Marcus Nyström
Marcus Nyström
Lund University Humanities Lab, Sweden
Verified email at - Homepage
Cited by
Cited by
Eye tracking: A comprehensive guide to methods and measures
K Holmqvist, M Nyström, R Andersson, R Dewhurst, H Jarodzka, ...
OUP Oxford, 2011
An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data
M Nyström, K Holmqvist
Behavior research methods 42 (1), 188-204, 2010
Eye tracker data quality: what it is and how to measure it
K Holmqvist, M Nyström, F Mulvey
Proceedings of the symposium on eye tracking research and applications, 45-52, 2012
The influence of calibration method and eye physiology on eyetracking data quality
M Nyström, R Andersson, K Holmqvist, J Van De Weijer
Behavior research methods 45 (1), 272-288, 2013
A vector-based, multidimensional scanpath similarity measure
H Jarodzka, K Holmqvist, M Nyström
Proceedings of the 2010 symposium on eye-tracking research & applications …, 2010
How a picture facilitates the process of learning from text: Evidence for scaffolding
A Eitel, K Scheiter, A Schüler, M Nyström, K Holmqvist
Learning and Instruction 28, 48-63, 2013
It depends on how you look at it: Scanpath comparison in multiple dimensions with MultiMatch, a vector-based approach
R Dewhurst, M Nyström, H Jarodzka, T Foulsham, R Johansson, ...
Behavior research methods 44 (4), 1079-1100, 2012
Conveying clinical reasoning based on visual observation via eye-movement modelling examples
H Jarodzka, T Balslev, K Holmqvist, M Nyström, K Scheiter, P Gerjets, ...
Instructional Science 40 (5), 813-827, 2012
One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms
R Andersson, L Larsson, K Holmqvist, M Stridh, M Nyström
Behavior research methods 49 (2), 616-637, 2017
Detection of saccades and postsaccadic oscillations in the presence of smooth pursuit
L Larsson, M Nyström, M Stridh
IEEE Transactions on biomedical engineering 60 (9), 2484-2493, 2013
Semantic override of low-level features in image viewing-both initially and overall
M Nyström, K Holmqvist
Journal of Eye-Movement Research 2 (2), 2: 1-2: 11, 2008
Sampling frequency and eye-tracking measures: how speed affects durations, latencies, and more
R Andersson, M Nyström, K Holmqvist
Journal of Eye Movement Research 3 (3), 1-12, 2010
Detection of fixations and smooth pursuit movements in high-speed eye-tracking data
L Larsson, M Nyström, R Andersson, M Stridh
Biomedical Signal Processing and Control 18, 145-152, 2015
Fit-for-duty test for estimation of drivers’ sleepiness level: Eye movements improve the sleep/wake predictor
C Ahlstrom, M Nyström, K Holmqvist, C Fors, D Sandberg, A Anund, ...
Transportation research part C: emerging technologies 26, 20-32, 2013
Comparing scanpaths during scene encoding and recognition: A multi-dimensional approach
T Foulsham, R Dewhurst, M Nyström, H Jarodzka, R Johansson, ...
Journal of Eye Movement Research 5 (4), 1-14, 2012
Is the eye-movement field confused about fixations and saccades? A survey among 124 researchers
RS Hessels, DC Niehorster, M Nyström, R Andersson, ITC Hooge
Royal Society open science 5 (8), 180502, 2018
Consequences of eye color, positioning, and head movement for eye‐tracking data quality in infant research
RS Hessels, R Andersson, ITC Hooge, M Nyström, C Kemner
Infancy 20 (6), 601-633, 2015
Post-saccadic oscillations in eye movement data recorded with pupil-based eye trackers reflect motion of the pupil inside the iris
M Nyström, I Hooge, K Holmqvist
Vision research 92, 59-66, 2013
Is human classification by experienced untrained observers a gold standard in fixation detection?
ITC Hooge, DC Niehorster, M Nyström, R Andersson, RS Hessels
Behavior Research Methods 50 (5), 1864-1881, 2018
Pupil size influences the eye-tracker signal during saccades
M Nyström, I Hooge, R Andersson
Vision research 121, 95-103, 2016
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