ReviewJournal of robotic surgery2026
Force sensing and haptic feedback in robotic surgery: a bibliometric and knowledge-mapping analysis of technological evolution and translational trajectories.
Review in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Force sensing and haptic feedback are increasingly important for restoring information on instrument-tissue interaction during robotic surgery, yet the development and clinical translation of this field remain incompletely characterized. This study mapped the global research landscape, intellectual structure, technological evolution, and translational trajectory of force sensing and haptic feedback in robotic surgery. Publications from January 1, 2010, through the final search date of July 30, 2026, were retrieved from the Web of Science Core Collection, Scopus, and PubMed. After deduplication, metadata quality control, and eligibility assessment, 2,872 publications from 960 sources were analyzed using bibliometric performance indicators, science mapping, citation-burst detection, logistic growth modeling, and exploratory topic modeling. Annual output increased from 56 publications in 2010 to 393 in 2025, with 54.46% of the corpus published during 2020-2025. Logistic modeling placed the literature within a rapid-growth phase, although the observed output in 2025 exceeded the smoothed model trajectory. China contributed the largest number of publications, whereas the United States ranked first in country-level cumulative citations. Publications involving authors from more than one country accounted for 11.98% of the corpus, indicating comparatively limited international collaboration. The knowledge structure shifted from master-slave teleoperation and bilateral control toward miniaturized force sensing, sensorized instruments, robotic palpation, sensorless force estimation, and force-aware intelligent assistance. Exploratory topic modeling did not yield sufficiently coherent or stable themes for definitive classification. Overall, the published literature suggests a shift from component-level engineering toward integrated systems and early-stage clinical evaluation; however, these bibliometric patterns should not be interpreted as evidence of established clinical effectiveness. Future research should prioritize standardized reporting, task- and tissue-specific force thresholds, independent external validation, human-factor assessment, and prospective multicenter studies.
Indexed as
Identifiers
42634062What OpenQuestion holds
Registered trials
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.