Evidence map›Paper›PMID 33556807›Full record

ReviewBiosensors & bioelectronics2021

Wireless and battery-free platforms for collection of biosignals.

Tucker Stuart, Le Cai, Alex Burton, Philipp Gutruf

Abstract readReview
In one paragraph

Review in Biosensors & bioelectronics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Enzyme-containing-hydrogel/TiOScientific reports · 2025
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Biosymbiotic platform for chronic long-range monitoring of biosignals in limited resource settings.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Measuring Biosignals with Single Circuit Boards.Bioengineering (Basel, Switzerland) · 2022
    Review
  18. Review
  19. What can AI-TENG do for Low Abundance Biosensing?Frontiers in bioengineering and biotechnology · 2022
    Review
  20. 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

4 authors.

Tucker StuartDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.
Le CaiDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.
Alex BurtonDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.
Philipp GutrufDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA; Department of Electrical Engineering, University of Arizona, Tucson, AZ, 85721, USA; Bio5 Institute, University of Arizona, Tucson, AZ, 85721, USA; Neuroscience GIDP, University of Arizona, Tucson, AZ, 85721, USA. Electronic address: pgutruf@email.arizona.edu.

Funding

Optimizing the restoration and rehabilitation of function using cortically-controlled FES following SCIR01NS112535 · NINDS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI TRESCH, MATTHEW · 2019 to 2023
$2.6M
NINDS NIH HHS R01 NS112535
6 · The paper itself

Abstract

Recent progress in biosensors have quantitively expanded current capabilities in exploratory research tools, diagnostics and therapeutics. This rapid pace in sensor development has been accentuated by vast improvements in data analysis methods in the form of machine learning and artificial intelligence that, together, promise fantastic opportunities in chronic sensing of biosignals to enable preventative screening, automated diagnosis, and tools for personalized treatment strategies. At the same time, the importance of widely accessible personal monitoring has become evident by recent events such as the COVID-19 pandemic. Progress in fully integrated and chronic sensing solutions is therefore increasingly important. Chronic operation, however, is not truly possible with tethered approaches or bulky, battery-powered systems that require frequent user interaction. A solution for this integration challenge is offered by wireless and battery-free platforms that enable continuous collection of biosignals. This review summarizes current approaches to realize such device architectures and discusses their building blocks. Specifically, power supplies, wireless communication methods and compatible sensing modalities in the context of most prevalent implementations in target organ systems. Additionally, we highlight examples of current embodiments that quantitively expand sensing capabilities because of their use of wireless and battery-free architectures.

Indexed as

Artificial IntelligenceBioelectric Energy SourcesBiosensing TechniquesCOVID-19Electric Power SuppliesElectrophysiological PhenomenaEquipment DesignHumansPandemicsRemote Sensing TechnologySARS-CoV-2TelemetryWearable Electronic DevicesWireless TechnologyBattery-freeBiosignalsDiagnosticsSensorsTherapeuticsWireless

Identifiers

PMID33556807
PMCPMC8112193

What Socratic 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 Socratic graph.