Evidence map›Paper›PMID 40212111›Full record

ArticleSmall science2024

Wearable Sensors for Physiological Condition and Activity Monitoring.

Pillalamarri Srikrishnarka, Joonas Haapasalo, Juan P Hinestroza, Zhipei Sun, Nonappa

Abstract read
In one paragraph

Article in Small science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. 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

5 authors.

Pillalamarri SrikrishnarkaFaculty of Engineering and Natural Sciences Korkeakoulunkatu 6 FI-33720 Tampere Finland.ORCID https://orcid.org/0000-0001-5187-6879
Joonas HaapasaloDepartment of Neurosurgery Tampere University Hospital and Tampere University Kuntokatu 2 33520 Tampere Finland.ORCID https://orcid.org/0000-0002-6468-4937
Juan P HinestrozaDepartment of Fiber Science and Apparel Design Cornell University Ithaca NY 14853 USA.ORCID https://orcid.org/0000-0002-8534-1407
Zhipei SunDepartment of Electronics and Nanoengineering Aalto University P.O. Box 13500 FI-00076 Aalto Finland.ORCID https://orcid.org/0000-0002-9771-5293
NonappaFaculty of Engineering and Natural Sciences Korkeakoulunkatu 6 FI-33720 Tampere Finland.ORCID https://orcid.org/0000-0002-6804-4128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid technological advancements have transformed the healthcare sector from traditional diagnosis and treatment to personalized health management. Biofluids such as teardrops, sweat, interstitial fluids, and exhaled breath condensate offer a rich source of metabolites that can be linked to the physiological status of an individual. More importantly, these biofluids contain biomarkers similar to those in the blood. Therefore, developing sensors for the noninvasive determination of biofluid-based metabolites can overcome traditionally invasive and laborious blood-test-based diagnostics. In this context, wearable devices offer real-time and continuous physiological conditions and activity monitoring. The first-generation wearables included wristwatches capable of tracking heart rate variations, breathing rate, body temperature, stress responses, and sleeping patterns. However, wearable sensors that can accurately measure the metabolites are needed to achieve real-time analysis of biomarkers. In this review, recent progresses in wearable sensors utilized to monitor metabolites in teardrops, breath condensate, sweat, and interstitial fluids are thoroughly analyzed. More importantly, how metabolites can be selectively detected, quantified, and monitored in real-time is discussed. Furthermore, the review includes a discussion on the utility of, multifunctional sensors that combine metabolite sensing, human activity monitoring, and on-demand drug delivery system for theranostic applications.

Indexed as

biomarkerscondition monitoringsmetaboliteswearable sensors

Identifiers

PMID40212111
PMCPMC11935081

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.