Hemiparetic gait following stroke. Part I: Characteristics

http://www.dancescientist.com/Documents/chen_2004a.pdf

Gait differences between individuals with post-stroke hemiparesis and non-disabled controls at matched speeds.

Stroke survivors are at high risk for falls in all poststroke stages. Falls may have severe consequences, both physically and psychosocially. Individuals with stroke have an increased risk for hip fractures, and after such a fracture, they less often regain independent mobility. In addition, fear of falling is a common consequence of falls, which may lead to decreased physical activity, social deprivation and, eventually, loss of independence. Important risk factors for falls are balance and gait deficits. Stroke-related balance deficits comprise reduced postural stability during quiet standing and delayed and less coordinated responses to both self-induced and external balance perturbations. Gait deficits include reduced propulsion at push-off, decreased hip and knee flexion during the swing phase, and reduced stability during the stance phase. Interventions addressing these deficits can be expected to prevent falls more successfully. Preliminary evidence shows that task-specific exercise programs targeting balance and gait deficits can indeed reduce the number of falls in individuals with stroke. Technological advances in assistive devices are another promising area. More research is needed, however, to provide conclusive evidence of the efficacy of these interventions regarding the prevention of falls in individuals with stroke.

/pdf/falls-in-individuals-with-stroke-18f71l39al.pdf

Falls in individuals with stroke

Motor recovery after stroke is related to neural plasticity, which involves developing new neuronal interconnections, acquiring new functions, and compensating for impairment. However, neural plasticity is impaired in the stroke-affected hemisphere. Therefore, it is important that motor recovery therapies facilitate neural plasticity to compensate for functional loss. Stroke rehabilitation programs should include meaningful, repetitive, intensive, and task-specific movement training in an enriched environment to promote neural plasticity and motor recovery. Various novel stroke rehabilitation techniques for motor recovery have been developed based on basic science and clinical studies of neural plasticity. However, the effectiveness of rehabilitative interventions among patients with stroke varies widely because the mechanisms underlying motor recovery are heterogeneous. Neurophysiological and neuroimaging studies have been developed to evaluate the heterogeneity of mechanisms underlying motor recovery for effective rehabilitation interventions after stroke. Here, we review novel stroke rehabilitation techniques associated with neural plasticity and discuss individualized strategies to identify appropriate therapeutic goals, prevent maladaptive plasticity, and maximize functional gain in patients with stroke.

https://downloads.hindawi.com/journals/srt/2013/128641.pdf

Rehabilitation with Poststroke Motor Recovery: A Review with a Focus on Neural Plasticity

Many neurological and musculoskeletal diseases impair movement, which limits people’s function and social participation. Quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion capture systems and highly trained personnel. Here, we present a method for predicting clinically relevant motion parameters from an ordinary video of a patient. Our machine learning models predict parameters include walking speed (r = 0.73), cadence (r = 0.79), knee flexion angle at maximum extension (r = 0.83), and Gait Deviation Index (GDI), a comprehensive metric of gait impairment (r = 0.75). These correlation values approach the theoretical limits for accuracy imposed by natural variability in these metrics within our patient population. Our methods for quantifying gait pathology with commodity cameras increase access to quantitative motion analysis in clinics and at home and enable researchers to conduct large-scale studies of neurological and musculoskeletal disorders. In the context of diseases impairing movement, quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion capture systems and trained personnel. Here, the authors present a method for predicting clinically relevant motion parameters from an ordinary video of a patient.

Deep neural networks enable quantitative movement analysis using single-camera videos.

Mechanical methods of quantifying gait are more sensitive to change than is direct clinical inspection. To assess gait parameters and patterns of patients with stroke, and the temporal changes of these parameters, a foot-switch gait analyzer was used to test 49 ambulatory patients with stroke and 24 controls. Patients walked significantly slower than controls, with decreased cadence, increased gait cycle, and increased time in double limb support. Patients' hemiplegic limbs spent more time in swing and stance when compared to controls; their unaffected limbs spent significantly more time in stance and single limb support compared to controls. Patients' hemiplegic side, when compared with the unaffected side, spent less time in stance and more time in swing. A flatfoot pattern was typically noted on the affected side. General gait parameters improved over time, with the largest changes occurring in the first 12 months. However, the percentage of time spent in double and single limb support, stance and swing, parameters which describe the asymmetrical pattern of gait, did not change over time. Abnormal gait was due to difficulty in moving the body over an unstable limb. Gait analysis can be of importance in documenting abnormalities and determining the effects of therapeutic modalities.

/pdf/gait-parameters-following-stroke-a-practical-assessment-4xnfip0v6v.pdf

Gait parameters following stroke: a practical assessment.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Nickel Vl

Author Tools

Chat about Author

Papers

Gait parameters following stroke: a practical assessment.