Evidence map›Paper›PMID 40852091›Full record

ArticleAdvanced intelligent systems (Weinheim an der Bergstrasse, Germany)2025

Cloud-Based Control System with Sensing and Actuating Textile-Based IoT Gloves for Telerehabilitation Applications.

Kadir Ozlem, Cagatay Gumus, Ayse Feyza Yilmaz, Asli Tuncay Atalay, Ozgur Atalay, Gökhan Ince

Abstract read
In one paragraph

Article in Advanced intelligent systems (Weinheim an der Bergstrasse, Germany), 2025. 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. Review
  2. 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.

Kadir OzlemFaculty of Computer and Informatics Engineering Computer Engineering Department Istanbul Technical University 34469 Istanbul Türkiye.ORCID https://orcid.org/0000-0002-0506-2863
Cagatay GumusFaculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University 34437 Istanbul Türkiye.ORCID https://orcid.org/0000-0002-3449-1560
Ayse Feyza YilmazFaculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University 34437 Istanbul Türkiye.ORCID https://orcid.org/0000-0002-3507-2624
Asli Tuncay AtalayFaculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University 34437 Istanbul Türkiye.ORCID https://orcid.org/0000-0002-9866-6331
Ozgur AtalayFaculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University 34437 Istanbul Türkiye.ORCID https://orcid.org/0000-0003-1050-0685
Gökhan InceFaculty of Computer and Informatics Engineering Computer Engineering Department Istanbul Technical University 34469 Istanbul Türkiye.ORCID https://orcid.org/0000-0002-0034-030X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remote manipulation devices extend human capabilities over vast distances or in inaccessible environments, removing constraints between patients and treatment. The integration of therapeutic and assistive devices with the Internet of Things (IoT) has demonstrated high potential to develop and enhance intelligent rehabilitation systems in the e-health domain. Within such devices, soft robotic products distinguish themselves through their lightweight and adaptable characteristics, facilitating secure collaboration between humans and robots. The objective of this research is to combine a textile-based sensorized glove with an air-driven soft robotic glove, operated wirelessly using the developed control system architecture. The sensing glove equipped with capacitive sensors on each finger captures the movements of the medical staff's hand. Meanwhile, the pneumatic rehabilitation glove designed to aid patients affected by impaired hand function due to stroke, brain injury, or spinal cord injury replicates the movements of the medical personnel. The proposed artificial intelligence-based system detects finger gestures and actuates the pneumatic system, responding within an average response time of 48.4 ms. The evaluation of the system further in terms of accuracy and transmission quality metrics verifies the feasibility of the proposed system integrating textile gloves into IoT infrastructure, enabling remote motion sensing and actuation.

Indexed as

cloud computingmachine learningremote rehabilitationsoft roboticstextile sensors and actuators

Identifiers

PMID40852091
PMCPMC12370170

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.