Evidence map›Paper›PMID 38756421›Full record

ArticleIEEE sensors letters2024

Impedance-based biomechanical method for robust inverse kinematics from noisy data.

Serhii Bahdasariants, Matthew G Yough, Valeriya Gritsenko

Abstract read
In one paragraph

Article in IEEE sensors letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

3 authors.

Serhii BahdasariantsDepartment of Human Performance, West Virginia University, Morgantown, WV 26506, USA.
Matthew G YoughDepartment of Human Performance, West Virginia University, Morgantown, WV 26506, USA.
Valeriya GritsenkoDepartment of Human Performance, West Virginia University, Morgantown, WV 26506, USA.

Funding

West Virginia University Stroke COBREP20GM109098 · NIGMS · WEST VIRGINIA UNIVERSITY · PI HRUSKA, MARTIN · 2014 to 2024
$24.5M
Stroke and Alzheimers Disease Related DementiasT32AG052375 · NIA · WEST VIRGINIA UNIVERSITY · PI Paul D Chantler, BERNARD G. SCHREURS · 2017 to 2026
$3.5M
NIA NIH HHS T32 AG052375NIGMS NIH HHS P20 GM109098
6 · The paper itself

Abstract

This paper presents a novel method for solving the inverse kinematic problem of capturing human reaching movements using a dynamic biomechanical model. The model consists of rigid segments connected by joints and actuated by markers. The method was validated against a rotation matrix-based method using motion capture data recorded during reaching movements performed by healthy human volunteers. The results showed that the proposed method achieved low errors in joint angles and compensated for noise in motion capture data. The angles were comparable to those calculated using the standard marker-based method. The proposed bioinspired method can be used in real-time medical applications for processing noisy marker data with occlusions.

Indexed as

motion capturemotor assessmentreaching

Identifiers

PMID38756421
PMCPMC11095830

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.