The aim of this study was to determine the muscle co-activations and joint stiffnesses around the hip, knee, and ankle during different walking speeds and to define the relationships between muscle co-activation and joint stiffness. Twenty-seven healthy subjects (age: 19.6 ± 2.2 years, height: 176.0 ± 6.0 cm, mass: 69.7 ± 8.9 kg) were recruited. Muscle co-activations (CoI) and lower limb joints stiffnesses were investigated during stance phase at different walking speeds using Repeated Measures ANOVA with Sidak post-hoc tests. Correlations between muscle co-activations, joints stiffnesses, and walking speeds were also investigated using Pearson Product Moment correlations. The results indicated that the hip and ankle joints stiffness increased with walking speed (p < 0.001) during the weight acceptance phase, and positive correlations were seen between walking speed and Rectus Femoris (RF) and Biceps Femoris (BF) CoI (p < 0.001), and a negative correlation was seen between walking speed and tibialis anterior (TA) and lateral gastrocnemius (LG) CoI (p < 0.001) during the weight acceptance phase, and the RF/BF CoI during pre-swing. These results provide new information on the variations in muscle co-activation around the hip, knee and ankle joints and their association with joint stiffness, and on the responses of stiffness and muscle co-activation to walking speed. The techniques presented could have further application and help our understanding of the effects of gait retraining and injury mechanisms.
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http://dx.doi.org/10.1016/j.jbiomech.2023.111715 | DOI Listing |
Aging Clin Exp Res
January 2025
Department of Physical Medicine and Rehabilitation, Kansai Medical University, Osaka, Japan.
Background: Falls on stairs are a major cause of severe injuries among older adults, with stair descent posing significantly greater risks than ascent. Variations in stair descent phenotypes may reflect differences in physical function and biomechanical stability, and their identification may prevent falls.
Aims: This study aims to classify stair descent phenotypes in older adults and investigate the biomechanical and physical functional differences between these phenotypes using hierarchical cluster analysis.
Acta Bioeng Biomech
June 2024
1Graduate School of Humanities and Social Sciences, Hiroshima University, Japan.
: This study aimed to investigate the differences in spatiotemporal gait parameters in patients who underwent surgery for hip fractures when using walking poles and T-canes. : This cross-sectional study enrolled eight patients who underwent surgery for a unilateral hip fracture (mean age of 79.0 ± 7.
View Article and Find Full Text PDFDigit Biomark
December 2024
VivoSense, Inc., Newport Coast, CA, USA.
Introduction: Wrist-worn accelerometers can capture stepping behavior passively, continuously, and remotely. Methods utilizing peak detection, threshold crossing, and frequency analysis have been used to detect steps from wrist-worn accelerometer data, but it remains unclear how different approaches perform across a range of walking speeds and free-living activities. In this study, we evaluated the performance of four open-source methods for deriving step counts from wrist-worn accelerometry data, when applied to data from a range of structured locomotion and free-living activities.
View Article and Find Full Text PDFCJC Open
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Background: Supervised exercise programs improve walking impairment and quality of life (QoL) in patients with peripheral artery disease (PAD). However, such programs are underutilized, due to their limited accessibility. A feasible and effective exercise program is needed.
View Article and Find Full Text PDFCureus
December 2024
Faculty of Education, University of Teacher Education Fukuoka, Fukuoka, JPN.
Introduction: The purpose of this study was to clarify the impact of an intervention combining exercise, lifestyle guidance, and community-building activities on the walking function of community-dwelling elderly individuals.
Methods: A total of 391 elderly participants (362 females, 29 males), aged 65 and above, were involved in a one-year intervention consisting of physical activities in a health exercise club, community-building activities, and dementia cafes. The walking function was assessed using an artificial intelligence (AI)-based gait analysis tool and health status was evaluated using a questionnaire.
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