Gait patterns in adults with cerebral palsy have, to our knowledge, never been assessed. This contrasts with the large number of studies which have attempted to categorize gait patterns in children with cerebral palsy. Several methodological approaches have been developed to objectively classify gait patterns in patients with central nervous system lesions. These methods enable the identification of groups of patients with common underlying clinical problems. One method is cluster analysis, a multivariate statistical method which is used to classify an entire data set into homogeneous groups or "clusters". The aim of this study was to determine, using cluster analysis, the principal gait patterns which can be found in adults with cerebral palsy. Data from 3D motion analyses of 44 adults with cerebral palsy were included. A hierarchical cluster analysis was used to subgroup the different gait patterns based on spatiotemporal and kinematic parameters in the sagittal and frontal planes. Five clusters were identified (C1-C5) among which, 3 subgroups were determined, based on spontaneous gait speed (C1/C2: slow, C3/C4: moderate and C5: almost normal). The different clusters were related to specific kinematic parameters that can be assessed in routine clinical practice. These 5 classifications can be used to follow changes in gait patterns throughout growth and aging as well to assess the effects of different treatments (physiotherapy, surgery, botulinum toxin, etc.) on gait patterns in adults with cerebral palsy.
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http://dx.doi.org/10.1016/j.gaitpost.2013.07.110 | DOI Listing |
Sensors (Basel)
January 2025
Wearable and Gait Assessment Research (WAGAR) Group, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia.
Introduction: Gait analysis is a vital tool in the assessment of human movement and has been widely used in clinical settings to identify potential abnormalities in individuals. However, there is a lack of consensus on the normative values for gait metrics in large populations. The primary objective of this study is to establish a normative database of spatiotemporal gait metrics across various age groups, contributing to a broader understanding of human gait dynamics.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Advanced Institute of Convergence Technology, 145 Gwanggyo-ro, Yeongtong-gu, Suwon-si 16229, Gyeonggi-do, Republic of Korea.
According to South Korea's Ministry of Employment and Labor, approximately 25,000 construction workers suffered from various injuries between 2015 and 2019. Additionally, about 500 fatalities occur annually, and multiple studies are being conducted to prevent these accidents and quickly identify their occurrence to secure the golden time for the injured. Recently, AI-based video analysis systems for detecting safety accidents have been introduced.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Parkinson's disease (PD) is characterized by a slow, short-stepping, shuffling gait pattern caused by a combination of motor control limitations due to a reduction in dopaminergic neurons. Gait disorders are indicators of global health, cognitive status, and risk of falls and increase with disease progression. Therefore, the use of quantitative information on the gait mechanisms of PD patients is a promising approach, particularly for monitoring gait disorders and potentially informing therapeutic interventions, though it is not yet a well-established tool for early diagnosis or direct assessment of disease progression.
View Article and Find Full Text PDFJ Clin Med
January 2025
Neuromuscular Control Laboratory, Yeungnam University, Gyeongsan-si 38541, Republic of Korea.
: Gait disturbances characterized by asymmetries in lower limb strength and gait patterns are frequently observed in stroke patients, which increases gait variability and fall risk. However, the extent to which lower limb strength asymmetry influences gait asymmetry and variability in this population remains unclear. : This cross-sectional study included 84 participants, comprising stroke survivors and age- and sex-matched healthy older adults.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Women's and Children's Health, University of Padova, 35128 Padova, Italy.
Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder that causes a range of developmental problems including cognitive and behavioral impairment and learning disabilities. FXS is caused by full mutations (FM) of the gene expansions to over 200 repeats, with hypermethylation of the cytosine-guanine-guanine (CGG) tandem repeated region in its promoter, resulting in transcriptional silencing and loss of gene function. Female carriers of FM are typically less impaired than males.
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