Evidence map›Paper›PMID 31318673›Full record

ArticleThe American journal of occupational therapy : official publication of the American Occupational Therapy Association

Capturing Upper Limb Gross Motor Categories Using the Kinect® Sensor.

Na Jin Seo, Vincent Crocher, Egli Spaho, Charles R Ewert, Mojtaba F Fathi, Pilwon Hur, Sara A Lum, Elizabeth M Humanitzki, Abigail L Kelly, Viswanathan Ramakrishnan and 1 more

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In one paragraph

Article in The American journal of occupational therapy : official publication of the American Occupational Therapy Association. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

11 authors.

Na Jin SeoNa Jin Seo, PhD, is Associate Professor, Division of Occupational Therapy, Department of Health Professions, and Associate Professor, Department of Health Science and Research, Medical University of South Carolina, Charleston; seon@musc.edu.
Vincent CrocherVincent Crocher, PhD, is Research Associate, School of Engineering, University of Melbourne, Parkville, Victoria, Australia. At the time of the study, he was Postdoctoral Researcher, Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee.
Egli SpahoEgli Spaho, DPT, is Physical Therapist, Ascension All Saints Hospital, Racine, Wisconsin. At the time of the study, he was Research Assistant, Department of Kinesiology, University of Wisconsin-Milwaukee.
Charles R EwertCharles R. Ewert, BS, is Associate Software Engineer, Northwestern Mutual, Milwaukee, Wisconsin. At the time of the study, he was Research Assistant, Department of Computer Science, University of Wisconsin-Milwaukee.
Mojtaba F FathiMojtaba F. Fathi, PhD, is Research Associate, Department of Mechanical Engineering, University of Wisconsin-Milwaukee.
Pilwon HurPilwon Hur, PhD, is Assistant Professor, Department of Mechanical Engineering, Texas A&M University, College Station.
Sara A LumSara A. Lum, MS, OTR/L, is Occupational Therapist, Wake Forest Baptist Medical Center, Winston-Salem, North Carolina. At the time of the study, she was Student, Division of Occupational Therapy, Department of Health Professions, Medical University of South Carolina, Charleston.
Elizabeth M HumanitzkiElizabeth M. Humanitzki, MS, OTR/L, is Occupational Therapist, Coastal Therapy Services Inc., Charleston, South Carolina. At the time of the study, she was Student, Division of Occupational Therapy, Department of Health Professions, Medical University of South Carolina, Charleston.
Abigail L KellyAbigail L. Kelly, MS, is Instructor, Department of Stomatology, Medical University of South Carolina, Charleston. At the time of the study, she was Research Associate, Department of Public Health Sciences, Medical University of South Carolina, Charleston.
Viswanathan RamakrishnanViswanathan Ramakrishnan, PhD, is Professor, Department of Public Health Sciences, Medical University of South Carolina, Charleston.
Michelle L WoodburyMichelle L. Woodbury, PhD, OTR/L, is Associate Professor, Division of Occupational Therapy, Department of Health Professions, and Associate Professor, Department of Health Science and Research, Medical University of South Carolina, Charleston.

Funding

Treating Depression and Enhancing Locomotor Recovery Post-strokeP20GM109040 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KAUTZ, STEVEN A. · 2014 to 2024
$23.5M
Improving Outcome Measurement for Medical Rehabilitaiton Clinical TrialsR24HD065688 · NICHD · BOSTON UNIVERSITY MEDICAL CAMPUS · PI JETTE, ALAN MAURICE, ZAFONTE, ROSS DENNIS · 2010 to 2014
$3.9M
NICHD NIH HHS R24 HD065688NIGMS NIH HHS P20 GM109040
6 · The paper itself

Abstract

importanceAlong with growth in telerehabilitation, a concurrent need has arisen for standardized methods of tele-evaluation.

objectiveTo examine the feasibility of using the Kinect sensor in an objective, computerized clinical assessment of upper limb motor categories.

designWe developed a computerized Mallet classification using the Kinect sensor. Accuracy of computer scoring was assessed on the basis of reference scores determined collaboratively by multiple evaluators from reviewing video recording of movements. In addition, using the reference score, we assessed the accuracy of the typical clinical procedure in which scores were determined immediately on the basis of visual observation. The accuracy of the computer scores was compared with that of the typical clinical procedure.

settingResearch laboratory.

participantsSeven patients with stroke and 10 healthy adult participants. Healthy participants intentionally achieved predetermined scores. OUTCOMES AND MEASURES: Accuracy of the computer scores in comparison with accuracy of the typical clinical procedure (immediate visual assessment).

resultsThe computerized assessment placed participants' upper limb movements in motor categories as accurately as did typical clinical procedures. CONCLUSIONS AND RELEVANCE: Computerized clinical assessment using the Kinect sensor promises to facilitate tele-evaluation and complement telehealth applications. WHAT THIS ARTICLE ADDS: Computerized clinical assessment can enable patients to conduct evaluations remotely in their homes without therapists present.

Indexed as

StrokeStroke RehabilitationTelerehabilitationAdultHumansMovementUpper Extremity

Identifiers

PMID31318673
PMCPMC6638702

What OpenQuestion holds

Textmetadata
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.