Evidence map›Paper›PMID 42337570›Full record

ArticleJournal of neuroengineering and rehabilitation2026

Passive sensing of gait and medication-related fluctuations in Parkinson's disease.

Juyoung Jenna Yun, Charalambos Hadjipanayi, Arya Jahangiri, Alan Bannon, Timothy G Constandinou, Shlomi Haar

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 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

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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

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Juyoung Jenna YunDepartment of Brain Sciences, Imperial College London, London, UK.
Charalambos HadjipanayiCare Research and Technology Centre, UK Dementia Research Institute, London, UK.
Arya JahangiriCare Research and Technology Centre, UK Dementia Research Institute, London, UK.
Alan BannonCare Research and Technology Centre, UK Dementia Research Institute, London, UK.
Timothy G ConstandinouCare Research and Technology Centre, UK Dementia Research Institute, London, UK.
Shlomi HaarDepartment of Brain Sciences, Imperial College London, London, UK. s.haar@imperial.ac.uk.ORCID https://orcid.org/0000-0003-2213-6585

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGait impairment is a hallmark symptom of Parkinson's Disease (PD). Traditional clinical assessments cannot capture real-world motor fluctuations, as they are sparsely performed. We validated the use of nearables, passive sensing technologies, including Kinect RGB-D cameras and ultra-wideband (UWB) radar, for continuous, objective assessment of gait fluctuations in PD within a home-like setting.

methodsFifteen PD patients with mild symptoms and fourteen age- and sex-matched healthy controls (HC) performed 4-metre walking tasks in a living lab facility. Patients repeated the task during "ON" and "OFF" states of their daily medication cycle. Gait features, including stride length, stride time, and gait speed, were extracted from Kinect, radar, and a ground-truth smart floor. Data were analysed to assess inter-sensor agreements and group-level differences.

resultsStride time demonstrated the highest agreement between devices (r = 0.903), while stride length was weaker (r = 0.779). Nevertheless, stride length from both Kinect and radar distinguished PD OFF from HC (camera q = 0.020; radar q = 0.005), and radar additionally differentiated ON from OFF (q = 0.020). Neither device differentiated PD ON from HC, indicating medication reduced observable gait differences.

conclusionsAlthough some spatial metrics show device discrepancies, both systems demonstrate sensitivity to gait patterns and medication-dependent changes, supporting their use for longitudinal, real-world monitoring of motor symptoms.

Indexed as

Antiparkinson AgentsGaitGait AnalysisGait Disorders, NeurologicParkinson DiseaseAgedFemaleHumansMaleMiddle AgedAntiparkinson Agents

Identifiers

PMID42337570
PMCPMC13349001

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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 Socratic graph.