Evidence map›Paper›PMID 41593357›Full record

Observational studyJournal of neurology2026

Real-time detection and subtyping of "On-meds" freezing of gait in Parkinson's disease using lower-limb acceleration data.

Wenbiao Xian, Bin Hu, Taylor Chomiak, Fengjuan Su, Zhong Pei

Abstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wenbiao XianDepartment of Neurology, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.ORCID http://orcid.org/0000-0001-8549-3534
Bin HuDivision of Translational Neuroscience, Department of Clinical Neurosciences, Cumming School of Medicine, Hotchkiss Brain Institute, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.
Taylor ChomiakDivision of Translational Neuroscience, Department of Clinical Neurosciences, Cumming School of Medicine, Hotchkiss Brain Institute, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.
Fengjuan SuDepartment of Neurology, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Zhong PeiDepartment of Neurology, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China. peizhong@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-7986-3452

Funding

Guangdong Province International Cooperation Base for Early Intervention and Functional Rehabilitation of Neurological Diseases 2020A0505020004Guangdong Provincial Clinical Research Center for Neurological Diseases 2020B1111170002Guangzhou Major Difficult and Rare Diseases Project 2024MDRD02Medical Science and Technology Foundation of Guangdong Province A2023065National Natural Science Foundation of China 82071255National Natural Science Foundation of China 82271266
6 · The paper itself

Abstract

backgroundAlthough many patients with Parkinson's disease (PD) report experiencing episodes of freezing of gait (FOG) at home under ON medication ("On-meds") conditions, objective and accurate diagnosis of different types of FOG events remains an extremely challenging task.

methodsWe conducted an observational, case-control study enrolling 75 consecutive PD patients, who were classified into "freezer" (n = 50) and "non-freezer" (n = 25) group, based on responses to the FOG Questionnaire and clinical confirmation. A modified timed up and go (TUG) protocol comprised one single‑task TUG (sTUG) and two dual‑task TUGs (cognitive, manual). Synchronized video and a single wearable sensor (Ambulosono) provided parallel capture for real‑time detection and subtyping of FOG.

resultsIn the "freezers" group, 337 FOG episodes occurred during TUG testing, whereas none were recorded in the "non‑freezers" group (p < 0.01). The mean frequency was 2.25 FOG episodes per person per test. Compared with the sTUG test (74 FOG episodes), dual-task trials identified 263 FOG episodes, representing a 255% increase (p < 0.01). Trembling, shuffling and akinetic subtypes were identifiable on the device display (GMGI), with sensitivity 87.2% and specificity 89.5% versus video. Wearable data also localized subtypes by gait phase (initiation, turning, midway and ending).

conclusions"On-meds" FOGs can be objectively diagnosed among self-reported freezers using a dual task protocol during gait tests. Parallel video and wearable sensor recordings facilitate the real-time detection and subtyping of "On-meds" FOGs, which can substantially improve the current clinical practice.

Indexed as

Gait Disorders, NeurologicLower ExtremityParkinson DiseaseAccelerationAccelerometryAgedCase-Control StudiesFemaleHumansMaleMiddle AgedWearable Electronic DevicesDual taskFreezing of gaitParkinson’s diseaseReal-time detectionSensorTimed up and go test

Identifiers

PMID41593357

What OpenQuestion holds

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Registered trials

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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.