Evidence map›Paper›PMID 34035945›Full record

ArticleRoyal Society open science2021

Shortcomings of human-in-the-loop optimization of an ankle-foot prosthesis emulator: a case series.

Cara Gonzalez Welker, Alexandra S Voloshina, Vincent L Chiu, Steven H Collins

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. User preference in the personalized control of an ankle prosthesis: a case study.Journal of neuroengineering and rehabilitation · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Walking Ankle Biomechanics of Individuals With Transtibial Amputations Using a Prescribed Prosthesis and a Portable Bionic Prosthesis Under Myoelectric Control.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024
    Article
  8. Design, Control, and Evaluation of a Robotic Ankle-Foot Prosthesis Emulator.IEEE transactions on medical robotics and bionics · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. A robotic emulator for the systematic exploration of transtibial biarticular prosthesis designs.Journal of rehabilitation and assistive technologies engineering
    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 at 2 institutions in 1 country.

Cara Gonzalez WelkerDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-2769-501X
Alexandra S VoloshinaDepartment of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA.
Vincent L ChiuDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-4265-7882
Steven H CollinsDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.
Stanford University · USUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-in-the-loop optimization allows for individualized device control based on measured human performance. This technique has been used to produce large reductions in energy expenditure during walking with exoskeletons but has not yet been applied to prosthetic devices. In this series of case studies, we applied human-in-the-loop optimization to the control of an active ankle-foot prosthesis used by participants with unilateral transtibial amputation. We optimized the parameters of five control architectures that captured aspects of successful exoskeletons and commercial prostheses, but none resulted in significantly lower metabolic rate than generic control. In one control architecture, we increased the exposure time per condition by a factor of five, but the optimized controller still resulted in higher metabolic rate. Finally, we optimized for self-reported comfort instead of metabolic rate, but the resulting controller was not preferred. There are several reasons why human-in-the-loop optimization may have failed for people with amputation. Control architecture is an unlikely cause given the variety of controllers tested. The lack of effect likely relates to changes in motor adaptation, learning, or objectives in people with amputation. Future work should investigate these potential causes to determine whether human-in-the-loop optimization for prostheses could be successful.

Indexed as

amputationoptimizationprosthesis

Identifiers

PMID34035945
PMCPMC8097204
OpenAlexW3158715160

What Socratic 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 Socratic graph.