↓ Skip to main content

Measuring leg movements during sleep using accelerometry: comparison with EMG and piezo-electric scored events

Overview of attention for article published in Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, January 2013
Altmetric Badge

Mentioned by

twitter
1 X user
facebook
1 Facebook page

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
26 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Measuring leg movements during sleep using accelerometry: comparison with EMG and piezo-electric scored events
Published in
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, January 2013
DOI 10.1109/embc.2013.6611134
Pubmed ID
Authors

Philip I. Terrill, Matthew Leong, Katrina Barton, Craig Freakley, Carl Downey, Mark Vanniekerk, Greg Jorgensen, James Douglas

Abstract

Periodic Limb Movements during Sleep (PLMS) can cause significant disturbance to sleep, resulting in daytime sleepiness and reduced quality of life. In conventional clinical practice, PLMS are measured using overnight electromyogram (EMG) of the tibialis anterior muscle, although historically they have also been measured using piezo-electric gauges placed over the muscle. However, PLMS counts (PLM index) do not correlate well with clinical symptomology. In this study, we propose that because EMG and piezo derived signals measure muscle activation rather than actual movement, they may count events with no appreciable movement of the limb and therefore no contribution to sleep disturbance. The aim of this study is thus to determine the percentage of clinically scored limb movements which are not associated with movement of the great toe measured using accelerometry. 9 participants were studied simultaneously with an overnight diagnostic polysomnogram (including EMG and piezo instrumentation of the right leg) and high temporal resolution accelerometry of the right great toe. Limb movements were scored, and peak acceleration during each scored movement was quantified. Across the participant population, 54.9% (range: 26.7-76.3) and 39.0% (range: 4.8-69.6) of limb movements scored using piezo and EMG instrumentation respectively, were not associated with toe movement measured with accelerometry. If sleep disturbance is the consequence of the limb movements, these results may explain why conventional piezo or EMG derived PLMI is poorly correlated with clinical symptomology.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 27%
Student > Doctoral Student 3 12%
Student > Master 3 12%
Student > Postgraduate 2 8%
Researcher 2 8%
Other 3 12%
Unknown 6 23%
Readers by discipline Count As %
Engineering 9 35%
Medicine and Dentistry 4 15%
Computer Science 1 4%
Psychology 1 4%
Agricultural and Biological Sciences 1 4%
Other 4 15%
Unknown 6 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 November 2013.
All research outputs
#19,947,956
of 25,377,790 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#2,758
of 4,376 outputs
Outputs of similar age
#221,321
of 289,014 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#212
of 281 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,376 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 289,014 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 281 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.