PTOTSLPOtherJournal of neuroengineering and rehabilitation2026

Robotics and artificial intelligence applications in neurorehabilitation: a bibliometric analysis (2003-2025).

Burhan Taşkaya, Cengiz Taşkaya

PMID 41486253

WHAT IT FOUND

The literature on robotics and AI in neurorehabilitation has grown rapidly since 2010, but remains heavily focused on stroke and exoskeleton design.

There is little published research on Parkinson’s disease, spinal cord injury, or paediatric populations, and the field lacks clinical validation data.

Key findings

01Publications in this field have increased sharply, rising from fewer than 3 per year before 2010 to 69 in 2024.

02Research is concentrated on stroke and exoskeletons, leaving significant gaps in Parkinson’s disease, spinal cord injury, and paediatric neurodevelopmental disorders.

03The analysis mapped bibliometric trends only and did not examine clinical outcomes or methodological quality, so it provides no evidence on treatment efficacy.

STILL TO COME

How it was doneWhat they foundWhat it means for PTsWhat it means for OTsWhat it means for SLPs

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What it does not show

The analysis only mapped publication counts and keywords; it did not assess the quality of the studies, the specific AI algorithms used, or any clinical outcomes. The search was limited to English-language articles in the Web of Science Core Collection and excluded conference proceedings, which may omit emerging engineering developments. The keyword-based definition of the field may have missed relevant studies that did not use the specified terms. 2025 data are incomplete because the search closed on 18 August 2025.

Declared interests

No conflicts of interest or funding sources were declared in the provided text.

The easy way to misread this

Do not interpret the rapid growth in publications or the high citation counts as evidence that robotic and AI-assisted neurorehabilitation is clinically effective. This study only mapped bibliometric trends and explicitly did not examine clinical outcomes or methodological quality.

Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →