ArticleSensors (Basel, Switzerland)2021
Atypical Gait Cycles in Parkinson's Disease.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 15 citations in OpenAlex.
- A toolbox for the identification of foot-floor contact sequences to analyze atypical gait cycles in a real-life scenario: application on patients after proximal femur fracture and healthy elderly.Journal of neuroengineering and rehabilitation · 2025Article
- Foot-Floor Contact Sequences: A Metric for Gait Assessment in Parkinson's Disease after Deep Brain Stimulation.Sensors (Basel, Switzerland) · 2024Article
- Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics.PeerJ. Computer science · 2024Article
- Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders.Frontiers in human neuroscience · 2022Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is important to find objective biomarkers for evaluating gait in Parkinson's Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (-4% of the gait cycle,
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Registered trials
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