freeze-index 1.0.1

Unified freezing of gait index computation

Formalization of the Freeze Index Computation

This repository contains the code inherent to Magnes' review and exploration of the freeze index first introduced in [1]. The implementations reported herein are the ones introduced by Bachlin [2], Cockx [3], Zach [4], in addition to Moore's [1] and the newly proposed multitaper method. This work has been published in Frontiers in Neurology, 16, 2025.

Please cite this work/repository as:

Schaer A, Maurenbrecher H, Mangiante C, Sobkuliak R, Müsch K, Sanchez Lopez P, Moraud EM, Ergeneman O, Chatzipirpiridis G. Toward a unified gait freeze index: a standardized benchmark for clinical and regulatory evaluations. Frontiers in Neurology, 16:1528963, 2025.

Setup

Installation and Importing

Installation

pip install freeze-index

Typical import and use

import numpy as np

from freezing import freezeindex as filib

x = np.random.randn(100)
t, fi = filib.compute_multitaper_fi(x, ...)

Comparing Definitions [only available in source repo]

Source repo available at https://github.com/magnesag/freeze-index

Requirements

1. Python >=3.10
2. (optional) Latex -- for paper-ready plots set USE_TEX=True in aux/cfg.py

Daphnet Dataset

The Daphnet Freezing of Gait dataset is used for comparisons. It has a permissive CC BY 4.0 license and the data can be found under data/ folder.

Source (accessed on 19.08.2024): https://archive.ics.uci.edu/dataset/245/daphnet+freezing+of+gait

Python Environment for Source Usage

To manage Python library dependencies, it is strongly suggested to use uv:

# Set up environment
uv sync
# Run $module with
uv run $module
# Run tests with
uv run pytest

Executable Comparisons xcomparisons

The xcomparisons folder contains executable scripts that perform comparisons.

The scripts take care of parsing all data files, running the FI computations and comparisons, and save the resulting plots in the res/ subdirectory. The res/ subdirectory is not tracked and automatically generated if inexistent by the script. Results are sorted by input file and proxy choice.

Performance Evaluation on White Noise

To evaluate the FI definitions' theoretical performance when computing the FI on white noise run the simulation.py script from the root directory as

uv run -m xcomparisons.simulation

Definitions Comparison

To compare FI definitions on the Daphnet dataset, run the script run_variants_comparison.py from root project directory as

uv run -m xcomparisons.run_variants_comparison

Multitaper Parameter Sweep

To run the multitaper parametric sweep and thus to inspect the effects of each parameter of the multitaper method on the FI run

uv run -m xcomparisons.run_multitaper_sweep

Proxy Evaluation

To evaluate the effect of proxy choice on the FI for the multitaper definition, run

uv run -m xcomparisons.run_proxy_sweep

References

[1] Moore ST, MacDougall HG, Ondo WG. Ambulatory monitoring of freezing of gait in Parkinson's disease. Journal of neuroscience methods. 2008 Jan 30;167(2):340-8.
[2] Bachlin M, Plotnik M, Roggen D, Maidan I, Hausdorff JM, Giladi N, Troster G. Wearable assistant for Parkinson’s disease patients with the freezing of gait symptom. IEEE Transactions on Information Technology in Biomedicine. 2009 Nov 10;14(2):436-46.
[3] Cockx H, Nonnekes J, Bloem BR, van Wezel R, Cameron I, Wang Y. Dealing with the heterogeneous presentations of freezing of gait: how reliable are the freezing index and heart rate for freezing detection?. Journal of neuroengineering and rehabilitation. 2023 Apr 27;20(1):53.
[4] Zach H, Janssen AM, Snijders AH, Delval A, Ferraye MU, Auff E, Weerdesteyn V, Bloem BR, Nonnekes J. Identifying freezing of gait in Parkinson's disease during freezing provoking tasks using waist-mounted accelerometry. Parkinsonism & related disorders. 2015 Nov 1;21(11):1362-6.