School of Apparel and Art Design, Xi'an Polytechnic University, No. 19 Jinhua South Road, Xi'an 710048, China.
School of Design, The Hong Kong Polytechnic University, Hong Kong, China.
Sensors (Basel). 2024 Sep 16;24(18):5998. doi: 10.3390/s24185998.
Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems have been designed to monitor users' gait patterns, they commonly spend a lot of time and effort to extract gait metrics from signal data. This study aims to design an artificial intelligence-empowered and economic-friendly gait monitoring system. A pair of intelligent shoes with a single inertial sensor and a smartphone application were developed as a gait monitoring system to detect users' gait cycle, stand phase time, swing phase time, stride length, and foot clearance. We recruited 30 participants (24.09 ± 1.89 years) to collect gait data and used the Vicon motion capture system to verify the accuracy of the gait metrics. The results show that the gait monitoring system performs better on the assessment of the gait metrics. The accuracy of stride length and foot clearance is 96.17% and 92.07%, respectively. The artificial intelligence-empowered gait monitoring system holds promising potential for improving gait analysis and monitoring in the medical and healthcare fields.
步态不稳定在医学和医疗保健中至关重要，因为它与平衡障碍和身体损伤有关。随着传感器技术的发展，尽管已经设计出许多可穿戴的步态检测和识别系统来监测用户的步态模式，但它们通常需要花费大量的时间和精力从信号数据中提取步态指标。本研究旨在设计一种人工智能赋能且经济实惠的步态监测系统。我们开发了一种带有单个惯性传感器的智能鞋和一个智能手机应用程序作为步态监测系统，以检测用户的步态周期、站立相时间、摆动相时间、步长和足廓清。我们招募了 30 名参与者（24.09±1.89 岁）来收集步态数据，并使用 Vicon 运动捕捉系统验证步态指标的准确性。结果表明，步态监测系统在步态指标的评估上表现更好。步长和足廓清的准确率分别为 96.17%和 92.07%。人工智能赋能的步态监测系统在改善医学和医疗保健领域的步态分析和监测方面具有广阔的应用前景。
