Joseph Anna M, Kian Azadeh, Begg Rezaul
Institute for Health and Sport, Victoria University, Melbourne, VIC 3000, Australia.
Sensors (Basel). 2024 Dec 10;24(24):7880. doi: 10.3390/s24247880.
The continuous, automated monitoring of sensor-based data for walking capacity and mobility has expanded gait analysis applications beyond controlled laboratory settings to real-world, everyday environments facilitated by the development of portable, cost-efficient wearable sensors. In particular, the integration of Inertial Measurement Units (IMUs) into smart shoes has proven effective for capturing detailed foot movements and spatiotemporal gait characteristics. While IMUs enable accurate foot trajectory estimation through the double integration of acceleration data, challenges such as drift errors necessitate robust correction techniques to ensure reliable performance. This review analyzes current literature on shoe-based systems utilizing IMUs to estimate spatiotemporal gait parameters and foot trajectory characteristics, including foot-ground clearance. We explore the challenges and advancements in achieving accurate 3D foot trajectory estimation using IMUs in smart shoes and the application of advanced techniques like zero-velocity updates and error correction methods. These developments present significant opportunities for achieving reliable and efficient real-time gait assessment in everyday environments.
基于传感器的数据对步行能力和移动性进行持续、自动监测，这使得步态分析应用从受控的实验室环境扩展到了现实世界的日常环境，便携式、经济高效的可穿戴传感器的发展推动了这一进程。特别是，将惯性测量单元（IMU）集成到智能鞋中已被证明在捕捉详细的足部运动和时空步态特征方面是有效的。虽然IMU通过对加速度数据进行双重积分能够实现准确的足部轨迹估计，但诸如漂移误差等挑战需要强大的校正技术来确保可靠的性能。本综述分析了当前关于利用IMU的基于鞋子的系统来估计时空步态参数和足部轨迹特征（包括足部离地间隙）的文献。我们探讨了在智能鞋中使用IMU实现准确的三维足部轨迹估计所面临的挑战和进展，以及零速度更新和误差校正方法等先进技术的应用。这些进展为在日常环境中实现可靠且高效的实时步态评估提供了重大机遇。
