ArticleBiosensors2019
Article in Biosensors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Visual perturbation training to reduce visual dependency in Parkinson's disease: A randomized controlled trial.PloS one · 2026Trial
- Flexible and Self-Powered Wearable Sensors for Tremor Monitoring in Parkinson'S Disease: Recent Advances in Materials and Device Architectures.Advanced healthcare materials · 2026Review
- Using explainable AI to identify disease-relevant and deep brain stimulation treatment-sensitive gait features in Parkinson's disease.Journal of neuroengineering and rehabilitation · 2026Article
- Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- A non-expensive bidimensional assessment can detect subtle alterations in gait performance in people in the early stages of Parkinson's disease.Frontiers in neurology · 2023Article
- Within-subject variation in the cognitive timed up and go test as an explanatory variable in fall risk in patients with parkinson's disease.Journal of rehabilitation medicine · 2021Article
- Muscle activation strategies of people with early-stage Parkinson's during walking.Journal of neuroengineering and rehabilitation · 2021Article
- Atypical Gait Cycles in Parkinson's Disease.Sensors (Basel, Switzerland) · 2021Article
- A synthetic kinematic index of trunk displacement conveying the overall motor condition in Parkinson's disease.Scientific reports · 2021Observational
- Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units.Sensors (Basel, Switzerland) · 2021Article
- Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson's Disease by Wearable Sensors: Controlled Study.JMIR mHealth and uHealth · 2020Article
- Transverse Strips Instead of Wearable Laser Lights Alleviate the Sequence Effect Toward a Destination in Parkinson's Disease Patients With Freezing of Gait.Frontiers in neurology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigated the difference in the gait of patients with Parkinson's disease (PD), age-matched controls and young controls during three walking patterns. Experiments were conducted with 24 PD, 24 age-matched controls and 24 young controls, and four gait intervals were measured using inertial measurement units (IMU). Group differences between the mean and variance of the gait parameters (stride interval, stance interval, swing interval and double support interval) for the three groups were calculated and statistical significance was tested. The results showed that the variance in each of the four gait parameters of PD patients was significantly higher compared with the controls, irrespective of the three walking patterns. This study showed that the variance of any of the gait interval parameters obtained using IMU during any of the walking patterns could be used to differentiate between the gait of PD and control people.
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Registered trials
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.