitoring.

Indexed as

electrodermal activityoptimal locationtorsowearable sensor

Identifiers

PMID40176780
PMCPMC11963145

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.