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Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients

Overview of attention for article published in Medical & Biological Engineering & Computing, October 2015
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Mentioned by

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2 tweeters

Citations

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57 Dimensions

Readers on

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165 Mendeley
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Title
Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients
Published in
Medical & Biological Engineering & Computing, October 2015
DOI 10.1007/s11517-015-1395-3
Pubmed ID
Authors

Claas Ahlrichs, Albert Samà, Michael Lawo, Joan Cabestany, Daniel Rodríguez-Martín, Carlos Pérez-López, Dean Sweeney, Leo R. Quinlan, Gearòid Ò Laighin, Timothy Counihan, Patrick Browne, Lewy Hadas, Gabriel Vainstein, Alberto Costa, Roberta Annicchiarico, Sheila Alcaine, Berta Mestre, Paola Quispe, Àngels Bayes, Alejandro Rodríguez-Molinero

Abstract

Freezing of gait (FOG) is a common motor symptom of Parkinson's disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly detected by a support vector machine (SVM). Then, classifier's outputs are aggregated over time to determine a confidence value, which is used for the final classification of freezing (i.e., second and third approach). All variations are trained with signals of 15 patients and evaluated with signals from another 5 patients. Using a linear SVM kernel, the third approach provides 98.7 % accuracy and a geometric mean of 96.1 %. Moreover, it is investigated whether frequency features are enough to reliably detect FOG. Results show that these features allow the method to detect FOG with accuracies above 90 % and that frequency features enable a reliable monitoring of FOG by using simply a waist sensor.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 164 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 19%
Student > Master 24 15%
Researcher 21 13%
Student > Bachelor 14 8%
Student > Doctoral Student 13 8%
Other 25 15%
Unknown 36 22%
Readers by discipline Count As %
Engineering 57 35%
Neuroscience 18 11%
Medicine and Dentistry 16 10%
Computer Science 12 7%
Sports and Recreations 4 2%
Other 14 8%
Unknown 44 27%

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 09 May 2016.
All research outputs
#9,966,542
of 13,029,564 outputs
Outputs from Medical & Biological Engineering & Computing
#1,211
of 1,352 outputs
Outputs of similar age
#167,678
of 262,993 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#22
of 34 outputs
Altmetric has tracked 13,029,564 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,352 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 9th percentile – i.e., 9% 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 262,993 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.