Evidence map›Paper›PMID 35052335›Full record

ReviewHealthcare (Basel, Switzerland)2022

Pathway of Trends and Technologies in Fall Detection: A Systematic Review.

Rohit Tanwar, Neha Nandal, Mazdak Zamani, Azizah Abdul Manaf

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Falls in older adults: a practical approach.Arquivos de neuro-psiquiatria · 2022
    Pooled it
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Radar-Based Fall Detection: A Survey.IEEE robotics & automation magazine · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Deep Learning Multi-Class Approach for Human Fall Detection Based on Doppler Signatures.International journal of environmental research and public health · 2023
    Article
  15. A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence.International journal of environmental research and public health · 2022
    Review
  16. 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.

Rohit TanwarSchool of Computer Science, University of Petroleum & Energy Studies, Dehradun 248007, India.ORCID 0000-0002-9087-6019
Neha NandalDepartment of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad 500090, India.
Mazdak ZamaniDepartment of Computer Science, New York University, New York, NY 10012, USA.ORCID 0000-0002-6421-0053
Azizah Abdul ManafIndependent Researcher, Kuala Lumpur 54100, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a fall is predicted or detected accurately on time and prevented by providing timely help. Various methods have been proposed to prevent or predict falls in elderly people. This paper systematically reviews all the publications, projects, and patents around the world in the field of fall prediction, fall detection, and fall prevention. The related works are categorized based on the methodology which they used, their types, and their achievements.

Indexed as

fall detectionfall predictionfall preventionfall risk factorsgait assessment

Identifiers

PMID35052335
PMCPMC8776012

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.