Evidence map›Paper›PMID 35600893›Full record

ArticleFrontiers in bioengineering and biotechnology2022

First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study.

Susannah M Engdahl, Samuel A Acuña, Erica L King, Ahmed Bashatah, Siddhartha Sikdar

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. 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
1.8field-weighted citation impact, top 16% 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, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Clinical, Safety, and Engineering Perspectives on Wearable Ultrasound Technology: A Review.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024
    Review
  5. Article
  6. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. A-Mode Ultrasound-Based Prediction of Transfemoral Amputee Prosthesis Walking Kinematics via an Artificial Neural Network.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology 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

5 authors at 1 institution in 1 country.

Susannah M EngdahlDepartment of Bioengineering, George Mason University, Fairfax, VA, United States.
Samuel A AcuñaDepartment of Bioengineering, George Mason University, Fairfax, VA, United States.
Erica L KingDepartment of Bioengineering, George Mason University, Fairfax, VA, United States.
Ahmed BashatahDepartment of Bioengineering, George Mason University, Fairfax, VA, United States.
Siddhartha SikdarDepartment of Bioengineering, George Mason University, Fairfax, VA, United States.
George Mason University · US

Funding

Sonomyographic Upper Limb Prosthetics: A New ParadigmU01EB027601 · NIBIB · GEORGE MASON UNIVERSITY · PI KALIKI, RAHUL REDDY, SIKDAR, SIDDHARTHA · 2020 to 2024
$3.5M
NIBIB NIH HHS U01 EB027601
6 · The paper itself

Abstract

Ultrasound-based sensing of muscle deformation, known as sonomyography, has shown promise for accurately classifying the intended hand grasps of individuals with upper limb loss in offline settings. Building upon this previous work, we present the first demonstration of real-time prosthetic hand control using sonomyography to perform functional tasks. An individual with congenital bilateral limb absence was fitted with sockets containing a low-profile ultrasound transducer placed over forearm muscle tissue in the residual limbs. A classifier was trained using linear discriminant analysis to recognize ultrasound images of muscle contractions for three discrete hand configurations (rest, tripod grasp, index finger point) under a variety of arm positions designed to cover the reachable workspace. A prosthetic hand mounted to the socket was then controlled using this classifier. Using this real-time sonomyographic control, the participant was able to complete three functional tasks that required selecting different hand grasps in order to grasp and move one-inch wooden blocks over a broad range of arm positions. Additionally, these tests were successfully repeated without retraining the classifier across 3 hours of prosthesis use and following simulated donning and doffing of the socket. This study supports the feasibility of using sonomyography to control upper limb prostheses in real-world applications.

Indexed as

functional tasksgesture recognitionprosthesis controlrehabilitationsonomyographyultrasound imagingupper limb

Identifiers

PMID35600893
PMCPMC9114778
OpenAlexW4225400793

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.