The purpose of this study was to compare estimates of gastrocnemius muscle length (GML) obtained using a segmented versus straight-line model in children. Kinematic data were acquired on eleven typically developing children as they walked under the following conditions: normal gait, crouch gait, equinus gait, and crouch with equinus gait. Maximum and minimum GML, and GML change were calculated using two models: straight-line and segmented. A two-way RMANOVA was used to compare GML characteristics. Results indicated that maximum GML and GML change during simulated pathological gait patterns were influenced by model used to calculate gastrocnemius muscle length (interaction: P = .004 and P = .026). Maximum GML was lower in the simulated gait patterns compared with normal gait (P < .001). Maximum GML was higher with the segmented model compared with the straight-line model (P = .030). Using either model, GML change in equinus gait and crouch with equinus gait was lower compared with normal gait (P < .001). Overall, minimum GML estimated with the segmented model was higher compared with the straight-line model (P < .01). The key findings of our study indicate that GML is significantly affected by both gait pattern and method of estimation. The GML estimates tended to be lower with the straight-line model versus the segmented model.
Smita Rao, Fred Dietz, and H. John Yack
Diane Richmond, Kathleen Castro, Vaibhavi Rathod, Thais Medeiros da Costa Dias, Nelson Marinho de Lima Filho, Judith Meer, and Smita Rao
Context: Yoga is increasingly popular, not only as a form of recreational exercise but also as a physician-recommended intervention for health conditions. While serious adverse effects accompanying yoga practice are rare, poses that involve upper-extremity weight-bearing have a high risk of discomfort. To better understand factors contributing to adverse effects, there is a critical need for robust instruments that objectively evaluate pose performance. The purpose of this study was to assess the interrater reliability of an observational scale developed to assess the alignment of 3 yoga poses. Design: Cross-sectional experimental study. Methods: Thirty-eight individuals were given standardized instructions and performed 3 poses (Downward Dog, Plank, and Side Plank). Lateral videos were rated by 2 raters. A rating scale evaluating the alignment of 7 regions was developed by the study team with input from yoga teachers. Descriptive statistics were used to summarize the percentage of subjects showing ideal alignment and deviations. Interrater reliability was quantified using Cohen kappa coefficient (κ). Results: In Downward Dog, the prevalence of ideal alignment was 20%, 28%, and 37%, at the neck, shoulder, and back, respectively; κ ranged from .44 to .69. In Plank, the prevalence of ideal alignment was 31%, 45%, and 54% at the neck, shoulder, and back, respectively; κ ranged from .47 to .95. In Side Plank, the prevalence of ideal alignment was 16, 41%, and 24%, at the neck, shoulder, and back, respectively; κ ranged from .20 to .84. Conclusion: The observational scale found a high prevalence of deviations, and demonstrated fair to substantial interrater agreement.
Sarah P. Shultz, Jinsup Song, Andrew P. Kraszewski, Jocelyn F. Hafer, Smita Rao, Sherry Backus, Rajshree M. Hillstrom, and Howard J. Hillstrom
It has been suggested that foot type considers not only foot structure (high, normal, low arch), but also function (overpronation, normal, oversupination) and flexibility (reduced, normal, excessive). Therefore, this study used canonical regression analyses to assess which variables of foot structure, function, and flexibility can accurately discriminate between clinical foot type classifications. The feet of 61 asymptomatic, healthy adults (18–77 years) were classified as cavus (N = 24), rectus (N = 54), or planus (N = 44) using standard clinical measures. Custom jigs assessed foot structure and flexibility. Foot function was assessed using an emed-x plantar pressure measuring device. Canonical regression analyses were applied separately to extract essential structure, flexibility, and function variables. A third canonical regression analysis was performed on the extracted variables to identify a combined model. The initial combined model included 30 extracted variables; however 5 terminal variables (malleolar valgus index, arch height index while sitting, first metatarsophalangeal joint laxity while standing, pressure-time integral and maximum contact area of medial arch) were able to correctly predict 80.7% of foot types. These remaining variables focused on specific foot characteristics (hindfoot alignment, arch height, midfoot mechanics, Windlass mechanism) that could be essential to discriminating foot type.