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Related Concept Videos

Parkinson Disease ll: Pathophysiology01:24

Parkinson Disease ll: Pathophysiology

Parkinson disease (PD) is a progressive neurodegenerative disorder primarily affecting movement, with additional non-motor features. Its pathophysiology involves complex interactions among genetic susceptibility, environmental exposures, and cellular dysfunction, including dopaminergic neuron loss, protein aggregation, and mitochondrial impairment.Selective NeurodegenerationA key feature is the degeneration of dopaminergic neurons in the substantia nigra pars compacta, leading to reduced...
Parkinson's Disease: Overview01:15

Parkinson's Disease: Overview

Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is to...
Parkinson Disease l: Introduction01:24

Parkinson Disease l: Introduction

Parkinson’s disease is a chronic, progressive neurodegenerative disorder that primarily affects movement. It is characterized by motor symptoms such as resting tremors, muscle rigidity, bradykinesia (slowness of movement), and postural instability. Patients may notice hand tremors at rest, stiffness during movement, or a shuffling gait. In addition to motor features, non-motor symptoms include sleep disturbances, mood and behavioral changes, constipation, and cognitive impairment, all of which...
Parkinson's Disease: Treatment01:24

Parkinson's Disease: Treatment

Neurodegenerative disorders, such as Parkinson's Disease (PD), involve the gradual and irreversible destruction of neurons in particular brain areas. These disorders exhibit standard features like proteinopathies, selective vulnerability of some neurons, and an interaction of intrinsic properties, genetics, and environmental influences in neural injury.
Parkinson's Disease is primarily a result of the loss of dopaminergic neurons in the substantia nigra pars compacta. The cornerstone of its...

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Related Experiment Video

Updated: May 13, 2026

Applying the RatWalker System for Gait Analysis in a Genetic Rat Model of Parkinson's Disease
04:08

Applying the RatWalker System for Gait Analysis in a Genetic Rat Model of Parkinson's Disease

Published on: January 18, 2021

Insights into gait disorders: walking variability using phase plot analysis, Parkinson's disease.

Patrick Esser1, Helen Dawes, Johnny Collett

  • 1Movement Science Group, Oxford Brookes University, Gipsy Lane Campus, Headington, Oxford OX3 0BP, UK.

Gait & Posture
|March 21, 2013
PubMed
Summary
This summary is machine-generated.

Gait variability analysis using phase plots can differentiate Parkinson's disease (PD) patients from typically developed adults (TDAs) using short walks. This method offers a promising, less demanding approach for fall risk assessment in PD.

Keywords:
AccelerometryGaitParkinson's diseaseVariability

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Related Experiment Videos

Last Updated: May 13, 2026

Applying the RatWalker System for Gait Analysis in a Genetic Rat Model of Parkinson's Disease
04:08

Applying the RatWalker System for Gait Analysis in a Genetic Rat Model of Parkinson's Disease

Published on: January 18, 2021

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
08:56

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Movement Science

Background:

  • Gait variability is a sensitive indicator for fall risk in Parkinson's disease (PD).
  • Current methods for assessing gait variability require extensive data collection, posing challenges for patients.

Purpose of the Study:

  • To investigate the efficacy of phase plot variability analysis in distinguishing individuals with PD from typically developed adults (TDAs).
  • To determine if short walking trials (two 10-m walks) are sufficient for reliable gait analysis in PD.

Main Methods:

  • Participants included 14 individuals with PD and 10 age-matched TDAs.
  • An inertial measurement unit recorded center of mass (CoM) motion at 100 Hz during 10-m walks.
  • Phase plot analysis derived parameters like SDA (spread) and β (angular vector) from vertical CoM excursion.

Main Results:

  • No significant differences were found in cadence or stride length between PD and TDAs.
  • Significant differences were observed in walking speed (p=.041), β (p=.010), and SDA (p=.004) between groups.
  • Phase plot parameters demonstrated reliability across two sequential 10-m walks in PD patients.

Conclusions:

  • Phase plot analysis of CoM motion effectively differentiates PD from TDAs.
  • This method provides a reliable and less demanding approach for assessing gait in PD using short walks.