Evidence map›Paper›PMID 39926788›Full record

ReviewJournal of pharmacy & bioallied sciences2024

Exploring the Impact of Brain-Computer Interfaces on Health Care: Innovations, Challenges, and Future Prospects: A Review Article.

Soni K Sah, Vaishali Taksande, Deepali Jadhav, Archana T Maurya

Abstract readReview
In one paragraph

Review in Journal of pharmacy & bioallied sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Soni K SahUG Nursing Student, Smt Radhikabai Meghe Memorial College of Nursing Sawangi (M) Wardha, Maharashtra, India.
Vaishali TaksandeDepartment of Obstetrics and Gynaecological Nursing Smt Radhikabai Meghe Memorial College of Nursing Sawangi (M) Wardha, Maharashtra, India.
Deepali JadhavDepartment of Physiology, Jawaharlal Nehru Medical College Sawangi Meghe Wardha, Maharashtra, India.
Archana T MauryaDepartment of Child Health Nursing Smt Radhikabai Meghe Memorial College of Nursing Sawangi (M) Wardha, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain-Computer Interfaces (BCIs) are an innovative technology that methods with a great possibility to revolutionize the sphere of medicine with the help of integration of human brain and external devices. In this article, we discuss how BCIs can be incorporated into hospitals and civil rehabilitation centers, possibly for rehabilitation, communication, and cognitive treatments. This review aims to discuss the advancement, usefulness, difficulties, and potential in regards to the use of BCIs in healthcare. We describe trends in the development of BCIs from simple experimental paradigms to multimedia advanced devices and their usage in clinical practice: assistive technology in patients with motor disorders, neurorehabilitation of post-stroke patients, and cognitive prosthesis for humans with neurodegenerative diseases. The article also emphasizes on present-day issues including signal quality, comfort level of the users, and the ethical parameter of the technique along with the research going on and future work streams. Thus, by evaluating the modern developments in the field and highlighting the existing problems, this article will try to give a briefing on the current stage of application of BCIs in the sphere of healthcare.

Indexed as

Brain computer interfaceelectrical brain signalsneuroimaging techniquessynchron

Identifiers

PMID39926788
PMCPMC11805155

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.