Evidence map›Paper›PMID 33019099›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2020

Sonomyography Combined with Vibrotactile Feedback Enables Precise Target Acquisition Without Visual Feedback.

Shriniwas Patwardhan, Biswarup Mukherjee, Ananya Dhawan, Meena Alzamani, Abdul Noor, Susannah Engdahl, Wilsaan M Joiner, Siddhartha Sikdar

Open access · greenAbstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Sonomyography shows feasibility as a tool to quantify joint movement at the muscle level.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2022
    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

8 authors at 1 institution in 1 country.

Shriniwas Patwardhan
Biswarup Mukherjee
Ananya Dhawan
Meena Alzamani
Abdul Noor
Susannah Engdahl
Wilsaan M Joiner
Siddhartha Sikdar
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

Upper limb prosthesis users currently lack haptic feedback from their terminal devices, which significantly limits their ability to meaningfully interact with their environment. Users therefore rely heavily on visual feedback when using terminal devices. Previously, it has been shown that force-related feedback from an end-effector or virtual environment can help the user minimize errors and improve performance. Currently, myoelectric control systems enable the user to control the velocity of terminal devices. We have developed a novel control method using ultrasound sensing, called sonomyography, that enables position control based on mechanical deformation of muscles. In this paper, we investigated whether the proprioceptive feedback from muscle deformation combined with vibrotactile haptic feedback can minimize the need for visual feedback. Able bodied subjects used sonomyography to control a virtual cursor, and performed a target acquisition task. The effect of visual and haptic feedback on performance of a target acquisition task was systematically tested. We found that subjects made large errors when they tried to reacquire a target without visual feedback, but in the presence of real-time haptic feedback, the precision of the target position improved, and were similar to when visual feedback was used for target acquisition. This result has implications for improving the performance of prosthetic control systems.

Indexed as

Artificial LimbsFeedback, SensoryFeedbackHumans

Identifiers

PMID33019099
PMCPMC7733223
OpenAlexW3082466147

What OpenQuestion 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 OpenQuestion graph.