Evidence map›Paper›PMID 36014257›Full record

ReviewMicromachines2022

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview.

Roberto De Fazio, Veronica Mattei, Bassam Al-Naami, Massimo De Vittorio, Paolo Visconti

Open access · goldAbstract readReview
In one paragraph

Review in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
5.3field-weighted citation impact, top 3% of its field
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

14 citing papers in PubMed, 46 citations in OpenAlex.

  1. Trial
  2. Review
  3. Research on Flexible Sensors for Wearable Devices: A Review.Nanomaterials (Basel, Switzerland) · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. A Review on Automated Sleep Study.Annals of biomedical engineering · 2024
    Review
  9. Review
  10. Article
  11. Digital health in chronic obstructive pulmonary disease.Chronic diseases and translational medicine · 2023
    Review
  12. Review
  13. Review
  14. 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

5 authors at 2 institutions in 2 countries.

Roberto De FazioDepartment of Innovation Engineering, University of Salento, 73100 Lecce, Italy.ORCID 0000-0003-0893-138X
Veronica MatteiDepartment of Innovation Engineering, University of Salento, 73100 Lecce, Italy.ORCID 0000-0003-1799-0453
Bassam Al-NaamiDepartment of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan.ORCID 0000-0002-1249-009X
Massimo De VittorioDepartment of Innovation Engineering, University of Salento, 73100 Lecce, Italy.
Paolo ViscontiDepartment of Innovation Engineering, University of Salento, 73100 Lecce, Italy.ORCID 0000-0002-4058-4042
University of Salento · ITHashemite University · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep's functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG-electroencephalography, ECG-electrocardiography, EMG-electromyography, EOG-electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems.

Indexed as

ECGEEGEOGpolysomnographysensorssleep dysfunctionsleep stagingwearable devices

Identifiers

PMID36014257
PMCPMC9412310
OpenAlexW4292254517

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.