Evidence map›Paper›PMID 40969573›Full record

ArticleIEEE robotics and automation letters2025

A novel seamless magnetic-based actuating mechanism for end-effector-based robotic rehabilitation platforms.

Sima Ghafoori, Ali Rabiee, Maryam Norouzi, Musa K Jouaneh, Reza Abiri

Abstract read
In one paragraph

Article in IEEE robotics and automation letters, 2025. 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. 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

5 authors.

Sima GhafooriDepartment of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, 02881 USA.
Ali RabieeDepartment of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, 02881 USA.
Maryam NorouziDepartment of Mechanical Engineering, University of Rhode Island, Kingston, RI, 02881 USA.
Musa K JouanehDepartment of Mechanical Engineering, University of Rhode Island, Kingston, RI, 02881 USA.
Reza AbiriDepartment of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, 02881 USA.

Funding

Training CoreP20GM103430 · NIGMS · UNIVERSITY OF RHODE ISLAND · PI Christopher Lee Hemme · 2012 to 2026
$63.6M
NIGMS NIH HHS P20 GM103430
6 · The paper itself

Abstract

Rehabilitation robotics continues to confront sub-stantial challenges, particularly in achieving smooth, safe, and intuitive human-robot interactions for upper limb motor training. Many current systems depend on complex mechanical designs, direct physical contact, and multiple sensors, which not only elevate costs but also reduce accessibility. Additionally, delivering seamless weight compensation and precise motion tracking remains a highly complex undertaking. To overcome these obstacles, we have developed a novel magnetic-based actuation mechanism for end-effector robotic rehabilitation. This innovative approach enables smooth, non-contact force transmission, significantly enhancing patient safety and comfort during upper limb training. To ensure consistent performance, we integrated an Extended Kalman Filter (EKF) alongside a controller for real-time position tracking, allowing the system to maintain high accuracy or recover even in the event of sensor malfunction or failure. In a user study with 12 participants, 75% rated the system highly for its smoothness, while 66.7% commended its safety and effective weight compensation. The EKF demonstrated precise tracking performance, with root mean square error (RMSE) values remaining within acceptable limits (under 2 cm). By combining magnetic actuation with advanced closed-loop control algorithms, this system marks a significant advancement in the field of upper limb rehabilitation robotics.

Indexed as

Extended Kalman Filtermagnetic actuationrobotic rehabilitationweight compensation

Identifiers

PMID40969573
PMCPMC12442580

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Registered trials

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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.