Evidence map›Paper›PMID 31545345›Full record

ArticleBiostatistics (Oxford, England)2021

Adaptive empirical pattern transformation (ADEPT) with application to walking stride segmentation.

Marta Karas, Marcin Stra Czkiewicz, William Fadel, Jaroslaw Harezlak, Ciprian M Crainiceanu, Jacek K Urbanek

Open access · greenAbstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2021. 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
6.5field-weighted citation impact, top 4% of its field
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, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Comparing Step-Counting Algorithms for High-Resolution Wrist Accelerometry Data in Older Adults in the ARIC Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  5. Article
  6. Validation of the Pittsburgh Performance Fatigability Index in the Study of Muscle, Mobility and Aging.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023
    Article
  7. Article
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  11. Review
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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

6 authors at 4 institutions in 1 country.

Marta KarasDepartment of Biostatistics, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD 21205, USA.
Marcin Stra CzkiewiczDepartment of Biostatistics, Harvard University, 655 Huntington Avenue, Boston, MA 02115, USA.
William FadelDepartment of Biostatistics, Indiana University, 410 W 10th St, Indianapolis, IN 46202, USA.
Jaroslaw HarezlakDepartment of Epidemiology and Biostatistics, Indiana University Bloomington, 1025 E 7th St, Bloomington, IN 47405, USA.
Ciprian M CrainiceanuDepartment of Biostatistics, Johns Hopkins University, 615 N Wolfe Street, Baltimore, MD 21205, USA.
Jacek K UrbanekDivision of Geriatric Medicine and Gerontology, Department of Medicine, Johns Hopkins University, 2024 E Monument St, Baltimore, MD 21205, USA.
Johns Hopkins University · USHarvard University · USIndiana University Bloomington · USIndiana University – Purdue University Indianapolis · US

Funding

Statistical methods for analyzing objectively measured physical activity dataR01HL130483 · NHLBI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Chongzhi Di · 2016 to 2026
$4.4M
Statistical models for multi-modal brain imaging studies of HIV-associated cognitive declineR01MH108467 · NIMH · INDIANA UNIVERSITY INDIANAPOLIS · PI HAREZLAK, JAROSLAW · 2015 to 2019
$2.0M
NHLBI NIH HHS R01 HL130483NIMH NIH HHS R01 MH108467
6 · The paper itself

Abstract

Quantifying gait parameters and ambulatory monitoring of changes in these parameters have become increasingly important in epidemiological and clinical studies. Using high-density accelerometry measurements, we propose adaptive empirical pattern transformation (ADEPT), a fast, scalable, and accurate method for segmentation of individual walking strides. ADEPT computes the covariance between a scaled and translated pattern function and the data, an idea similar to the continuous wavelet transform. The difference is that ADEPT uses a data-based pattern function, allows multiple pattern functions, can use other distances instead of the covariance, and the pattern function is not required to satisfy the wavelet admissibility condition. Compared to many existing approaches, ADEPT is designed to work with data collected at various body locations and is invariant to the direction of accelerometer axes relative to body orientation. The method is applied to and validated on accelerometry data collected during a $450$-m outdoor walk of $32$ study participants wearing accelerometers on the wrist, hip, and both ankles. Additionally, all scripts and data needed to reproduce presented results are included in supplementary material available at Biostatistics online.

Indexed as

GaitWalkingAccelerometryHumansMonitoring, AmbulatoryADEPTGaitPattern segmentationPhysical activityWalkingWearable accelerometers

Identifiers

PMID31545345
PMCPMC8036002
OpenAlexW2977100515

What OpenQuestion holds

Textmetadata
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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.