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Interpolating accurate saccade peak velocity measures and velocity profiles from low sample frequency data

Mulvey, Fiona LU ; Perrone, Gian and Holmqvist, Kenneth LU (2011) In Behavior Research Methods
Abstract
This study describes an interpolation-based approach to the extraction of velocity measures, including peak velocities, from eye data with sampling frequencies from 62.5Hz to 1250Hz. The approach takes into account the known physical constraints of rotation through interpolation on the velocity profile under smoothness constraints and the application of classical mechanics. The result is accurate velocity profiles from all saccades, regardless of amplitude, above 31.25ms in duration at a sample rate of 62.5Hz. The method is tested by downsampling high speed data and

comparing original peak velocities and main sequence with those interpolated from lower sample rates. SMI HiSpeed and SR Research EyeLink II high speed data smoothed... (More)
This study describes an interpolation-based approach to the extraction of velocity measures, including peak velocities, from eye data with sampling frequencies from 62.5Hz to 1250Hz. The approach takes into account the known physical constraints of rotation through interpolation on the velocity profile under smoothness constraints and the application of classical mechanics. The result is accurate velocity profiles from all saccades, regardless of amplitude, above 31.25ms in duration at a sample rate of 62.5Hz. The method is tested by downsampling high speed data and

comparing original peak velocities and main sequence with those interpolated from lower sample rates. SMI HiSpeed and SR Research EyeLink II high speed data smoothed using the Savitzky-Golay FIR smoothing filter, decimated to 62:5; 125; 250, and 625Hz, correlate with the original

measured peaks; r = :95 to :99. This method represents a new approach in terms of processing eye data, emphasizing the spatial over the frequency domain. It requires good precision in the data, but reduces dependency on high sample rate for velocity measures. Results suggest that the spatial

domain oers superior possibilities for the extraction of events from low frequency data, and that calculus based error metrics which can identifying physically unsound movements are more appropriate than unilateral filtering, especially in data recorded at low sample rate. Using classical mechanics to identify physically unsound movement in the data also offers tools for comparing data quality and noise characteristics at all sample rates, across various hardware, filters, individuals, calibrations or groups. (Less)
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organization
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Contribution to specialist publication or newspaper
publication status
submitted
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categories
Popular Science
in
Behavior Research Methods
publisher
The Psychonomic Society
ISSN
1554-351X
language
English
LU publication?
yes
id
f686bbd9-2345-4467-b0a1-9801e6a533f7 (old id 2204627)
date added to LUP
2011-11-18 14:10:51
date last changed
2016-04-15 14:06:42
@misc{f686bbd9-2345-4467-b0a1-9801e6a533f7,
  abstract     = {This study describes an interpolation-based approach to the extraction of velocity measures, including peak velocities, from eye data with sampling frequencies from 62.5Hz to 1250Hz. The approach takes into account the known physical constraints of rotation through interpolation on the velocity profile under smoothness constraints and the application of classical mechanics. The result is accurate velocity profiles from all saccades, regardless of amplitude, above 31.25ms in duration at a sample rate of 62.5Hz. The method is tested by downsampling high speed data and<br/><br>
comparing original peak velocities and main sequence with those interpolated from lower sample rates. SMI HiSpeed and SR Research EyeLink II high speed data smoothed using the Savitzky-Golay FIR smoothing filter, decimated to 62:5; 125; 250, and 625Hz, correlate with the original<br/><br>
measured peaks; r = :95 to :99. This method represents a new approach in terms of processing eye data, emphasizing the spatial over the frequency domain. It requires good precision in the data, but reduces dependency on high sample rate for velocity measures. Results suggest that the spatial<br/><br>
domain oers superior possibilities for the extraction of events from low frequency data, and that calculus based error metrics which can identifying physically unsound movements are more appropriate than unilateral filtering, especially in data recorded at low sample rate. Using classical mechanics to identify physically unsound movement in the data also offers tools for comparing data quality and noise characteristics at all sample rates, across various hardware, filters, individuals, calibrations or groups.},
  author       = {Mulvey, Fiona and Perrone, Gian and Holmqvist, Kenneth},
  issn         = {1554-351X},
  language     = {eng},
  publisher    = {The Psychonomic Society},
  series       = {Behavior Research Methods},
  title        = {Interpolating accurate saccade peak velocity measures and velocity profiles from low sample frequency data},
  year         = {2011},
}