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Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training

Overview of attention for article published in BMC Research Notes, July 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
29 Mendeley
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Title
Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
Published in
BMC Research Notes, July 2016
DOI 10.1186/s13104-016-2156-6
Pubmed ID
Authors

Chin-Shiuh Shieh, Chin-Dar Tseng, Li-Yun Chang, Wei-Chun Lin, Li-Fu Wu, Hung-Yu Wang, Pei-Ju Chao, Chien-Liang Chiu, Tsair-Fwu Lee

Abstract

Vibroarthrographic (VAG) signals are used as useful indicators of knee osteoarthritis (OA) status. The objective was to build a template database of knee crepitus sounds. Internships can practice in the template database to shorten the time of training for diagnosis of OA. A knee sound signal was obtained using an innovative stethoscope device with a goniometer. Each knee sound signal was recorded with a Kellgren-Lawrence (KL) grade. The sound signal was segmented according to the goniometer data. The signal was Fourier transformed on the correlated frequency segment. An inverse Fourier transform was performed to obtain the time-domain signal. Haar wavelet transform was then done. The median and mean of the wavelet coefficients were chosen to inverse transform the synthesized signal in each KL category. The quality of the synthesized signal was assessed by a clinician. The sample signals were evaluated using different algorithms (median and mean). The accuracy rate of the median coefficient algorithm (93 %) was better than the mean coefficient algorithm (88 %) for cross-validation by a clinician using synthesis of VAG. The artificial signal we synthesized has the potential to build a learning system for medical students, internships and para-medical personnel for the diagnosis of OA. Therefore, our method provides a feasible way to evaluate crepitus sounds that may assist in the diagnosis of knee OA.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 17%
Student > Bachelor 4 14%
Student > Master 3 10%
Professor 2 7%
Researcher 2 7%
Other 5 17%
Unknown 8 28%
Readers by discipline Count As %
Engineering 9 31%
Medicine and Dentistry 6 21%
Nursing and Health Professions 2 7%
Physics and Astronomy 1 3%
Computer Science 1 3%
Other 2 7%
Unknown 8 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2016.
All research outputs
#1,154,875
of 8,088,896 outputs
Outputs from BMC Research Notes
#246
of 1,994 outputs
Outputs of similar age
#24,658
of 128,056 outputs
Outputs of similar age from BMC Research Notes
#6
of 27 outputs
Altmetric has tracked 8,088,896 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,994 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 128,056 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.