Gait & posture · 2026
Upper body kinematics during walking and their relationship to fall risk after stroke.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Embrechts Elissa, Hallemans Ann, Van Criekinge Tamaya
Аннотация
INTRODUCTION: Falls are highly prevalent after stroke. Although trunk control is critical for dynamic stability during walking, the contribution of upper body (head, neck, thorax, spine) kinematics to fall risk discrimination and prediction remains unknown. This study examined whether trunk kinematics during walking differentiate people with stroke (PwS) with high versus low fall-risk and whether these measures improve fall risk classification.
METHODS: Fifty sub-acute PwS from a public 3D gait dataset were analysed. Participants walked barefoot at self-selected speed while full-body kinematics were recorded (Vicon®). Fall risk was classified with the Tinetti Performance-Oriented Mobility Assessment (≤18/28 = high risk). Sagittal and frontal upper body kinematics and thoraco-pelvic coordination (continuous relative phase, CRP) were computed. Group differences were tested using ANCOVA adjusted for age and walking speed. Linear discriminant analysis assessed fall risk prediction using walking speed alone and combined with trunk kinematics.
RESULTS: Participants were classified as high (n = 22) and low (n = 28) fall risk. High-risk PwS showed significantly greater mean and maximal sagittal spinal flexion, greater maximal frontal head angle, and lower mean and maximal CRP indicating reduced thoraco-pelvic dissociation. Sagittal head and neck kinematics did not differ. Walking speed alone yielded an AUC of 0.83. Adding maximal sagittal spine angle improved AUC to 0.87 and specificity (0.75-0.88) without affecting sensitivity.
CONCLUSION: High fall risk PwS showed greater trunk flexion, reduced thoraco-pelvic coordination, and greater frontal plane head angle during walking. Walking speed alone strongly predicted fall risk, while adding trunk kinematics improved specificity without affecting sensitivity.
METHODS: Fifty sub-acute PwS from a public 3D gait dataset were analysed. Participants walked barefoot at self-selected speed while full-body kinematics were recorded (Vicon®). Fall risk was classified with the Tinetti Performance-Oriented Mobility Assessment (≤18/28 = high risk). Sagittal and frontal upper body kinematics and thoraco-pelvic coordination (continuous relative phase, CRP) were computed. Group differences were tested using ANCOVA adjusted for age and walking speed. Linear discriminant analysis assessed fall risk prediction using walking speed alone and combined with trunk kinematics.
RESULTS: Participants were classified as high (n = 22) and low (n = 28) fall risk. High-risk PwS showed significantly greater mean and maximal sagittal spinal flexion, greater maximal frontal head angle, and lower mean and maximal CRP indicating reduced thoraco-pelvic dissociation. Sagittal head and neck kinematics did not differ. Walking speed alone yielded an AUC of 0.83. Adding maximal sagittal spine angle improved AUC to 0.87 and specificity (0.75-0.88) without affecting sensitivity.
CONCLUSION: High fall risk PwS showed greater trunk flexion, reduced thoraco-pelvic coordination, and greater frontal plane head angle during walking. Walking speed alone strongly predicted fall risk, while adding trunk kinematics improved specificity without affecting sensitivity.