Evidence map›Paper›PMID 40880672›Full record

ArticleIEEE transactions on medical robotics and bionics2025

Enhancing Robot Transparency in Human-Robot Prosthesis Interaction to Mitigate Terrain Misrecognition Error.

I-Chieh Lee, Ming Liu, He Huang

Abstract read
In one paragraph

Article in IEEE transactions on medical robotics and bionics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

I-Chieh LeeDepartment of Biomedical Engineering, North Carolina State University, Raleigh, NC, USA.
Ming LiuDepartment of Biomedical Engineering, North Carolina State University, Raleigh, NC, USA.
He HuangDepartment of Biomedical Engineering, North Carolina State University, Raleigh, NC, USA.

Funding

Error Tolerance in Wearer-Robot SystemsR01EB024570 · NIBIB · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI HUANG, HE · 2018 to 2022
$1.8M
NIBIB NIH HHS R01 EB024570
6 · The paper itself

Abstract

Clear and effective communication between humans and robots is crucial when they work closely together. As wearable robots become more intelligent and automated, anticipatory control is limited for amputees because they lack prior knowledge of the timing and nature of changes in the robot's motion, making human-machine collaboration more challenging. This study addresses the need for improved wearable robot transparency by enhancing a prosthetic controller to provide users with advanced notifications of locomotion mode changes. Five transfemoral amputees (TFA) wore our designed knee prosthesis and walked on a treadmill. We simulated a terrain misrecognition error by switching the locomotion mode from treadmill walking to stair ascent. Our study focused on three main questions: 1.) What is the ideal timing that the TFAs need to mitigate for machine errors? 2.) How do TFAs compensate for prosthetic knee errors? And 3.) How does the robotic prosthetic leg respond to the TFAs' corrective actions? We found that the enhanced transparency system helps TFAs anticipate changes and adjust their gait to compensate for the terrain misrecognition error. Specifically, providing notifications about 650 milliseconds before a locomotion mode change significantly reduced the effect of robot errors. Although the error compensation from TFAs resulted in a larger magnitude of error induced by the prosthetic knee, the TFAs were able to tolerate it and improve balance stability. According to questionnaires on user preferences, with notification of prosthetic knee motion, the TFAs could trust the device more even though the devices might have occasional errors. This study demonstrates that simple notifications of the robot's movement intent enhance the predictability of prosthetic motion, facilitating anticipatory adjustments that improve safety and user trust.

Indexed as

machine fault preventionpowered knee prosthesisRobot transparencytransfemoral amputee

Identifiers

PMID40880672
PMCPMC12387520

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.