Evidence map›Paper›PMID 35173983›Full record

ArticleJournal of forensic biomechanics2014

Biomechanical Analysis of Concealed Pack Load Influences on Terrorist Gait Signatures Derived from Gröbner Basis Theory.

Sean S Kohles, Anum Barki, Kimberly D Kendricks, Ronald F Tuttle

Abstract read
In one paragraph

Article in Journal of forensic biomechanics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sean S KohlesDivision of Biomaterials & Biomechanics Department of Restorative Dentistry Oregon Health & Science University Portland.
Anum BarkiDepartment of Engineering Physics Air Force Institute of Technology, Wright Patterson Air Force Base.
Kimberly D KendricksDepartment of Mathematics and Computer Science Center for Human Performance and Sensor Applications Central State University Wilberforce.
Ronald F TuttleDepartment of Engineering Physics Air Force Institute of Technology, Wright Patterson Air Force Base.

Funding

Composition/Functional Elasticity of Engineered TissuesR03DE014288 · NIDCR · KOHLES BIOENGINEERING · PI KOHLES, SEAN S · 2002 to 2003
$137k
NIDCR NIH HHS R03 DE014288
6 · The paper itself

Abstract

This project examines kinematic gait parameters as forensic predictors of the influence associated with individuals carrying concealed weighted packs up to 20% of their body weight. An initial inverse dynamics approach combined with computational algebra provided lower limb joint angles during the stance phase of gait as measured from 12 human subjects during normal walking. The following paper describes the additional biomechanical analysis of the joint angle data to produce kinetic and kinematic parameters further characterizing human motion. Results include the rotational velocities and accelerations of the hip, knee, and ankle as well as inertial moments and kinetic energies produced at these joints. The reported findings indicate a non-statistically significant influence of concealed pack load, body mass index, and gender on joint kinetics (p>0.05). Ratios of loaded to unloaded kinematics, however, identified some statistical influence on gait (p<0.05). On-going studies are examining an additional subject cohort with greater pack loads in an effort to identify alterations in gait signatures as a counter-terrorism approach.

Indexed as

BiomechanicsConcealed pack loadsCounter-terrorismGait parametersInverse dynamicsKinesiology

Identifiers

PMID35173983
PMCPMC8846570

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.