Evidence map›Paper›PMID 41377282›Full record

ArticleAnnals of medicine and surgery (2012)2025

Wearable exoskeletons as catalysts for postoperative recovery and rehabilitation.

Muhammad Khizar, Muhammad Zaib, Qaima Ali, Raghabendra Kumar Mahato

Abstract readLetter
In one paragraph

Article in Annals of medicine and surgery (2012), 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

4 authors.

Muhammad KhizarFaculty of Medicine, Georgian American University, Manifest Medical Research Co., Tbilisi, Georgia.
Muhammad ZaibFaculty of Medicine, Georgian American University, Manifest Medical Research Co., Tbilisi, Georgia.
Qaima AliFaculty of Medicine, Liaquat College of Medicine & Dentistry, Karachi, Pakistan.
Raghabendra Kumar MahatoFaculty of Medicine, Gandaki Medical College Teaching Hospital and Research Center, Pokhara, Nepal.ORCID https://orcid.org/0009-0009-9434-1650

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable robotic exoskeletons are emerging as pivotal tools in postoperative recovery, enabling early mobilization through powered joint assistance. This letter discusses their clinical and technological relevance in accelerating functional rehabilitation. Meta-analyses and clinical studies have demonstrated superior outcomes in joint motion, gait performance, and shorter hospital stays compared to conventional therapy. Devices such as Japan's HAL (Hybrid Assistive Limb) and Honda Walking Assist exemplify the fusion of biomechanics and AI-driven control, providing customizable torque support and real-time feedback. Implementation in Japan, Taiwan, the United States, and Europe underscores global recognition of their utility. Future research should focus on multicenter trials and ethical integration frameworks.

Indexed as

artificial intelligence in healthcareearly mobilizationgait retrainingpostoperative rehabilitationwearable robotic exoskeletons

Identifiers

PMID41377282
PMCPMC12688792

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.