Assessing lower limb angles from sagittal plane images captured with a smartphone for post-stroke gait.

BACKGROUND: Clinical gait analysis of sagittal plane lower-limb kinematics using video images is a quantitative tool for clinicians. However, the reliability and validity of limb kinematics after stroke using video images has not been fully investigated. OBJECTIVE: This study aimed to examine the wi...

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Detalles Bibliográficos
Publicado en:Physiotherapy Practice & Research Vol. 44; no. 2; pp. 69 - 78
Autores principales: Kitaji, Yu, Sato, Haruhiko, Ishida, Shinnosuke, Harashima, Hiroaki, Miyano, Satoshi
Formato: pictorial research tables/charts Journal Article
Publicado: Sage Publications Inc. 2023
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:BACKGROUND: Clinical gait analysis of sagittal plane lower-limb kinematics using video images is a quantitative tool for clinicians. However, the reliability and validity of limb kinematics after stroke using video images has not been fully investigated. OBJECTIVE: This study aimed to examine the within-session inter-rater reliability and criterion-related validity of lower limb angles measured in sagittal plane images captured using a smartphone for assessing post-stroke gait and to determine which asymmetric parameters are associated with faster gait velocity. METHODS: Thirty-two patients with stroke were included; video images were recorded as they walked at their preferred pace for 1–3 cycles. Lower limb angles (contact, push-off, and excursion angles) and degree of asymmetry were determined based on video images using markers of acromion, greater trochanter, and fifth metatarsal head. Measurement reliability was calculated using the two-way random effects model of intraclass correlation coefficients and minimal detectable change. The criterion validity investigated Pearson's correlation between lower limb angles and their asymmetry and gait velocity. RESULTS: The lower value of the 95% confidence interval of intraclass correlation coefficients (2.3) of the lower limb was 0.891, and the maximum minimal detectable change was 9.6 degrees. Push-off angle showed a moderate-to-strong correlation with gait velocity, whereas the asymmetry of the push-off angle showed a weak correlation with gait velocity. CONCLUSIONS: Assessing post-stroke gait utilizing video images using a smartphone is feasible. The push-off angle, in particular, may provide insight into the clinical assessment of post-stroke gait.