Evidence map›Paper›PMID 33287011›Full record

ArticleEntropy (Basel, Switzerland)2020

Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study.

David Cuesta-Frau, Jakub Schneider, Eduard Bakštein, Pavel Vostatek, Filip Spaniel, Daniel Novák

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Slope Entropy Characterisation: The Role of theEntropy (Basel, Switzerland) · 2022
    Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

6 authors.

David Cuesta-FrauTechnological Institute of Informatics, Alcoi Campus, Universitat Politècnica de València, 46022 Valencia, Spain.ORCID 0000-0002-0076-0515
Jakub SchneiderDepartment of Cybernetics, Czech Technical University in Prague, 166 36 Prague, Czech Republic.
Eduard BakšteinDepartment of Cybernetics, Czech Technical University in Prague, 166 36 Prague, Czech Republic.ORCID 0000-0002-4672-4923
Pavel VostatekMINDPAX, Vinohrady, 128 00 Prague, Czech Republic.
Filip SpanielNational Institute of Mental Health, 250 67 Klecany, Czech Republic.
Daniel NovákDepartment of Cybernetics, Czech Technical University in Prague, 166 36 Prague, Czech Republic.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bipolar Disorder (BD) is an illness with high prevalence and a huge social and economic impact. It is recurrent, with a long-term evolution in most cases. Early treatment and continuous monitoring have proven to be very effective in mitigating the causes and consequences of BD. However, no tools are currently available for a massive and semi-automatic BD patient monitoring and control. Taking advantage of recent technological developments in the field of wearables, this paper studies the feasibility of a BD episodes classification analysis while using entropy measures, an approach successfully applied in a myriad of other physiological frameworks. This is a very difficult task, since actigraphy records are highly non-stationary and corrupted with artifacts (no activity). The method devised uses a preprocessing stage to extract epochs of activity, and then applies a quantification measure, Slope Entropy, recently proposed, which outperforms the most common entropy measures used in biomedical time series. The results confirm the feasibility of the approach proposed, since the three states that are involved in BD, depression, mania, and remission, can be significantly distinguished.

Indexed as

actigraphybipolar disorderpermutation entropysample entropyslope entropytime series classification

Identifiers

PMID33287011
PMCPMC7711446

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.