IEEE J Biomed Health Inform. 2020 Apr;24(4):1188-1195. doi: 10.1109/JBHI.2019.2930091. Epub 2019 Jul 22.
As turns and walking speed modulation are crucial for functional mobility, development of a field-based tool to objectively evaluate non-steady-state gait is essential. This study aimed to quantify spatiotemporal gait using three Android smartphones during steady-state walking, turns, and gait speed modulation in laboratory and free-living environments. In total, 24 adults ambulated along a 10-m walkway in both environments under seven conditions: straight walking, 90° left or right turn, and modulating gait speed from usual-slow, usual-fast, slow-fast, and fast-slow. Two smartphones were attached to the body, with another phone placed in a shoulder bag. Gait velocity, step time, step length, cadence, and symmetry were computed from smartphone-based tri-axial accelerometers and validated with motion capture and video, in laboratory and free-living environments, respectively. Validity was assessed using Pearson's correlation and Bland-Altman analysis. Gait velocity results revealed moderate to very high validity across all walking conditions, smartphone models, smartphone locations, and environments. Correlations for gait velocity ranged between 0.87-0.91 and 0.79-0.83 for straight walking, 0.86-0.95 and 0.86-0.89 for turning, and 0.51-0.90 and 0.67-0.89 for speed modulation trials, in laboratory and free-living environments, respectively. Step time, step length, and cadence demonstrated high to very high correlations for straight walking and turns. However, symmetry results revealed high correlations only during straight walking in the laboratory. Conditions that included slow walking showed negligible to moderate validity with a high bias. In conclusion, smartphones can be employed as field-based devices to assess steady-state walking, turning, and speed modulation across environment, model, and placement when walking faster than 0.5 m/s.
由于转弯和行走速度调节对于功能性移动至关重要，因此开发一种基于现场的工具来客观评估非稳态步态是必不可少的。本研究旨在使用三部安卓智能手机在实验室和自然环境中评估在稳态行走、转弯和步态速度调节期间的时空步态。总共 24 名成年人在实验室和自然环境中沿着 10 米的走道进行了七种条件下的直走、90°左右转弯和步态速度调节：通常慢、通常快、慢快、快快慢。两部智能手机附着在身体上，另一部手机放在肩包中。智能手机三轴加速度计计算了步态速度、步时、步长、步频和对称性，并分别在实验室和自然环境中通过运动捕捉和视频进行了验证。使用 Pearson 相关和 Bland-Altman 分析评估了有效性。所有行走条件、智能手机模型、智能手机位置和环境下，步态速度结果均显示出中等至非常高的有效性。直走时的步态速度相关性在 0.87-0.91 和 0.79-0.83 之间，转弯时的步态速度相关性在 0.86-0.95 和 0.86-0.89 之间，速度调节试验时的步态速度相关性在 0.51-0.90 和 0.67-0.89 之间。直走和转弯时，步时、步长和步频具有高到非常高的相关性。然而，仅在实验室直走时对称性结果显示出高相关性。包括慢走的条件仅具有高偏差的高到非常高的相关性。结论，当行走速度大于 0.5m/s 时，智能手机可作为基于现场的设备，在环境、模型和位置方面评估稳态行走、转弯和速度调节。
