Evidence map›Paper›PMID 28813566›Full record

ArticleJournal of vision2017

A nonlinear generalization of the Savitzky-Golay filter and the quantitative analysis of saccades.

Weiwei Dai, Ivan Selesnick, John-Ross Rizzo, Janet Rucker, Todd Hudson

Abstract read
In one paragraph

Article in Journal of vision, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  5. Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience.International journal of applied earth observation and geoinformation : ITC journal · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Weiwei DaiDepartment of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA.
Ivan SelesnickDepartment of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA.
John-Ross RizzoDepartment of Neurology, School of Medicine, New York University, New York, NY, USA.
Janet RuckerDepartment of Neurology, School of Medicine, New York University, New York, NY, USA.
Todd HudsonDepartment of Neurology, School of Medicine, New York University, New York, NY, USA.

Funding

Rehabilitation Medicine Scientist Training (RMST) ProgramK12HD001097 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BONINGER, MICHAEL L. · 1995 to 2016
$14.1M
NICHD NIH HHS K12 HD001097
6 · The paper itself

Abstract

The Savitzky-Golay (SG) filter is widely used to smooth and differentiate time series, especially biomedical data. However, time series that exhibit abrupt departures from their typical trends, such as sharp waves or steps, which are of physiological interest, tend to be oversmoothed by the SG filter. Hence, the SG filter tends to systematically underestimate physiological parameters in certain situations. This article proposes a generalization of the SG filter to more accurately track abrupt deviations in time series, leading to more accurate parameter estimates (e.g., peak velocity of saccadic eye movements). The proposed filtering methodology models a time series as the sum of two component time series: a low-frequency time series for which the conventional SG filter is well suited, and a second time series that exhibits instantaneous deviations (e.g., sharp waves, steps, or more generally, discontinuities in a higher order derivative). The generalized SG filter is then applied to the quantitative analysis of saccadic eye movements. It is demonstrated that (a) the conventional SG filter underestimates the peak velocity of saccades, especially those of small amplitude, and (b) the generalized SG filter estimates peak saccadic velocity more accurately than the conventional filter.

Indexed as

AlgorithmsModels, TheoreticalHumansImaging, Three-DimensionalPhantoms, ImagingSaccades

Identifiers

PMID28813566
PMCPMC5852949

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.