Evidence map›Paper›PMID 39918767›Full record

ReviewMedical & biological engineering & computing2025

Patient performance assessment methods for upper extremity rehabilitation in assist-as-needed therapy strategies: a comprehensive review.

Erkan Ödemiş, Cabbar Veysel Baysal, Mustafa İnci

Abstract readReview
In one paragraph

Review in Medical & biological engineering & computing, 2025. 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

3 authors.

Erkan ÖdemişDepartment of Biomedical Engineering, Çukurova University, 01330, Sarıçam, Adana, Turkey. eodemis@cu.edu.tr.ORCID https://orcid.org/0000-0003-0212-4288
Cabbar Veysel BaysalDepartment of Biomedical Engineering, Çukurova University, 01330, Sarıçam, Adana, Turkey.ORCID http://orcid.org/0000-0003-1490-8725
Mustafa İnciDepartment of Mechatronics Engineering, İskenderun Technical University, 31200, Hatay, Turkey.ORCID http://orcid.org/0000-0002-0900-5946

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to comprehensively review patient performance assessment (PPA) methods used in assist-as-needed (AAN) robotic therapy for upper extremity rehabilitation. AAN strategies adjust robotic assistance according to the patient's performance, aiming to enhance engagement and recovery in individuals with motor impairments. This review categorizes the implemented PPA methods in the literature for the first time in such a wide scope and suggests future research directions to improve adaptive and personalized therapy. At first, the studies are examined to evaluate PPA methods, which are subsequently categorized according to their underlying implementation strategies: position error-based methods, force-based methods, electromyography (EMG), electroencephalography (EEG)-based methods, performance indicator-based methods, and physiological signal-based methods. The advantages and limitations of each method are discussed. In addition to the classification of PPA methods, the current study also examines clinically tested AAN strategies applied in upper extremity rehabilitation and their clinical outcomes. Clinical findings from these trials demonstrate the potential of AAN strategies in improving motor function and patient engagement. Nevertheless, more extensive clinical testing is necessary to establish the long-term benefits of these strategies over conventional therapies. Ultimately, this review aims to guide future developments in the field of robotic rehabilitation, providing researchers with insights into optimizing AAN strategies for enhanced patient outcomes.

Indexed as

RoboticsUpper ExtremityElectroencephalographyElectromyographyHumansA comprehensive reviewAssist-as-neededPerformance assessmentRobotic rehabilitationUpper extremely rehabilitation

Identifiers

PMID39918767
PMCPMC12204900

What OpenQuestion holds

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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.