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Updated: Jun 27, 2026

Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study
Published on: March 14, 2017
Smartphone-Derived Movement Analysis for Musculoskeletal Assessment: Smartphone-Estimated Relative Vertical Power
Chanon Fapinyo1, Weerasak Tapanya2, Nitiphoom Sinnathakorn1
1Department of Orthopaedics, School of Medicine, University of Phayao, Phayao 56000, Thailand.
Abstract:
Background and Objectives: Assessing knee extensor (KE) strength is important for detecting muscle weakness in older adults, yet dynamometry is often impractical in community settings. This study examined whether smartphone-derived kinematics during the Five Times Sit-to-Stand Test (FTSST) could predict seated isometric KE strength. Materials and Methods: A cross-sectional study included 105 community-dwelling older adults (68.19 ± 5.85 years). A smartphone application extracted rising time, vertical velocity, and smartphone-estimated relative vertical power during the FTSST. KE strength was measured as maximum voluntary isometric contraction (MVIC) using fixed-frame dynamometry with a Lafayette dynamometer head. Bioelectrical impedance-derived body composition variables were reported descriptively but excluded from the primary prediction models to maintain a transparent movement-based model independent of device-specific body-composition estimates. Hierarchical regression models used smartphone-derived variables and transparent non-BIA covariates. Agreement was examined using Bland-Altman analysis. Results: Smartphone-estimated relative vertical power showed the strongest correlation with MVIC (r = 0.787, p < 0.001). The combined model including sex, age, femur length, and smartphone-estimated relative vertical power explained 71.6% of MVIC variance (adjusted R2 = 0.716, SEE = 3.276 kg), outperforming vertical velocity, rising time, and total FTSST time models. Internal validation using repeated 10-fold cross-validation showed CV-R2 = 0.701, CV-adjusted R2 = 0.689, CV-RMSE = 3.343 kg, and CV-MAE = 2.739 kg. Bland-Altman analysis showed minimal mean bias (0.00 kg), 95% limits of agreement from -6.296 to 6.296 kg, and significant proportional bias (slope = -0.172, p = 0.002), indicating overestimation in weaker individuals and underestimation in stronger individuals. Conclusions: Consistent with our hypothesis, smartphone-estimated relative vertical power was the strongest kinematic predictor of seated isometric KE strength among the evaluated FTSST-derived variables. This approach may support community screening and monitoring, but it should not replace standardized dynamometry for precise individual-level strength quantification.

