Evidence map›Paper›PMID 31656719›Full record

ArticleIEEE access : practical innovations, open solutions2019

A Phase Variable Approach for Improved Rhythmic and Non-Rhythmic Control of a Powered Knee-Ankle Prosthesis.

Siavash Rezazadeh, David Quintero, Nikhil Divekar, Emma Reznick, Leslie Gray, Robert D Gregg

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Controlling Powered Prosthesis Joint Impedance Over Continuous Stance Transitions Between Walking and Stair Ascent/Descent.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
  5. Using EMG Biofeedback to Restore Closed-Loop Neural Control on a Powered Prosthetic Ankle.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
  6. Article
  7. Article
  8. A Task-Agnostic Knee Exoskeleton for Reducing Osteoarthritis Pain Across Activities of Daily Life: A Pilot Study.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  9. Adapting Biomimetic Kinematics for Controlling a Powered-Knee, Passive-Ankle Prosthesis Across Inclines.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  10. Unified Control of a Powered Knee-Ankle Prosthesis Enables Walking, Stairs, Transitions, and Other Daily Ambulation Activities.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025
    Article
  11. Ambilateral Activity Recognition and Continuous Adaptation with a Powered Knee-Ankle Prosthesis.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Improving Amputee Endurance over Activities of Daily Living with a Robotic Knee-Ankle Prosthesis: A Case Study.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2023
    Article
  16. Controlling Powered Prosthesis Kinematics over Continuous Transitions Between Walk and Stair Ascent.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2023
    Article
  17. Powered Knee and Ankle Prosthesis Control for Adaptive Ambulation at Variable Speeds, Inclines, and Uneven Terrains.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2023
    Article
  18. A Unified Controller for Natural Ambulation on Stairs and Level Ground with a Powered Robotic Knee Prosthesis.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2023
    Article
  19. 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
  20. Real-Time Gait Phase and Task Estimation for Controlling a Powered Ankle Exoskeleton on Extremely Uneven Terrain.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2023
    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.

Siavash RezazadehDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0002-0312-3167
David QuinteroSchool of Engineering, San Francisco State University, San Francisco, CA 94132, USA.ORCID 0000-0001-5963-6730
Nikhil DivekarDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Emma ReznickDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Leslie GraySchool of Health Professions, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.ORCID 0000-0003-2990-0240
Robert D GreggDepartment of Electrical Engineering and Computer Science, Robotics Institute, University of Michigan, Ann Arbor, MI 48109, USA.

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

Although there has been recent progress in control of multi-joint prosthetic legs for rhythmic tasks such as walking, control of these systems for non-rhythmic motions and general real-world maneuvers is still an open problem. In this article, we develop a new controller that is capable of both rhythmic (constant-speed) walking, transitions between speeds and/or tasks, and some common volitional leg motions. We introduce a new piecewise holonomic phase variable, which, through a finite state machine, forms the basis of our controller. The phase variable is constructed by measuring the thigh angle, and the transitions in the finite state machine are formulated through sensing foot contact along with attributes of a nominal reference gait trajectory. The controller was implemented on a powered knee-ankle prosthesis and tested with a transfemoral amputee subject, who successfully performed a wide range of rhythmic and non-rhythmic tasks, including slow and fast walking, quick start and stop, backward walking, walking over obstacles, and kicking a soccer ball. Use of the powered leg resulted in clinically significant reductions in amputee compensations for rhythmic tasks (including vaulting and hip circumduction) when compared to use of the take-home passive leg. In addition, considerable improvements were also observed in the performance for non-rhythmic tasks. The proposed approach is expected to provide a better understanding of rhythmic and non-rhythmic motions in a unified framework, which in turn can lead to more reliable control of multi-joint prostheses for a wider range of real-world tasks.

Indexed as

Powered prosthesesrehabilitation roboticstransfemoral amputees

Identifiers

PMID31656719
PMCPMC6813797

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.