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  • Getting Started
  • User Guides
  • API Reference
  • Examples
  • Blog
    • Changelog
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  • Data Loading and Handling
    • Loading example data
    • Working with reference data
    • Loading Digital Mobility Outcome (DMO) data
    • Mobilise-D TVS Dataset
    • Custom Data and Datasets
  • Full Pipelines and Pipeline Helper
    • Gait Sequence Iterator
    • The Mobilise-D pipeline: Step-by-Step Breakdown
    • Evaluation of final walking bout level DMOs
    • Preconfigured Mobilised Pipelines
  • Gait Sequence Detection
    • GSD Iluz
    • GSD Paraschiv-Ionescu
    • GSD Evaluation
    • GSD Evaluation Challenges
    • GSD TVS Evaluation
  • Initial Contact Detection
    • ICD Ionescu
    • Shin Algo
    • HKLee algo
    • ICD Evaluation
  • Left/Right Classification
    • McCamley L/R Classifier
    • Ullrich L/R Classifier
    • LRC Evaluation
  • Cadence Estimation
    • Cadence from Initial Contacts
    • Cadence Evaluation
  • Stride Length Calculation
    • SL Zijlstra
    • Stride Length Evaluation
  • Detecting Turns
    • ElGohary Turning Algo
  • Creating final Walking Bouts
    • Assembling WBs
  • DMO Aggregation
    • Mobilised Aggregator
    • Threshold Checker
    • CVS Official Aggregation Script
  • Data Transformations and Filtering
    • Generic Data Transforms
    • General Filter Introduction
    • Resampling data
    • Continuous Wavelet Transform (CWT) - Filter
    • Gaussian Smoothing
    • Savitzky-Golay Filter Example
  • Development Guides
    • Pretrained models and predefined Parameters
  • Examples
  • Gait...

Gait Sequence Detection#

GSD Iluz

This example shows how to use the GSD Iluz algorithm and some examples on how the results compare to the original

GSD Paraschiv-Ionescu

GSD Paraschiv-Ionescu

GSD Evaluation

GSD Evaluation

GSD Evaluation Challenges

GSD Evaluation Challenges

GSD TVS Evaluation

GSD TVS Evaluation
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