Evidence map›Paper›PMID 32997618›Full record

ArticleIEEE transactions on bio-medical engineering2021

Robust Method for Mid-Activity Tracking and Evaluation of Ankle Health Post-Injury.

Samer Mabrouk, Daniel Whittingslow, Omer T Inan

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

3 authors.

Samer Mabrouk
Daniel Whittingslow
Omer T Inan

Funding

Wearable lung sounds, fluid, and body temperature monitoring for patients with COVID-19R01EB023808 · NIBIB · GEORGIA INSTITUTE OF TECHNOLOGY · PI INAN, OMER TOLGA · 2016 to 2020
$2.2M
NIBIB NIH HHS R01 EB023808
6 · The paper itself

Abstract

objectiveTo present a robust methodology for evaluating ankle health during ambulation using a wearable device. Methods: We developed a novel data capture system that leverages changes within the ankle during ambulation for real-time tracking of bioimpedance. The novel analysis compares the range of reactance at 5 kHz to the range of reactance at 100 kHz; which removes the technique's previous reliance on a known baseline. To aid in interpretation of the measurements, we developed a quantitative simulation model based on a literature review of the effects on joint bioimpedance of variations in edematous fluid volume, muscle fiber tears, and blood flow changes. Results: The results of the simulation predicted a significant difference in the ratio of the range of the reactance from 5 kHz to 100 kHz between the healthy and injured ankles. These results were validated in 15 subjects - with 11 healthy ankles and 7 injured ankles measured. The injured subjects had lateral ankle sprains 2-4 weeks prior to the measurement. The analysis technique differentiated between the healthy and the injured population (p<<0.01), and a correlation (R = 0.8) with a static protocol previously validated for its sensitivity to edema. Conclusion: The technology presented can detect variations in ankle edema and structural integrity of ankles, and thus could provide valuable feedback to clinicians and patients during the rehabilitation of an ankle injury. Significance: This technology could lead to better-informed decision making regarding a patient's readiness to return to activity and / or tailoring rehabilitation activities to an individual's changing needs.

Indexed as

Ankle InjuriesSprains and StrainsAnkleAnkle JointHumansWalking

Identifiers

PMID32997618
PMCPMC8034603

What OpenQuestion holds

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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.