ArticleFrontiers in bioengineering and biotechnology2023
Identification of characteristics of foot position and angle during swing phase in fallers using principal component analysis.
Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Effect of knee sleeves on joint angle variability during gait in older adults: a principal component analysis.Frontiers in bioengineering and biotechnology · 2025Article
- Estimating Indicators for Assessing Knee Motion Impairment During Gait Using In-Shoe Motion Sensors: A Feasibility Study.Sensors (Basel, Switzerland) · 2024Article
- The Effects of a Floss Band on Ankle Range of Motion, Balance, and Gait in Chronic Stroke: A Randomized Controlled Study.Healthcare (Basel, Switzerland) · 2024Article
- Errors in Estimating Lower-Limb Joint Angles and Moments during Walking Based on Pelvic Accelerations: Influence of Virtual Inertial Measurement Unit's Frontal Plane Misalignment.Sensors (Basel, Switzerland) · 2024Article
- Knee sleeves improve gait symmetry during fast walking in older adults.Frontiers in bioengineering and biotechnology · 2024Article
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Authors and funding
12 authors.
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Abstract
Identifying the characteristics of fallers is important for preventing falls because such events may reduce quality of life. It has been reported that several variables related to foot positions and angles during gait (e.g., sagittal foot angle and minimum toe clearance) differ between fallers and non-fallers. However, examining such representative discrete variables may not be sufficient to detect crucial information, which may be contained in the large portions of unanalyzed data. Therefore, we aimed to identify the comprehensive characteristics of foot position and angle during the swing phase of gait in non-fallers and fallers using principal component analysis (PCA). Thirty non-fallers and 30 fallers were recruited for this study. We performed PCA to reduce the dimensions of foot positions and angles during the swing phase and obtained principal component scores (PCSs) for each principal component vector (PCV), which were then compared between groups. The results revealed that the PCS of PCV3 in fallers was significantly larger than that in non-fallers (
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