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Faster and improved 3-D head digitization in MEG using Kinect

Overview of attention for article published in Frontiers in Neuroscience, October 2014
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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25 Dimensions

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63 Mendeley
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Title
Faster and improved 3-D head digitization in MEG using Kinect
Published in
Frontiers in Neuroscience, October 2014
DOI 10.3389/fnins.2014.00326
Pubmed ID
Authors

Santosh Vema Krishna Murthy, Matthew MacLellan, Steven Beyea, Timothy Bardouille

Abstract

Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant's structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices-Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows-for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (1 min compared to 3 min) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20-30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in the NextEngine laser scan (~1 min). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 2%
Germany 1 2%
Brazil 1 2%
Unknown 60 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 24%
Student > Master 9 14%
Student > Ph. D. Student 9 14%
Student > Bachelor 7 11%
Student > Doctoral Student 4 6%
Other 8 13%
Unknown 11 17%
Readers by discipline Count As %
Engineering 12 19%
Medicine and Dentistry 10 16%
Neuroscience 9 14%
Computer Science 7 11%
Psychology 4 6%
Other 8 13%
Unknown 13 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 30 October 2014.
All research outputs
#6,358,223
of 22,765,347 outputs
Outputs from Frontiers in Neuroscience
#4,222
of 9,878 outputs
Outputs of similar age
#70,515
of 260,389 outputs
Outputs of similar age from Frontiers in Neuroscience
#47
of 115 outputs
Altmetric has tracked 22,765,347 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 9,878 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has gotten more attention than average, scoring higher than 56% 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 260,389 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 115 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 58% of its contemporaries.