Evidence map›Paper›PMID 42460004›Full record

Article... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks2024

HealthSense: Unobtrusive Continuous Stress Monitoring Using a Novel Dual ECG-PPG Patch.

Glenn Fernandes, Boyang Wei, Christopher Romano, Deniz Ulusel, Henry K Dambanemuya, Yang Gao, Roozbeh Ghaffari, John Rogers, Nabil Alshurafa

Abstract read
In one paragraph

Article in ... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Glenn FernandesDepartment of Computer Science, Northwestern University, Evanston, IL, USA.
Boyang WeiDepartment of Computer Science, Northwestern University, Evanston, IL, USA.
Christopher RomanoDepartment of Preventive Medicine, Northwestern University, Evanston, IL, USA.
Deniz UluselDepartment of Computer Science, Northwestern University, Evanston, IL, USA.
Henry K DambanemuyaDepartment of Computer Science, Northwestern University, Evanston, IL, USA.
Yang GaoDepartment of Preventive Medicine, Northwestern University, Evanston, IL, USA.
Roozbeh GhaffariDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
John RogersDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
Nabil AlshurafaDepartment of Computer Science, Northwestern University, Evanston, IL, USA.

Funding

EAT: A Reliable Eating Assessment Technology for Free-living Individuals.R01DK129843 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2021 to 2025
$3.3M
SenseWhy: Overeating in Obesity Through the Lens of Passive Sensing.K25DK113242 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2018 to 2022
$881k
BehaviorSight: Privacy enhancing wearable system to detect health risk behaviors in real-time.R21EB030305 · NIBIB · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2020 to 2020
$607k
WildCam: A Privacy Conscious Wearable Eating Detection Camera People will Actually Wear in the WildR03DK127128 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALSHURAFA, NABIL · 2021 to 2022
$234k
NIBIB NIH HHS R21 EB030305NIDDK NIH HHS K25 DK113242NIDDK NIH HHS R01 DK129843NIDDK NIH HHS R03 DK127128
6 · The paper itself

Abstract

Stress, a significant risk factor for chronic disease, manifests as changes in heart rate, respiration rate, and blood pressure. Non-invasive wearables like smartwatches can continuously track these physiological indicators to predict stress, enabling clinicians to develop and test interventions. However, most current devices are rigid and lack skin conformity, resulting in suboptimal signal quality and adherence during extended use. Furthermore, existing flexible sensors employ either electrocardiogram (ECG) or photoplethysmography (PPG), but not both, which is useful for calculating pulse arrival time (PAT) - known to correlate with stress. Addressing these challenges, we introduce HealthSense, a novel, flexible, and skin-conformable device that integrates ECG, PPG, and Inertial Measurement Unit (IMU) sensors into a single wearable. We assessed the comfort of wearing HealthSense and the feasibility of stress prediction by conducting a stress-induction study with 11 participants. Participants rated the comfort level of wearing the device on a Likert scale of 1-5, with 80% rating it as a 5 (most comfortable). Using statistical features, heart rate variability (HRV) related features, and PAT from our sensor data, we trained machine learning (ML) models to predict minute-level perceived and physiological stress with F1-scores of 85.5% and 87.7%, respectively. Additionally, using SHAP values, we identified PAT, systolic time, and pulse as the most significant contributors to the predictions. These findings enhance the understanding of physiological manifestations of stress and lays the groundwork for future stress-reduction interventions.

Identifiers

PMID42460004
PMCPMC13371000

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.