Evidence map›Paper›PMID 39650466›Full record

ArticlePeerJ. Computer science2024

Intelligent sensors in assistive systems for deaf people: a comprehensive review.

Caio César Sabino Soares, Luis Augusto Silva, Anita Fernandes, Gabriel Villarrubia González, Valderi R Q Leithardt, Wemerson Delcio Parreira

Abstract read
In one paragraph

Article in PeerJ. Computer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Caio César Sabino Soares *Polytechnic School, Universidade do Vale do Itajaí, Itajai, Santa Catarina, Brazil.
Luis Augusto SilvaDepartment of Computer Science, Universidad de Salamanca, Salamanca, Spain.
Anita FernandesPolytechnic School, Universidade do Vale do Itajaí, Itajai, Santa Catarina, Brazil.
Gabriel Villarrubia GonzálezDepartment of Computer Science, Universidad de Salamanca, Salamanca, Spain.
Valderi R Q LeithardtInstituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Lisboa, Portugal.
Wemerson Delcio Parreira *Faculty of Electrical Engineering, Polytechnic School, Pontifical Catholic University of Campinas, Campinas, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research aims to conduct a systematic literature review (SLR) on intelligent sensors and the Internet of Things (IoT) in assistive devices for the deaf and hard of hearing. This study analyzes the current state and promise of intelligent sensors in improving the daily lives of those with hearing impairments, addressing the critical need for improved communication and environmental interaction. We investigate the functionality, integration, and use of sensor technologies in assistive devices, assessing their impact on autonomy and quality of life. The key findings show that many sensor-based applications, including vibration detection, ambient sound recognition, and signal processing, lead to more effective and intuitive user experiences. The study emphasizes the importance of energy efficiency, cost-effectiveness, and user-centric design in developing accessible and sustainable assistive solutions. Moreover, it discusses the challenges and future directions in scaling these technologies for widespread adoption, considering the varying needs and preferences of the end-users. Finally, the study advocates for continual innovation and interdisciplinary collaboration in advancing assistive technologies. It highlights the importance of IoT and intelligent sensors in fostering a more inclusive and empowered environment for the deaf and hard-of-hearing people. This review covers studies published between 2011 and 2024, highlighting advances in sensor technologies for assistive systems in this timeframe.

Indexed as

Assistive devicesCommunication enhancementDeaf and hard of hearingInternet of Things (IoT)Smart sensors

Identifiers

PMID39650466
PMCPMC11623048

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.