Evidence map›Paper›PMID 30546971›Full record

ArticleIEEE journal of translational engineering in health and medicine2018

Intuitive Clinician Control Interface for a Powered Knee-Ankle Prosthesis: A Case Study.

David Quintero, Emma Reznick, Daniel J Lambert, Siavash Rezazadeh, Leslie Gray, Robert D Gregg

Open access · goldAbstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

11 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Data-Driven Variable Impedance Control of a Powered Knee-Ankle Prosthesis for Adaptive Speed and Incline Walking.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Analysis of Continuously Varying Kinematics for Prosthetic Leg Control Applications.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2021
    Article
  8. Effects of a Powered Knee-Ankle Prosthesis on Amputee Hip Compensations: A Case Series.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2020
    Article
  9. Wearer-Prosthesis Interaction for Symmetrical Gait: A Study Enabled by Reinforcement Learning Prosthesis Control.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2020
    Article
  10. Article
  11. Predicting Individualized Joint Kinematics over a Continuous Range of Slopes and Speeds.Proceedings of the ... IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics
    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

6 authors at 2 institutions in 1 country.

David QuinteroDepartment of BioengineeringThe University of Texas at DallasRichardsonTX75080USA.
Emma ReznickDepartment of BioengineeringThe University of Texas at DallasRichardsonTX75080USA.
Daniel J LambertDepartment of Electrical EngineeringThe University of Texas at DallasRichardsonTX75080USA.
Siavash RezazadehDepartment of BioengineeringThe University of Texas at DallasRichardsonTX75080USA.
Leslie GrayDepartment of Health Care SciencesThe University of Texas Southwestern Medical CenterDallasTX75390USA.
Robert D GreggDepartment of BioengineeringThe University of Texas at DallasRichardsonTX75080USA.
The University of Texas at Dallas · USSouthwestern Medical Center · US

Funding

Controlling Robot-Assisted Locomotion with Extended Kalman Filter Estimates of Phase and ActivityR01HD094772 · NICHD · UNIVERSITY OF TEXAS DALLAS · PI Robert D Gregg · 2018 to 2026
$4.3M
PHASE-BASED CONTROL OF LOCOMOTION FOR HIGH-PERFORMANCE PROSTHESES AND ORTHOSESDP2HD080349 · NICHD · UNIVERSITY OF TEXAS DALLAS · PI GREGG, ROBERT D · 2013 to 2013
$2.3M
NICHD NIH HHS DP2 HD080349NICHD NIH HHS R01 HD094772
6 · The paper itself

Abstract

This paper presents a potential solution to the challenge of configuring powered knee-ankle prostheses in a clinical setting. Typically, powered prostheses use impedance-based control schemes that contain several independent controllers which correspond to consecutive periods along the gait cycle. This control strategy has numerous control parameters and switching rules that are generally tuned by researchers or technicians and not by a certified prosthetist. We propose an intuitive clinician control interface (CCI) in which clinicians tune a powered knee-ankle prosthesis based on a virtual constraint control scheme, which tracks desired periodic joint trajectories based on a continuous measurement of the phase (or progression) of gait. The interface derives virtual constraints from clinician-designed joint kinematic trajectories. An experiment was conducted in which a certified prosthetist used the control interface to configure a powered knee-ankle prosthesis for a transfemoral amputee subject during level-ground walking trials. While it usually takes engineers hours of tuning individual parameters by trial and error, the CCI allowed the clinician to tune the powered prosthesis controller in under 10 min. This allowed the clinician to improve several amputee gait outcome metrics, such as gait symmetry. These results suggest that the CCI can improve the clinical viability of emerging powered knee-ankle prostheses.

Indexed as

legged locomotionProstheticsrobot controluser interfaces

Identifiers

PMID30546971
PMCPMC6286184
OpenAlexW2900866834

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.