Evidence map›Paper›PMID 38181071›Full record

ArticleScience advances2024

Ambient health sensing on passive surfaces using metamaterials.

Dat T Nguyen, Qihang Zeng, Xi Tian, Patrick Chia, Changsheng Wu, Yuxin Liu, John S Ho

Abstract read
In one paragraph

Article in Science advances, 2024. 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
  2. Article
  3. Review
  4. Article
  5. Photonic Nanomaterials for Wearable Health Solutions.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  6. Review
  7. Review
  8. 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

7 authors.

Dat T NguyenIntegrative Sciences and Engineering Program, National University of Singapore, Singapore 119077, Singapore.ORCID 0000-0003-2750-3145
Qihang ZengDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.ORCID 0000-0002-3904-8015
Xi TianDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.ORCID 0000-0003-1633-1210
Patrick ChiaSIA-NUS Digital Aviation Corporate Laboratory, National University of Singapore, Singapore 117602, Singapore.ORCID 0009-0002-6195-189X
Changsheng WuInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0002-0921-6356
Yuxin LiuInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0003-0623-9402
John S HoIntegrative Sciences and Engineering Program, National University of Singapore, Singapore 119077, Singapore.ORCID 0000-0002-9458-9033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambient sensors can continuously and unobtrusively monitor a person's health and well-being in everyday settings. Among various sensing modalities, wireless radio-frequency sensors offer exceptional sensitivity, immunity to lighting conditions, and privacy advantages. However, existing wireless sensors are susceptible to environmental interference and unable to capture detailed information from multiple body sites. Here, we present a technique to transform passive surfaces in the environment into highly sensitive and localized health sensors using metamaterials. Leveraging textiles' ubiquity, we engineer metamaterial textiles that mediate near-field interactions between wireless signals and the body for contactless and interference-free sensing. We demonstrate that passive surfaces functionalized by these metamaterials can provide hours-long cardiopulmonary monitoring with accuracy comparable to gold standards. We also show the potential of distributed sensors and machine learning for continuous blood pressure monitoring. Our approach enables passive environmental surfaces to be harnessed for ambient sensing and digital health applications.

Indexed as

Digital HealthEngineeringHumansLightingMachine LearningPrivacy

Identifiers

PMID38181071
PMCPMC10776016

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.