Evidence map›Paper›PMID 37635763›Full record

ArticleAnnual reviews in control2023

A Review of Current State-of-the-Art Control Methods for Lower-Limb Powered Prostheses.

Rachel Gehlhar, Maegan Tucker, Aaron J Young, Aaron D Ames

Abstract read
In one paragraph

Article in Annual reviews in control, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Design and evaluation of a bone-anchored, neurally-controlled knee prosthesis.Journal of neuroengineering and rehabilitation · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Vibrotactile Haptic and Gesture Feedback in a Smartwatch for Controlling a Multi-Activity Powered Knee-Ankle Prosthesis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025
    Article
  14. Adapting Biomimetic Kinematics for Controlling a Powered-Knee, Passive-Ankle Prosthesis Across Inclines.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  15. A Task-Agnostic Approach to Unified Multi-Activity Gait Phase Estimation via Bilateral Sensing.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  16. Implementation and Validation of a Data-Driven Variable Impedance Controller on the Össur Power Knee.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2025
    Article
  17. Article
  18. Article
  19. Review
  20. 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
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

4 authors.

Rachel GehlharDepartment of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA.
Maegan TuckerDepartment of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA.
Aaron J YoungWoodruff School of Mechanical Engineering, Georgia Institute of Technology, North Avenue, Atlanta, 30332, GA, USA.
Aaron D AmesDepartment of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA.

Funding

A new framework for self-adaptive artificial intelligence to personalize assistance for patients using robotic exoskeletons and prosthesesDP2HD111709 · NICHD · GEORGIA INSTITUTE OF TECHNOLOGY · PI YOUNG, AARON JOHN · 2022 to 2025
$2.4M
NICHD NIH HHS DP2 HD111709
6 · The paper itself

Abstract

Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge - the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user. In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: high-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.

Indexed as

controllower-limbprosthesesroboticsuser-customization

Identifiers

PMID37635763
PMCPMC10449377

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.