Evidence map›Paper›PMID 42866729›Full record

ArticleAnnals of medicine and surgery (2012)2026

Brain-computer interfaces and neuroprostheses for severe speech impairment in amyotrophic lateral sclerosis.

Syed Tawassul Hassan, Muhammad Shaheer Bin Faheem, Ali Jan Yaqubi, Mohammed Salem Brhaish

Abstract readEditorial
In one paragraph

Article in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Syed Tawassul HassanDepartment of Medicine, Karachi Medical and Dental College, Karachi Metropolitan University, Karachi, Sindh, Pakistan.
Muhammad Shaheer Bin FaheemDepartment of Medicine, Karachi Institute of Medical Sciences, KIMS, Karachi, Sindh, Pakistan.
Ali Jan YaqubiDepartment of Medicine, Kabul University of Medical Sciences "Abu Ali Ibn Sina", Kabul, Afghanistan.ORCID https://orcid.org/0009-0004-0888-1583
Mohammed Salem BrhaishDepartment of Medicine, Hadhramout University, Mukalla, Yemen.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disorder that frequently culminates in severe dysarthria and anarthria, profoundly isolating patients and diminishing their quality of life. Traditional speech therapy and conventional augmentative and alternative communication devices rely on residual motor control and become ineffective in late-stage ALS. In response, brain-computer interfaces and speech neuroprostheses have emerged as transformative solutions. By decoding neural signals directly from the motor cortex and translating them into synthesized speech, these devices bypass compromised neuromuscular pathways. Recent high-impact clinical trials have demonstrated unprecedented success, achieving high-speed decoding and integrating artificial intelligence-driven voice banking to preserve a patient's unique vocal identity. However, significant translational challenges remain, including signal degradation, surgical risks, high socioeconomic costs, and ethical dilemmas regarding patient autonomy and data privacy. This perspective reviews the current state-of-the-art in speech neuroprosthetics, analyzes the barriers to widespread clinical implementation, and advocates for increased interdisciplinary collaboration and funding to establish these technologies as a standard of care for patients with severe speech impairments.

Indexed as

amyotrophic lateral sclerosisanarthriabrain–computer interfacesneuroprostheticsspeech restoration

Identifiers

PMID42866729
PMCPMC13657498

What OpenQuestion holds

Textmetadata
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.