Evidence map›Paper›PMID 31191931›Full record

ArticleJournal of rehabilitation and assistive technologies engineering

Quantifying performance metrics of cervical spine mobilization for improved education and clinical outcomes: Early experience with a novel wearable device.

Ryan Kope, Jordan O'Brien, Jackie Sadi, David M Walton, Louis M Ferreira

Abstract read
In one paragraph

Article in Journal of rehabilitation and assistive technologies engineering. 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
–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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

5 authors.

Ryan Kope1Western University Faculty of Engineering, London, Canada.
Jordan O'Brien1Western University Faculty of Engineering, London, Canada.
Jackie Sadi1Western University Faculty of Engineering, London, Canada.
David M Walton1Western University Faculty of Engineering, London, Canada.
Louis M Ferreira2St Joseph's Health Care, London, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEvaluation of manual skills training for spinal rehabilitation has been stagnant for 40 years. Observation and mimicry are coupled with feedback from "expert" observers to train and evaluate learners, relying on rater experience to discern speed and force. Spinal manipulation is a controlled act under the Regulated Health Professions Act (1991) as it is not without risk. The discordance between current methods for evaluating proficiency and the potential risks of inadequate application is a critical gap.

methodsThis work reports a novel wearable device that measures finger forces via microstrain bending of the physiotherapist's nail. The device leaves the tactile finger pad unobstructed and does not interfere with treatment application. Five expert-level physiotherapists performed a standard postero-anteriorly directed spinal segmental mobilization treatment for 1 min at 1-1.5 Hz rhythm.

resultsThe device successfully measured all treatment forces (0.2-27.3 N). Physiotherapists applied a maximum force rate of 0.03 ± 0.01 N/s with a rhythm of 1.76 ± 0.38 Hz. In 15 trials, there were no device failures. The device was easily applied and removed, and physiotherapists were able to walk about and interact normally with patients.

conclusionsThese results indicate that this technology can be integrated into a skills training program to provide quantitative feedback for objective assessments.

Indexed as

Manual skills trainingrehabilitationsensors/sensor applicationsspinal rehabilitationtactile sensors

Identifiers

PMID31191931
PMCPMC6453047

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Registered trials

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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.