Evidence map›Paper›PMID 30319392›Full record

ArticleFrontiers in aging neuroscience2018

Reliability of a Novel Video-Based Method for Assessing Age-Related Changes in Upper Limb Kinematics.

Daniel A Pupo, John W Kakareka, Jonathan Krynitsky, Lorenzo Leggio, Tom Pohida, Stephanie Studenski, Brandon K Harvey

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2018. 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, top 89% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

7 authors at 6 institutions in 1 country.

Daniel A PupoTranslational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States.
John W KakarekaSignal Processing and Instrumentation Section, Office of Intramural Research, Center for Information Technology (CIT), National Institutes of Health, Bethesda, MD, United States.
Jonathan KrynitskySignal Processing and Instrumentation Section, Office of Intramural Research, Center for Information Technology (CIT), National Institutes of Health, Bethesda, MD, United States.
Lorenzo LeggioSection on Clinical Psychoneuroendocrinology and Neuropsychopharmacology, National Institute on Alcohol Abuse and Alcoholism (NIAAA) and National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, United States.
Tom PohidaSignal Processing and Instrumentation Section, Office of Intramural Research, Center for Information Technology (CIT), National Institutes of Health, Bethesda, MD, United States.
Stephanie StudenskiTranslational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States.
Brandon K HarveyOptogenetics and Transgenic Technology Core, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States.
National Institutes of Health · USCenter for Information Technology · USNational Institute on Aging · USNational Institute on Alcohol Abuse and Alcoholism · USNational Institute on Drug Abuse · USSignal Processing (United States) · US

Funding

Signal Processing And Instrumentation SectionZIACT000261 · CIT · CENTER FOR INFORMATION TECHNOLOGY · PI POHIDA, THOMAS J · 2009 to 2021
$16.7M
6 · The paper itself

Abstract

Monitoring age-related changes in motor function can be used to identify deviations that represent underlying diseases for which early diagnosis is often paramount for efficacious, interventional therapies. Currently, the availability of cost-effective and reliable diagnostic tools capable of routine monitoring is limited. Adequate diagnostic systems are needed to identify, monitor and distinguish early subclinical symptoms of neurological diseases from normal aging-associated changes. Herein, we describe the development, initial validation and reliability of the Hand-Arm Movement Monitoring System (HAMMS), a video-based data acquisition system built using a programmable, versatile platform for acquiring temporal and spatial metrics of hand and arm movements. A healthy aging population of 111 adults were used to evaluate the HAMMS via a repetitive motion test of changing target size. The test required participants to move a fiducial on their hand between two targets presented on a video monitor. The test-retest reliability based on Intraclass Correlation Coefficient (ICCs) for the system ranged from 0.56 to 0.87 and the Linear Correlation Coefficients (LCCs) ranged from 0.58 to 0.87. Average speed, average acceleration, speed error and center offset all demonstrated a positive correlation with age. Using an intertarget path of hand motion, we observed an age-dependent increase in the average number of points outside the most direct motion path, indicating a reduction in hand-arm movement control with age. The reliability, flexibility and programmability of the HAMMS makes this low cost, video-based platform an effective tool for evaluating longitudinal changes in hand-arm related movements and a potential diagnostic device for neurological diseases where hand-arm movements are affected.

Indexed as

agingfiducial markerskinematicsreliabilityupper extremitiesvideo-based monitoring

Identifiers

PMID30319392
PMCPMC6166023
OpenAlexW2893316927

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.