Evidence map›Paper›PMID 42898783›Full record

ReviewFrontiers in robotics and AI2026

Low-cost robotics and AI technologies for rehabilitation and health monitoring.

João Silva Sequeira

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2026. 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

1 author.

João Silva SequeiraInstitute for Systems and Robotics, Instituto Superior Técnico, Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reviews robotics technologies applied to rehabilitation. Besides a literature review, selected to highlight relevant topics/aspects, the paper presents a few examples of low cost technologies (which are particularly important in ageing demographics and struggling economies) and discusses applications in the overlap between rehabilitation and regular health monitoring. The purpose of this study is to frame rehabilitation robotics in terms of the existing technologies and to showcase low cost demonstrators with relevance in rehabilitation scenarios. Besides the encouraging results, obtained in real-world tests (a distinctive characteristic of the paper), the role of AI techniques in the development of low cost devices is also highlighted. Moreover, the paper also discusses the influence of human factors in the acceptance and adoption of alternative/disruptive technologies.

Indexed as

diabetic footepilepsy traitsmachine learningrehabilitation taxonomiesrobot canerobot kinematicsthermographic images

Identifiers

PMID42898783
PMCPMC13678294

What OpenQuestion holds

Textmetadata
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.