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RESEARCH PAPER

Biomechanical characteristics before, during, and after freezing of gait episodes in individuals with Parkinson's disease.

PMID
41931955
Journal
Gait & posture
Publication Date
2026-06-01
Grade
E

AI Summary

Using lumbar accelerometer data from the DeFoG dataset, the authors show that a frequency-domain FoG-ratio and time-domain RMS reliably distinguish baseline, pre-FoG, FoG, and post-FoG windows during turning and walking, with AP FoG-ratio correlating with reported freezing severity.

Why It Matters

Delivers objective, event-level sensor biomarkers that can improve phase-aware FoG detection, remote monitoring, patient stratification, and outcome measurement for symptomatic/cueing interventions, though it offers little direct insight into disease-modifying biology.

Abstract

INTRODUCTION: Freezing of gait (FoG) in Parkinson's disease (PD) is an episodic failure to initiate or sustain gait, elevating fall risk. While clinical observation remains the gold standard, inertial sensors enable the objective, event-level characterization of movements. We aimed to quantify sensor signatures across baseline, pre-FoG, FoG, and post-FoG windows and to test whether a frequency-domain FoG-ratio and time-domain acceleration (RMS) differentiate these windows during Turning and Walking. METHODS: We analyzed the DeFoG dataset, recorded during off-medication periods during home-like tasks. A single lumbar accelerometer was worn during standardized protocols with video-verified FoG annotations. Medium-duration events (2-5 s) were segmented into 2-s baseline, 2-s pre-FoG, the FoG itself, and 2-s post-FoG. Features per axis (antero-posterior, AP; medio-lateral, ML; and vertical, V) were: (i) RMS acceleration and (ii) FoG-ratio. RESULTS: FoG-ratio peaks at FoG: strong window effects in Turning (all axes) and Walking (AP, V), with FoG > baseline, pre-, and post-windows. RMS complements this: in Turning, AP and V rise post-FoG; in Walking, AP and V are already elevated pre- and during FoG, indicating mounting instability. The AP FoG-ratio during Turning was positively correlated with the New Freezing of Gait Questionnaire score. CONCLUSION: The FoG-ratio reliably discriminated the FoG window across tasks at the event level. RMS changes captured task- and phase-specific amplitude dynamics that, together with known pre-FoG degradations, may inform future phase-aware detection pipelines. This association supports the clinical relevance of AP FoG-ratio during turning and suggests that it may reflect perceived freezing severity.

Score Breakdown

AI Score
35.0
Base Score
14.2
Rank Score
13.6
Narrative Velocity
-
AI Confidence
-
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