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Record W7084749944 · doi:10.1109/tmrb.2025.3617956

Design and Validation of a Compact Concentric-Tube Robot for Percutaneous Nephrolithotomy

2025· article· en· W7084749944 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Medical Robotics and Bionics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsLondon Health Sciences Centre
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRobotPercutaneous nephrolithotomyFootprintRobotic armRoboticsPercutaneousSoftwareSurgical robot

Abstract

fetched live from OpenAlex

Concentric-tube robots (CTRs) have garnered significant attention in various minimally invasive procedures due to their small size and dexterity. Despite extensive technical advancements in the development of CTRs, there is a lack of design approaches specific to their function as surgical instruments. This study proposes a compact CTR specifically designed for percutaneous nephrolithotomy (PCNL), adaptable for both hand-held operation and mounting on a passive arm. We employ a parallel carriage-based design to reduce the device's cross-sectional footprint (46 mm diameter, 322 mm length) and localize the center of mass (570 g mass) beneath the grip area, enhancing ergonomic comfort and control. An ergonomic evaluation of the robot during the handling of the robot by expert urologists, as well as non-clinicians, showed better ergonomics than standard hand-held PCNL devices. Additionally, closed-loop position control of the distal end of the CTR was implemented based on resolved-motion rate inverse kinematics. The performance of the robot was empirically validated through experiments on a life-size abdominal phantom. The results showed mean closed-loop position errors of 1.2±0.8 mm for autonomous navigation to 100 target points on the stone, indicating a performance level in line with the specific requirements of PCNL.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.287
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it