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Related Experiment Video

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Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
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Adaptive empirical pattern transformation (ADEPT) with application to walking stride segmentation.

Marta Karas1, Marcin Stra Czkiewicz2, William Fadel3

  • 1Department of Biostatistics, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD 21205, USA.

Biostatistics (Oxford, England)
|September 24, 2019
PubMed
Summary

Researchers developed adaptive empirical pattern transformation (ADEPT), a novel method for accurately segmenting walking strides from accelerometer data. This fast and scalable technique enhances ambulatory monitoring for clinical and epidemiological studies.

Keywords:
ADEPTGaitPattern segmentationPhysical activityWalkingWearable accelerometers

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Area of Science:

  • Biostatistics
  • Wearable Technology
  • Human Movement Analysis

Background:

  • Accurate gait parameter quantification is crucial for epidemiological and clinical research.
  • Ambulatory monitoring of gait changes requires reliable data segmentation methods.

Purpose of the Study:

  • To introduce adaptive empirical pattern transformation (ADEPT), a novel method for segmenting individual walking strides.
  • To provide a fast, scalable, and accurate approach for analyzing high-density accelerometry data.

Main Methods:

  • Proposed adaptive empirical pattern transformation (ADEPT) for stride segmentation.
  • Utilized covariance between a scaled pattern function and data, similar to wavelet transform but with data-driven patterns.
  • Ensured invariance to accelerometer axis orientation and applicability across various body locations.

Main Results:

  • ADEPT demonstrated accuracy and scalability in segmenting walking strides.
  • The method was validated on accelerometry data from 32 participants during a 450-m outdoor walk.
  • Results were reproducible using provided scripts and data.

Conclusions:

  • ADEPT offers a robust and versatile method for gait analysis using accelerometry.
  • The technique advances ambulatory monitoring capabilities for research applications.
  • Open access to data and scripts facilitates further research and validation.